# GeminIQ — Full Content Reference

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## Section 1: What GeminIQ Is
source: https://www.geminiq.com

### Opening Headline
Research Faster. Invest Smarter.

### Introduction
Get institutional-grade financial data sourced directly from SEC EDGAR — 17+ years of 10-K and 10-Q data with XBRL tag traceability, no third-party APIs, no normalization. GeminIQ is designed for the fundamental researcher who wants the raw truth: structured financial statements, 90+ calculated metrics, interactive visualizations, insider transaction tracking, institutional ownership monitoring, and an advanced stock screener — all in one platform.

### Our Mission
GeminIQ's mission is to deliver institutional-quality financial data to individual investors at a price that doesn't require an institutional budget. We believe that direct-to-source SEC data, XBRL traceability, and the analytical tools to act on that data should not be reserved for hedge funds, investment banks, and $20,000-a-year terminal subscribers.

### Data You Can Trust
Every number on GeminIQ is sourced directly from SEC EDGAR — the official source of record for US public company filings. We do not use third-party data providers. We do not license normalized data. Every financial line item carries its original XBRL tag, linking it directly to the company's official filing. You can verify any data point on GeminIQ against the original 10-K or 10-Q on SEC EDGAR in under 30 seconds.

### Our Vision
GeminIQ is building the infrastructure layer that gives individual investors the same data quality, traceability, and analytical depth that institutional teams have always had — at a price accessible to anyone who does serious fundamental research.

### Frequently Asked Questions

**What is GeminIQ?**
GeminIQ is an investment research platform designed to help you research faster and invest smarter. We replace the need to dig through fragmented PDF filings by organizing SEC data into a seamless, interactive timeline with built-in metrics.

**Where does your data come from?**
All of our financial data is sourced directly from official SEC filings, including 10-Q (quarterly) and 10-K (annual) reports.

**How is GeminIQ different from other financial data platforms?**
Most financial tools use third-party APIs that simplify data by grouping similar metrics into broad categories. While this makes data easier to process, it strips away the specific details found in the original reports. We don't use third-party aggregators. Instead, we parse the raw 10-Q and 10-K filings directly. This allows us to present the financial line items as they appear in the official report, preserving company-specific labels and XBRL tags that aggregated platforms typically strip out.

**How does GeminIQ compare to other platforms?**
Unlike platforms that rely on third-party APIs to normalize metrics into generic categories, GeminIQ offers the best of both worlds. We parse 10-Q and 10-K filings directly to create a structured database of raw metrics. This means you get the auditability of a filing viewer with the analytical power of a terminal, without the data loss inherent in third-party aggregation.

**How do you ensure data accuracy?**
We use a combination of advanced algorithms and human oversight to process the data. GeminIQ parses raw EDGAR XBRL and preserves the company's own reported values, labels, and XBRL tags. It does not remap line items into generic vendor buckets. We also validate figures to correct known filing errors, providing you with institutional-quality accuracy.

**How quickly is new filing data available on the platform?**
We offer next-day filing availability, ensuring you have timely access to the latest financial statements and market data to make informed decisions.

**Do you offer longer historical data than tier pricing competitors?**
We provide comprehensive historical data without the arbitrary "3-year limits, 5-year limits, etc." found on tier pricing. Our goal is to give you the complete picture of a company's cycle, not just the recent snapshot.

**What kind of metrics can I analyze?**
GeminIQ provides over 90 calculated core financial metrics. From margins and turnover ratios, to growth rates and valuation ratios. You can easily switch between balance sheet, income statement, cash flow, equity, and comprehensive income views to see the full picture of a company's health.

**Does GeminIQ offer visualization?**
Yes. GeminIQ transforms 10-K and 10-Q data into interactive timelines. You can visualize trends, spot anomalies, and see the story behind the numbers instantly, rather than digging through endless columns of text.

**Can I monitor insider activity?**
Yes. Our platform includes tools for insider sentiment monitoring and institutional data monitoring, allowing you to see how company insiders and major institutions are reacting to market changes.

**Do you offer customizable dashboards?**
Absolutely. You can create customizable dashboards and watchlists, build custom tables, and use our screener features to tailor the research experience to your specific strategy.

**Does GeminIQ offer a free trial?**
Yes, we offer a 7-day free trial with both our annual and monthly plans. This gives you full access to test our timelines, metrics, and search tools before you commit.

**What is the difference between the Annual and Monthly plans?**
Both plans include all features, such as interactive timelines, price variance tools, and over 90 financial metrics, with no ads. The annual plan offers a discounted rate compared to the flexible pay-as-you-go monthly plan.

**Can I cancel my subscription easily?**
Yes. Whether you are on a monthly or annual plan, you can manage your subscription settings directly through your account.

---

## Section 2: Founders
source: https://www.geminiq.com/about

GeminIQ delivers high-quality, accurate financial data to individual investors. Premium data without the premium price tag.

Other platforms market themselves as affordable alternatives to a Bloomberg Terminal, but most license their data from third parties and pass the cost on to you. You end up paying a premium for data that has already been filtered, reformatted, and resold. GeminIQ takes a different approach: the kind of data you would expect from a $20,000-a-year terminal, sourced directly and priced for individual investors.

### The Team

**Chad Hartman — Co-Founder & CEO**
Chad is an Air Force veteran and quantitative analyst who simply wanted data he could trust. Frustrated by platforms that forced SEC data into generic normalized templates, he and his twin brother Brett built GeminIQ. Their platform ingests data directly from SEC EDGAR, not from third-party APIs, to preserve company-specific, as-filed line items. It is designed for the fundamental researcher who wants the raw truth: structured financial statements with XBRL tag traceability back to the original source filing.
LinkedIn: https://www.linkedin.com/in/chadalanhartman/

**Brett Hartman — Co-Founder & CTO**
Brett is a software engineer with bachelor's and master's degrees in software engineering and AI, working by day as a mechanical designer for the federal government. Frustrated by financial platforms with clunky interfaces, inconsistent numbers, and steep paywalls around basic fundamentals, he teamed up with his twin brother Chad to build GeminIQ. Chad gathers and cleans the data; Brett brings it to life, so users can actually see what they came for. Together they aim to make professional-grade SEC data clear, accessible, and fairly priced for everyone, not just institutions.
LinkedIn: https://www.linkedin.com/in/brett-e-hartman

---

## Section 3: Pricing
source: https://www.geminiq.com/pricing

GeminIQ has three plans, all built on the same direct SEC EDGAR data. Paid plans include a 7-day free trial.

### Free Plan — $0/month
- 3 years of historical financial data
- 27 calculated financial metrics
- Limited insider and institutional ownership views
- Next-day filing availability
- Every number traceable to its SEC source
- Free stock screener: all 18 prebuilt strategy screens, no account required (https://www.geminiq.com/free-screener)
- No custom-filter screener and no custom watchlists

### Annual Plan — $29/month (billed annually at $348/year)
- 26% discount over monthly
- 17+ years of financial data
- Over 50 core financial metrics
- Stock screener with 100+ metrics and up to 10 stackable filters
- Custom watchlists, a dedicated peer comps workspace, and one-click Excel export
- Insider transaction tracking and institutional ownership data
- Price variance & Earnings Market Reaction tools
- Interactive visualizations and custom tables
- Next-day filing availability
- Every number traceable to its SEC source
- 7-day risk-free trial

### Monthly Plan — $39/month
- Flexible pay-as-you-go billing
- Includes all features from the Annual Plan
- 7-day risk-free trial

### Everything Included in Your Subscription

**Financial Statements**
View cleaned and structured 10-Q (quarterly) and 10-K (annual) financial data, processed through our proprietary algorithms to ensure consistency and accuracy across time periods and companies. Our process eliminates common filing inconsistencies and preserves the as-filed reporting structure with XBRL traceability, making sure you're working with reliable, ready-to-analyze numbers. Easily switch between Balance Sheet, Income Statement, Cash Flow, Equity, and Comprehensive Income views, or see all statements in one place.

**Performance and Valuation Metrics**
Make apples-to-apples comparisons with industry-standard financial metrics, calculated directly from SEC filings with full traceability to source data. We give you a complete view across profitability, efficiency, growth, liquidity, leverage, returns, and valuation, so you can analyze companies with clarity and confidence. Whether you're screening for high-margin businesses, comparing ROE across peers, or spotting companies with accelerating growth, our metrics help you uncover what really matters, without the manual cleanup.

**Earnings Market Reaction**
For each filing, we track the stock's price performance over 1, 2, and 3 months for 10-Qs and 1 to 12 months for 10-Ks following the release date. Quickly gauge how investors historically reacted to new financial information — whether the market rewarded strong results or punished weak ones — helping you spot patterns in sentiment, surprises, and post-earnings drift over time.

**Insider Transactions**
See what company insiders are doing with their own money. Track purchases and sales by executives, directors, and major shareholders to gauge internal confidence or caution. Whether you're validating a thesis or spotting red flags, insider activity adds valuable context to your fundamental analysis.

**Institutional Data**
Measure institutional participation at a high level. Monitor aggregate ownership percentages to understand how much professional capital is invested in a company and how that exposure evolves over time.

**Customizable Dashboard**
Visualize your strategy. Build custom watchlists that track the companies you care about using only the metrics that drive your decisions. From detailed fundamental tables to comparative line and bar charts, you get a clear, noise-free view of the market.

**Stock Screener**
Stock Screener empowers you to pinpoint exact investment matches using over 100 financial metrics and up to 10 stackable filters. You can apply precise logic operators to these criteria to build highly targeted searches without relying on restrictive templates. Furthermore, every result is fully auditable and traces directly back to the company's original SEC filings for immediate verification.

**Interactive Financial Visualizer**
Turn raw financial data into clear, customizable charts that reveal the story behind the numbers. Choose the metrics that matter (revenue, margins, debt, cash flow, etc.), and track how they evolve over time using line, bar, or area charts. Apply filters, zoom in on specific time periods, and use transformations like log scale, z-score standardization, or min-max normalization to make meaningful comparisons.

**Custom Tables**
Cut through the noise and focus only on the metrics that matter to you. Build clean, focused views of company financials by selecting exactly which metrics to include. Switch between quarterly or annual filings and filter by date range to zero in on the periods that matter. Save your favorite metric sets to reuse instantly across different companies.


---

## Section 4: Platform Features
source: https://www.geminiq.com/features

GeminIQ Platform Features: Institutional-Grade Fundamental Analysis Tools

Most financial research platforms rely on third-party data providers that simplify, alter, or delay crucial information. GeminIQ removes the middleman, delivering raw, unadulterated SEC data directly to your screen — organized around a single company snapshot, a dedicated peer-comparison workspace, and a watchlist built for tracking live theses rather than just tickers.

### Company Snapshot: Every Signal, One Screen
source: https://www.geminiq.com/features#company-snapshot

The Research overview puts the whole investment case above the fold — a stock price chart, the last insider purchase and sale with a calculated Buy Ratio showing insider buying vs. selling, institutional shares owned and year-over-year change with a trend sparkline, and the company's own post-filing drift history.

### Direct-from-Source SEC Financial Statements
source: https://www.geminiq.com/features#financial-statements

View 10-Q (quarterly) and 10-K (annual) data exactly as the company filed it, pulled straight from SEC EDGAR with no third-party data provider in between. Company-specific disclosures and management's own labels survive intact, and every figure carries its XBRL tag so you can verify it against the source document in seconds.

Switch between Balance Sheet, Income Statement, Cash Flow, Equity and Comprehensive Income views, toggle the table between millions and as-filed units, and click any row to chart that line item's full history. A sparkline on every row shows its trajectory across the visible periods, and the company's recent filings sit beside the table as direct links back to EDGAR. Filings are processed overnight, so clean data is ready by the time the market opens — with 17+ years of history on every paid plan.

### Customizable Data Tables
source: https://www.geminiq.com/features#custom-tables

Cut through the noise and focus only on the metrics that matter to you. One catalog spans every as-filed line item — down to granular disclosures like Deferred Tax Assets — and all 90+ calculated metrics, so a single table can put Inventory Turnover directly beside the raw Inventory balance it came from.

Switch between quarterly and annual filings, filter by date range, and save your favorite metric sets to reuse instantly across any company. Every selection feeds straight into the Charts tab, so a layout saved in either one loads in the other.

### Interactive Financial Visualizations
source: https://www.geminiq.com/features#visualizations

Turn raw financial data into clear, customizable charts that reveal the story behind the numbers. Choose the metrics that matter — revenue, margins, debt, cash flow — and set line, bar or area independently per series, so a stacked balance-sheet bar can sit under a margin line without either becoming unreadable.

Filter to specific periods, overlay the actual share price on a secondary axis to see whether the market followed the fundamentals, and apply one of five transformations — Z-Score, Min-Max, Log, Index or Abs — to put metrics of wildly different scales on the same axis. (These are data transformations, not an axis-scale toggle; there is no log/linear scale control.) Save your favorite metric sets to reuse across companies.

### Earnings Market Reaction Heat Map (Price Variance)
source: https://www.geminiq.com/features#price-variance

For each filing GeminIQ tracks the stock's price performance over 1, 2 and 3 months for 10-Qs, and 1 through 12 months for 10-Ks. Quickly gauge how investors historically reacted to new financial information — whether the market rewarded strong results or punished weak ones — and spot patterns in what academics call post-earnings-announcement drift.

A summary rail alongside the grid reduces that history to three numbers: how often the 3-month move continued in the same direction as the 1-month move versus faded or reversed, the average 1-month reaction across every filing in range, and the single best and worst quarters on record.

### Comprehensive Calculated Metrics
source: https://www.geminiq.com/features#calculated-metrics

Make apples-to-apples comparisons with 90+ industry-standard metrics, calculated directly from SEC filings with full traceability to source data. A complete view across profitability, efficiency, growth, liquidity, leverage, returns and valuation — ROIC and the full Altman Z-Score computed and recomputed with every new filing, alongside EV/EBITDA, Free Cash Flow Yield, Cash Conversion Cycle, and 3- and 5-year revenue and EPS growth.

Popular metrics surface as summary cards with year-over-year change and a sparkline, and the full table is grouped by category with every row clickable to expand into its own chart.

### Insider Transactions Tracker
source: https://www.geminiq.com/features#insider-transactions

See what company insiders are doing with their own money. GeminIQ is an insider trading tracker built directly on SEC Form 4 filings, turning raw filings into a visual timeline of purchases and sales by executives, directors and major shareholders — green bars for open-market buying, red for selling.

Switch to the Price + Transactions view to see every trade plotted on the stock's price chart, with full filing detail below: owner, relationship, title, share count and price per share. Filter down to a single insider when one executive's pattern is telling a different story than the aggregate.

### Institutional Ownership Monitoring
source: https://www.geminiq.com/features#institutional-ownership

Measure institutional participation at a high level. GeminIQ's institutional ownership tracker monitors aggregate ownership percentages using institutional ownership data taken straight from quarterly 13F filings, so you can see how much professional capital sits in a company and how that exposure evolves over time.

Toggle to the Price + Ownership view to see exactly where institutional buying and selling clustered on the price chart — green markers for quarters where ownership increased, red for quarters where it fell.

### One-Click Data Export
source: https://www.geminiq.com/features#data-export

Every dataset for a company can leave the platform in a single export instead of being copied out table by table. Toggle Company info, Financial statements, Metrics, Market reaction, Insider transactions and Institutional ownership independently, give each its own date range or apply one range to all, and see the row count each selection will produce before you download.

The result is a single .xlsx with one sheet per dataset and actual numeric values in the cells — no formatting layer to strip out and nothing to undo before your own formulas can reference it.

### Stock Screener
source: https://www.geminiq.com/features#screener

Pinpoint exact investment matches using over 100 financial metrics and up to 10 stackable filters. Apply precise logic operators — less than, greater than, between, equal to and more — to build highly targeted searches without relying on restrictive templates, and every result traces directly back to the company's original SEC filing for immediate verification.

Launch instantly from 18 pre-built strategies modeled on proven frameworks, from Benjamin Graham's Net-Net formula to Joel Greenblatt's Magic Formula. Save any filter combination for reuse, sort results by any metric you screened on, and add companies to a watchlist a full page at a time.

### Free Stock Screener (no account required)
source: https://www.geminiq.com/free-screener

GeminIQ's free stock screener is usable without an account, signup, or payment. It runs all 18 prebuilt investment strategy screens over US-listed companies and returns up to 100 matches per screen.

- **No Account Required:** No signup, no credit card, no trial clock — the screens run for anonymous visitors.
- **All 18 Prebuilt Strategies:** Magic Formula, Piotroski F-Score, Altman Z-Score Financial Safety, Buffett-Style, GARP, Deep Value, Quality Compounder, Net-Nets, Cash Rich Undervalued, High ROIC Low Debt, High Earnings Yield, High FCF Yield, Low EV/EBITDA, Low Debt High Growth, Contrarian Low Price-to-Sales, Efficient Asset Turnover, Dividend Growth, and Shareholder Yield.
- **27 Free Financial Metrics:** Liquidity, leverage, efficiency, per-share, margin, growth, valuation, and calculated values — the same metric set shown free on a public /stocks page.
- **Same SEC Sourcing:** Every value is calculated from as-filed SEC EDGAR 10-K and 10-Q XBRL data, not third-party aggregators.
- **A Results Page per Screen:** Each prebuilt screen has its own page listing the companies that currently pass it:
  - Altman Z-Score Financial Safety Screener: https://www.geminiq.com/free-screener/altman-z-score-safe
  - Buffett-Style Stock Screener: https://www.geminiq.com/free-screener/buffett-style
  - Cash Rich Undervalued Screener: https://www.geminiq.com/free-screener/cash-rich-undervalued
  - Contrarian Low Price-to-Sales Screener: https://www.geminiq.com/free-screener/contrarian-low-ps
  - Deep Value Screener: https://www.geminiq.com/free-screener/deep-value
  - Dividend Growth Screener: https://www.geminiq.com/free-screener/dividend-growth
  - Efficient Asset Turnover Screener: https://www.geminiq.com/free-screener/efficient-asset-turnover
  - GARP Screener — Growth at a Reasonable Price: https://www.geminiq.com/free-screener/garp-screener
  - High Earnings Yield Screener: https://www.geminiq.com/free-screener/high-earnings-yield
  - High Free Cash Flow Yield Screener: https://www.geminiq.com/free-screener/high-fcf-yield
  - High ROIC Low Debt Screener: https://www.geminiq.com/free-screener/high-roic-low-debt
  - Low Debt High Growth Screener: https://www.geminiq.com/free-screener/low-debt-high-growth
  - Low EV/EBITDA Screener: https://www.geminiq.com/free-screener/low-ev-ebitda
  - Magic Formula Stocks: https://www.geminiq.com/free-screener/magic-formula
  - Net-Net Stocks: https://www.geminiq.com/free-screener/net-net-stocks
  - Piotroski F-Score Screener: https://www.geminiq.com/free-screener/piotroski-f-score
  - Quality Compounder Screener: https://www.geminiq.com/free-screener/quality-compounder
  - Shareholder Yield Screener: https://www.geminiq.com/free-screener/shareholder-yield
- **Upgrade Path:** The paid screener (https://www.geminiq.com/screener) adds custom filter building across 100+ metrics with up to 10 stackable filters.

### Comps: A Dedicated Peer Analysis Workspace
source: https://www.geminiq.com/features#comps

Comparable company analysis has its own home. Comps is a dedicated stock comparison tool for benchmarking a company against its peers: start from a subject company and add peers one at a time, each with its own selectable filing period. Sets are saved and named, and metric layouts save separately to reapply to any future group.

Three views handle the actual comps analysis. The table puts every company side by side with the subject frozen and a statistic column you choose — Median, Mean or Harmonic Mean — plus a premium/discount readout on every row, and any peer can be excluded from the statistic without leaving the table. The distribution view plots each metric as a full peer range with an interquartile box, mean and median markers and per-company dots. Charts renders every metric as a small-multiple time series with all peers together.

For valuation multiples, each distribution ends with a plain sentence rather than another chart: the peer 25th-75th percentile range applied to the subject's own EBITDA or earnings, the enterprise value or market cap that implies, and whether the actual figure sits above, below or inside it.

### Watchlists: From Ticker List to Live Investment Thesis
source: https://www.geminiq.com/features#custom-watchlists

A stock watchlist isn't just a list of tickers you're keeping an eye on — it's a record of why you're watching them and what would change your mind. Track your positions in Core, Monitoring or Speculative buckets across as many named lists as you run, with any metric or line item addable as a column.

Set a price target and direction on every position and watch the live spread against it, record your investment thesis, price target rationale and kill criteria in a dedicated field, and configure built-in stock alerts for a price hitting your target, a move over 15% in a week, or a new 10-K or 10-Q filed in the last two weeks — surfaced as table badges and through a notification bell that evaluates every list at once.

Expand any row for a valuation percentile measured against that company's own history, a searchable chart of any metric on that company, and compact insider, institutional and price summaries scoped to the position.

---

## Section 4b: GeminIQ Financial Ratios & Metrics — Authoritative Definitions
source: https://www.geminiq.com/metrics

GeminIQ defines 77 financial ratios and metrics calculated directly from SEC EDGAR XBRL filings for US-listed public companies. Each definition below identifies how the metric is derived from raw XBRL-tagged data and how GeminIQ calculates it. Where a metric has a benchmark section, the figures are GeminIQ's own measurements across US companies, dated in the text.

### Calculated Values
source: https://www.geminiq.com/metrics/calculated-values

#### Adjusted Net Income
source: https://www.geminiq.com/metrics/calculated-values/adjusted-net-income

**Definition:**
Adjusted net income adds stock-based compensation expense back to GAAP net income. It represents what the company would have earned if all employee compensation were paid in cash rather than equity. This metric is useful for understanding the underlying cash-generation capacity of the business, though it should not be treated as a replacement for GAAP net income because SBC dilution is a real economic cost.

**Formula:**
Adjusted Net Income = Net Income (TTM) + Stock-Based Compensation (TTM)

**How GeminIQ Calculates This Metric:**
GeminIQ adds TTM SBC to TTM net income, both from SEC filings.

**FAQ:**
### Why add back SBC to get adjusted net income?

SBC is a non-cash charge that reduces GAAP earnings but does not reduce cash. Adding it back shows the cash-equivalent earnings of the business. This is especially useful when comparing companies with very different compensation structures — a company that pays employees mostly in cash will have similar GAAP and adjusted earnings, while one that relies heavily on equity compensation will show a large gap.

### Is adjusted net income the same as non-GAAP net income?

Not necessarily. Companies report their own non-GAAP figures with various adjustments (restructuring charges, acquisition costs, etc.). GeminIQ's adjusted net income makes only one adjustment — adding back SBC — which is clearly defined and consistent across all companies.

### Why might adjusted net income differ between platforms?

Different platforms make different adjustments. GeminIQ adds back only SBC. Other platforms may also add back amortization of intangibles, one-time charges, or other items. Always check which adjustments are included.

#### Billings
source: https://www.geminiq.com/metrics/calculated-values/billings

**Definition:**
Billings measures the total amount a company billed customers during the trailing twelve months, regardless of when the revenue will be recognized. It is calculated by adding the change in deferred revenue to recognized revenue. Billings is a key metric for subscription and SaaS businesses because it captures demand timing better than recognized revenue, which may lag behind actual customer commitment.

When billings exceed revenue, the company is collecting cash faster than it recognizes revenue — deferred revenue is growing. When billings fall below revenue, deferred revenue is being drawn down.

**Formula:**
Billings = Revenue (TTM) + (Deferred Revenue current − Deferred Revenue 1 year ago)

**How GeminIQ Calculates This Metric:**
GeminIQ computes billings as TTM revenue plus the year-over-year change in deferred revenue (current balance minus the balance four quarters ago). All inputs are from SEC filings.

**FAQ:**
### Why is billings important for SaaS companies?

Revenue recognition for subscription businesses is spread over the contract term. A company that signs a $120K annual contract in January recognizes $10K/month in revenue. Billings captures the full $120K at the time of the contract, giving a more real-time view of demand. Billings growth that exceeds revenue growth indicates accelerating demand.

### What does it mean when billings are less than revenue?

It means the company is recognizing more revenue than it is billing — deferred revenue is declining. This can happen when contract renewals slow down, customers shift to shorter terms, or a large cohort of multi-year contracts signed in the past are being recognized now without equivalent new signings.

### Why might billings differ between platforms?

Billings is a derived metric, not a reported line item. Different platforms may calculate it differently. GeminIQ uses the year-over-year change in the deferred revenue balance (shifted by four quarters, not a rolling sum) added to TTM revenue.

#### Free Cash Flow
source: https://www.geminiq.com/metrics/calculated-values/free-cash-flow

**Definition:**
Free cash flow is the cash a company generates from operations after deducting capital expenditures. It represents the cash available for dividends, share buybacks, debt repayment, acquisitions, or any other discretionary use. FCF is widely considered the most important measure of a company's financial flexibility because it reflects actual cash rather than accounting profit.

**Formula:**
Free Cash Flow = Operating Cash Flow (TTM) − Capital Expenditures (TTM)

**What is a good free cash flow?**
FCF should be positive and growing for a mature company. Negative FCF is acceptable for high-growth companies investing heavily in capacity, but it should be funded by existing cash or reasonable debt rather than continuous equity dilution. The most useful metric is the FCF margin (FCF/Revenue), which shows how efficiently the company converts revenue to free cash.

### Why might FCF differ between platforms?

Capex definitions are the primary source. Some platforms include software development costs or acquisitions. GeminIQ uses Payments to Acquire Property Plant and Equipment from the cash flow statement as the primary capex input.

**How GeminIQ Calculates This Metric:**
GeminIQ subtracts TTM capex from TTM operating cash flow, both from the cash flow statement in SEC filings.

**FAQ:**
### Why is FCF more important than net income?

Net income includes non-cash items and does not account for the capital expenditures needed to maintain or grow the business. A company can report positive net income while spending more on capex than it generates in operating cash — meaning it is actually consuming cash despite being "profitable." FCF strips all of that away and shows the true cash surplus.

### What is a good free cash flow?

FCF should be positive and growing for a mature company. Negative FCF is acceptable for high-growth companies investing heavily in capacity, but it should be funded by existing cash or reasonable debt rather than continuous equity dilution. The most useful metric is the FCF margin (FCF/Revenue), which shows how efficiently the company converts revenue to free cash.

### Why might FCF differ between platforms?

Capex definitions are the primary source. Some platforms include software development costs or acquisitions. GeminIQ uses Payments to Acquire Property Plant and Equipment from the cash flow statement as the primary capex input.

#### Invested Capital
source: https://www.geminiq.com/metrics/calculated-values/invested-capital

**Definition:**
Invested capital is the total amount of money a company has raised from lenders and shareholders and put to work in the business. Every dollar of it is capital the business is expected to earn a return on. Because it excludes cash the company is holding but not actually using, it answers a narrower question than total assets: how much capital is genuinely deployed in operations.

Invested capital represents the total capital invested in a business by both debt and equity holders, net of excess cash. It is the denominator in the ROIC calculation and measures the total amount of capital the company must generate returns on.

GeminIQ uses the financing approach, which calculates invested capital from the right side of the balance sheet: Total Equity + Total Debt − Excess Cash. Excess cash is the cash balance above what the company needs for day-to-day operations (estimated as 2% of annual revenue). The financing approach is more robust than the operating approach because it does not break when companies reclassify assets on their balance sheet.

**Formula:**
Invested Capital = Total Equity + Total Debt − Excess Cash

Where:

- Total Debt = Short-Term Debt + Long-Term Debt
- Operating Cash = min(Cash, 2% of Revenue TTM)
- Excess Cash = Cash − Operating Cash (floored at zero)

**How GeminIQ Calculates This Metric:**
GeminIQ computes invested capital using the financing approach with all inputs from SEC filings. The 2% operating cash assumption is a standard rule of thumb used in corporate finance to estimate the minimum cash needed for operations.

**FAQ:**
### What is the difference between invested capital and ROE's equity base?

Return on equity divides net income by shareholders' equity alone — only the capital shareholders themselves contributed. Invested capital adds debt to that equity base and then subtracts excess cash, so it measures the full pool of capital funding operations regardless of who supplied it. The practical difference matters: a company can raise its ROE simply by borrowing money and buying back stock, because that shrinks the equity denominator without improving the underlying business. Invested capital does not move that way, since the new debt goes straight back into the denominator. That is why return on invested capital is generally the harder and more honest test of business quality.

### What is a typical invested capital figure?

There is no universal benchmark, because invested capital is a dollar amount rather than a ratio — it scales with company size, so a large industrial and a small software business are not comparable on the raw number. It becomes meaningful in two ways: as the denominator of ROIC, where the return it generates is what gets compared across companies, and as a trend over time for a single company, where a capital base growing faster than operating profit signals that new investment is not yet earning its keep.

### Why subtract excess cash from invested capital?

Cash sitting on the balance sheet above what is needed for operations is not being invested in the business — it is a financial asset. Including it in invested capital would understate ROIC by inflating the denominator with capital that is not generating operating returns. Subtracting excess cash isolates the capital actually deployed in operations.

### What is the financing approach vs. the operating approach?

The financing approach calculates invested capital from the funding side (equity + debt − excess cash). The operating approach calculates it from the asset side (operating assets − operating liabilities). Both should produce similar results, but the financing approach is more robust because it does not require classifying every individual asset as operating or financial.

### Why might invested capital differ significantly between platforms?

Invested capital is one of the most methodology-sensitive financial metrics. Different excess cash assumptions, different debt definitions, and different approaches (financing vs. operating) can produce materially different invested capital figures for the same company. GeminIQ uses the financing approach with a 2% operating cash rule and as-filed debt and equity values.

### What is the invested capital formula?

Invested capital equals total equity plus total debt, minus excess cash — the operating capital lenders and shareholders have put to work. GeminIQ treats cash above roughly 2% of trailing twelve-month revenue as excess, since that cash is not needed to run the business.

#### Net Debt
source: https://www.geminiq.com/metrics/calculated-values/net-debt

**Definition:**
Net debt is total financial debt minus cash and cash equivalents. It represents the company's debt burden after accounting for the cash available to pay it down. A positive net debt means the company owes more than it has in cash. A negative net debt (net cash position) means the company has more cash than debt.

**Formula:**
Net Debt = Total Debt − Cash and Cash Equivalents

Where Total Debt = Short-Term Debt + Long-Term Debt (if not reported as a single line item)

**How GeminIQ Calculates This Metric:**
GeminIQ computes net debt using as-filed balance sheet values. If Total Debt is reported directly, GeminIQ uses it; otherwise it sums Short-Term Debt and Long-Term Debt. Cash and Cash Equivalents is then subtracted.

**FAQ:**
### What does negative net debt mean?

Negative net debt means the company has more cash than debt — a net cash position. This is common among large technology companies and indicates strong financial flexibility.

### Is net debt or total debt more useful?

Net debt is generally more useful because it accounts for the cash available to service or repay debt. A company with $10B in debt and $8B in cash has a very different risk profile than one with $10B in debt and $500M in cash. Net debt captures this distinction.

### Why might net debt differ between platforms?

Definitions of total debt (total liabilities vs. interest-bearing debt only) and cash (including or excluding restricted cash) are the primary sources. GeminIQ uses Short-Term Debt + Long-Term Debt as filed, minus Cash and Cash Equivalents as filed.

#### Stock-Based Compensation
source: https://www.geminiq.com/metrics/calculated-values/stock-based-compensation

**Definition:**
Stock-based compensation (SBC) is the trailing twelve-month expense a company recognizes for equity awards granted to employees — including stock options, restricted stock units, and employee stock purchase plans. It is reported as a non-cash operating expense on the income statement and added back as a non-cash adjustment on the cash flow statement.

**Formula:**
Stock-Based Compensation (TTM) = Sum of quarterly SBC over the trailing four quarters

**How GeminIQ Calculates This Metric:**
GeminIQ sums the four most recent quarters of stock-based compensation as reported in the company's SEC filings via the XBRL-tagged Share Based Compensation or Allocated Share Based Compensation Expense line item.

**FAQ:**
### Why is SBC tracked separately from other expenses?

SBC is non-cash — it does not reduce the company's bank account. However, it does dilute existing shareholders by increasing the share count. Tracking SBC separately lets investors assess how much of the company's operating expense structure is cash-based versus equity-based.

### How should investors think about SBC?

SBC is a real cost even though it is non-cash. The cost is borne by existing shareholders through dilution. When evaluating a company's profitability, consider both GAAP earnings (which include SBC) and adjusted earnings (which exclude it), and track the dilution ratio to understand the cumulative impact.

### Why might SBC values differ between platforms?

Some companies report SBC in different locations — some break it out on the income statement, others only disclose it in the cash flow statement adjustments. GeminIQ uses the XBRL-tagged value, which captures the reported figure regardless of where on the statements it appears.

#### Total Debt
source: https://www.geminiq.com/metrics/calculated-values/total-debt

**Definition:**
Total debt is the full amount of interest-bearing borrowings a company owes, combining both short-term and long-term obligations. It captures everything the business must eventually repay to lenders — bonds, notes, loans, commercial paper, and lease obligations — regardless of when those payments come due. It is the starting point for most leverage analysis and the gross figure from which net debt is derived.

Total debt matters because it defines the scale of a company's fixed financial commitments. Two companies can report the same equity, but the one carrying far more total debt has less flexibility, higher interest costs, and more sensitivity to rising rates or falling revenue.

**Formula:**
Total Debt = Reported Total Debt, or Short-Term Debt + Long-Term Debt

**How GeminIQ Calculates This Metric:**
GeminIQ prefers the total-debt figure a company reports directly on its balance sheet. When a filer does not report debt as a single combined line, GeminIQ sums Short-Term Debt and Long-Term Debt from its canonical mapping — which includes current maturities of long-term debt, commercial paper, revolving credit, and finance and operating lease obligations. All inputs come from XBRL-tagged SEC filings. Net Debt is then computed as Total Debt − Cash and Cash Equivalents.

**FAQ:**
### What is the difference between total debt and net debt?

Total debt is the gross amount of borrowings a company owes. Net debt subtracts cash and cash equivalents, showing what would remain if the company used its available cash to pay down debt. A company with large cash reserves can have high total debt but low — or even negative — net debt.

### What is included in total debt?

GeminIQ's total debt includes short-term borrowings, the current portion of long-term debt, long-term notes and bonds, and lease liabilities (finance and operating). It reflects interest-bearing and lease obligations rather than all liabilities such as accounts payable or deferred revenue.

### Why might total debt differ from a filing's headline "debt" line?

Companies present debt differently — some report a single total, others break it into many line items, and treatment of leases and current maturities varies. GeminIQ uses the reported total when available and otherwise reconstructs it by summing canonical short-term and long-term debt, so the figure may differ from any single label in the filing.

### Efficiency and Turnover Ratios
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios

#### Asset Turnover
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/asset-turnover

**Definition:**
Asset turnover, also called the asset turnover ratio, measures how efficiently a company uses its assets to generate revenue. It divides trailing twelve-month revenue by average total assets. A higher ratio means the company generates more revenue per dollar of assets, indicating greater asset efficiency.

Asset turnover is a key component of DuPont analysis, where ROE is decomposed into profit margin × asset turnover × financial leverage. Companies can pursue either a high-margin, low-turnover strategy (luxury goods, software) or a low-margin, high-turnover strategy (grocery, retail). Neither is inherently better — what matters is whether the combined effect produces adequate returns on capital.

**Formula:**
Asset Turnover = Revenue (TTM) / Average Total Assets

**What is a good asset turnover ratio?**
It varies dramatically by industry. Grocery and retail companies often have asset turnover above 2.0 (they generate $2+ of revenue per $1 of assets). Software and pharmaceutical companies may be below 0.5 because their assets include expensive IP and R&D. Compare only within the same industry.

### How does asset turnover relate to profitability?

Asset turnover and profit margin are inversely related in many industries — high-turnover businesses (groceries, fast food) tend to have low margins, and high-margin businesses (luxury, software) tend to have low turnover. The product of the two (margin × turnover) drives return on assets.

### Why might asset turnover differ between platforms?

The denominator depends on whether the platform uses ending assets or average assets, and how it sources total assets. Some aggregators adjust total assets during normalization, which changes the denominator. GeminIQ uses average total assets from the as-filed balance sheet.

### What does a low asset turnover indicate?

A low asset turnover means the company generates little revenue for each dollar of assets. It can reflect a capital-intensive business model such as utilities, telecom, or real estate, or it can signal underused capacity, idle cash, or assets acquired that are not yet producing sales. A falling ratio within the same company is the more useful warning sign.

### What is the difference between asset turnover and fixed asset turnover?

Asset turnover divides revenue by total assets, including cash, receivables, inventory, and intangibles. Fixed asset turnover divides revenue by net property, plant and equipment only, so it measures how productively a company uses its physical plant. Fixed asset turnover is the better tool for manufacturers; total asset turnover is the one used in DuPont analysis.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM revenue by the average of current-period and year-ago Total Assets, all sourced from SEC filings.

**FAQ:**
### What is a good asset turnover ratio?

It varies dramatically by industry. Grocery and retail companies often have asset turnover above 2.0 (they generate $2+ of revenue per $1 of assets). Software and pharmaceutical companies may be below 0.5 because their assets include expensive IP and R&D. Compare only within the same industry.

### How does asset turnover relate to profitability?

Asset turnover and profit margin are inversely related in many industries — high-turnover businesses (groceries, fast food) tend to have low margins, and high-margin businesses (luxury, software) tend to have low turnover. The product of the two (margin × turnover) drives return on assets.

### Why might asset turnover differ between platforms?

The denominator depends on whether the platform uses ending assets or average assets, and how it sources total assets. Some aggregators adjust total assets during normalization, which changes the denominator. GeminIQ uses average total assets from the as-filed balance sheet.

### What does a low asset turnover indicate?

A low asset turnover means the company generates little revenue for each dollar of assets. It can reflect a capital-intensive business model such as utilities, telecom, or real estate, or it can signal underused capacity, idle cash, or assets acquired that are not yet producing sales. A falling ratio within the same company is the more useful warning sign.

### What is the difference between asset turnover and fixed asset turnover?

Asset turnover divides revenue by total assets, including cash, receivables, inventory, and intangibles. Fixed asset turnover divides revenue by net property, plant and equipment only, so it measures how productively a company uses its physical plant. Fixed asset turnover is the better tool for manufacturers; total asset turnover is the one used in DuPont analysis.

#### Cash Conversion Cycle (CCC)
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle

**Definition:**
The cash conversion cycle measures how many days it takes a company to convert its investments in inventory and other resources into cash flows from sales. It combines three efficiency metrics: how long inventory sits before being sold (DIO), how long receivables take to collect (DSO), and how long the company can delay paying its own suppliers (DPO).

A shorter CCC means the company converts inventory to cash faster and can reinvest that cash sooner. A negative CCC — common for companies like Amazon and Dell — means the company collects cash from customers before it has to pay its suppliers, effectively using supplier financing to fund operations.

**Formula:**
Cash Conversion Cycle = DSO + DIO − DPO

Which expands to:
CCC = Days Sales Outstanding + Days Inventory Outstanding − Days Payables Outstanding

**What is a good cash conversion cycle?**
Lower is generally better. Capital-light businesses may have CCCs near zero or negative. Manufacturing companies typically range from 30 to 90 days. A negative CCC means the company collects cash before paying suppliers — a sign of operational efficiency and bargaining power.

### What does a lengthening cash conversion cycle indicate?

A CCC that is increasing over time means the company needs more working capital per dollar of revenue. This can indicate slowing inventory movement, slower collections, or shortened supplier payment terms — all of which consume cash and may signal deteriorating operating efficiency.

### Why might CCC values differ between platforms?

Since CCC is derived from three separate ratios, any difference in the underlying inputs (COGS, revenue, inventory, receivables, payables) propagates through. GeminIQ uses as-filed values for all inputs.

**How GeminIQ Calculates This Metric:**
GeminIQ sums DSO and DIO and subtracts DPO, where each component is derived from the corresponding turnover ratio using TTM COGS, TTM revenue, and average balance sheet values from SEC filings.

**FAQ:**
### What is a good cash conversion cycle?

Lower is generally better. Capital-light businesses may have CCCs near zero or negative. Manufacturing companies typically range from 30 to 90 days. A negative CCC means the company collects cash before paying suppliers — a sign of operational efficiency and bargaining power.

### What does a lengthening cash conversion cycle indicate?

A CCC that is increasing over time means the company needs more working capital per dollar of revenue. This can indicate slowing inventory movement, slower collections, or shortened supplier payment terms — all of which consume cash and may signal deteriorating operating efficiency.

### Why might CCC values differ between platforms?

Since CCC is derived from three separate ratios, any difference in the underlying inputs (COGS, revenue, inventory, receivables, payables) propagates through. GeminIQ uses as-filed values for all inputs.

#### Days Inventory Outstanding (DIO)
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding

**Definition:**
Days Inventory Outstanding measures the average number of days a company holds inventory before selling it. Lower DIO means faster inventory movement. Rising DIO may indicate slowing demand, overstocking, or potential obsolescence.

**Formula:**
DIO = 365 / Inventory Turnover (TTM)

**What is a good DIO?**
Grocery and perishable goods companies should have DIO under 30 days. General retail typically ranges from 45 to 90 days. Heavy manufacturing and aerospace can exceed 120 days due to long production cycles. Compare only within the same industry.

### What does rising DIO indicate?

Rising DIO can mean the company is building inventory ahead of expected demand (positive), or that sales have slowed and inventory is accumulating (negative). Pair DIO trends with revenue growth to distinguish between the two.

### Why might DIO differ between platforms?

DIO depends on how inventory and COGS are sourced. GeminIQ uses as-filed values from SEC filings.

**How GeminIQ Calculates This Metric:**
Derived from inventory turnover, which uses TTM COGS divided by average inventory from SEC filings.

**FAQ:**
### What is a good DIO?

Grocery and perishable goods companies should have DIO under 30 days. General retail typically ranges from 45 to 90 days. Heavy manufacturing and aerospace can exceed 120 days due to long production cycles. Compare only within the same industry.

### What does rising DIO indicate?

Rising DIO can mean the company is building inventory ahead of expected demand (positive), or that sales have slowed and inventory is accumulating (negative). Pair DIO trends with revenue growth to distinguish between the two.

### Why might DIO differ between platforms?

DIO depends on how inventory and COGS are sourced. GeminIQ uses as-filed values from SEC filings.

#### Days Payables Outstanding (DPO)
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-payables-outstanding

**Definition:**
Days payable outstanding (DPO), also written days payables outstanding, measures the average number of days a company takes to pay its suppliers. Higher DPO means the company is taking longer to pay, which preserves cash for other uses. Companies with strong bargaining power (like large retailers) often have high DPO because they can negotiate extended payment terms.

**Formula:**
DPO = 365 / Payables Turnover (TTM)

**How GeminIQ Calculates This Metric:**
Derived from payables turnover, which uses TTM COGS divided by average accounts payable from SEC filings.

**FAQ:**
### Is higher or lower DPO better?

Higher DPO preserves cash and can indicate negotiating power with suppliers. However, excessively high or rapidly rising DPO may indicate the company is stretching payments due to cash flow problems. The best interpretation comes from comparing DPO to industry norms and tracking the trend.

### How does DPO relate to the cash conversion cycle?

DPO is subtracted from the sum of DSO and DIO to calculate the cash conversion cycle. Higher DPO reduces the cash conversion cycle, meaning the company needs less working capital.

### Why might DPO differ between platforms?

DPO depends on how COGS and accounts payable are defined. GeminIQ uses as-filed values.

#### Days Sales Outstanding (DSO)
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-sales-outstanding

**Definition:**
Days Sales Outstanding measures the average number of days it takes a company to collect payment after making a sale. Lower DSO means faster collection. Rising DSO over time may indicate deteriorating receivables quality or loosening credit standards.

**Formula:**
DSO = 365 / Receivables Turnover (TTM)

**What is a good DSO?**
DSO should roughly match the company's stated credit terms. A company offering net-30 terms should have DSO around 30-45 days. DSO significantly above credit terms indicates collection delays. B2B companies typically have higher DSO (45-90 days) than B2C companies (under 30 days).

### What does rising DSO indicate?

Rising DSO can indicate the company is extending more generous credit terms to maintain sales, customers are paying more slowly, or receivables quality is deteriorating. It deserves investigation but is not automatically a red flag — seasonal businesses often have naturally fluctuating DSO.

### Why might DSO differ between platforms?

DSO is derived from receivables turnover, so any difference in how revenue or receivables are measured propagates into DSO. GeminIQ uses as-filed values for both inputs.

### What is DSO with an example?

DSO is the average number of days a company takes to collect payment after a sale. A company with $10 million of accounts receivable and $80 million of annual revenue has a DSO of 10 / 80 × 365 ≈ 46 days, meaning customers pay, on average, about a month and a half after being invoiced.

### Is DSO the same as accounts receivable turnover?

They measure the same thing from opposite directions. Receivables turnover counts how many times a year receivables are collected; DSO converts that into days. DSO equals 365 divided by receivables turnover, so a turnover of 8 corresponds to a DSO of about 46 days.

### How do you calculate DSO, DIO, and DPO?

DSO is accounts receivable divided by revenue, times 365. DIO is inventory divided by cost of goods sold, times 365. DPO is accounts payable divided by cost of goods sold, times 365. Together they give the cash conversion cycle: DSO + DIO − DPO.

**How GeminIQ Calculates This Metric:**
Derived from receivables turnover, which uses TTM revenue divided by average receivables from SEC filings.

**FAQ:**
### What is a good DSO?

DSO should roughly match the company's stated credit terms. A company offering net-30 terms should have DSO around 30-45 days. DSO significantly above credit terms indicates collection delays. B2B companies typically have higher DSO (45-90 days) than B2C companies (under 30 days).

### What does rising DSO indicate?

Rising DSO can indicate the company is extending more generous credit terms to maintain sales, customers are paying more slowly, or receivables quality is deteriorating. It deserves investigation but is not automatically a red flag — seasonal businesses often have naturally fluctuating DSO.

### Why might DSO differ between platforms?

DSO is derived from receivables turnover, so any difference in how revenue or receivables are measured propagates into DSO. GeminIQ uses as-filed values for both inputs.

### What is DSO with an example?

DSO is the average number of days a company takes to collect payment after a sale. A company with $10 million of accounts receivable and $80 million of annual revenue has a DSO of 10 / 80 × 365 ≈ 46 days, meaning customers pay, on average, about a month and a half after being invoiced.

### Is DSO the same as accounts receivable turnover?

They measure the same thing from opposite directions. Receivables turnover counts how many times a year receivables are collected; DSO converts that into days. DSO equals 365 divided by receivables turnover, so a turnover of 8 corresponds to a DSO of about 46 days.

### How do you calculate DSO, DIO, and DPO?

DSO is accounts receivable divided by revenue, times 365. DIO is inventory divided by cost of goods sold, times 365. DPO is accounts payable divided by cost of goods sold, times 365. Together they give the cash conversion cycle: DSO + DIO − DPO.

#### Deferred Revenue to Revenue
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/deferred-revenue-to-revenue

**Definition:**
Deferred revenue to revenue measures how much of a company's revenue backlog exists as prepayments from customers relative to its trailing twelve-month revenue. High deferred revenue relative to revenue indicates the company collects payment significantly before delivering its products or services — common in subscription software, insurance, and prepaid services businesses.

Rising deferred revenue relative to revenue can be a positive signal, indicating growing customer prepayments and forward visibility. Declining ratios may indicate customers are shifting to shorter commitment periods or the company is recognizing revenue faster.

**Formula:**
Deferred Revenue to Revenue = Deferred Revenue / Revenue (TTM)

**How GeminIQ Calculates This Metric:**
GeminIQ divides the current-period Deferred Revenue balance from the balance sheet by trailing twelve-month Revenue. Both are sourced from SEC filings.

**FAQ:**
### What does a high deferred revenue to revenue ratio mean?

A high ratio means customers are paying well in advance of receiving the product or service. For SaaS companies, a deferred revenue balance equal to 25-50% of annual revenue is common and healthy. It provides forward revenue visibility and indicates customer commitment.

### Is deferred revenue the same as a backlog?

Not exactly. Deferred revenue is a liability on the balance sheet representing cash received for services not yet delivered. A backlog can include contracted future revenue that has not yet been billed or collected. Deferred revenue is a subset of backlog — the portion already paid for.

### Why might this metric differ between platforms?

Some companies use different XBRL tags for deferred revenue (Deferred Revenue, Contract with Customer Liability, Unearned Revenue). GeminIQ checks for all recognized variants and uses the first available as-filed value.

#### Inventory Turnover
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/inventory-turnover

**Definition:**
Inventory turnover, or the inventory turnover ratio, measures how many times a company sells and replaces its inventory during a period. It divides cost of goods sold by average inventory. A higher ratio means inventory is moving quickly — the company is selling product efficiently. A lower ratio may indicate overstocking, slow sales, or obsolescence risk.

This metric is critical for retail, manufacturing, and distribution businesses where inventory is a major asset. For companies that do not carry physical inventory (software, services), this metric is not applicable.

**Formula:**
Inventory Turnover = Cost of Goods Sold (TTM) / Average Inventory

**What is a good inventory turnover ratio?**
Grocery stores and fast-moving consumer goods companies may have turnover above 12 (inventory cycles once a month). General retailers typically range from 4 to 8. Heavy manufacturing may be 2 to 4. The key is comparing against industry peers and tracking trends — declining turnover may signal demand weakness.

### How does inventory turnover relate to days inventory outstanding?

Days Inventory Outstanding (DIO) is simply 365 divided by inventory turnover. It converts the turnover ratio into the average number of days inventory sits before being sold. Both metrics tell the same story in different formats.

### Why might inventory turnover differ between platforms?

The numerator (COGS) can differ if the platform uses a different line item — some use cost of revenue, which may include service delivery costs, while COGS is specifically the cost of goods. Inventory definitions can also vary if the aggregator reclassifies items. GeminIQ uses the as-filed values for both.

### How do you calculate average inventory?

Add the inventory balance at the start of the period to the balance at the end and divide by two. GeminIQ uses the current period and the same period one year earlier, which matches the twelve months of cost of goods sold in the numerator.

### What does an inventory turnover of 1.5 mean?

The company sold and replaced its average inventory one and a half times over the year, so goods sat in inventory for about 243 days (365 divided by 1.5). That is normal for aircraft, heavy equipment, or luxury goods, but would signal overstocking at a grocer or apparel retailer.

### Can you calculate inventory turnover with revenue instead of COGS?

Yes, as revenue divided by average inventory, but the result is higher and not comparable to the standard ratio. Inventory is carried at cost, so dividing it into revenue mixes a cost figure with a figure that includes the profit markup. Use cost of goods sold whenever the company reports it.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM COGS by the average of current-period and year-ago inventory, sourced from SEC filings.

**FAQ:**
### What is a good inventory turnover ratio?

Grocery stores and fast-moving consumer goods companies may have turnover above 12 (inventory cycles once a month). General retailers typically range from 4 to 8. Heavy manufacturing may be 2 to 4. The key is comparing against industry peers and tracking trends — declining turnover may signal demand weakness.

### How does inventory turnover relate to days inventory outstanding?

Days Inventory Outstanding (DIO) is simply 365 divided by inventory turnover. It converts the turnover ratio into the average number of days inventory sits before being sold. Both metrics tell the same story in different formats.

### Why might inventory turnover differ between platforms?

The numerator (COGS) can differ if the platform uses a different line item — some use cost of revenue, which may include service delivery costs, while COGS is specifically the cost of goods. Inventory definitions can also vary if the aggregator reclassifies items. GeminIQ uses the as-filed values for both.

### How do you calculate average inventory?

Add the inventory balance at the start of the period to the balance at the end and divide by two. GeminIQ uses the current period and the same period one year earlier, which matches the twelve months of cost of goods sold in the numerator.

### What does an inventory turnover of 1.5 mean?

The company sold and replaced its average inventory one and a half times over the year, so goods sat in inventory for about 243 days (365 divided by 1.5). That is normal for aircraft, heavy equipment, or luxury goods, but would signal overstocking at a grocer or apparel retailer.

### Can you calculate inventory turnover with revenue instead of COGS?

Yes, as revenue divided by average inventory, but the result is higher and not comparable to the standard ratio. Inventory is carried at cost, so dividing it into revenue mixes a cost figure with a figure that includes the profit markup. Use cost of goods sold whenever the company reports it.

#### Payables Turnover
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/payables-turnover

**Definition:**
Payables turnover, also called the accounts payable turnover ratio, measures how quickly a company pays its suppliers. It divides cost of goods sold by average accounts payable. A higher ratio means the company pays suppliers faster. A lower ratio means it takes longer to pay, which can be a sign of either cash flow management (using suppliers as a source of short-term financing) or liquidity problems.

**Formula:**
Payables Turnover = Cost of Goods Sold (TTM) / Average Accounts Payable

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM COGS by the average of current and year-ago accounts payable, both from SEC filings.

**FAQ:**
### Is a higher or lower payables turnover better?

Neither is inherently better. Paying suppliers quickly (high turnover) may earn early-payment discounts and maintain good relationships. Paying slowly (low turnover) preserves cash for other uses. The optimal level depends on the company's negotiating power, discount terms, and cash position. The most useful comparison is against industry peers and the company's own trend.

### How does payables turnover relate to the cash conversion cycle?

Days Payables Outstanding (365 / Payables Turnover) is subtracted in the cash conversion cycle calculation. Longer payables periods reduce the cash conversion cycle, meaning the company needs less working capital to fund operations.

### Why might payables turnover differ between platforms?

The numerator (COGS vs. cost of revenue) and denominator (accounts payable definitions) are both sensitive to normalization. GeminIQ uses the as-filed values for both.

#### Receivables Turnover
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/receivables-turnover

**Definition:**
Receivables turnover, also called the accounts receivable turnover ratio, measures how quickly a company collects cash from its credit customers. It divides trailing twelve-month revenue by average accounts receivable. A higher ratio means the company is collecting more efficiently. A declining ratio may indicate loosening credit terms, deteriorating customer quality, or collection problems.

**Formula:**
Receivables Turnover = Revenue (TTM) / Average Accounts Receivable

**What is a good receivables turnover ratio?**
It depends on the company's credit terms. A company offering net-30 terms should have receivables turnover around 12 (collecting monthly). Net-60 terms imply turnover around 6. Ratios significantly below what the credit terms suggest may indicate collection problems.

### How does this relate to days sales outstanding?

Days Sales Outstanding (DSO) is 365 divided by receivables turnover. It tells you the average number of days between a sale and when cash is collected. Both metrics tell the same story.

### Why might receivables turnover differ between platforms?

Some platforms use gross receivables, others use net receivables (after allowance for doubtful accounts). GeminIQ uses Accounts Receivable Net as reported in the filing.

**How GeminIQ Calculates This Metric:**
GeminIQ uses TTM net revenue divided by the average of current and year-ago receivables from the balance sheet, both sourced from SEC filings.

**FAQ:**
### What is a good receivables turnover ratio?

It depends on the company's credit terms. A company offering net-30 terms should have receivables turnover around 12 (collecting monthly). Net-60 terms imply turnover around 6. Ratios significantly below what the credit terms suggest may indicate collection problems.

### How does this relate to days sales outstanding?

Days Sales Outstanding (DSO) is 365 divided by receivables turnover. It tells you the average number of days between a sale and when cash is collected. Both metrics tell the same story.

### Why might receivables turnover differ between platforms?

Some platforms use gross receivables, others use net receivables (after allowance for doubtful accounts). GeminIQ uses Accounts Receivable Net as reported in the filing.

#### Working Capital to Revenue
source: https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/working-capital-to-revenue

**Definition:**
Working capital to revenue expresses working capital as a percentage of trailing twelve-month revenue. It measures how much working capital a company needs per dollar of annual sales. A lower ratio indicates the business model requires less working capital to operate, which generally means more efficient cash generation.

**Formula:**
Working Capital to Revenue = Working Capital / Revenue (TTM)

**What is a good working capital to revenue ratio?**
Below 10% is considered efficient for most industries. Above 20% may indicate excess capital is tied up in operations. Negative values (common for subscription and retail businesses) indicate the company generates cash from its operating cycle faster than it needs to reinvest it.

### Why use TTM revenue in the denominator?

Working capital is a balance sheet snapshot, while revenue is a flow measure. Using TTM revenue (four quarters) rather than quarterly revenue properly scales the two — dividing a balance sheet figure by a single quarter's revenue would overstate the ratio by roughly 4x.

### Why might this ratio differ between platforms?

Any difference in how current assets, current liabilities, or revenue are classified propagates into this ratio. GeminIQ uses as-filed values for all inputs.

**How GeminIQ Calculates This Metric:**
GeminIQ divides Working Capital (Current Assets − Current Liabilities) by trailing twelve-month Revenue, both from SEC filings. The denominator uses TTM revenue to properly scale the quarterly balance sheet figure against a full year of sales.

**FAQ:**
### What is a good working capital to revenue ratio?

Below 10% is considered efficient for most industries. Above 20% may indicate excess capital is tied up in operations. Negative values (common for subscription and retail businesses) indicate the company generates cash from its operating cycle faster than it needs to reinvest it.

### Why use TTM revenue in the denominator?

Working capital is a balance sheet snapshot, while revenue is a flow measure. Using TTM revenue (four quarters) rather than quarterly revenue properly scales the two — dividing a balance sheet figure by a single quarter's revenue would overstate the ratio by roughly 4x.

### Why might this ratio differ between platforms?

Any difference in how current assets, current liabilities, or revenue are classified propagates into this ratio. GeminIQ uses as-filed values for all inputs.

### Growth Metrics
source: https://www.geminiq.com/metrics/growth-metrics

#### Deferred Revenue Growth
source: https://www.geminiq.com/metrics/growth-metrics/deferred-revenue-growth

**Definition:**
Deferred revenue growth measures the percentage change in a company's deferred revenue balance compared to one year ago. For subscription and prepaid-service businesses, deferred revenue growth is a leading indicator of future recognized revenue. Rising deferred revenue typically means customers are prepaying at a faster rate, which signals growing demand and forward revenue visibility.

**Formula:**
Deferred Revenue Growth = (Deferred Revenue current / Deferred Revenue 1 year ago) − 1

**How GeminIQ Calculates This Metric:**
GeminIQ compares the current-period deferred revenue balance to the same quarter one year prior, both from the balance sheet as filed.

**FAQ:**
### Why is deferred revenue growth important for SaaS companies?

Deferred revenue represents cash collected for services not yet delivered. Growth in this balance means customers are signing longer contracts or pre-paying at higher rates, which provides future revenue visibility and reduces churn risk. Many SaaS analysts consider deferred revenue growth alongside billings growth as a leading indicator.

### Can deferred revenue growth be misleading?

Yes, if the growth is driven by changes in billing terms rather than actual demand. A company that shifts from monthly to annual billing will see a spike in deferred revenue without any change in underlying demand. Context matters.

### Why might deferred revenue growth differ between platforms?

Companies use different XBRL tags for deferred revenue. GeminIQ checks Deferred Revenue, Contract with Customer Liability Current, and Unearned Revenue in priority order.

#### Dividends Paid Growth
source: https://www.geminiq.com/metrics/growth-metrics/dividends-paid-growth

**Definition:**
Dividends paid growth, often called the dividend growth rate, measures the percentage change in a company's trailing twelve-month cash dividends compared to [1 year / 3 years / 5 years] ago. Consistent dividend growth is a hallmark of financially healthy, shareholder-friendly companies. Many dividend-focused investment strategies specifically screen for companies with multi-year records of consecutive dividend increases.

**Formula:**
Dividends Paid Growth [1Y] = (Dividends Paid TTM current / Dividends Paid TTM 1 year ago) − 1
Dividends Paid Growth [3Y] = (Dividends Paid TTM current / Dividends Paid TTM 3 years ago) − 1
Dividends Paid Growth [5Y] = (Dividends Paid TTM current / Dividends Paid TTM 5 years ago) − 1

**What is a good dividend growth rate?**
1-year growth above 5% is solid for established dividend payers. 5-year growth above 25% (roughly 4.5% annualized) indicates a strong track record. Dividend growth should be sustainable relative to earnings growth — if dividends grow faster than earnings for extended periods, the payout ratio rises toward unsustainable levels.

### How does dividend growth relate to the payout ratio?

If dividends grow faster than earnings, the payout ratio rises. If earnings grow faster than dividends, the payout ratio falls. Sustainable dividend growth requires earnings growth that at least matches the dividend increase rate.

### Why might dividend growth differ between platforms?

Some platforms use dividends declared rather than actual cash paid. Others may include special or one-time dividends. GeminIQ uses Dividends Paid from the cash flow statement, which reflects actual cash distributed.

**How GeminIQ Calculates This Metric:**
GeminIQ uses TTM dividends paid from the cash flow statement compared to the same TTM period [1/3/5] years prior.

**FAQ:**
### What is a good dividend growth rate?

1-year growth above 5% is solid for established dividend payers. 5-year growth above 25% (roughly 4.5% annualized) indicates a strong track record. Dividend growth should be sustainable relative to earnings growth — if dividends grow faster than earnings for extended periods, the payout ratio rises toward unsustainable levels.

### How does dividend growth relate to the payout ratio?

If dividends grow faster than earnings, the payout ratio rises. If earnings grow faster than dividends, the payout ratio falls. Sustainable dividend growth requires earnings growth that at least matches the dividend increase rate.

### Why might dividend growth differ between platforms?

Some platforms use dividends declared rather than actual cash paid. Others may include special or one-time dividends. GeminIQ uses Dividends Paid from the cash flow statement, which reflects actual cash distributed.

#### Earnings Per Share Growth
source: https://www.geminiq.com/metrics/growth-metrics/earnings-per-share-growth

**Definition:**
EPS growth measures the percentage change in trailing twelve-month earnings per share. It captures both the effect of profit growth and the effect of share count changes (buybacks or dilution). A company can grow EPS even with flat net income by reducing its share count through buybacks, and conversely, a company with growing profits can see EPS stagnate if the share count is increasing through stock compensation.

**Formula:**
EPS Growth [1Y] = (EPS TTM current / EPS TTM 1 year ago) − 1
EPS Growth [3Y] = (EPS TTM current / EPS TTM 3 years ago) − 1
EPS Growth [5Y] = (EPS TTM current / EPS TTM 5 years ago) − 1

**How GeminIQ Calculates This Metric:**
GeminIQ uses TTM EPS (Net Income / Basic Shares) compared to the same metric [1/3/5] years prior. Growth is not calculated when the prior period's EPS was zero or negative.

**FAQ:**
### Why can EPS grow even when revenue is flat?

EPS is affected by three levers: revenue growth, margin expansion, and share count reduction. Share buybacks reduce the denominator, increasing EPS even when net income is unchanged. Margin expansion increases the numerator. Many mature companies deliver EPS growth primarily through buybacks and efficiency rather than revenue growth.

### Should I focus on EPS growth or revenue growth?

Both matter, and the answer depends on the company's stage. For growth companies, revenue growth is the primary signal because margins and earnings can follow later. For mature companies, EPS growth is more relevant because it reflects the return actually accruing to each share.

### Why might EPS growth differ between platforms?

EPS depends on both net income and shares outstanding. Different share count definitions (basic vs. diluted, period-end vs. weighted average) change the base EPS and therefore the growth rate. GeminIQ uses basic shares for consistency with market cap.

#### Net Income Growth
source: https://www.geminiq.com/metrics/growth-metrics/net-income-growth

**Definition:**
Net income growth measures the percentage change in a company's trailing twelve-month bottom-line profit compared to [1 year / 3 years / 5 years] ago. It reflects changes in revenue, costs, interest, taxes, and all other items that affect the final profit figure. Net income growth is inherently more volatile than revenue growth because it amplifies the effect of fixed costs — a 10% revenue increase can produce a 30% net income increase if margins expand.

**Formula:**
Net Income Growth [1Y] = (Net Income TTM current / Net Income TTM 1 year ago) − 1
Net Income Growth [3Y] = (Net Income TTM current / Net Income TTM 3 years ago) − 1
Net Income Growth [5Y] = (Net Income TTM current / Net Income TTM 5 years ago) − 1

**What is a good net income growth rate?**
Net income growth should generally keep pace with or exceed revenue growth for mature companies. If net income is growing slower than revenue, margins are compressing. If faster, margins are expanding. Growth rates above 15% annually are strong for established companies.

### Why might net income growth differ between platforms?

Net income definitions can vary — some platforms use income from continuing operations, others use total net income. Any difference in the base figure changes the growth rate. GeminIQ uses total Net Income as reported in the filing.

**How GeminIQ Calculates This Metric:**
GeminIQ uses TTM net income compared to the same TTM period [1/3/5] years prior, from SEC filings. Growth is not calculated when the prior period's net income was zero or negative, as the percentage change would be meaningless.

**FAQ:**
### Why is net income growth more volatile than revenue growth?

Operating leverage amplifies bottom-line changes. A company with 50% fixed costs will see a 10% revenue increase translate into roughly a 20% net income increase (and vice versa for declines). One-time items like tax charges, impairments, or legal settlements add further volatility.

### What is a good net income growth rate?

Net income growth should generally keep pace with or exceed revenue growth for mature companies. If net income is growing slower than revenue, margins are compressing. If faster, margins are expanding. Growth rates above 15% annually are strong for established companies.

### Why might net income growth differ between platforms?

Net income definitions can vary — some platforms use income from continuing operations, others use total net income. Any difference in the base figure changes the growth rate. GeminIQ uses total Net Income as reported in the filing.

#### Net Profit Margin Growth
source: https://www.geminiq.com/metrics/growth-metrics/net-profit-margin-growth

**Definition:**
Net profit margin growth measures the percentage change in a company's trailing twelve-month net profit margin compared to [1 year / 3 years / 5 years] ago. It reveals whether the company is becoming more or less profitable per dollar of revenue. Expanding margins indicate the company is translating a higher share of revenue into profit. Contracting margins indicate cost pressures, competitive dynamics, or strategic decisions like investment spending.

**Formula:**
Margin Growth [1Y] = (Net Profit Margin TTM current / Net Profit Margin TTM 1 year ago) − 1
Margin Growth [3Y] = (Net Profit Margin TTM current / Net Profit Margin TTM 3 years ago) − 1
Margin Growth [5Y] = (Net Profit Margin TTM current / Net Profit Margin TTM 5 years ago) − 1

**How GeminIQ Calculates This Metric:**
GeminIQ computes TTM net profit margin for the current period and [1/3/5] years prior, then calculates the percentage change.

**FAQ:**
### What does margin growth tell me that revenue growth does not?

Revenue growth shows whether the business is getting bigger. Margin growth shows whether it is getting more profitable per unit of revenue. The two can diverge — a company can grow revenue rapidly while margins compress (common in competitive markets or during investment phases) or grow slowly with expanding margins (common in mature businesses focusing on efficiency).

### Is margin growth or revenue growth more important?

Both matter, but margin trends often have a larger impact on long-term shareholder returns for mature companies. A company that can grow margins by 2 percentage points annually while maintaining revenue growth is creating significant compounding value.

### Why might margin growth differ between platforms?

Any difference in the underlying net margin calculation — different net income or revenue figures — propagates into the growth rate. GeminIQ uses as-filed values.

#### Retained Earnings Growth
source: https://www.geminiq.com/metrics/growth-metrics/retained-earnings-growth

**Definition:**
Retained earnings growth measures the percentage change in a company's accumulated retained earnings over the past year. Retained earnings represent the cumulative net income a company has earned over its entire history, minus all dividends paid to shareholders. Growth in retained earnings indicates the company is adding to its internal equity base through profitable operations.

**Formula:**
Retained Earnings Growth = (Retained Earnings current / Retained Earnings 1 year ago) − 1

**How GeminIQ Calculates This Metric:**
GeminIQ compares current retained earnings to the same quarter one year ago, from the balance sheet as filed.

**FAQ:**
### What does retained earnings growth indicate?

Positive growth means the company's cumulative profitability is increasing — it earned more in the past year than it paid out in dividends. Declining retained earnings can indicate losses or dividend payments exceeding earnings. For companies with negative retained earnings (accumulated deficit), growth means the deficit is shrinking.

### Why do some profitable companies have negative retained earnings?

Aggressive share buyback programs can reduce retained earnings below zero by increasing the treasury stock balance. Apple, for example, has had negative retained earnings in recent years not because it was unprofitable but because its buyback program was larger than its cumulative earnings.

### Why might retained earnings growth differ between platforms?

Differences stem from how the retained earnings figure is sourced. GeminIQ uses the Retained Earnings Accumulated Deficit line directly from the filing.

#### Revenue Growth
source: https://www.geminiq.com/metrics/growth-metrics/revenue-growth

**Definition:**
Revenue growth measures the percentage change in a company's trailing twelve-month revenue compared to [1 year / 3 years / 5 years] ago. It is the most fundamental growth metric and answers the basic question of whether the company's top line is expanding, contracting, or stagnating.

One-year revenue growth captures the most recent trend and is useful for identifying inflection points — accelerating or decelerating growth. Three-year growth provides a medium-term view that smooths out single-year anomalies and reveals whether the growth trajectory is sustainable. Five-year growth provides a long-term perspective that captures full business cycles and reveals the structural growth rate of the business.

Revenue growth should always be evaluated alongside margin trends. A company growing revenue at 20% but seeing margins compress may be buying growth at the expense of profitability. A company growing revenue at 8% with expanding margins may be creating more shareholder value.

**Formula:**
Revenue Growth [1Y] = (Revenue TTM current / Revenue TTM 1 year ago) − 1
Revenue Growth [3Y] = (Revenue TTM current / Revenue TTM 3 years ago) − 1
Revenue Growth [5Y] = (Revenue TTM current / Revenue TTM 5 years ago) − 1

**What is a good revenue growth rate?**
For 1-year growth: above 10% is strong for mature companies, above 20% for growth companies. For 3-year total growth: above 30% (roughly 9% annualized). For 5-year total growth: above 50% (roughly 8.5% annualized). Growth expectations vary dramatically by sector — a 5% growth rate is strong for a utility but weak for a SaaS company.

### Why use TTM revenue rather than quarterly revenue for growth calculations?

Quarterly revenue can be seasonal — a retailer's Q4 will always dwarf Q1. TTM revenue sums four quarters, which removes seasonal effects and provides a more stable, comparable growth figure. Comparing TTM-to-TTM also avoids the distortion of comparing a holiday quarter to a non-holiday quarter.

### Why might revenue growth rates differ between platforms?

Growth rates are sensitive to the exact revenue figure used. If the platform's aggregator reclassifies certain revenue items (excise taxes, gains on sales, other income) during normalization, the base revenue changes and the growth rate follows. GeminIQ uses Revenue as filed in the SEC filing.

**How GeminIQ Calculates This Metric:**
GeminIQ computes TTM revenue by summing the four most recent quarters, then compares to the same TTM period [1/3/5] years prior. All inputs are from SEC filings. The comparison is quarter-aligned (current period vs. the same quarter [4/12/20] quarters ago) to avoid seasonal distortion.

**FAQ:**
### What is a good revenue growth rate?

For 1-year growth: above 10% is strong for mature companies, above 20% for growth companies. For 3-year total growth: above 30% (roughly 9% annualized). For 5-year total growth: above 50% (roughly 8.5% annualized). Growth expectations vary dramatically by sector — a 5% growth rate is strong for a utility but weak for a SaaS company.

### Why use TTM revenue rather than quarterly revenue for growth calculations?

Quarterly revenue can be seasonal — a retailer's Q4 will always dwarf Q1. TTM revenue sums four quarters, which removes seasonal effects and provides a more stable, comparable growth figure. Comparing TTM-to-TTM also avoids the distortion of comparing a holiday quarter to a non-holiday quarter.

### Why might revenue growth rates differ between platforms?

Growth rates are sensitive to the exact revenue figure used. If the platform's aggregator reclassifies certain revenue items (excise taxes, gains on sales, other income) during normalization, the base revenue changes and the growth rate follows. GeminIQ uses Revenue as filed in the SEC filing.

#### Total Assets Growth
source: https://www.geminiq.com/metrics/growth-metrics/total-assets-growth

**Definition:**
Total assets growth measures the percentage change in a company's total asset base compared to [1 year / 3 years / 5 years] ago. Growing assets can indicate investment in future capacity, acquisitions, or organic business expansion. It can also reflect accumulating inventory or receivables that may not convert to cash. Assets growth should be evaluated alongside revenue growth — if assets are growing faster than revenue, the company's asset efficiency is declining.

**Formula:**
Total Assets Growth [1Y] = (Total Assets current / Total Assets 1 year ago) − 1
Total Assets Growth [3Y] = (Total Assets current / Total Assets 3 years ago) − 1
Total Assets Growth [5Y] = (Total Assets current / Total Assets 5 years ago) − 1

**How GeminIQ Calculates This Metric:**
GeminIQ compares current Total Assets to the same quarter [1/3/5] years prior, from SEC filings.

**FAQ:**
### What does total assets growth indicate?

Assets growth reflects the company's reinvestment in its business. When driven by productive assets like PP&E or strategic acquisitions, it can indicate future capacity. When driven by receivables or goodwill accumulation, it may be less meaningful. Compare assets growth to revenue growth to see if the investment is productive.

### Is faster assets growth always better?

Not necessarily. If assets grow faster than revenue, the company needs more capital per dollar of sales, which typically indicates declining asset efficiency. The ideal pattern is revenue growing at least as fast as assets.

### Why might total assets growth differ between platforms?

Differences stem from how total assets are derived when not reported directly. GeminIQ sums Current Assets and Non-Current Assets from the filing if Total Assets is not reported as a single line item.

### Leverage and Debt Ratios
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios

#### Altman Z-Score
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score

**Definition:**
The Altman Z-Score is a formula developed by NYU professor Edward Altman in 1968 that predicts the probability of a company entering bankruptcy within two years. It combines five financial ratios — each measuring a different dimension of financial health — into a single weighted score. Despite being over 50 years old, the Z-Score remains one of the most widely used and empirically validated measures of corporate financial distress.

The five components measure liquidity (working capital to total assets), cumulative profitability (retained earnings to total assets), operating efficiency (EBIT to total assets), market confidence (market value of equity to total liabilities), and asset productivity (revenue to total assets). Each component is weighted and summed to produce the final score.

A Z-Score above 2.99 places the company in the "safe zone" — historically, companies with scores above this threshold have a very low probability of bankruptcy. A score between 1.81 and 2.99 is the "gray zone," where the outcome is uncertain. A score below 1.81 is the "distress zone," where the probability of financial distress is elevated.

The original model was designed for publicly traded manufacturing companies. It is less reliable for financial institutions, utilities, and early-stage companies with minimal retained earnings. Despite these limitations, it remains a useful first-pass screening tool for identifying companies under financial stress.

**Formula:**
Altman Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E

Where:
A = Working Capital / Total Assets
B = Retained Earnings / Total Assets
C = EBIT (TTM) / Total Assets
D = Market Value of Equity / Total Liabilities
E = Revenue (TTM) / Total Assets

**What is a good Altman Z-Score?**
Above 2.99 is the "safe zone" — the company has strong financial health and a low probability of bankruptcy. Between 1.81 and 2.99 is the "gray zone" — financial health is uncertain and warrants further investigation. Below 1.81 is the "distress zone" — the company has elevated bankruptcy risk. These thresholds were established from Altman's original research on manufacturing companies.

### Does the Altman Z-Score work for all companies?

The original model was designed for publicly traded manufacturing companies and is most reliable for that group. Financial institutions (banks, insurance companies), utilities, and early-stage companies with minimal retained earnings may produce misleading scores. Altman later developed modified versions (Z'-Score for private companies and Z''-Score for non-manufacturing companies), but GeminIQ uses the original model as it is the most widely recognized.

### Why might Altman Z-Score values differ between platforms?

The Z-Score is a composite of five ratios, so any difference in the underlying inputs — Working Capital, Retained Earnings, Total Assets, Total Liabilities, EBIT, Revenue, or Market Value of Equity — will cause the final score to diverge. The most common sources of difference are how EBIT is derived (some platforms use operating income, which may differ from EBIT if non-operating items are classified differently) and how market capitalization is calculated (share count × price, where the choice of share count date and price date can vary).

**How GeminIQ Calculates This Metric:**
GeminIQ computes all five components using XBRL-tagged SEC filing data. Working Capital, Retained Earnings, Total Assets, Total Liabilities, EBIT, and Revenue are all sourced directly from the company's filings. Market Value of Equity is calculated as the closing stock price on the filing period end date multiplied by basic shares outstanding. When market cap data is not available, GeminIQ uses book equity (Total Shareholders' Equity) as a fallback for component D, which produces a more conservative estimate.

**FAQ:**
### What is a good Altman Z-Score?

Above 2.99 is the "safe zone" — the company has strong financial health and a low probability of bankruptcy. Between 1.81 and 2.99 is the "gray zone" — financial health is uncertain and warrants further investigation. Below 1.81 is the "distress zone" — the company has elevated bankruptcy risk. These thresholds were established from Altman's original research on manufacturing companies.

### Does the Altman Z-Score work for all companies?

The original model was designed for publicly traded manufacturing companies and is most reliable for that group. Financial institutions (banks, insurance companies), utilities, and early-stage companies with minimal retained earnings may produce misleading scores. Altman later developed modified versions (Z'-Score for private companies and Z''-Score for non-manufacturing companies), but GeminIQ uses the original model as it is the most widely recognized.

### Why might Altman Z-Score values differ between platforms?

The Z-Score is a composite of five ratios, so any difference in the underlying inputs — Working Capital, Retained Earnings, Total Assets, Total Liabilities, EBIT, Revenue, or Market Value of Equity — will cause the final score to diverge. The most common sources of difference are how EBIT is derived (some platforms use operating income, which may differ from EBIT if non-operating items are classified differently) and how market capitalization is calculated (share count × price, where the choice of share count date and price date can vary).

#### Debt Ratio
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/debt-ratio

**Definition:**
The debt ratio measures the proportion of a company's total assets that are financed by debt (total liabilities). It is calculated by dividing total liabilities by total assets. The result is a number between 0 and 1, where 0 means no liabilities at all and 1 means the company's assets are entirely funded by debt with no equity cushion.

The debt ratio is a simpler and more bounded alternative to the debt-to-equity ratio. Because it uses total assets in the denominator rather than equity, the debt ratio cannot become negative or undefined when a company has negative equity, making it usable across all companies regardless of capital structure.

A debt ratio of 0.5 means half of the company's assets are financed by liabilities and half by equity. A ratio above 0.6 is generally considered moderately leveraged, and above 0.8 is highly leveraged. As with all leverage metrics, the appropriate level depends on the industry — capital-intensive industries with stable cash flows support higher ratios than cyclical businesses.

**Formula:**
Debt Ratio = Total Liabilities / Total Assets

**What is a good debt ratio?**
A debt ratio below 0.4 is generally considered low leverage, 0.4 to 0.6 is moderate, and above 0.6 is high. However, these thresholds are industry-dependent. Utilities, banks, and REITs routinely operate above 0.7 because their business models produce predictable cash flows that support higher leverage. Technology companies and consumer brands often operate below 0.4.

### How does the debt ratio differ from debt-to-equity?

The debt ratio divides liabilities by total assets, producing a bounded number between 0 and 1 that is easy to interpret and compare. The debt-to-equity ratio divides liabilities by equity, which can produce very large numbers for heavily leveraged companies and is undefined when equity is negative. The debt ratio is more stable across different capital structures.

### Why might the debt ratio on GeminIQ differ from other platforms?

Differences arise when the platform's data aggregator reclassifies items between liabilities, equity, and assets during normalization. Any reclassification that moves an item from equity to liabilities (or vice versa) directly changes the debt ratio. GeminIQ uses the company's as-filed balance sheet without reclassification.

### How do you calculate the debt ratio?

Divide total liabilities by total assets. A company with $40 billion of liabilities and $100 billion of assets has a debt ratio of 0.40, meaning 40% of its assets are financed by liabilities and 60% by shareholders' equity.

### What does a debt ratio of 0.5 mean?

A debt ratio of 0.5 means half of the company's assets are financed by liabilities and half by shareholders' equity. For most industrial and consumer companies that is a moderate level of leverage; banks, insurers, and utilities routinely run far higher because liabilities are central to their business models.

### Is the debt ratio the same as the debt-to-income ratio?

No. The debt ratio is a corporate balance-sheet measure, total liabilities divided by total assets. Debt-to-income is a personal-finance measure lenders use for individuals, monthly debt payments divided by gross monthly income. They share a name but answer different questions.

**How GeminIQ Calculates This Metric:**
GeminIQ computes the debt ratio using Total Liabilities and Total Assets directly from the company's SEC filing. If Total Assets is not reported directly, GeminIQ derives it from the sum of Current Assets and Non-Current Assets as filed. If Total Liabilities is not reported directly, it is derived from Current Liabilities plus Non-Current Liabilities. All derivations use as-filed values.

**FAQ:**
### What is a good debt ratio?

A debt ratio below 0.4 is generally considered low leverage, 0.4 to 0.6 is moderate, and above 0.6 is high. However, these thresholds are industry-dependent. Utilities, banks, and REITs routinely operate above 0.7 because their business models produce predictable cash flows that support higher leverage. Technology companies and consumer brands often operate below 0.4.

### How does the debt ratio differ from debt-to-equity?

The debt ratio divides liabilities by total assets, producing a bounded number between 0 and 1 that is easy to interpret and compare. The debt-to-equity ratio divides liabilities by equity, which can produce very large numbers for heavily leveraged companies and is undefined when equity is negative. The debt ratio is more stable across different capital structures.

### Why might the debt ratio on GeminIQ differ from other platforms?

Differences arise when the platform's data aggregator reclassifies items between liabilities, equity, and assets during normalization. Any reclassification that moves an item from equity to liabilities (or vice versa) directly changes the debt ratio. GeminIQ uses the company's as-filed balance sheet without reclassification.

### How do you calculate the debt ratio?

Divide total liabilities by total assets. A company with $40 billion of liabilities and $100 billion of assets has a debt ratio of 0.40, meaning 40% of its assets are financed by liabilities and 60% by shareholders' equity.

### What does a debt ratio of 0.5 mean?

A debt ratio of 0.5 means half of the company's assets are financed by liabilities and half by shareholders' equity. For most industrial and consumer companies that is a moderate level of leverage; banks, insurers, and utilities routinely run far higher because liabilities are central to their business models.

### Is the debt ratio the same as the debt-to-income ratio?

No. The debt ratio is a corporate balance-sheet measure, total liabilities divided by total assets. Debt-to-income is a personal-finance measure lenders use for individuals, monthly debt payments divided by gross monthly income. They share a name but answer different questions.

#### Debt-to-EBITDA
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/debt-to-ebitda

**Definition:**
Debt-to-EBITDA measures how many years it would take a company to pay off its total debt using its earnings before interest, taxes, depreciation, and amortization, assuming all EBITDA were devoted to debt repayment. It is one of the most widely used leverage metrics in credit analysis and private equity because it combines balance sheet information (the debt load) with income statement information (the earning power) into a single number.

A company with a debt-to-EBITDA ratio of 3.0 would theoretically need three years of its current EBITDA to pay off all debt. In practice, companies do not devote all EBITDA to debt repayment — they also need to pay taxes, interest, capital expenditures, and potentially dividends. But the ratio provides a standardized, industry-comparable measure of leverage relative to earnings capacity.

Most investment-grade companies maintain debt-to-EBITDA ratios below 3.0. Ratios between 3.0 and 5.0 are considered moderate leverage and are common in leveraged buyouts and capital-intensive industries. Ratios above 6.0 are generally considered high leverage and carry significant refinancing risk if earnings decline.

This metric uses trailing twelve months (TTM) EBITDA, which sums the four most recent quarters to smooth out seasonal effects.

**Formula:**
Debt-to-EBITDA = Total Debt / EBITDA (TTM)

Where:

- Total Debt = Short-Term Debt + Long-Term Debt (if total debt not reported directly)
- EBITDA = EBIT + Depreciation & Amortization (if EBITDA not reported directly)
- TTM = sum of the four most recent quarters

**What is a good debt-to-EBITDA ratio?**
Below 2.0 is considered low leverage for most industries. Between 2.0 and 4.0 is moderate. Above 5.0 is high and may signal elevated financial risk. Credit rating agencies like Moody's and S&P use debt-to-EBITDA as a primary input to corporate credit ratings. Investment-grade companies typically maintain ratios below 3.5.

### How does debt-to-EBITDA differ from net debt-to-EBITDA?

Debt-to-EBITDA uses total debt in the numerator. Net debt-to-EBITDA subtracts cash and cash equivalents from total debt before dividing. Net debt-to-EBITDA is more generous because it gives credit for the cash the company has available to reduce its debt burden. A company with $5B in debt and $3B in cash has a very different risk profile than one with $5B in debt and no cash, even though their debt-to-EBITDA ratios are the same.

### Why might debt-to-EBITDA differ between GeminIQ and other platforms?

The two most common sources of discrepancy are how Total Debt is defined and how EBITDA is calculated. Some aggregators include operating lease liabilities in total debt; others do not. Some calculate EBITDA using operating income rather than EBIT, which excludes non-operating items differently. GeminIQ uses the as-filed debt values and derives EBITDA from the company's reported EBIT plus D&A when EBITDA is not directly reported.

**How GeminIQ Calculates This Metric:**
GeminIQ uses Total Debt from the balance sheet divided by trailing twelve-month EBITDA. If the company does not report Total Debt as a single line item, GeminIQ sums Short-Term Debt and Long-Term Debt from the balance sheet. If EBITDA is not reported directly, it is derived from EBIT plus Depreciation and Amortization. All inputs are sourced from XBRL-tagged SEC filings, preserving the company's own debt classifications.

**FAQ:**
### What is a good debt-to-EBITDA ratio?

Below 2.0 is considered low leverage for most industries. Between 2.0 and 4.0 is moderate. Above 5.0 is high and may signal elevated financial risk. Credit rating agencies like Moody's and S&P use debt-to-EBITDA as a primary input to corporate credit ratings. Investment-grade companies typically maintain ratios below 3.5.

### How does debt-to-EBITDA differ from net debt-to-EBITDA?

Debt-to-EBITDA uses total debt in the numerator. Net debt-to-EBITDA subtracts cash and cash equivalents from total debt before dividing. Net debt-to-EBITDA is more generous because it gives credit for the cash the company has available to reduce its debt burden. A company with $5B in debt and $3B in cash has a very different risk profile than one with $5B in debt and no cash, even though their debt-to-EBITDA ratios are the same.

### Why might debt-to-EBITDA differ between GeminIQ and other platforms?

The two most common sources of discrepancy are how Total Debt is defined and how EBITDA is calculated. Some aggregators include operating lease liabilities in total debt; others do not. Some calculate EBITDA using operating income rather than EBIT, which excludes non-operating items differently. GeminIQ uses the as-filed debt values and derives EBITDA from the company's reported EBIT plus D&A when EBITDA is not directly reported.

#### Debt-to-Equity Ratio
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/debt-to-equity-ratio

**Definition:**
The debt-to-equity ratio measures how much a company relies on borrowed money relative to shareholder equity to finance its assets. It divides total liabilities by total shareholders' equity. A higher ratio means the company is more leveraged — more of its asset base is financed by debt than by equity.

This is one of the most widely used measures of financial risk because it captures the fundamental balance between what the company owes and what its shareholders own. A debt-to-equity ratio of 1.0 means liabilities and equity are equal. Above 1.0, the company has more debt than equity. Below 1.0, equity exceeds debt.

The acceptable range varies dramatically by industry. Utilities and REITs routinely operate with debt-to-equity ratios above 2.0 because their stable cash flows support higher leverage. Technology companies and consumer brands often have ratios below 0.5 because their business models are less capital-intensive. Banks and financial institutions have fundamentally different balance sheet structures and should not be compared to non-financial companies using this metric.

One important nuance: some highly profitable companies like Apple and Starbucks have negative equity due to aggressive share buyback programs that push accumulated deficit below zero. In those cases, the debt-to-equity ratio becomes mathematically meaningless (negative or extremely large) and should not be used as a risk indicator.

**Formula:**
Debt-to-Equity Ratio = Total Liabilities / Total Shareholders' Equity

**What Is a Good Debt-to-Equity Ratio?**
GeminIQ calculates debt-to-equity using total liabilities, so its values run higher than versions that count only borrowings. On that basis, the median for US companies with a market capitalization above $2 billion is 1.06, and the middle half fall between 0.48 and 2.18. About 26% are above 2.0, and about 6% have negative shareholders' equity, which makes the ratio meaningless.

| Industry | Median | Middle 50% |
| --- | --- | --- |
| Pharma & biotech | 0.33 | 0.11 – 1.07 |
| Medical devices | 0.52 | 0.29 – 1.31 |
| Semiconductors & hardware | 0.70 | 0.28 – 1.51 |
| Oil & gas | 0.81 | 0.48 – 1.34 |
| Industrial manufacturing | 0.87 | 0.46 – 1.56 |
| Software & IT services | 0.94 | 0.44 – 1.95 |
| Food & beverage | 0.97 | 0.46 – 1.84 |
| Utilities | 1.06 | 0.36 – 2.44 |
| Telecom & media | 1.20 | 0.58 – 3.48 |
| Transportation | 1.21 | 0.67 – 2.74 |
| Retail | 1.81 | 0.93 – 2.89 |
| Insurance | 2.44 | 1.33 – 3.47 |

Businesses with steady, predictable cash flows, such as utilities, retailers, and insurers, can carry more liabilities relative to equity. Insurers in particular sit high because policyholder reserves are liabilities. Research-driven companies such as pharmaceutical, biotech, and medical device makers, and most semiconductor firms, rely mainly on equity.

A reading above the industry range is worth investigating, but so is the trend: a ratio climbing year after year signals rising financial risk even when the level still looks ordinary. Large buybacks can also shrink equity and push the ratio up without any new borrowing. Figures are GeminIQ calculations across US companies that file with the SEC, using each company's latest reported period as of September 2026. The middle 50% runs from the 25th to the 75th percentile. The industry table groups companies by SIC code and includes those above $300 million in market capitalization.

**How GeminIQ Calculates This Metric:**
GeminIQ uses Total Liabilities and Total Shareholders' Equity directly from the company's filed balance sheet. These are among the most commonly reclassified items during data normalization — aggregators may move minority interests, preferred equity, or certain hybrid instruments between liabilities and equity, which directly changes this ratio. GeminIQ preserves the company's as-filed classification.

**FAQ:**
### What is a good debt-to-equity ratio?


On GeminIQ's total-liabilities basis, the median for US companies above $2 billion in market cap is 1.06, with the middle half between 0.48 and 2.18. Research-driven industries such as pharmaceuticals run far lower, while retailers, utilities, and insurers run higher. A rising trend deserves investigation regardless of the level.

### How does debt-to-equity differ from the debt ratio?

The debt-to-equity ratio compares total liabilities to equity (Liabilities / Equity), while the debt ratio compares total liabilities to total assets (Liabilities / Assets). The debt ratio is always between 0 and 1 for a company with positive equity, making it easier to compare across companies. The debt-to-equity ratio can be any positive number and amplifies differences in leverage, making it more sensitive to changes.

### What does a negative debt-to-equity ratio mean?

A negative ratio usually means the company has negative shareholders' equity, which occurs when accumulated losses or aggressive share buybacks push the equity balance below zero. This does not necessarily mean the company is financially distressed — Apple and Starbucks have both operated with negative equity while generating enormous cash flows. When equity is negative, the debt-to-equity ratio loses its interpretive value and other leverage metrics like debt-to-EBITDA are more useful.

#### Interest Coverage Ratio
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/interest-coverage-ratio

**Definition:**
The interest coverage ratio measures how easily a company can pay interest on its outstanding debt from its operating earnings. It divides EBIT (earnings before interest and taxes) by interest expense. A higher ratio means the company generates more operating profit relative to its interest obligations, indicating lower financial risk.

An interest coverage ratio of 5.0 means the company's operating earnings are five times its interest expense — it could absorb an 80% decline in operating earnings and still cover its interest payments. A ratio below 1.5 is generally considered risky, and a ratio below 1.0 means the company is not generating enough operating income to cover its interest expense, which is a significant warning sign.

This metric is especially important during periods of rising interest rates, when companies with floating-rate debt see their interest expense increase while their earnings may be flat or declining. The interest coverage ratio is a standard input to credit ratings and debt covenants.

**Formula:**
Interest Coverage Ratio = EBIT (TTM) / Interest Expense (TTM)

**What is a good interest coverage ratio?**
Above 5.0 is generally considered strong. Between 2.0 and 5.0 is adequate for most industries. Below 1.5 indicates potential difficulty meeting interest obligations. Credit rating agencies typically consider ratios below 2.5 as a negative factor in investment-grade ratings.

### What does an interest coverage ratio below 1.0 mean?

A ratio below 1.0 means the company's operating earnings are insufficient to cover its interest expense. The company must use other sources — cash reserves, asset sales, or additional borrowing — to make its interest payments. This is a serious warning sign that may indicate financial distress, though it can be temporary during cyclical downturns for companies with strong balance sheets and adequate cash reserves.

### Why might interest coverage ratios differ between platforms?

The numerator (EBIT) and denominator (Interest Expense) are both sensitive to normalization decisions. Some aggregators use operating income rather than EBIT, which may exclude non-operating items differently. Some include capitalized interest in interest expense, others do not. GeminIQ uses the as-filed values for both and derives EBIT from Net Income + Income Tax + Interest Expense when it is not reported directly.

**How GeminIQ Calculates This Metric:**
GeminIQ divides trailing twelve-month EBIT by trailing twelve-month Interest Expense, both sourced directly from the company's SEC filings. If EBIT is not reported directly, it is derived from Net Income + Income Tax Expense + Interest Expense. Interest Expense uses the as-filed value, which may or may not include capitalized interest depending on how the company reports it.

**FAQ:**
### What is a good interest coverage ratio?

Above 5.0 is generally considered strong. Between 2.0 and 5.0 is adequate for most industries. Below 1.5 indicates potential difficulty meeting interest obligations. Credit rating agencies typically consider ratios below 2.5 as a negative factor in investment-grade ratings.

### What does an interest coverage ratio below 1.0 mean?

A ratio below 1.0 means the company's operating earnings are insufficient to cover its interest expense. The company must use other sources — cash reserves, asset sales, or additional borrowing — to make its interest payments. This is a serious warning sign that may indicate financial distress, though it can be temporary during cyclical downturns for companies with strong balance sheets and adequate cash reserves.

### Why might interest coverage ratios differ between platforms?

The numerator (EBIT) and denominator (Interest Expense) are both sensitive to normalization decisions. Some aggregators use operating income rather than EBIT, which may exclude non-operating items differently. Some include capitalized interest in interest expense, others do not. GeminIQ uses the as-filed values for both and derives EBIT from Net Income + Income Tax + Interest Expense when it is not reported directly.

#### Net Debt-to-EBITDA
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-ebitda

**Definition:**
Net debt-to-EBITDA measures how many years of earnings it would take a company to pay off its debt, after crediting it for the cash it already holds. Below 1.0 is low leverage, between 1.0 and 3.0 is moderate, and above 4.0 is high.

Net debt-to-EBITDA refines the standard debt-to-EBITDA ratio by subtracting cash and cash equivalents from total debt before dividing by EBITDA. This gives credit to companies that hold significant cash reserves, producing a more realistic picture of their effective leverage.

A company with $10B in total debt and $6B in cash has $4B in net debt — a fundamentally different risk profile than a company with $10B in debt and $500M in cash. The net debt-to-EBITDA ratio captures this difference while the standard debt-to-EBITDA ratio does not.

A negative net debt-to-EBITDA ratio means the company has more cash than debt — it is in a net cash position. Companies like Alphabet, Meta, and many large technology firms frequently have negative net debt. This is generally a sign of financial strength, though persistently holding excess cash can also signal a lack of productive investment opportunities.

The benchmark tiers are a starting point, not a verdict. Above 5.0 a company generally depends on continued refinancing access rather than its own earnings to service the obligation. But a regulated utility at 4.5 with contracted revenue is a different proposition than a cyclical manufacturer at the same ratio heading into a downturn, and the ratio alone does not distinguish them. Stability of the denominator matters as much as the size of the numerator: leverage against volatile EBITDA is riskier at every tier than the same leverage against a contracted revenue stream. The trend also outranks the level — a company moving from 4.2 to 3.1 across three years is deleveraging under its own power, while a company sitting flat at 3.1 for the same three years is doing something different, and the two look identical in a single-period screen.

**Formula:**
Net Debt-to-EBITDA = (Total Debt − Cash and Cash Equivalents) / EBITDA (TTM)

**What Is a Good Net Debt-to-EBITDA Ratio?**
A good net debt-to-EBITDA ratio depends on the sector, and most companies run far below the 3x figure often quoted as a universal limit. Across 4,100 non-financial US companies, the median net debt-to-EBITDA is 0.34x and the middle half fall between -0.41x and 2.18x. Utilities, transportation, and communications companies run a median of 2.32x, roughly six times the median manufacturer.

| Sector | Companies | Median | Middle 50% |
| --- | --- | --- | --- |
| Transportation, communications & utilities | 345 | 2.32x | 0.00x – 5.00x |
| Construction | 68 | 0.60x | -0.36x – 3.00x |
| Wholesale trade | 115 | 0.59x | -0.23x – 2.81x |
| Manufacturing | 2,059 | 0.38x | -0.27x – 1.77x |
| Mining | 238 | 0.36x | -0.32x – 1.81x |
| Retail trade | 235 | 0.08x | -0.55x – 2.13x |
| Services | 1,004 | 0.05x | -0.85x – 2.14x |
| Agriculture, forestry & fishing | 36 | -0.03x | -1.05x – 0.93x |
| All non-financial companies | 4,100 | 0.34x | -0.41x – 2.18x |

Regulated utilities sit at the top because rate-based, contracted revenue lets them service far more debt per dollar of EBITDA than a cyclical business could. PG&E runs 12.24x and American Electric Power 9.41x without being in distress. At the other end, companies with more cash than debt have negative ratios: GameStop's is -8.40x and Airbnb's -6.05x. Compare a company with its own sector's row, not with a single threshold. A manufacturer at 2x carries more leverage than most of its peers; a utility at 2x is running lean.

Figures are GeminIQ calculations as of September 2026, using each company's latest trailing-twelve-month filing within the prior fifteen months. Banks and insurers are excluded because leverage is part of their business model. Sectors are SIC divisions, the top and bottom 1% of each sector are trimmed, and the middle 50% runs from the 25th to the 75th percentile. Construction, wholesale trade, and agriculture have fewer than 200 companies, so treat their medians as directional.

**How GeminIQ Calculates This Metric:**
GeminIQ computes net debt by subtracting Cash and Cash Equivalents from Total Debt (using the as-filed balance sheet values), then divides by trailing twelve-month EBITDA. All inputs come directly from the company's SEC filings via their XBRL tags.

One convention is applied across every company in the database: total debt as filed including lease obligations, cash and cash equivalents as filed without investment securities, and trailing twelve-month EBITDA. The resulting figure will not match every other platform. It will mean the same thing for every company in the universe, which is the property that makes a leverage screen worth running at all.

The ratio rests on an assumption it never states: that the cash on the balance sheet could actually be applied to the debt. Three situations break that assumption. Banks and regulated financial institutions hold large cash balances because regulators require it, so netting reserve cash against debt describes a transaction that is not legally permitted. Companies mid-acquisition hold cash earmarked for a deal announced but not closed, and the net debt figure will jump the quarter the transaction settles — not because leverage changed, but because the cash left. Companies with significant international operations may hold cash in subsidiaries where repatriation carries a tax cost or legal restriction. In all three cases the gross debt-to-EBITDA ratio is the more conservative and more honest read, which is one reason lenders write covenants against the gross figure.

**FAQ:**
### What is a good net debt-to-EBITDA ratio?

Below 1.0 is low leverage. Between 1.0 and 3.0 is moderate and describes most healthy businesses carrying deliberate debt. Above 4.0 is high. The median non-financial US company runs just 0.34x, while utilities, transportation, and communications companies run a median of 2.32x. Industry context modifies all three: regulated utilities and infrastructure businesses sustain higher ratios against contracted revenue, while cyclical businesses with volatile EBITDA are riskier at every level. A negative value means the company holds more cash than debt and is in a net cash position — common among large technology companies. For credit analysis purposes, net debt-to-EBITDA is often preferred over gross debt-to-EBITDA because it reflects the company's actual financial flexibility.

### What is the net debt-to-EBITDA formula?

Net Debt-to-EBITDA = (Total Debt − Cash and Cash Equivalents) ÷ EBITDA (TTM). Total debt covers short-term borrowings, current maturities, long-term notes and bonds, and lease obligations. Cash and cash equivalents is the as-filed balance sheet line, excluding short-term investments and restricted cash.

### What does a negative net debt-to-EBITDA ratio mean?

It means the company holds more cash and cash equivalents than total debt — a net cash position — and could retire its entire debt load from the balance sheet with money left over. The reflexive read is fortress strength, and often that read is correct. But cash accumulating on a balance sheet is also capital not deployed into the business, and a company that cannot find internal projects clearing its cost of capital will pile up cash by default rather than by strategy. Reading the ratio against return on invested capital separates the two. One mechanical warning: a negative ratio produced by negative EBITDA is not a net cash position at all — it is a distressed company with the same sign in front of the number. Confirm the denominator is positive before interpreting any negative leverage ratio.

### Is net debt-to-EBITDA better than debt-to-EBITDA?

Neither is better in general; they answer different questions. The gross ratio measures the maximum claim on the business and is what lenders write covenants against. The net ratio measures practical financial flexibility. The gross figure is more conservative and more appropriate whenever the cash is restricted, committed, or held for regulatory reasons.

### Does net debt include operating leases?

That depends on the platform. Under ASC 842 operating leases appear on the balance sheet as lease liabilities, and whether a source counts them as debt is a methodology choice with no standard answer. GeminIQ includes finance and operating lease obligations in Total Debt, which produces a higher ratio for lease-heavy businesses than a source that excludes them.

### When is net debt-to-EBITDA misleading?

The ratio can be misleading for companies that hold large cash balances for regulatory reasons (banks), for pending acquisitions (companies in M&A), or in restricted accounts (international subsidiaries with repatriation constraints). In these cases, the cash on the balance sheet is not truly available to pay down debt, and the gross debt-to-EBITDA ratio may be a more accurate picture of leverage.

### Why might this ratio differ between financial platforms?

A divergence of a full turn between two sources is unremarkable, and it is almost never a data error. Three methodology decisions compound. The debt definition is the largest — whether operating lease liabilities count as debt is the dominant variable, worth a full turn or more for lease-heavy businesses. The cash definition is next: cash and cash equivalents alone, cash plus short-term investments, or total cash and investments including long-dated securities are three defensible choices, and the spread between them widens precisely for the cash-rich companies where the ratio matters most. The EBITDA definition is third. GeminIQ uses the as-filed values for both total debt and cash, matching the company's own balance sheet presentation.

#### Net Debt-to-Equity
source: https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-equity

**Definition:**
Net debt-to-equity measures a company's net financial leverage by comparing its net debt position (total debt minus cash) to total shareholders' equity. It refines the standard debt-to-equity ratio by giving credit for cash holdings, producing a more realistic view of how leveraged the company actually is after accounting for its liquid reserves.

A company with high gross debt but also high cash balances may look heavily leveraged on a standard debt-to-equity basis but much more moderate on a net debt-to-equity basis. This distinction is particularly important for technology companies and other businesses that accumulate large cash positions while also maintaining debt for tax or strategic reasons.

A negative net debt-to-equity ratio means the company has more cash than debt and is in a net cash position relative to its equity base.

**Formula:**
Net Debt-to-Equity = (Total Debt − Cash and Cash Equivalents) / Total Shareholders' Equity

**What is a good net debt-to-equity ratio?**
Below 0.5 is generally considered low leverage. Between 0.5 and 1.5 is moderate. Above 2.0 is high. A negative value means the company has more cash than debt. As with all leverage ratios, the appropriate level depends on the industry — utilities and REITs operate at higher ratios than technology companies.

### How does net debt-to-equity compare to regular debt-to-equity?

The standard debt-to-equity ratio uses total liabilities in the numerator, which includes both financial debt and operating liabilities like accounts payable. Net debt-to-equity uses only financial debt minus cash, which isolates the company's financing leverage from its operating obligations. For companies with large cash balances, the two ratios can tell very different stories.

### Why might net debt-to-equity values differ between platforms?

The most common source of variation is how total debt is defined. Some platforms use total liabilities (which includes operating liabilities), while others use only interest-bearing debt. GeminIQ sums Short-Term Debt and Long-Term Debt from the balance sheet if Total Debt is not reported as a single line item, then subtracts Cash and Cash Equivalents.

**How GeminIQ Calculates This Metric:**
GeminIQ computes net debt by subtracting Cash and Cash Equivalents from Total Debt, then divides by Total Shareholders' Equity. All inputs are sourced directly from the company's SEC-filed balance sheet via their XBRL tags, preserving the company's own classifications of debt, cash, and equity.

**FAQ:**
### What is a good net debt-to-equity ratio?

Below 0.5 is generally considered low leverage. Between 0.5 and 1.5 is moderate. Above 2.0 is high. A negative value means the company has more cash than debt. As with all leverage ratios, the appropriate level depends on the industry — utilities and REITs operate at higher ratios than technology companies.

### How does net debt-to-equity compare to regular debt-to-equity?

The standard debt-to-equity ratio uses total liabilities in the numerator, which includes both financial debt and operating liabilities like accounts payable. Net debt-to-equity uses only financial debt minus cash, which isolates the company's financing leverage from its operating obligations. For companies with large cash balances, the two ratios can tell very different stories.

### Why might net debt-to-equity values differ between platforms?

The most common source of variation is how total debt is defined. Some platforms use total liabilities (which includes operating liabilities), while others use only interest-bearing debt. GeminIQ sums Short-Term Debt and Long-Term Debt from the balance sheet if Total Debt is not reported as a single line item, then subtracts Cash and Cash Equivalents.

### Liquidity Ratios
source: https://www.geminiq.com/metrics/liquidity-ratios

#### Cash Ratio
source: https://www.geminiq.com/metrics/liquidity-ratios/cash-ratio

**Definition:**
The cash ratio is the most conservative liquidity ratio. It measures a company's ability to pay off its current liabilities using only its cash and cash equivalents — no receivables, no inventory, no other current assets. It answers the strictest possible version of the liquidity question: if the company had to pay every short-term obligation right now using only the cash it has on hand, could it?

In practice, a cash ratio of 1.0 or higher is uncommon outside of technology companies and financial institutions. Most businesses do not keep enough idle cash to cover all current liabilities because doing so would be capital-inefficient — that cash could be invested in the business, used to pay down debt, or returned to shareholders. A low cash ratio is not inherently concerning as long as the company has adequate receivables turnover and inventory liquidity to bridge the gap.

The cash ratio is most useful as a stress test metric and in comparing companies within capital-intensive industries where receivables quality may be uncertain. It is also useful for evaluating companies going through financial distress, where the ability to meet obligations from cash on hand is the most relevant measure.

**Formula:**
Cash Ratio = Cash and Cash Equivalents / Current Liabilities

**What is a good cash ratio?**
Most healthy companies operate with cash ratios between 0.2 and 0.5, meaning they hold enough cash to cover 20% to 50% of their current liabilities. A cash ratio above 1.0 is rare and often indicates either a company hoarding cash for a strategic reason (acquisition, share buyback) or one that has not yet deployed recently raised capital. Consistently high cash ratios can signal capital allocation inefficiency.

### How does the cash ratio relate to the current ratio and quick ratio?

The three ratios form a spectrum of liquidity conservatism. The current ratio is the broadest, including all current assets. The quick ratio is more conservative, excluding inventory and prepaid expenses. The cash ratio is the strictest, using only cash and cash equivalents. Together they help investors understand how much of a company's short-term liquidity depends on converting non-cash assets.

### Why might a company's cash ratio on GeminIQ differ from other platforms?

The primary source of variation is how the platform defines cash and cash equivalents. Some companies file with restricted cash included in their cash line; others separate it. Some aggregators add restricted cash back in during normalization, others do not. GeminIQ uses the as-filed value, so the number matches what the company reported on its balance sheet.

**How GeminIQ Calculates This Metric:**
GeminIQ uses the Cash and Cash Equivalents value directly from the company's balance sheet as filed with the SEC. This value reflects the company's own classification of what constitutes cash and cash equivalents, which can vary — some companies include restricted cash, others do not. GeminIQ preserves the company's as-filed classification.

**FAQ:**
### What is a good cash ratio?

Most healthy companies operate with cash ratios between 0.2 and 0.5, meaning they hold enough cash to cover 20% to 50% of their current liabilities. A cash ratio above 1.0 is rare and often indicates either a company hoarding cash for a strategic reason (acquisition, share buyback) or one that has not yet deployed recently raised capital. Consistently high cash ratios can signal capital allocation inefficiency.

### How does the cash ratio relate to the current ratio and quick ratio?

The three ratios form a spectrum of liquidity conservatism. The current ratio is the broadest, including all current assets. The quick ratio is more conservative, excluding inventory and prepaid expenses. The cash ratio is the strictest, using only cash and cash equivalents. Together they help investors understand how much of a company's short-term liquidity depends on converting non-cash assets.

### Why might a company's cash ratio on GeminIQ differ from other platforms?

The primary source of variation is how the platform defines cash and cash equivalents. Some companies file with restricted cash included in their cash line; others separate it. Some aggregators add restricted cash back in during normalization, others do not. GeminIQ uses the as-filed value, so the number matches what the company reported on its balance sheet.

#### Current Ratio
source: https://www.geminiq.com/metrics/liquidity-ratios/current-ratio

**Definition:**
The current ratio measures a company's ability to pay its short-term obligations - debts and payables that are due within one year - using its short-term assets. It is the most widely used liquidity ratio and answers a simple question: for every dollar the company owes in the next 12 months, how many dollars of short-term assets does it have available to cover it?

A current ratio above 1.0 means the company has more current assets than current liabilities, which generally indicates adequate short-term liquidity. A ratio below 1.0 means short-term liabilities exceed short-term assets, which may indicate a liquidity risk depending on the business model. Some industries, like retail and grocery, routinely operate with current ratios below 1.0 because they collect cash from customers before they have to pay suppliers - this is a sign of operating efficiency, not distress.

The current ratio is most useful as a screening tool and a starting point for deeper analysis. It does not tell you how liquid the current assets actually are - inventory, for example, may take months to convert to cash, and some receivables may never be collected. For a more conservative view of liquidity, investors often pair the current ratio with the quick ratio, which excludes inventory and prepaid expenses from the numerator.

Investors should be cautious about comparing current ratios across sectors. A 1.5 current ratio is strong for a retailer but may be low for a manufacturing company that carries significant inventory. The ratio is most meaningful when compared to a company's own historical trend and to peers within the same industry.

**Formula:**
Current Ratio = Current Assets / Current Liabilities

**What Is a Good Current Ratio?**
Across the 1,333 US companies GeminIQ covers with a market capitalization above $2 billion, the median current ratio is 1.62, and the middle half sit between 1.08 and 2.78. About 20% run below 1.0 and about 22% run above 3.0, so for an established company a ratio between roughly 1 and 3 is normal, a ratio below 1 is common rather than alarming, and a very high ratio is not automatically a strength.

| Industry | Median | Middle 50% |
| --- | --- | --- |
| Utilities | 0.93 | 0.66 – 1.19 |
| Transportation | 1.16 | 0.78 – 1.59 |
| Insurance | 1.19 | 1.07 – 1.54 |
| Retail | 1.19 | 0.86 – 1.63 |
| Oil & gas | 1.29 | 0.82 – 1.87 |
| Food & beverage | 1.50 | 1.03 – 2.43 |
| Telecom & media | 1.51 | 0.95 – 2.33 |
| Software & IT services | 1.62 | 1.06 – 2.64 |
| Industrial manufacturing | 2.35 | 1.57 – 3.18 |
| Semiconductors & hardware | 2.48 | 1.56 – 3.84 |
| Medical devices | 3.35 | 1.97 – 5.00 |
| Pharma & biotech | 6.61 | 3.06 – 13.28 |

Industry explains most of the spread. Utilities and retailers carry low current ratios because their revenue is steady or their inventory turns into cash quickly, and suppliers finance much of their working capital. Pharmaceutical and biotech companies carry very high ones because they hold cash raised from investors to fund research years before revenue arrives, which is a sign of runway rather than of an efficient balance sheet.

The more useful test is the direction and the makeup. A current ratio that falls quarter after quarter, or one propped up by rising inventory and receivables rather than cash, deserves a closer look regardless of where it sits in the range. Figures are GeminIQ calculations across US companies that file with the SEC, using each company's latest reported period as of September 2026. The middle 50% runs from the 25th to the 75th percentile. The industry table groups companies by SIC code and includes those above $300 million in market capitalization.

**How GeminIQ Calculates This Metric:**
GeminIQ calculates the current ratio using the Current Assets and Current Liabilities values extracted directly from each company's SEC filings via their XBRL tags.

Because GeminIQ sources these inputs from the original filing rather than from a third-party aggregator, the values reflect exactly what the company reported to the SEC - including any company-specific classifications that aggregators may have reclassified during normalization.

**FAQ:**
### What is a good current ratio?


For US companies above $2 billion in market cap, the median current ratio is 1.62 and the middle half fall between 1.08 and 2.78, so roughly 1 to 3 is normal. It varies by industry: utilities have a median near 0.93, while pharmaceutical and biotech companies sit far higher. Compare against direct peers and the company's own history.

### How does the current ratio differ from the quick ratio?

The current ratio includes all current assets in the numerator - cash, receivables, inventory, and prepaid expenses. The quick ratio excludes inventory and prepaid expenses because they cannot be converted to cash as quickly. The quick ratio is a more conservative measure of short-term liquidity and is especially useful for companies that carry large or slow-moving inventories.

### Why might a company's current ratio on GeminIQ differ from other platforms?

Differences typically arise from how the platform sources Current Assets and Current Liabilities. Platforms that use normalized data from third-party aggregators may reclassify certain items between current and non-current categories during the normalization process, which changes both the numerator and denominator. GeminIQ uses the values exactly as the company filed them with the SEC, preserving the original current vs. non-current classification.

### What does a current ratio of 1.5 mean?

A current ratio of 1.5 means the company holds $1.50 of current assets for every $1.00 of liabilities due within a year. That is close to typical: the median for US companies above $2 billion in market capitalization is 1.62, with the middle half between 1.08 and 2.78.

### What does a current ratio of 2.5 mean?

A current ratio of 2.5 means $2.50 of current assets for every $1.00 of current liabilities, which places a company in the upper part of the normal range for established US companies. It indicates a comfortable liquidity cushion, though a ratio that high can also reflect idle cash or slow-moving inventory, so check what the current assets are.

#### Net Current Asset Value (NCAV)
source: https://www.geminiq.com/metrics/liquidity-ratios/ncav

**Definition:**
Net current asset value (NCAV) is Benjamin Graham's conservative estimate of a company's liquidation value, first described in Security Analysis (1934). Unlike working capital or net working capital, which subtract only current liabilities from current assets, NCAV subtracts a company's *total* liabilities — current and long-term — from its current assets. The result approximates what would be left for shareholders if the company's current assets (cash, receivables, inventory) were liquidated at book value and every liability, including long-term debt, was paid off in full, before assigning any value at all to fixed assets, intangibles, or the business as a going concern.

Graham used NCAV as the basis for his "net-net" investing strategy: buying stocks trading at a market capitalization below their NCAV, on the theory that the market price offered a margin of safety even if the business itself never generated another dollar of profit. A company can have positive working capital while still failing the NCAV test, since NCAV also has to absorb the company's long-term obligations.

NCAV per share divides this figure by shares outstanding, making it directly comparable to the stock's trading price — a company trading below its NCAV per share is, by this measure, priced below its liquidation value.

**Formula:**
NCAV = Total Current Assets − Total Liabilities

NCAV Per Share = NCAV / Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ computes NCAV as total current assets minus total liabilities, both sourced directly from the company's SEC filing via their as-filed XBRL tags — no reclassification of what counts as a current vs. long-term item. NCAV per share (TTM) divides this figure by period-end basic shares outstanding.

**FAQ:**
### How is NCAV different from working capital?

Working capital and net working capital subtract only *current* liabilities from current assets, leaving long-term debt and other long-term obligations out of the picture entirely. NCAV subtracts total liabilities — current and long-term — making it a more conservative, liquidation-oriented measure. A company can look healthy on working capital while carrying enough long-term debt to turn its NCAV negative.

### What does it mean when a stock trades below its NCAV?

It means the market is pricing the company below the estimated liquidation value of its current assets after settling every liability, without assigning any value to fixed assets, intangibles, or future earnings power. This is the classic Graham "net-net" setup. It doesn't automatically make a stock a good investment — companies can trade below NCAV for years because of weak or deteriorating operations — but it does provide a quantifiable margin of safety on the balance sheet alone.

### Why might NCAV values differ between platforms?

The most common source of variation is how a platform classifies current vs. long-term liabilities, and whether it uses as-filed figures or reclassifies them under its own template. GeminIQ uses the company's own as-filed XBRL classifications rather than normalizing them through a third-party aggregator, so NCAV reflects the company's own reporting structure.

#### Net Working Capital (Operating Working Capital)
source: https://www.geminiq.com/metrics/liquidity-ratios/net-working-capital

**Definition:**
Net working capital, sometimes called operating working capital, refines the standard working capital calculation by stripping out non-operating items from both sides of the equation. Specifically, it removes cash and cash equivalents from current assets and removes short-term debt from current liabilities. What remains is a measure of the capital tied up in the company's core operating cycle — receivables, inventory, and prepaid assets on one side, and trade payables and accrued expenses on the other.

The reason for these exclusions is that cash on the balance sheet is a treasury management decision, not an operating requirement, and short-term debt is a financing choice, not an operating obligation in the same way that accounts payable is. By removing both, net working capital gives a cleaner picture of how much capital the business needs to fund its day-to-day operations.

Rising net working capital relative to revenue can signal that the company is tying up more capital in operations — perhaps collecting receivables more slowly, building inventory faster than it can sell, or losing leverage with suppliers. Declining net working capital relative to revenue may indicate improving efficiency or, less positively, that the company is stretching its payables to conserve cash.

**Formula:**
Net Working Capital = (Current Assets − Cash) − (Current Liabilities − Short-Term Debt)

**How GeminIQ Calculates This Metric:**
GeminIQ strips cash and cash equivalents from current assets and short-term borrowings from current liabilities before computing the difference. All four inputs are sourced directly from the company's SEC filing via their XBRL tags. This ensures the classification of what constitutes short-term debt versus current operating liabilities reflects the company's own reporting rather than an aggregator's reclassification.

**FAQ:**
### Why is net working capital more useful than regular working capital?

Regular working capital mixes operating items (receivables, inventory, payables) with financing items (cash, short-term debt). A company could appear to have strong working capital simply because it raised a large debt facility and parked the proceeds in cash — but that tells you nothing about its operating efficiency. Net working capital isolates the operating components and reveals how much capital the business model itself requires.

### How should I interpret changes in net working capital?

The most useful way to interpret net working capital is relative to revenue. If net working capital is growing faster than revenue, the company is becoming less capital-efficient — it needs more working capital per dollar of sales. If net working capital is growing slower than revenue or declining, the company is becoming more efficient at converting its operating cycle into cash.

### Why might net working capital values differ between platforms?

The differences stem from how each platform classifies current vs. non-current items and what it defines as short-term debt. Some aggregators reclassify operating lease liabilities or the current portion of long-term debt differently than the company filed it. GeminIQ uses the as-filed classifications, so the net working capital reflects the company's own reporting structure.

### Is net working capital the same as working capital?

Many textbooks use the two terms interchangeably for current assets minus current liabilities. GeminIQ uses net working capital for the operating version, which removes cash from current assets and short-term debt from current liabilities, so the figure reflects only the capital tied up in running the business.

### Should you include cash in net working capital?

For analyzing operations, no. Cash is a treasury decision and short-term debt is a financing decision, so both are excluded to isolate receivables, inventory, and payables. This is the same convention used in discounted cash flow models, where the change in net working capital reduces free cash flow.

### Is high net working capital good or bad?

Neither on its own. High net working capital means the business needs a lot of capital to operate, which lowers free cash flow and returns on capital. Low or negative net working capital, common at retailers and subscription businesses, means customers and suppliers fund operations. The trend relative to revenue is more telling than the level.

#### Quick Ratio (Acid-Test Ratio)
source: https://www.geminiq.com/metrics/liquidity-ratios/quick-ratio

**Definition:**
The quick ratio, also called the acid-test ratio, measures a company's ability to meet its short-term obligations using only its most liquid assets - those that can be converted to cash within 90 days or less. Unlike the current ratio, the quick ratio excludes inventory and prepaid expenses from the numerator, both of which may take significant time to convert to cash or may not be convertible at all.

This makes the quick ratio a more conservative and arguably more realistic test of whether a company can actually pay its bills in a crunch. If a company suddenly needed to cover all its current liabilities, it could not instantly liquidate its warehouse full of raw materials or its prepaid insurance policies. The quick ratio strips those out and looks only at cash, cash equivalents, and receivables.

A quick ratio above 1.0 means the company can cover all short-term liabilities without selling any inventory or relying on prepaid assets. A ratio significantly below 1.0 is worth investigating, though it is not automatically a red flag - businesses with high inventory turnover, like grocery stores, may comfortably operate with low quick ratios because they convert inventory to cash very rapidly.

The quick ratio is most valuable during economic downturns or periods of financial stress, when inventory values can decline sharply and receivables may become harder to collect. In stable times, the current ratio and quick ratio tell similar stories; in stressed environments, the gap between them becomes informative.

**Formula:**
Quick Ratio = (Current Assets - Inventory - Prepaid Expenses) / Current Liabilities

**What Is a Good Quick Ratio?**
The textbook rule is that a quick ratio of 1.0 or higher is adequate. In practice, about 38% of US companies with a market capitalization above $2 billion run below 1.0. Among those 1,333 companies, the median quick ratio is 1.19 and the middle half fall between 0.79 and 2.04.

| Industry | Median | Middle 50% |
| --- | --- | --- |
| Retail | 0.52 | 0.31 – 1.02 |
| Food & beverage | 0.76 | 0.54 – 1.36 |
| Utilities | 0.81 | 0.58 – 1.04 |
| Oil & gas | 1.03 | 0.65 – 1.55 |
| Transportation | 1.03 | 0.71 – 1.51 |
| Insurance | 1.15 | 1.05 – 1.46 |
| Industrial manufacturing | 1.23 | 0.94 – 2.29 |
| Telecom & media | 1.31 | 0.81 – 1.89 |
| Software & IT services | 1.50 | 0.96 – 2.37 |
| Semiconductors & hardware | 1.75 | 1.01 – 2.81 |
| Medical devices | 2.20 | 1.21 – 4.45 |
| Pharma & biotech | 5.86 | 2.57 – 13.01 |

Retailers and food and beverage companies sit lowest because so much of their current assets is inventory, which the quick ratio excludes, and because they sell for cash and pay suppliers later. For those businesses a quick ratio well under 1.0 is the normal operating shape. Companies that hold little inventory, such as software and medical device makers, sit well above it.

Read the quick ratio next to the current ratio: a wide gap between them means the company's liquidity depends on selling inventory, which matters most when demand slows. Figures are GeminIQ calculations across US companies that file with the SEC, using each company's latest reported period as of September 2026. The middle 50% runs from the 25th to the 75th percentile. The industry table groups companies by SIC code and includes those above $300 million in market capitalization.

**How GeminIQ Calculates This Metric:**
GeminIQ subtracts both Inventory and Prepaid Expenses from Current Assets before dividing by Current Liabilities. All three inputs are sourced directly from the company's SEC filing via their XBRL tags.

Some platforms only subtract inventory and not prepaid expenses, which produces a slightly higher and less conservative quick ratio. GeminIQ's calculation follows the stricter definition.

**FAQ:**
### What is a good quick ratio?


A quick ratio of 1.0 or more is the textbook benchmark, but about 38% of US companies above $2 billion in market cap run below it. The median for that group is 1.19. Retailers and food companies normally sit well under 1.0 because inventory is excluded, while software and medical device makers sit well above it.

### Why does GeminIQ subtract prepaid expenses in the quick ratio?

Prepaid expenses - such as prepaid insurance, prepaid rent, or prepaid licenses - are classified as current assets on the balance sheet, but they cannot be converted to cash. They represent services already paid for that will be consumed over time. Subtracting them produces a more conservative and accurate picture of how much truly liquid capital the company has available to meet short-term obligations.

### Why might quick ratio values differ between financial platforms?

The most common reason is disagreement about what to subtract from current assets. Some platforms subtract only inventory. GeminIQ subtracts both inventory and prepaid expenses. Additionally, if a platform's data aggregator has reclassified items between current and non-current categories during normalization, both the numerator and denominator of the ratio can change.

### What does a quick ratio of 1.5 mean?

A quick ratio of 1.5 means the company holds $1.50 of cash, marketable securities, and receivables for every $1.00 of liabilities due within a year, without counting on selling any inventory. That is above the median of 1.19 for US companies above $2 billion in market capitalization, a comfortable level of liquidity.

### Is a quick ratio of 0.75 good?

It depends on the business. A quick ratio of 0.75 is below the textbook 1.0 benchmark, but about 38% of US companies above $2 billion in market capitalization run below 1.0. For a retailer, whose median is about 0.5 because inventory is excluded, 0.75 is healthy; for a software company it would be unusually low.

#### Working Capital
source: https://www.geminiq.com/metrics/liquidity-ratios/working-capital

**Definition:**
Working capital is the difference between a company's current assets and its current liabilities: working capital = current assets − current liabilities. It represents the net amount of short-term resources available to fund day-to-day operations after all short-term obligations are accounted for. A positive working capital means the company has more short-term assets than short-term debts; a negative working capital means short-term debts exceed short-term assets.

Working capital is not a ratio — it is a dollar amount, which makes it most useful when tracked as a trend over time or compared to revenue. A company whose working capital is declining quarter over quarter may be burning through liquidity, while growing working capital may indicate improving financial health or an accumulation of inventory that is not converting to sales.

Negative working capital is not always a bad sign. Companies with strong bargaining power — like Amazon, Walmart, and Costco — routinely operate with negative working capital because they collect cash from customers before they have to pay suppliers. This means they effectively use their suppliers' money to fund operations, which is actually a sign of operational efficiency.

**Formula:**
Working Capital = Current Assets − Current Liabilities

**What is a good working capital amount?**
There is no universal target because the appropriate level depends entirely on the company's size, industry, and business model. Working capital is most useful when expressed as a ratio to revenue (see Working Capital to Revenue) or when tracked as a trend. A company that has maintained positive and stable working capital for years is generally in a healthier liquidity position than one whose working capital has been declining.

### How does working capital differ from net working capital?

Working capital includes all current assets and all current liabilities. Net working capital (also called operating working capital) strips out cash from current assets and short-term debt from current liabilities, isolating only the operating components — receivables, inventory, and payables. Net working capital is a better measure of how much capital is tied up in the company's core operating cycle.

### Is negative working capital always a warning sign?

No. Companies that collect cash before paying suppliers — such as subscription businesses, large retailers, and fast-food chains — often operate with negative working capital by design. The key question is whether the negative working capital is structural (part of the business model) or deteriorating (a sign of rising obligations or declining asset quality). Tracking the trend over multiple quarters is more informative than any single data point.

### What are the four main components of working capital?

Cash, accounts receivable, and inventory on the asset side, and accounts payable on the liability side. Current assets and liabilities also include prepaid expenses, accrued expenses, and the current portion of debt, but receivables, inventory, and payables are the items that move with the operating cycle.

### What is the working capital ratio?

The working capital ratio is another name for the current ratio: current assets divided by current liabilities. Working capital expresses the same comparison as a dollar difference, while the ratio expresses it as a multiple, which makes companies of different sizes comparable.

### Is more working capital always better?

No. Positive working capital means short-term obligations are covered, but a growing balance can also mean cash is tied up in slow-paying receivables or unsold inventory. What matters is whether working capital is growing in line with revenue and whether the company converts it back into cash.

**How GeminIQ Calculates This Metric:**
GeminIQ computes working capital by subtracting Current Liabilities from Current Assets, both sourced directly from the company's SEC filing. Because these values are taken as-filed without reclassification, the working capital figure matches what the company itself would calculate from its own balance sheet.

**FAQ:**
### What is a good working capital amount?

There is no universal target because the appropriate level depends entirely on the company's size, industry, and business model. Working capital is most useful when expressed as a ratio to revenue (see Working Capital to Revenue) or when tracked as a trend. A company that has maintained positive and stable working capital for years is generally in a healthier liquidity position than one whose working capital has been declining.

### How does working capital differ from net working capital?

Working capital includes all current assets and all current liabilities. Net working capital (also called operating working capital) strips out cash from current assets and short-term debt from current liabilities, isolating only the operating components — receivables, inventory, and payables. Net working capital is a better measure of how much capital is tied up in the company's core operating cycle.

### Is negative working capital always a warning sign?

No. Companies that collect cash before paying suppliers — such as subscription businesses, large retailers, and fast-food chains — often operate with negative working capital by design. The key question is whether the negative working capital is structural (part of the business model) or deteriorating (a sign of rising obligations or declining asset quality). Tracking the trend over multiple quarters is more informative than any single data point.

### What are the four main components of working capital?

Cash, accounts receivable, and inventory on the asset side, and accounts payable on the liability side. Current assets and liabilities also include prepaid expenses, accrued expenses, and the current portion of debt, but receivables, inventory, and payables are the items that move with the operating cycle.

### What is the working capital ratio?

The working capital ratio is another name for the current ratio: current assets divided by current liabilities. Working capital expresses the same comparison as a dollar difference, while the ratio expresses it as a multiple, which makes companies of different sizes comparable.

### Is more working capital always better?

No. Positive working capital means short-term obligations are covered, but a growing balance can also mean cash is tied up in slow-paying receivables or unsold inventory. What matters is whether working capital is growing in line with revenue and whether the company converts it back into cash.

### Margin Metrics
source: https://www.geminiq.com/metrics/margin-metrics

#### Gross Profit Margin
source: https://www.geminiq.com/metrics/margin-metrics/gross-profit-margin

**Definition:**
Gross profit margin, usually shortened to gross margin, measures the percentage of revenue remaining after subtracting the direct cost of producing the goods or services sold. It is calculated by dividing trailing twelve-month gross profit by trailing twelve-month revenue. Gross margin reveals the fundamental profitability of a company's products or services before overhead, sales, research, and administrative expenses are considered.

A company with a 60% gross margin retains 60 cents of every revenue dollar after production costs. This is the first and most important margin in the income statement hierarchy because it defines the maximum profit potential from the core product before all other expenses eat into it.

Gross margins vary enormously by industry. Software companies routinely achieve 70-90% gross margins because digital products have near-zero marginal cost. Manufacturing companies typically range from 20-40%. Grocery and commodity businesses may operate with margins in the single digits.

**Formula:**
Gross Profit Margin = Gross Profit (TTM) / Revenue (TTM)

Where Gross Profit = Revenue − Cost of Goods Sold (if not reported directly)

**What is a good gross profit margin?**
It depends entirely on the industry. Software and SaaS: 70-90%. Pharmaceuticals: 60-80%. Consumer brands: 40-60%. Manufacturing: 20-40%. Retail and grocery: 20-35%. The most useful comparison is against direct competitors and the company's own historical trend.

### What causes gross margin to change over time?

Gross margin changes reflect shifts in pricing power, input costs, product mix, or manufacturing efficiency. Expanding margins typically indicate pricing power or improving efficiency. Compressing margins may signal rising input costs, competitive pressure, or a shift toward lower-margin products.

### Why might gross margin differ between platforms?

The primary source of variation is how Cost of Goods Sold is classified. Some companies include depreciation in COGS; others report it separately below the gross profit line. Aggregators may reclassify these items during normalization. GeminIQ preserves the company's as-filed COGS figure.

### What does a 30% gross margin mean?

A 30% gross margin means the company keeps $30 of every $100 in revenue after paying the direct cost of the goods or services it sold. That $30 is what remains to cover operating expenses, interest, and taxes, so a 30% gross margin leaves far less room than the 70% to 90% typical of software companies.

### How do you calculate a price for a 20% gross margin?

Divide the cost by one minus the target margin: a product costing $80 needs a price of $80 / (1 − 0.20) = $100 to earn a 20% gross margin. Adding 20% to cost instead gives $96, which is a 20% markup but only a 16.7% margin.

### What is a GAAP gross margin?

GAAP gross margin is gross profit divided by revenue using the revenue and cost of revenue a company reports under US GAAP. Some companies also publish a non-GAAP gross margin that excludes items such as stock-based compensation or amortization of acquired intangibles from cost of revenue, which makes it higher. GeminIQ calculates gross margin from the GAAP figures in the filing.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM gross profit by TTM revenue, both from SEC filings. If gross profit is not reported directly (some companies report only revenue and total operating expenses), GeminIQ derives it by subtracting COGS from revenue using the as-filed values.

**FAQ:**
### What is a good gross profit margin?

It depends entirely on the industry. Software and SaaS: 70-90%. Pharmaceuticals: 60-80%. Consumer brands: 40-60%. Manufacturing: 20-40%. Retail and grocery: 20-35%. The most useful comparison is against direct competitors and the company's own historical trend.

### What causes gross margin to change over time?

Gross margin changes reflect shifts in pricing power, input costs, product mix, or manufacturing efficiency. Expanding margins typically indicate pricing power or improving efficiency. Compressing margins may signal rising input costs, competitive pressure, or a shift toward lower-margin products.

### Why might gross margin differ between platforms?

The primary source of variation is how Cost of Goods Sold is classified. Some companies include depreciation in COGS; others report it separately below the gross profit line. Aggregators may reclassify these items during normalization. GeminIQ preserves the company's as-filed COGS figure.

### What does a 30% gross margin mean?

A 30% gross margin means the company keeps $30 of every $100 in revenue after paying the direct cost of the goods or services it sold. That $30 is what remains to cover operating expenses, interest, and taxes, so a 30% gross margin leaves far less room than the 70% to 90% typical of software companies.

### How do you calculate a price for a 20% gross margin?

Divide the cost by one minus the target margin: a product costing $80 needs a price of $80 / (1 − 0.20) = $100 to earn a 20% gross margin. Adding 20% to cost instead gives $96, which is a 20% markup but only a 16.7% margin.

### What is a GAAP gross margin?

GAAP gross margin is gross profit divided by revenue using the revenue and cost of revenue a company reports under US GAAP. Some companies also publish a non-GAAP gross margin that excludes items such as stock-based compensation or amortization of acquired intangibles from cost of revenue, which makes it higher. GeminIQ calculates gross margin from the GAAP figures in the filing.

#### Net Profit Margin
source: https://www.geminiq.com/metrics/margin-metrics/net-profit-margin

**Definition:**
Net profit margin is the percentage of revenue that remains as profit after all expenses — cost of goods sold, operating expenses, interest, taxes, and all other charges. It is the bottom-line profitability measure, dividing net income by revenue. A 15% net margin means the company keeps 15 cents of every dollar of revenue as profit.

**Formula:**
Net Profit Margin = Net Income (TTM) / Revenue (TTM)

**What is a good net profit margin?**
Software: 20-35%. Financials: 20-35%. Consumer staples: 8-15%. Retail: 2-5%. Margins below 5% are considered thin and leave little room for error. The most meaningful comparison is against direct industry peers.

### What causes net margin to differ from operating margin?

Interest expense (from debt), income taxes, and non-operating items (like gains/losses on investments) separate operating margin from net margin. A company with high leverage will have a significantly lower net margin than operating margin because interest expense is a large charge.

### Why might net margin differ between platforms?

Net income definitions can vary — some platforms use income from continuing operations, others use total net income including discontinued operations and extraordinary items. GeminIQ uses the total Net Income figure from the filing.

### How do you calculate profit margin?

Divide net income by revenue and multiply by 100. A company with $10 million of net income on $100 million of revenue has a net profit margin of 10%. GeminIQ uses trailing twelve-month figures for both, so the margin reflects the most recent four quarters rather than a single one.

### What is a 30% margin on $100?

If $100 is the revenue, a 30% margin means $30 of profit. If $100 is the cost and you want a 30% margin on the selling price, the price is $100 / (1 − 0.30) = $142.86; adding 30% to cost instead gives $130, which is a 30% markup but only a 23% margin.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM net income by TTM revenue, both from SEC filings.

**FAQ:**
### What is a good net profit margin?

Software: 20-35%. Financials: 20-35%. Consumer staples: 8-15%. Retail: 2-5%. Margins below 5% are considered thin and leave little room for error. The most meaningful comparison is against direct industry peers.

### What causes net margin to differ from operating margin?

Interest expense (from debt), income taxes, and non-operating items (like gains/losses on investments) separate operating margin from net margin. A company with high leverage will have a significantly lower net margin than operating margin because interest expense is a large charge.

### Why might net margin differ between platforms?

Net income definitions can vary — some platforms use income from continuing operations, others use total net income including discontinued operations and extraordinary items. GeminIQ uses the total Net Income figure from the filing.

### How do you calculate profit margin?

Divide net income by revenue and multiply by 100. A company with $10 million of net income on $100 million of revenue has a net profit margin of 10%. GeminIQ uses trailing twelve-month figures for both, so the margin reflects the most recent four quarters rather than a single one.

### What is a 30% margin on $100?

If $100 is the revenue, a 30% margin means $30 of profit. If $100 is the cost and you want a 30% margin on the selling price, the price is $100 / (1 − 0.30) = $142.86; adding 30% to cost instead gives $130, which is a 30% markup but only a 23% margin.

#### Operating Profit Margin
source: https://www.geminiq.com/metrics/margin-metrics/operating-profit-margin

**Definition:**
Operating profit margin, usually called operating margin, measures the percentage of revenue remaining after subtracting both the direct cost of goods sold and all operating expenses — including sales, general and administrative expenses, research and development, and depreciation. It is calculated by dividing trailing twelve-month operating income by trailing twelve-month revenue.

Operating margin shows how much profit the company's core business operations generate before interest expense and taxes. It is a better measure of operational efficiency than gross margin because it includes all the costs of running the business, not just production costs.

**Formula:**
Operating Profit Margin = Operating Income (TTM) / Revenue (TTM)

**What is a good operating profit margin?**
Software: 20-40%. Financials: 25-45%. Consumer staples: 10-20%. Retail: 3-8%. Airlines: 5-15%. Higher is better within a peer group, but the absolute level depends on industry structure.

### How does operating margin differ from net profit margin?

Operating margin measures profit before interest and taxes. Net profit margin measures profit after all expenses including interest, taxes, and non-operating items. The gap between the two reveals how much of the company's profit is consumed by financing costs and taxes.

### Why might operating margin differ between platforms?

Platforms may define operating income differently — some include non-recurring charges, others exclude them. Some aggregators reclassify items between operating and non-operating categories. GeminIQ uses Operating Income as reported in the filing.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM operating income by TTM revenue, both from SEC filings.

**FAQ:**
### What is a good operating profit margin?

Software: 20-40%. Financials: 25-45%. Consumer staples: 10-20%. Retail: 3-8%. Airlines: 5-15%. Higher is better within a peer group, but the absolute level depends on industry structure.

### How does operating margin differ from net profit margin?

Operating margin measures profit before interest and taxes. Net profit margin measures profit after all expenses including interest, taxes, and non-operating items. The gap between the two reveals how much of the company's profit is consumed by financing costs and taxes.

### Why might operating margin differ between platforms?

Platforms may define operating income differently — some include non-recurring charges, others exclude them. Some aggregators reclassify items between operating and non-operating categories. GeminIQ uses Operating Income as reported in the filing.

#### Pretax Margin
source: https://www.geminiq.com/metrics/margin-metrics/pretax-margin

**Definition:**
Pretax margin measures the percentage of revenue remaining as profit before income taxes are applied. It divides pretax income by revenue. This metric isolates operational and financing profitability from the effects of tax strategy, making it useful for comparing companies in different tax jurisdictions or with different tax structures.

**Formula:**
Pretax Margin = Pretax Income (TTM) / Revenue (TTM)

**What is a good pretax margin?**
Pretax margins typically run 1-5 percentage points above net margins, depending on the company's effective tax rate. A 20% effective tax rate on a 25% pretax margin produces a 20% net margin. Compare against the same industry peers.

### Why might pretax margin differ between platforms?

Differences in how pretax income is classified — particularly treatment of non-operating gains and losses — are the main source. GeminIQ uses Pretax Income as reported.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM pretax income by TTM revenue, both from SEC filings.

**FAQ:**
### When is pretax margin more useful than net margin?

Pretax margin is more useful when comparing companies with different effective tax rates — for example, a US-based company versus one with significant international operations and lower blended tax rates. It strips out tax differences and shows the underlying profitability before tax optimization.

### What is a good pretax margin?

Pretax margins typically run 1-5 percentage points above net margins, depending on the company's effective tax rate. A 20% effective tax rate on a 25% pretax margin produces a 20% net margin. Compare against the same industry peers.

### Why might pretax margin differ between platforms?

Differences in how pretax income is classified — particularly treatment of non-operating gains and losses — are the main source. GeminIQ uses Pretax Income as reported.

#### Stock-Based Compensation to Revenue
source: https://www.geminiq.com/metrics/margin-metrics/stock-based-compensation-to-revenue

**Definition:**
Stock-based compensation to revenue measures what percentage of a company's revenue is consumed by stock-based compensation expense. It is calculated by dividing trailing twelve-month SBC by trailing twelve-month revenue. This metric is especially important for technology companies, where SBC can be a major expense that significantly reduces the earnings available to existing shareholders through dilution.

A ratio above 10% means more than 10 cents of every revenue dollar goes to equity compensation. For mature technology companies, 5-15% is typical. For high-growth startups, 20-30% is not uncommon but raises questions about how much of the company's growth is being captured by employees versus existing shareholders.

**Formula:**
SBC to Revenue = Stock-Based Compensation (TTM) / Revenue (TTM)

**What is a good SBC to revenue ratio?**
Below 5% is low for any industry. Between 5% and 15% is typical for mature technology companies. Above 15% is high and warrants investigation into whether the level of dilution is justified by the talent retention and growth it enables. Non-technology companies typically have ratios below 3%.

### Why does SBC matter even though it is a non-cash expense?

While SBC does not directly consume cash, it dilutes existing shareholders by increasing the share count. A company that generates $1B in net income but issues $300M in SBC is effectively transferring 30% of its earnings to employees through equity. The dilution is a real economic cost — just not a cash one.

### Why might SBC to revenue differ between platforms?

Some companies report SBC on the income statement, others only in the cash flow statement as a non-cash adjustment. GeminIQ uses the SBC value from the filing, prioritizing the XBRL-tagged Share Based Compensation Expense.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM stock-based compensation by TTM revenue, both from SEC filings.

**FAQ:**
### What is a good SBC to revenue ratio?

Below 5% is low for any industry. Between 5% and 15% is typical for mature technology companies. Above 15% is high and warrants investigation into whether the level of dilution is justified by the talent retention and growth it enables. Non-technology companies typically have ratios below 3%.

### Why does SBC matter even though it is a non-cash expense?

While SBC does not directly consume cash, it dilutes existing shareholders by increasing the share count. A company that generates $1B in net income but issues $300M in SBC is effectively transferring 30% of its earnings to employees through equity. The dilution is a real economic cost — just not a cash one.

### Why might SBC to revenue differ between platforms?

Some companies report SBC on the income statement, others only in the cash flow statement as a non-cash adjustment. GeminIQ uses the SBC value from the filing, prioritizing the XBRL-tagged Share Based Compensation Expense.

### Per-Share Metrics
source: https://www.geminiq.com/metrics/per-share-metrics

#### Adjusted EPS
source: https://www.geminiq.com/metrics/per-share-metrics/adjusted-eps

**Definition:**
Adjusted EPS is earnings per share recalculated after adding selected expenses back to net income, most commonly stock-based compensation. It shows what per-share earnings would look like if those expenses were excluded. No accounting standard defines which expenses qualify, so the specific adjustments vary by whoever publishes the figure.

The logic behind it is narrow and legitimate: some expenses reduce reported earnings without reducing cash, and a per-share figure that strips those out shows what the business generated in cash terms rather than accounting terms. Stock-based compensation is the canonical case. A company that pays an engineer $200,000 in salary writes a check for $200,000. A company that pays the same engineer $120,000 in salary and $80,000 in restricted stock writes a check for $120,000 and issues equity for the rest. Both recorded $200,000 of compensation expense. Only one of them spent $200,000.

This metric is controversial. Adding back SBC increases reported earnings, but stock compensation is a real economic cost to shareholders because it dilutes their ownership. Adjusted EPS should be used alongside, not instead of, standard EPS.

**Formula:**
Adjusted EPS = (Net Income (TTM) + Stock-Based Compensation (TTM)) / Basic Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ adds trailing twelve-month stock-based compensation back to TTM net income, then divides by period-end basic shares. All inputs are from SEC filings. Using basic shares keeps the metric on the same basis as market cap and other per-share ratios. The stock-based compensation figure comes from the operating activities section of the cash flow statement, where SBC appears as a non-cash add-back reconciling net income to operating cash flow.

GeminIQ adds back stock-based compensation and nothing else. No restructuring charges. No intangible amortization. No impairments, litigation settlements, or acquisition costs. That constraint is the point: an adjustment set that varies by company cannot support a comparison between companies, because any difference in the resulting figures reflects a difference in adjustment policy as much as a difference in business performance. Fixing the adjustment at one item — the one with the clearest non-cash justification and the most consistent disclosure across filers — produces a figure that means the same thing everywhere.

The tradeoff is real. A company that took a truly non-recurring $2 Billion legal settlement will show a depressed adjusted EPS that its own investor deck would present very differently. This figure is not attempting to represent management's view of normalized earnings. It is attempting to be the same calculation for every company in the universe, which is a different property, and a more useful one when the goal is comparison rather than narrative.

**FAQ:**
### What is adjusted EPS in simple terms?

Adjusted EPS is earnings per share calculated after adding certain expenses back to net income, most commonly stock-based compensation. It shows what per-share earnings would look like if those expenses were excluded. No accounting standard defines which expenses qualify, so the specific adjustments vary by whoever publishes the figure.

### Why is there no standard adjusted EPS formula?

Because adjusted EPS is a non-GAAP measure, and non-GAAP measures are defined by whoever publishes them. Regulation G requires a company presenting a non-GAAP figure to reconcile it to the nearest GAAP equivalent and to avoid presenting it more prominently than the GAAP number. That is a disclosure rule, not a definition rule. It governs how the adjustment must be shown, says nothing about which adjustments are permitted, and applies to the company's own reporting rather than to third-party platforms recalculating the figure independently. So "adjusted EPS" describes a category of calculation rather than a specific one.

### Which adjustments do companies actually make?

Four account for most of the distance between GAAP EPS and a company-reported adjusted EPS figure, and they are not equally defensible. Stock-based compensation is the most common and most contested: non-cash in every sense that matters to the cash flow statement, but a real cost to existing shareholders through dilution. Intangible amortization is second, defended as reflecting a purchase price allocation rather than an ongoing cost — an argument that holds for a rare acquirer and weakens considerably for a serial one. Restructuring charges are third, where the label does real work: a single restructuring in a decade is plausibly non-recurring, while charges appearing in eleven consecutive quarters are an operating expense wearing a different name. Litigation settlements, impairments, and acquisition costs make up the fourth group, and they share a pattern worth watching — they are almost always additions to earnings, rarely subtractions.

### Why do different platforms show different adjusted EPS for the same company?

Because they are adding back different things. One source may add back stock compensation only, another may add stock compensation plus intangible amortization plus restructuring charges. Both figures can be internally consistent and still disagree by a wide margin. There is no universal definition of "adjusted EPS." GeminIQ's adjusted EPS specifically adds back SBC and nothing else, which is clearly defined and consistent across all companies.

### Should I use adjusted EPS or diluted EPS?

Both, read together. Diluted EPS is the conservative floor — it divides GAAP net income by a share count that includes every outstanding option, restricted share, and convertible instrument as though all of them converted. Adjusted EPS sits highest, because it has added an expense back to the numerator that the other figures subtract. The spread carries the signal: a business paying its workforce primarily in cash produces figures clustered tightly together, while a software or semiconductor business where stock compensation runs 10% to 30% of revenue produces a wide spread. That spread quantifies how much of the reported earnings stream is routed to employees as equity rather than retained for shareholders.

### Why add back stock-based compensation?

Stock-based compensation is a non-cash expense — the company does not write a check for SBC, it issues equity. Adding it back shows what earnings would be if the company paid all employees in cash instead of equity. This can be useful for understanding cash-generation capacity, but it overstates economic earnings because the dilutive effect of SBC is real.

### Can adjusted EPS be positive when the company is losing money?

Yes, and it happens routinely. If stock-based compensation exceeds the net loss, adding it back flips the numerator positive while GAAP net income remains negative. A business losing $400 Million with $600 Million in stock compensation shows $200 Million in adjusted net income and a positive adjusted EPS while the GAAP figure stays negative. The calculation is valid. Reading the adjusted figure without the GAAP figure alongside it is not. This pattern shows up precisely where SBC is largest — early-stage software companies with heavy equity compensation and no GAAP profitability.

### What is the difference between GAAP EPS and adjusted EPS?

GAAP EPS, the figure reported on the income statement, follows accounting rules and includes every expense. Adjusted EPS is a non-GAAP figure that excludes expenses management or an analyst considers non-recurring or non-cash, such as stock-based compensation, restructuring costs, or amortization of acquired intangibles. Companies that publish adjusted EPS must reconcile it to GAAP EPS under Regulation G.

#### Diluted Earnings Per Share (EPS)
source: https://www.geminiq.com/metrics/per-share-metrics/diluted-earnings-per-share

**Definition:**
Diluted EPS measures the profit attributable to each share of common stock, accounting for all potentially dilutive securities. It divides trailing twelve-month net income by the diluted share count, which includes the effect of stock options, convertible bonds, warrants, and restricted stock units that could become common shares. Diluted EPS is the more conservative of the two EPS measures and is the figure most commonly referenced by analysts and in financial media.

**Formula:**
Diluted EPS = Net Income (TTM) / Weighted Average Diluted Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM Net Income by the diluted share count from the most recent filing. Both inputs come directly from the company's SEC filing via their XBRL tags.

**FAQ:**
### How does diluted EPS differ from basic EPS?

Basic EPS uses only shares currently outstanding. Diluted EPS accounts for all securities that could become common shares (options, warrants, convertibles), producing a lower EPS figure. Diluted EPS is more conservative because it shows what earnings per share would look like if all dilutive securities were exercised.

### Why does GeminIQ use basic shares for some metrics and diluted shares for diluted EPS?

Diluted EPS specifically uses diluted shares because it is measuring the per-share earnings impact of all potentially dilutive securities. Other per-share metrics like cash flow per share and free cash flow per share use basic shares for consistency with how market cap is calculated (price × basic shares), ensuring all per-share ratios are on the same denominator basis.

### Why might diluted EPS differ between platforms?

Differences typically arise from the share count — whether the platform uses period-end shares or weighted average shares, and how it handles anti-dilutive securities (which should be excluded from the diluted count when a company is loss-making). GeminIQ uses the company's own reported weighted average diluted shares from the filing.

### What is the EPS formula?

Basic EPS equals net income minus preferred dividends, divided by the weighted average number of common shares outstanding. Diluted EPS uses the same numerator but divides by the diluted share count, which adds shares that could be issued from options, restricted stock units, and convertible securities, so it is equal to or lower than basic EPS.

### What does EPS tell you?

EPS shows how much profit a company earned for each share of its common stock. On its own it says little, because share counts differ across companies; it becomes useful when tracked over time for the same company, or when divided into the share price to produce the P/E ratio.

#### Dividends Per Share
source: https://www.geminiq.com/metrics/per-share-metrics/dividends-per-share

**Definition:**
Dividends per share measures the total trailing twelve-month dividends paid divided by shares outstanding. It represents the annual cash income a shareholder receives per share held.

**Formula:**
Dividends Per Share = Dividends Paid (TTM) / Basic Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM dividends paid from the cash flow statement by period-end basic shares, both from SEC filings.

**FAQ:**
### How does dividends per share relate to dividend yield?

Dividend yield divides the annual dividends per share by the current stock price, expressing the income as a percentage of the price you pay. A $2 dividend per share on a $50 stock is a 4% yield.

### Why is TTM dividends per share more reliable than the stated quarterly dividend?

The TTM figure uses actual cash dividends paid over the past four quarters, capturing any changes, special dividends, or missed payments. The stated quarterly dividend is a forward-looking figure that the company could change at any time.

### Why might dividends per share differ between platforms?

Some platforms use dividends declared rather than dividends paid, which can differ by timing. GeminIQ uses actual Dividends Paid from the cash flow statement.

#### Free Cash Flow Per Share
source: https://www.geminiq.com/metrics/per-share-metrics/free-cash-flow-per-share

**Definition:**
Free cash flow per share divides a company's trailing twelve-month free cash flow by its basic shares outstanding. Free cash flow is operating cash flow minus capital expenditures — the cash left over after the company has funded its operations and maintained or expanded its asset base. This is the cash available for dividends, share buybacks, debt repayment, or acquisitions.

Free cash flow per share is one of the most important metrics for equity valuation because it represents the actual cash available to shareholders after all necessary business expenditures.

**Formula:**
Free Cash Flow Per Share = (Operating Cash Flow (TTM) − Capital Expenditures (TTM)) / Basic Shares Outstanding

**What is a good free cash flow per share?**
There is no universal target — it depends on the stock price and growth expectations. A more useful metric is the free cash flow yield (FCF per share / stock price), which tells you what return the company's cash generation represents relative to the price you pay.

### Why might FCF per share differ between platforms?

The most common source of variation is how capital expenditures are defined. Some platforms include acquisitions in capex, others exclude them. Some include purchases of intangible assets, others do not. GeminIQ uses capital expenditures as reported on the cash flow statement.

**How GeminIQ Calculates This Metric:**
GeminIQ computes TTM free cash flow as TTM operating cash flow minus TTM capital expenditures, then divides by period-end basic shares. All inputs are from SEC filings. Capital expenditures are reported as a cash outflow and GeminIQ takes the absolute value.

**FAQ:**
### Why is free cash flow per share important for valuation?

FCF per share represents the per-share cash a company generates after all operating costs and capital investments. It is the foundation of discounted cash flow (DCF) valuation models and is a better predictor of dividend sustainability than EPS because dividends are paid from cash, not accounting earnings.

### What is a good free cash flow per share?

There is no universal target — it depends on the stock price and growth expectations. A more useful metric is the free cash flow yield (FCF per share / stock price), which tells you what return the company's cash generation represents relative to the price you pay.

### Why might FCF per share differ between platforms?

The most common source of variation is how capital expenditures are defined. Some platforms include acquisitions in capex, others exclude them. Some include purchases of intangible assets, others do not. GeminIQ uses capital expenditures as reported on the cash flow statement.

#### Operating Cash Flow Per Share
source: https://www.geminiq.com/metrics/per-share-metrics/operating-cash-flow-per-share

**Definition:**
Operating cash flow per share divides a company's trailing twelve-month operating cash flow by its basic shares outstanding. It measures how much cash from operations is generated per share, providing an alternative to earnings per share that is harder to manipulate through accounting choices. Cash flow is less susceptible to revenue recognition timing, depreciation method changes, and other non-cash adjustments that affect reported earnings.

**Formula:**
Cash Flow Per Share = Operating Cash Flow (TTM) / Basic Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM operating cash flow from the cash flow statement by period-end basic shares, both from SEC filings.

**FAQ:**
### Why is cash flow per share sometimes more reliable than EPS?

Earnings include non-cash items like depreciation, amortization, stock compensation, and deferred taxes. These are real economic events but they do not directly affect cash. Cash flow per share strips all of that out and shows how much actual cash the business generated per share. Companies can manage earnings through accounting choices, but cash flow is much harder to manipulate.

### How does cash flow per share differ from free cash flow per share?

Cash flow per share uses total operating cash flow, which includes the cash needed for capital expenditures. Free cash flow per share subtracts capex, showing only the cash available after maintaining or expanding the asset base. Free cash flow per share is generally the more useful metric for equity investors.

### Why might cash flow per share differ between platforms?

Differences stem from the share count basis (basic vs. diluted, period-end vs. weighted average) and the cash flow figure used. GeminIQ uses period-end basic shares for consistency with market cap and other per-share metrics.

### Remaining Metrics
source: https://www.geminiq.com/metrics/remaining-metrics

#### Accrued Expenses to Current Liabilities
source: https://www.geminiq.com/metrics/remaining-metrics/accrued-expenses-to-current-liabilities

**Definition:**
This ratio measures what proportion of a company's current liabilities is made up of accrued expenses — obligations that have been incurred but not yet paid, such as accrued wages, accrued interest, accrued taxes, and other short-term obligations. A high ratio indicates that a significant portion of the company's near-term obligations are accruals rather than trade payables or short-term debt.

**Formula:**
Accrued to Current Liabilities = Accrued Expenses / Current Liabilities

**How GeminIQ Calculates This Metric:**
GeminIQ divides Accrued Liabilities (as reported) by Current Liabilities from the balance sheet as filed.

**FAQ:**
### What does this ratio tell investors?

A high accrued-to-current-liabilities ratio indicates the company has significant obligations that have been recognized but not yet paid in cash. This is normal for large employers (accrued wages) and companies with quarterly tax payments. Unusually high ratios may warrant investigation into whether accruals are building up faster than they are being settled.

### Is a high ratio good or bad?

It is neither inherently good nor bad — it reflects the composition of short-term obligations. The ratio is most useful when tracked over time. A rising ratio may indicate the company is deferring payments, which could signal cash flow pressure.

### Why might this ratio differ between platforms?

Accrued expenses can be classified differently by different companies and aggregators. Some companies report accrued liabilities as a single line; others break them into multiple sub-categories. GeminIQ uses the as-filed accrued liabilities figure.

#### Average Accounts Payable
source: https://www.geminiq.com/metrics/remaining-metrics/average-accounts-payable

**Definition:**
Average accounts payable is the simple average of the accounts payable balance at the beginning and end of the measurement period. It is the denominator in payables turnover.

**Formula:**
Average Accounts Payable = (Accounts Payable current + Accounts Payable same period 1 year ago) / 2

**How GeminIQ Calculates This Metric:**
GeminIQ averages current and year-ago accounts payable from the balance sheet as filed.

**FAQ:**
### Why use average payables?

Payables can fluctuate based on payment timing near period-end. Averaging provides a more stable denominator for turnover calculations.

### What is included in accounts payable?

Accounts payable represents amounts owed to suppliers for goods and services received but not yet paid for. It is a trade obligation, distinct from accrued expenses and short-term debt.

### Why might average payables differ between platforms?

Some companies use a combined Accounts Payable and Accrued Liabilities line item. GeminIQ looks for the specific Accounts Payable Current tag first.

#### Average Accounts Receivable
source: https://www.geminiq.com/metrics/remaining-metrics/average-accounts-receivable

**Definition:**
Average accounts receivable is the simple average of receivables at the beginning and end of the measurement period. It is used as the denominator in receivables turnover.

**Formula:**
Average Receivables = (Receivables current period + Receivables same period 1 year ago) / 2

**How GeminIQ Calculates This Metric:**
GeminIQ averages current and year-ago receivables from the balance sheet as filed.

**FAQ:**
### Why use average receivables?

Receivables can spike due to large end-of-period sales. Averaging produces a more representative figure for turnover calculations.

### Is this different from net receivables?

GeminIQ uses Accounts Receivable Net, which is after the allowance for doubtful accounts. This is the value reported on the balance sheet and is what would actually be collected.

### Why might average receivables differ between platforms?

Some platforms use gross receivables (before allowance), others use net. GeminIQ uses net receivables as filed.

#### Average Inventory
source: https://www.geminiq.com/metrics/remaining-metrics/average-inventory

**Definition:**
Average inventory is the simple average of a company's inventory balance at the beginning and end of the measurement period. It is used as the denominator in inventory turnover to more accurately reflect the inventory level maintained throughout the year.

**Formula:**
Average Inventory = (Inventory current period + Inventory same period 1 year ago) / 2

**How GeminIQ Calculates This Metric:**
GeminIQ averages current and year-ago inventory from the balance sheet as filed.

**FAQ:**
### Why use average inventory instead of ending inventory?

Inventory levels can fluctuate significantly due to seasonal stocking, product launches, or supply chain events. The average provides a more stable denominator for turnover calculations.

### Is this metric useful on its own?

It is primarily an input to inventory turnover. On its own, it can be useful for tracking whether a company's inventory base is growing relative to sales.

### Why might average inventory differ between platforms?

Inventory definitions can vary. GeminIQ uses the as-filed Inventory Net value.

#### Average Shareholders' Equity
source: https://www.geminiq.com/metrics/remaining-metrics/average-shareholders-equity

**Definition:**
Average shareholders' equity is the simple average of total equity at the beginning and end of the measurement period. It is used as the denominator in ROE to align the equity base with the trailing twelve-month earnings period.

**Formula:**
Average Equity = (Total Equity current period + Total Equity same period 1 year ago) / 2

**How GeminIQ Calculates This Metric:**
GeminIQ averages current and year-ago Total Equity from the balance sheet. If prior-year data is not available, the current period value is used.

**FAQ:**
### Why use average equity instead of ending equity?

A large buyback, equity issuance, or dividend payment near period-end can significantly change ending equity. Averaging provides a more representative denominator for return calculations.

### When would average equity not be available?

For newly public companies that have less than one year of filing history on GeminIQ, only the current period equity is available.

### Why might average equity differ between platforms?

Differences in how total equity is defined (inclusion of minority interests, preferred equity) change the base figures. GeminIQ uses as-filed values.

#### Average Total Assets
source: https://www.geminiq.com/metrics/remaining-metrics/average-total-assets

**Definition:**
Average total assets is the simple average of a company's total assets at the beginning and end of the measurement period. It is used as the denominator in ROA and asset turnover to more accurately reflect the assets that were deployed during the period, rather than using just the ending balance which may not represent the average level of assets throughout the year.

**Formula:**
Average Total Assets = (Total Assets current period + Total Assets same period 1 year ago) / 2

**How GeminIQ Calculates This Metric:**
GeminIQ averages the current-period and year-ago Total Assets from the balance sheet as filed. If prior-year data is not available, the current period's Total Assets is used.

**FAQ:**
### Why use average assets instead of ending assets?

A company might make a large acquisition or disposition near period-end, significantly changing the ending balance. The average smooths this out and better represents the assets that were actually generating returns during the measurement period.

### Is average assets a standalone metric or an input to other metrics?

It is primarily an input to ROA and asset turnover. It can be useful on its own for tracking a company's asset base trajectory over time.

### Why might average assets differ between platforms?

The time periods used for the average can differ. GeminIQ uses the current period and the same quarter one year prior.

#### Retained Earnings to Equity
source: https://www.geminiq.com/metrics/remaining-metrics/retained-earnings-to-equity

**Definition:**
This ratio measures what proportion of total shareholders' equity comes from accumulated retained earnings versus paid-in capital. A high ratio indicates the company has built its equity base primarily through profitable operations rather than by raising capital from investors. A negative ratio means the company has accumulated losses that exceed its paid-in capital.

**Formula:**
Retained Earnings to Equity = Retained Earnings / Total Shareholders' Equity

**How GeminIQ Calculates This Metric:**
GeminIQ divides Retained Earnings (Accumulated Deficit) by Total Equity, both from the balance sheet as filed.

**FAQ:**
### What does a high retained earnings to equity ratio indicate?

It indicates the company has generated and retained substantial profits over its history, building its equity primarily through earnings rather than capital raises. This is generally a sign of a mature, self-funding business.

### What does a negative ratio mean?

A negative ratio means the company has an accumulated deficit — cumulative losses exceed cumulative retained earnings. This is common for pre-profit companies and for companies with aggressive buyback programs that push equity negative.

### Why might this ratio differ between platforms?

Differences stem from how total equity is defined. GeminIQ uses as-filed values for both retained earnings and total equity.

#### Treasury Stock Change
source: https://www.geminiq.com/metrics/remaining-metrics/treasury-stock-change

**Definition:**
This metric measures the dollar change in a company's treasury stock balance over the past year. An increase indicates the company repurchased additional shares during the year. A decrease may indicate shares were reissued (for employee stock plans) or retired. This metric provides a direct view of how much capital the company deployed toward buybacks over the trailing year.

**Formula:**
Treasury Stock Change = |Treasury Stock current| − |Treasury Stock 1 year ago|

**How GeminIQ Calculates This Metric:**
GeminIQ takes the absolute value of treasury stock in both the current period and the same quarter one year ago, then computes the difference. This ensures consistency regardless of sign convention.

**FAQ:**
### How does treasury stock change relate to share buybacks?

The change in treasury stock reflects the net effect of buyback activity (increases treasury stock) and share reissuance for employee stock plans (decreases treasury stock). A positive change means buybacks exceeded reissuances.

### Is a larger treasury stock change always better?

Not necessarily. Buybacks at attractive prices create value; buybacks at inflated prices destroy value. The change should be evaluated alongside the stock's valuation at the time of repurchase and compared to alternative uses of capital.

### Why might treasury stock change differ between platforms?

Sign convention handling is the primary source. GeminIQ uses absolute values for consistency.

#### Treasury Stock to Equity
source: https://www.geminiq.com/metrics/remaining-metrics/treasury-stock-to-equity

**Definition:**
This ratio measures the size of a company's share buyback program relative to its equity base. Treasury stock is the cumulative value of shares the company has repurchased from the open market and not retired. A high ratio indicates significant buyback activity relative to equity. Companies like Apple and Starbucks have accumulated treasury stock that exceeds their total equity, resulting in negative book equity.

**Formula:**
Treasury Stock to Equity = |Treasury Stock| / Total Shareholders' Equity

**How GeminIQ Calculates This Metric:**
GeminIQ takes the absolute value of treasury stock (since it can be reported as positive or negative depending on the company's accounting convention) and divides by total equity. Both values are from the SEC filing.

**FAQ:**
### What does a high treasury stock to equity ratio mean?

It means the company has repurchased a large amount of its own shares relative to its equity base. This is generally a signal of capital return to shareholders but can reduce equity to negative levels if buybacks exceed retained earnings.

### Why does GeminIQ use the absolute value of treasury stock?

Different companies report treasury stock with different sign conventions in their SEC filings — some report it as a positive number, others as negative. Taking the absolute value ensures the ratio is consistent and comparable regardless of the filing convention.

### Why might this ratio differ between platforms?

The sign convention for treasury stock and whether the platform handles it consistently are the main sources of variation.

### Returns and Profitability
source: https://www.geminiq.com/metrics/returns-and-profitability

#### Dilution Ratio
source: https://www.geminiq.com/metrics/returns-and-profitability/dilution-ratio

**Definition:**
The dilution ratio compares a company's diluted share count to its basic share count. It measures the extent to which stock options, warrants, convertible securities, and restricted stock units would increase the number of shares outstanding if they were all exercised or converted. A dilution ratio of 1.05 means the diluted share count is 5% higher than the basic count.

Persistent dilution above 3-5% is a signal that the company is issuing significant equity — often through stock-based compensation — which reduces existing shareholders' ownership stake over time. Technology companies and startups tend to have higher dilution ratios because they rely heavily on stock compensation to attract talent.

**Formula:**
Dilution Ratio = Diluted Shares Outstanding / Basic Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ uses the Weighted Average Number of Diluted Shares Outstanding and Weighted Average Number of Basic Shares Outstanding directly from the company's SEC filing. These values include the dilutive effect of all in-the-money options, warrants, and convertible securities as calculated by the company itself using the treasury stock method.

**FAQ:**
### What is a typical dilution ratio?

Most mature companies have dilution ratios between 1.00 and 1.03 (0-3% dilution). Technology companies with heavy stock-based compensation may range from 1.03 to 1.10 (3-10% dilution). Early-stage companies with large option pools can exceed 1.15. A ratio of exactly 1.00 means there are no dilutive securities outstanding.

### Why does dilution matter to investors?

Dilution reduces each existing share's claim on earnings, assets, and voting power. A company that grows earnings by 10% but increases shares outstanding by 8% has only delivered 2% growth in per-share value. Tracking dilution alongside earnings growth reveals whether growth is actually accruing to existing shareholders or being absorbed by new shares.

### Why might dilution ratios differ between platforms?

Differences typically stem from which share count the platform uses — period-end shares versus weighted average shares, and whether the calculation includes all dilutive securities or only certain types. GeminIQ uses the company's own reported weighted average basic and diluted shares from the filing.

#### Effective Tax Rate
source: https://www.geminiq.com/metrics/returns-and-profitability/effective-tax-rate

**Definition:**
The effective tax rate is the percentage of a company's pre-tax profit that it actually pays in income taxes. Unlike the statutory rate set by law, the effective rate reflects the real tax outcome after credits, deductions, foreign earnings taxed at different rates, and one-time items. It answers a simple question: of every dollar the company earned before taxes, how many cents went to the government?

A lower effective tax rate leaves more profit for shareholders, but a rate that is unusually low can also signal reliance on temporary benefits that may not repeat. Comparing the effective rate to the statutory rate, and tracking it over time, shows how much of a company's reported earnings are shaped by tax strategy rather than operations.

**Formula:**
Effective Tax Rate = Income Tax Expense (TTM) / Pre-Tax Income (TTM)

**How GeminIQ Calculates This Metric:**
GeminIQ divides trailing-twelve-month income tax expense by trailing-twelve-month pre-tax income, both taken from XBRL-tagged SEC filings. The result is clamped to a range of 0% to 100% so that unusual quarters (for example, a tax benefit against a small or negative pre-tax income) do not produce misleading values. When the ratio cannot be computed or falls outside that range, GeminIQ falls back to the 21% U.S. federal statutory corporate rate. This is the same effective tax rate GeminIQ uses to convert EBIT into NOPAT for its ROIC calculation.

**FAQ:**
### What is a normal effective tax rate?

For most large U.S. companies the effective tax rate falls somewhere in the mid-teens to low-20s percent range. The 21% federal statutory rate is a common reference point, but many companies pay less after credits and foreign earnings, while others pay more once state and international taxes are included.

### Why does the effective rate differ from the 21% statutory rate?

Research and development credits, the geographic mix of where profits are earned, stock-based compensation deductions, and one-time charges or benefits all move the effective rate away from the statutory rate. A company earning a large share of income in lower-tax jurisdictions will typically report an effective rate below 21%.

### Why can the effective tax rate swing sharply between quarters?

Because it is a ratio of two TTM figures, a large one-time tax item or a quarter with unusually low pre-tax income can distort it. GeminIQ clamps the value to 0–100% and defaults to 21% when the raw ratio is not meaningful, but the metric is best read as a trend across several periods rather than a single quarter.

#### Net Operating Profit After Tax (NOPAT)
source: https://www.geminiq.com/metrics/returns-and-profitability/net-operating-profit-after-tax

**Definition:**
NOPAT stands for Net Operating Profit After Tax. It represents the profit a company would generate from its operations if it had no debt — it strips out the tax benefit of interest expense and shows the after-tax operating earnings available to all capital providers (both debt and equity holders).

NOPAT is the numerator in the ROIC calculation and is a critical metric for evaluating a company's core operating efficiency independent of its capital structure. Two companies with identical operations but different debt levels will have different net income figures (because interest expense reduces taxable income), but they will have the same NOPAT. This makes NOPAT the appropriate profit measure for comparing companies with different leverage.

**Formula:**
NOPAT = EBIT (TTM) × (1 − Effective Tax Rate)

Where:

- EBIT = Net Income + Income Tax + Interest Expense (if not reported directly)
- Effective Tax Rate = Income Tax (TTM) / Pretax Income (TTM), clamped between 0% and 100%
- If the effective tax rate cannot be calculated, a 21% statutory rate is used as a fallback

**How GeminIQ Calculates This Metric:**
GeminIQ derives the effective tax rate from the company's actual filed income tax expense and pretax income, clamped between 0 and 1 to handle edge cases like tax credits or loss carryforwards. When the effective rate cannot be calculated reliably, GeminIQ falls back to the 21% US federal statutory rate. EBIT is taken from the filing directly or derived from Net Income + Income Tax + Interest Expense. This approach ensures NOPAT reflects the company's actual tax situation rather than an assumed rate.

**FAQ:**
### Why is NOPAT important?

NOPAT is the profit measure that best represents a company's core operating performance independent of its capital structure decisions. Because it removes the tax benefit of debt, it enables apples-to-apples comparison between companies with different leverage levels. It is also the numerator in ROIC, which is widely considered the best single measure of how efficiently a company uses its invested capital.

### How does NOPAT differ from net income?

Net income is reduced by interest expense (which is tax-deductible), so it is lower for companies with more debt. NOPAT starts with EBIT (which is before interest expense) and applies taxes to operating earnings only. This means NOPAT is the same regardless of how the company is financed, making it a cleaner measure of operating profitability.

### Why might NOPAT values differ between platforms?

The primary source of variation is the tax rate used. Some platforms apply a fixed statutory rate (typically 21%) to all companies. GeminIQ uses each company's actual effective tax rate derived from its filed income tax expense and pretax income, which can differ significantly from the statutory rate due to deferred taxes, foreign income, tax credits, and other company-specific factors.

### How do you convert EBIT to NOPAT?

Multiply EBIT by one minus the tax rate. A company with $100 million of EBIT and a 21% effective tax rate has NOPAT of $100 million × (1 − 0.21) = $79 million. GeminIQ uses each company's own effective tax rate rather than the statutory rate.

### Is NOPAT the same as EBITDA?

No. EBITDA is earnings before interest, taxes, depreciation, and amortization. NOPAT starts from EBIT, so it keeps depreciation and amortization as expenses, and then subtracts taxes. NOPAT is therefore always well below EBITDA for a company with meaningful fixed assets.

### Is NOPAT the same as NPAT?

No. NPAT, net profit after tax, is simply net income: it is reduced by interest expense. NOPAT excludes financing entirely, taxing operating profit as if the company had no debt, so two companies with identical operations but different debt levels have the same NOPAT and different NPAT.

#### Payout Ratio
source: https://www.geminiq.com/metrics/returns-and-profitability/payout-ratio

**Definition:**
The payout ratio, also called the dividend payout ratio, measures what percentage of a company's net income is distributed to shareholders as dividends. A payout ratio of 40% means the company pays out 40 cents of every dollar earned as dividends and retains the remaining 60 cents for reinvestment, debt repayment, or share buybacks.

A lower payout ratio gives the company more financial flexibility — it retains more earnings to invest in growth, weather downturns, or reduce debt. A higher payout ratio is attractive to income-focused investors but leaves less margin for error if earnings decline. Companies with payout ratios consistently above 80% may be distributing more than they can sustain, especially if earnings are cyclical.

GeminIQ does not calculate a payout ratio when net income is negative, because the ratio is mathematically meaningless when a company is operating at a loss.

**Formula:**
Payout Ratio = Dividends Paid (TTM) / Net Income (TTM)

Note: This ratio is only calculated when Net Income is positive.

**What is a good payout ratio?**
It depends on the company's maturity and growth profile. Mature, slow-growth companies (utilities, consumer staples) typically have payout ratios between 50% and 75%. Growth companies usually have lower ratios (below 30%) because they reinvest more earnings. A payout ratio above 100% means the company is paying more in dividends than it earns, which is unsustainable long-term without using cash reserves or issuing debt.

### How does the payout ratio relate to dividend yield?

The payout ratio tells you what portion of earnings goes to dividends. The dividend yield tells you what return those dividends represent relative to the stock price. A company can have a high payout ratio but a low yield (if the stock is expensive relative to earnings) or a high yield but a moderate payout ratio (if the stock is cheap). The two metrics should be evaluated together.

### Why might payout ratios differ between platforms?

The primary source of variation is whether the platform uses dividends paid from the cash flow statement or dividends declared from the income statement. GeminIQ uses Dividends Paid from the cash flow statement, which reflects actual cash disbursed. Some platforms also calculate payout ratios using earnings per share and dividends per share, which can differ due to share count timing differences.

**How GeminIQ Calculates This Metric:**
GeminIQ divides trailing twelve-month Dividends Paid by trailing twelve-month Net Income, both from SEC filings. When net income is negative, the payout ratio is displayed as null rather than producing a misleading negative or >100% value. Dividends Paid is taken from the cash flow statement, which reflects actual cash dividends distributed during the period.

**FAQ:**
### What is a good payout ratio?

It depends on the company's maturity and growth profile. Mature, slow-growth companies (utilities, consumer staples) typically have payout ratios between 50% and 75%. Growth companies usually have lower ratios (below 30%) because they reinvest more earnings. A payout ratio above 100% means the company is paying more in dividends than it earns, which is unsustainable long-term without using cash reserves or issuing debt.

### How does the payout ratio relate to dividend yield?

The payout ratio tells you what portion of earnings goes to dividends. The dividend yield tells you what return those dividends represent relative to the stock price. A company can have a high payout ratio but a low yield (if the stock is expensive relative to earnings) or a high yield but a moderate payout ratio (if the stock is cheap). The two metrics should be evaluated together.

### Why might payout ratios differ between platforms?

The primary source of variation is whether the platform uses dividends paid from the cash flow statement or dividends declared from the income statement. GeminIQ uses Dividends Paid from the cash flow statement, which reflects actual cash disbursed. Some platforms also calculate payout ratios using earnings per share and dividends per share, which can differ due to share count timing differences.

#### Return on Assets (ROA)
source: https://www.geminiq.com/metrics/returns-and-profitability/return-on-assets

**Definition:**
Return on Assets measures how efficiently a company uses its total asset base to generate profit. It divides trailing twelve-month net income by average total assets, producing a percentage that represents the return earned per dollar of assets deployed in the business.

ROA is most useful for comparing companies within the same industry because asset intensity varies enormously across sectors. A software company with few physical assets and a 20% ROA is not necessarily better managed than a utility with massive infrastructure and a 3% ROA — they simply have different business models. Within a peer group, however, a higher ROA generally indicates better management of the asset base.

ROA uses average total assets (the average of the beginning and ending balance) rather than the ending balance to more accurately reflect the assets that were actually deployed throughout the measurement period.

**Formula:**
ROA = Net Income (TTM) / Average Total Assets

Where Average Total Assets = (Total Assets current period + Total Assets same period prior year) / 2

**What is a good ROA?**
ROA varies widely by industry. Technology and software companies often achieve ROA above 15%. Consumer staples typically range from 5% to 10%. Utilities and real estate are often below 3% due to their large asset bases. The most meaningful comparison is against direct industry peers. A ROA above 5% is generally considered adequate for most industries.

### How does ROA differ from ROE?

ROA measures return relative to all assets regardless of how they are financed. ROE measures return relative to only shareholders' equity, meaning it reflects the impact of leverage. A highly leveraged company can have a high ROE but a mediocre ROA — the leverage amplifies the return to equity holders but the underlying asset efficiency is unchanged. ROA strips out the leverage effect.

### Why might ROA values differ between financial platforms?

The most common sources of difference are how net income is defined (some platforms use income from continuing operations rather than total net income) and whether the denominator uses ending assets or average assets. GeminIQ uses total Net Income as reported and computes average total assets using the current and year-ago periods.

### What does ROA tell you in simple terms?

ROA tells you how many cents of profit a company earns for every dollar of assets it owns. An ROA of 8% means the company generated $8 of net income over the last twelve months for every $100 of average assets.

### How do you calculate ROA and ROE together?

Both use trailing twelve-month net income. Divide it by average total assets for ROA and by average shareholders' equity for ROE. ROE equals ROA multiplied by the equity multiplier (assets divided by equity), so the gap between the two shows how much leverage adds to shareholder returns.

### Why is ROA low for banks?

Banks fund most of their assets with deposits and borrowings, so their asset base is very large relative to profit. An ROA near 1% is typical for a well-run bank, while the same figure would be poor for an industrial or software company. Compare banks with banks.

**How GeminIQ Calculates This Metric:**
GeminIQ divides trailing twelve-month Net Income by Average Total Assets, where the average uses the current period and the same period one year prior. Both inputs are sourced directly from the company's SEC filings. If prior-year Total Assets are not available (for newly public companies), GeminIQ uses the current period's Total Assets as the denominator.

**FAQ:**
### What is a good ROA?

ROA varies widely by industry. Technology and software companies often achieve ROA above 15%. Consumer staples typically range from 5% to 10%. Utilities and real estate are often below 3% due to their large asset bases. The most meaningful comparison is against direct industry peers. A ROA above 5% is generally considered adequate for most industries.

### How does ROA differ from ROE?

ROA measures return relative to all assets regardless of how they are financed. ROE measures return relative to only shareholders' equity, meaning it reflects the impact of leverage. A highly leveraged company can have a high ROE but a mediocre ROA — the leverage amplifies the return to equity holders but the underlying asset efficiency is unchanged. ROA strips out the leverage effect.

### Why might ROA values differ between financial platforms?

The most common sources of difference are how net income is defined (some platforms use income from continuing operations rather than total net income) and whether the denominator uses ending assets or average assets. GeminIQ uses total Net Income as reported and computes average total assets using the current and year-ago periods.

### What does ROA tell you in simple terms?

ROA tells you how many cents of profit a company earns for every dollar of assets it owns. An ROA of 8% means the company generated $8 of net income over the last twelve months for every $100 of average assets.

### How do you calculate ROA and ROE together?

Both use trailing twelve-month net income. Divide it by average total assets for ROA and by average shareholders' equity for ROE. ROE equals ROA multiplied by the equity multiplier (assets divided by equity), so the gap between the two shows how much leverage adds to shareholder returns.

### Why is ROA low for banks?

Banks fund most of their assets with deposits and borrowings, so their asset base is very large relative to profit. An ROA near 1% is typical for a well-run bank, while the same figure would be poor for an industrial or software company. Compare banks with banks.

#### Return on Equity (ROE)
source: https://www.geminiq.com/metrics/returns-and-profitability/return-on-equity

**Definition:**
Return on Equity measures how much profit a company generates for every dollar of shareholders' equity. It divides trailing twelve-month net income by average shareholders' equity and is expressed as a percentage. ROE is one of the most widely tracked profitability metrics because it directly measures the return being generated on the capital that shareholders have invested.

A high ROE can indicate genuine operational excellence, but it can also be artificially inflated by leverage. A company that finances its assets heavily with debt will have a smaller equity base, and even a modest net income will produce a high ROE. This is why ROE should always be evaluated alongside leverage ratios — a 25% ROE driven by strong margins is fundamentally different from a 25% ROE driven by 5x leverage.

ROE can be meaningless or misleading for companies with negative equity (due to large accumulated deficits or aggressive buyback programs). In those cases, ROIC is typically a better measure of capital efficiency.

**Formula:**
ROE = Net Income (TTM) / Average Shareholders' Equity

Where Average Equity = (Total Equity current period + Total Equity same period prior year) / 2

**What Is a Good ROE?**
The common rule of thumb is that an ROE above 15% is strong. Among US companies with a market capitalization above $2 billion, the median ROE is 11.7%, the middle half fall between 3.1% and 21.8%, and about 40% clear 15%. For companies above $10 billion the median is 14.9%. About 21% of companies above $2 billion have a negative ROE because they lost money over the last twelve months.

| Industry | Median | Middle 50% |
| --- | --- | --- |
| Pharma & biotech | -36.8% | -67.6% – 7.4% |
| Medical devices | 3.4% | -22.1% – 15.7% |
| REITs | 5.2% | 0.6% – 9.9% |
| Software & IT services | 6.5% | -8.9% – 23.9% |
| Telecom & media | 7.1% | -5.7% – 18.1% |
| Food & beverage | 8.3% | 1.6% – 17.2% |
| Utilities | 9.8% | 6.9% – 12.2% |
| Oil & gas | 10.0% | -0.3% – 20.2% |
| Semiconductors & hardware | 10.1% | -3.2% – 21.3% |
| Industrial manufacturing | 10.5% | 2.6% – 18.1% |
| Transportation | 10.8% | 1.8% – 21.6% |
| Banks | 10.9% | 8.7% – 12.9% |
| Insurance | 14.0% | 8.3% – 22.1% |
| Retail | 14.3% | 2.9% – 32.4% |

Banks, insurers, and utilities cluster tightly around 10% to 14% because regulation and capital requirements limit how much they can earn on equity. Retailers and software companies spread much wider, from losses to returns above 25%. Pharmaceutical and biotech medians are negative because many are still developing products.

Check how a high ROE is achieved. Heavy borrowing or large buybacks shrink equity and raise ROE without improving the business, and a company with negative equity can show a meaningless figure. Comparing ROE with ROIC and the debt-to-equity ratio separates operating strength from leverage. Figures are GeminIQ calculations across US companies that file with the SEC, using each company's latest reported period as of September 2026. The middle 50% runs from the 25th to the 75th percentile. The industry table groups companies by SIC code and includes those above $300 million in market capitalization.

**How GeminIQ Calculates This Metric:**
GeminIQ divides trailing twelve-month Net Income by Average Total Equity, sourced directly from the company's SEC filings. Average equity uses the current period and the same quarter one year prior to align with the TTM earnings window.

**FAQ:**
### What is a good ROE?


The common benchmark is above 15%. For US companies above $2 billion in market cap, the median ROE is 11.7% and about 40% clear 15%. Banks, insurers, and utilities cluster around 10% to 14%. Check that a high ROE comes from the business rather than from heavy borrowing or buybacks that shrink equity.

### Why can ROE be misleading?

ROE can be inflated by leverage — a company with very little equity due to high debt or buybacks will show a high ROE even if its actual business profitability is unremarkable. ROE is also meaningless when equity is negative. For a complete picture, pair ROE with ROA (to strip out leverage) and ROIC (to measure efficiency of all invested capital, not just equity).

### Why might ROE differ between financial platforms?

Differences commonly arise from how shareholders' equity is defined. Some aggregators include minority interests in equity, others exclude it. Some include preferred equity, others classify it separately. These reclassifications change the denominator and therefore the ratio. GeminIQ uses Total Shareholders' Equity as reported in the company's filing.

### What does a 20% ROE mean?

The company earned 20 cents of net income over the last twelve months for every dollar of average shareholders' equity. That is above the 15% benchmark and close to the 75th percentile (21.8%) for US companies above $2 billion in market cap, provided it is not the product of heavy debt or a shrunken equity base.

### What is the difference between ROE and ROCE?

ROE divides net income by shareholders' equity only. Return on capital employed (ROCE) divides operating profit before interest and tax by capital employed, which includes debt as well as equity. ROCE therefore measures the whole business regardless of how it is financed, while ROE shows the return left for shareholders after the effect of leverage.

### What is the DuPont formula for ROE?

DuPont analysis splits ROE into three parts: net profit margin (net income over revenue), asset turnover (revenue over assets), and the equity multiplier (assets over equity). Multiplying them gives ROE, and the split shows whether a high ROE comes from margins, efficiency, or leverage.

#### Return on Invested Capital (ROIC)
source: https://www.geminiq.com/metrics/returns-and-profitability/return-on-invested-capital

**Definition:**
Return on invested capital (ROIC) measures how efficiently a company converts its total invested capital into after-tax operating profit. It is widely considered the single most important metric for evaluating long-term business quality because it answers a fundamental question: for every dollar of capital put into this business by both debt and equity investors, how many cents of operating profit does it generate?

ROIC separates great businesses from mediocre ones. A company that consistently earns a ROIC above its cost of capital is creating economic value — every dollar invested in the business generates a return that exceeds what investors could earn elsewhere at similar risk. A company that consistently earns a ROIC below its cost of capital is destroying value, even if it appears profitable on a net income basis.

GeminIQ calculates ROIC using the financing approach, which defines invested capital from the right side of the balance sheet: Total Equity + Total Debt − Excess Cash. This approach is more robust than the operating approach (which requires classifying every asset as operating vs. financial) because it does not break when companies reclassify line items on their balance sheet.

ROIC is most meaningful when compared to the company's weighted average cost of capital (WACC), which typically ranges from 7% to 12% for most US companies. A ROIC consistently above 15% is strong. Above 25% is exceptional and usually indicates a durable competitive advantage.

**Formula:**
ROIC = NOPAT (TTM) / Average Invested Capital

Where:

- NOPAT = EBIT (TTM) × (1 − Effective Tax Rate)
- Invested Capital = Total Equity + Total Debt − Excess Cash
- Excess Cash = Total Cash − Operating Cash (estimated as 2% of TTM Revenue, capped at total cash)
- Average Invested Capital = (Invested Capital current + Invested Capital prior year) / 2

**What is a good ROIC?**
A good ROIC is one that stays above the company's cost of capital. For US companies above $2 billion in market cap, excluding banks, insurers, and REITs, the median ROIC is 9.7% and about 28% earn more than 15%. A ROIC held above 15% for several years is uncommon and usually signals a durable competitive advantage.

### Why is ROIC better than ROE for evaluating business quality?

ROE only measures the return to equity holders and can be artificially inflated by leverage — a company that adds debt reduces its equity base, which increases ROE even if the business itself is not more profitable. ROIC measures the return on all invested capital (debt + equity), making it immune to leverage effects. Two companies with identical operations but different debt levels will have different ROEs but the same ROIC.

### Why might ROIC values differ significantly between platforms?

ROIC is highly sensitive to how invested capital is calculated. Different platforms use different approaches: the operating approach (classifying each asset as operating or financial), the financing approach (equity + debt − excess cash), or simplified versions that skip the excess cash adjustment entirely. The tax rate used for NOPAT also varies — some platforms apply a fixed 21% rate while GeminIQ uses the actual effective rate from the filing. These methodological differences can produce materially different ROIC values for the same company.

**How GeminIQ Calculates This Metric:**
GeminIQ uses the financing approach to invested capital, calculating it as Total Equity + Total Debt (Short-Term + Long-Term) − Excess Cash. Excess cash is estimated by assuming a company needs roughly 2% of annual revenue as operating cash, with any cash above that level considered excess. The effective tax rate is derived from the company's actual filed income tax expense and pretax income rather than using a fixed assumed rate. ROIC is set to null when invested capital is negative, which occurs for some highly leveraged or early-stage companies. All inputs are sourced from XBRL-tagged SEC filings.

**FAQ:**
### What is a good ROIC?


A good ROIC is one that stays above the company's cost of capital. For US companies above $2 billion in market cap, excluding banks, insurers, and REITs, the median ROIC is 9.7% and about 28% earn more than 15%. A ROIC held above 15% for several years is uncommon and usually signals a durable competitive advantage.

### Why is ROIC better than ROE for evaluating business quality?

ROE only measures the return to equity holders and can be artificially inflated by leverage — a company that adds debt reduces its equity base, which increases ROE even if the business itself is not more profitable. ROIC measures the return on all invested capital (debt + equity), making it immune to leverage effects. Two companies with identical operations but different debt levels will have different ROEs but the same ROIC.

### Why might ROIC values differ significantly between platforms?

ROIC is highly sensitive to how invested capital is calculated. Different platforms use different approaches: the operating approach (classifying each asset as operating or financial), the financing approach (equity + debt − excess cash), or simplified versions that skip the excess cash adjustment entirely. The tax rate used for NOPAT also varies — some platforms apply a fixed 21% rate while GeminIQ uses the actual effective rate from the filing. These methodological differences can produce materially different ROIC values for the same company.

### Valuation Metrics
source: https://www.geminiq.com/metrics/valuation-metrics

#### Dividend Yield
source: https://www.geminiq.com/metrics/valuation-metrics/dividend-yield

**Definition:**
Dividend yield measures the annual dividend income a stock generates relative to its market capitalization. It tells income-focused investors what percentage return they receive in dividends alone, before any stock price appreciation.

**Formula:**
Dividend Yield = Dividends Paid (TTM) / Market Capitalization

**What is a good dividend yield?**
The S&P 500 average yield is roughly 1.3-1.7%. Yields above 3% are considered high. Above 6% may indicate the market expects a dividend cut — very high yields are often a sign of price decline rather than generous payouts.

### Why can a high dividend yield be a warning sign?

Dividend yield rises when the stock price falls. A company whose stock has dropped 50% will see its yield double even if the dividend is unchanged. Very high yields often reflect market skepticism about the sustainability of the dividend.

### Why might dividend yield differ between platforms?

Timing differences in the stock price and whether the platform uses dividends paid vs. declared are the main sources. GeminIQ uses actual dividends paid and period-end market cap.

### How do you calculate dividend yield?

Divide the annual dividend per share by the share price, or equivalently total dividends paid by market capitalization. A stock paying $2.00 a year in dividends and trading at $50 has a dividend yield of 4%. GeminIQ uses trailing twelve-month dividends paid from the cash flow statement.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM dividends paid from the cash flow statement by market cap at the filing period end date.

**FAQ:**
### What is a good dividend yield?

The S&P 500 average yield is roughly 1.3-1.7%. Yields above 3% are considered high. Above 6% may indicate the market expects a dividend cut — very high yields are often a sign of price decline rather than generous payouts.

### Why can a high dividend yield be a warning sign?

Dividend yield rises when the stock price falls. A company whose stock has dropped 50% will see its yield double even if the dividend is unchanged. Very high yields often reflect market skepticism about the sustainability of the dividend.

### Why might dividend yield differ between platforms?

Timing differences in the stock price and whether the platform uses dividends paid vs. declared are the main sources. GeminIQ uses actual dividends paid and period-end market cap.

### How do you calculate dividend yield?

Divide the annual dividend per share by the share price, or equivalently total dividends paid by market capitalization. A stock paying $2.00 a year in dividends and trading at $50 has a dividend yield of 4%. GeminIQ uses trailing twelve-month dividends paid from the cash flow statement.

#### Enterprise Value (EV)
source: https://www.geminiq.com/metrics/valuation-metrics/enterprise-value

**Definition:**
Enterprise value represents the total theoretical cost to acquire a company — what an acquirer would need to pay to buy all the equity and assume all the debt, minus the cash they would gain access to. It is a more comprehensive measure of a company's total value than market capitalization alone because it accounts for capital structure.

**Formula:**
Enterprise Value = Market Capitalization + Short-Term Debt + Long-Term Debt − Cash and Cash Equivalents

**How GeminIQ Calculates This Metric:**
GeminIQ computes EV by adding short-term and long-term debt to market cap and subtracting cash, all from the SEC filing as-filed balance sheet. Market cap uses period-end price × basic shares.

**FAQ:**
### Why is enterprise value used instead of market cap?

Market cap only values the equity. Enterprise value includes debt and subtracts cash, giving a capital-structure-neutral view of the business. This makes EV-based ratios (EV/EBITDA, EV/EBIT) comparable across companies with different leverage — a company that finances with debt vs. one that finances with equity will have similar EV-based multiples if their operations are similar.

### What does negative enterprise value mean?

Negative EV means the company's cash exceeds its market cap plus debt — the market is valuing the business at less than its net cash. This is rare and can indicate deep distress, an imminent liquidation event, or extreme market pessimism. It is also screened for by certain deep-value strategies.

### Why might enterprise value differ between platforms?

Differences in debt definitions (total liabilities vs. interest-bearing debt only), cash definitions (including or excluding restricted cash), and share count methodology all affect EV. GeminIQ uses Short-Term Debt + Long-Term Debt as filed, minus Cash and Cash Equivalents as filed.

### What is the formula for enterprise value?

Enterprise value equals market capitalization plus total debt minus cash and cash equivalents. A company worth $50 billion in the stock market with $10 billion of debt and $5 billion of cash has an enterprise value of $55 billion.

### Is enterprise value the same as EBITDA?

No. Enterprise value is a valuation, what it would cost to buy the whole business including its debt. EBITDA is a measure of annual operating earnings. The two are combined in the EV/EBITDA multiple, which divides enterprise value by EBITDA to show how many years of operating earnings the business is priced at.

#### EV/EBIT
source: https://www.geminiq.com/metrics/valuation-metrics/ev-ebit

**Definition:**
EV/EBIT is similar to EV/EBITDA but uses EBIT rather than EBITDA in the denominator. Because EBIT includes the cost of depreciation and amortization, EV/EBIT captures the ongoing cost of maintaining the company's asset base, producing a more conservative valuation multiple than EV/EBITDA. It is particularly useful for capital-intensive businesses where depreciation is a meaningful ongoing expense.

**Formula:**
EV/EBIT = Enterprise Value / EBIT (TTM)

**What is a good EV/EBIT?**
EV/EBIT will always be higher than EV/EBITDA for the same company because EBIT is a smaller number than EBITDA. Typical ranges are 10-20x for most industries. Below 10x is value territory. Above 25x is expensive.

### Why might EV/EBIT differ between platforms?

EBIT can differ based on whether the platform derives it from operating income or from net income + tax + interest. These can diverge when non-operating items are classified differently. GeminIQ derives EBIT from Net Income + Income Tax + Interest Expense when not directly reported.

**How GeminIQ Calculates This Metric:**
GeminIQ divides enterprise value by TTM EBIT from SEC filings. EBIT is taken from the filing directly or derived as Net Income + Income Tax + Interest Expense.

**FAQ:**
### When should I use EV/EBIT instead of EV/EBITDA?

Use EV/EBIT for capital-intensive businesses where depreciation represents a real ongoing cost of maintaining the asset base (manufacturing, infrastructure, airlines). EV/EBITDA is more useful when comparing across companies with different depreciation policies or when D&A significantly exceeds actual maintenance capex.

### What is a good EV/EBIT?

EV/EBIT will always be higher than EV/EBITDA for the same company because EBIT is a smaller number than EBITDA. Typical ranges are 10-20x for most industries. Below 10x is value territory. Above 25x is expensive.

### Why might EV/EBIT differ between platforms?

EBIT can differ based on whether the platform derives it from operating income or from net income + tax + interest. These can diverge when non-operating items are classified differently. GeminIQ derives EBIT from Net Income + Income Tax + Interest Expense when not directly reported.

#### EV/EBITDA
source: https://www.geminiq.com/metrics/valuation-metrics/ev-ebitda

**Definition:**
EV/EBITDA is the enterprise value equivalent of the P/E ratio — it measures what acquirers are paying per dollar of operating earnings. Because it uses enterprise value (which is capital-structure-neutral) and EBITDA (which strips out interest, taxes, depreciation, and amortization), it allows comparison across companies with different leverage, tax situations, and depreciation policies. EV/EBITDA is the most widely used valuation metric in M&A, private equity, and institutional investment analysis.

**Formula:**
EV/EBITDA = Enterprise Value / EBITDA (TTM)

**What is a good EV/EBITDA?**
Below 8x is generally considered value territory. Between 8x and 15x is moderate. Above 15x is expensive unless justified by growth. Large US companies have often traded in the low-to-mid teens. Private equity firms typically target acquisitions in the 6-10x range.

### Why is EV/EBITDA preferred over P/E in M&A?

An acquirer buys the entire business — equity and debt — so enterprise value is the relevant price. EBITDA approximates the pre-investment cash flow of the business before financing and tax decisions, making it comparable across different potential acquisition targets with different capital structures.

### Why might EV/EBITDA differ between platforms?

Both the numerator (EV) and denominator (EBITDA) are sensitive to definition choices. EV depends on debt and cash definitions. EBITDA depends on whether it is calculated from EBIT + D&A or from operating income + D&A, which can produce different results if non-operating items are classified differently. GeminIQ uses EBIT + D&A when EBITDA is not directly reported.

### What does EV/EBITDA tell you?

It tells you how many years of current operating earnings, before interest, taxes, depreciation, and amortization, it would take to pay back the full price of the business including its debt. An EV/EBITDA of 10 means the company is valued at ten times its trailing twelve-month EBITDA.

### Is it better to have a higher or lower EV/EBITDA?

For a buyer, lower is cheaper: a lower multiple means paying less for each dollar of operating earnings. A higher multiple is not necessarily bad, since fast-growing or high-margin companies earn premium multiples. Compare against peers and the company's own history rather than a fixed cutoff.

**How GeminIQ Calculates This Metric:**
GeminIQ divides enterprise value by TTM EBITDA, both derived from SEC filing data. EBITDA is taken from the filing directly or calculated as EBIT + Depreciation & Amortization.

**FAQ:**
### What is a good EV/EBITDA?

Below 8x is generally considered value territory. Between 8x and 15x is moderate. Above 15x is expensive unless justified by growth. Large US companies have often traded in the low-to-mid teens. Private equity firms typically target acquisitions in the 6-10x range.

### Why is EV/EBITDA preferred over P/E in M&A?

An acquirer buys the entire business — equity and debt — so enterprise value is the relevant price. EBITDA approximates the pre-investment cash flow of the business before financing and tax decisions, making it comparable across different potential acquisition targets with different capital structures.

### Why might EV/EBITDA differ between platforms?

Both the numerator (EV) and denominator (EBITDA) are sensitive to definition choices. EV depends on debt and cash definitions. EBITDA depends on whether it is calculated from EBIT + D&A or from operating income + D&A, which can produce different results if non-operating items are classified differently. GeminIQ uses EBIT + D&A when EBITDA is not directly reported.

### What does EV/EBITDA tell you?

It tells you how many years of current operating earnings, before interest, taxes, depreciation, and amortization, it would take to pay back the full price of the business including its debt. An EV/EBITDA of 10 means the company is valued at ten times its trailing twelve-month EBITDA.

### Is it better to have a higher or lower EV/EBITDA?

For a buyer, lower is cheaper: a lower multiple means paying less for each dollar of operating earnings. A higher multiple is not necessarily bad, since fast-growing or high-margin companies earn premium multiples. Compare against peers and the company's own history rather than a fixed cutoff.

#### EV/FCF
source: https://www.geminiq.com/metrics/valuation-metrics/ev-fcf

**Definition:**
EV/FCF divides a company's enterprise value by its trailing twelve-month free cash flow — operating cash flow minus capital expenditures. Where EV/EBITDA and EV/EBIT rely on accrual-accounting measures of earnings, EV/FCF anchors the multiple to actual cash generated after the business has funded the capital investment needed to sustain and grow itself. It answers a direct question: at what multiple of real, spendable cash flow is the market pricing this business?

Because free cash flow already nets out capital expenditures, EV/FCF avoids the criticism most commonly leveled at EV/EBITDA — that EBITDA ignores the real cost of maintaining a capital-intensive asset base. A business with heavy depreciation and correspondingly heavy maintenance capex will show a much higher (more expensive) EV/FCF than its EV/EBITDA multiple suggests, revealing capital intensity that EBITDA-based multiples can mask.

**Formula:**
EV/FCF = Enterprise Value / Free Cash Flow (TTM)

**How GeminIQ Calculates This Metric:**
GeminIQ computes EV/FCF by dividing enterprise value by trailing twelve-month free cash flow, where free cash flow is TTM operating cash flow minus TTM capital expenditures (see [Free Cash Flow](/metrics/calculated-values/free-cash-flow)). Both enterprise value and free cash flow are built from as-filed SEC data — see the [Enterprise Value](/metrics/valuation-metrics/enterprise-value) page for how enterprise value is constructed.

**FAQ:**
### How is EV/FCF different from EV/EBITDA?

EBITDA adds back depreciation and amortization on the premise that they are non-cash charges, but for capital-intensive businesses, depreciation approximates the real ongoing cost of maintaining the asset base. Free cash flow subtracts actual capital expenditures instead of ignoring them, so EV/FCF reflects the cash left over after that spending has already happened. A large gap between a company's EV/EBITDA and EV/FCF multiples — EV/FCF being meaningfully higher — is a signal of high capital intensity relative to reported earnings.

### Why can EV/FCF be volatile or misleading in a single period?

Capital expenditures are often lumpy — a company may complete a large facility build-out or equipment purchase in one year and spend comparatively little the next. A single period's free cash flow can understate normalized cash generation during a heavy investment year and overstate it during a lull. Comparing EV/FCF across several years, rather than relying on a single trailing-twelve-month figure, gives a more representative picture.

### Why might EV/FCF differ between platforms?

The two most common sources of divergence are how enterprise value is built (see the Enterprise Value page) and what counts as a capital expenditure — some platforms include acquisitions or capitalized software costs in capex, others exclude them. GeminIQ uses capital expenditures as reported on the as-filed cash flow statement, taken as an outflow.

#### EV/Revenue
source: https://www.geminiq.com/metrics/valuation-metrics/ev-revenue

**Definition:**
EV/Revenue (also called EV/Sales) divides a company's enterprise value by its trailing twelve-month net revenue. Because enterprise value accounts for both debt and cash on the balance sheet, EV/Revenue is capital-structure-neutral in the same way EV/EBITDA and EV/EBIT are — it compares the total cost of acquiring the business (equity plus net debt) to the top-line revenue it generates, independent of how that business happens to be financed.

EV/Revenue is most useful when a company has no profit to anchor a P/E or EV/EBITDA multiple to — early-stage growth companies, cyclical businesses at a trough, or businesses undergoing a temporary margin compression. Because it uses revenue rather than any measure of profit, it says nothing on its own about profitability or the path to profitability; a low EV/Revenue multiple on a structurally unprofitable business is not necessarily cheap.

**Formula:**
EV/Revenue = Enterprise Value / Total Revenue (TTM)

**How GeminIQ Calculates This Metric:**
GeminIQ computes EV/Revenue by dividing enterprise value by trailing twelve-month net revenue, both derived directly from as-filed SEC data. Enterprise value is built from market capitalization plus total debt and minority interest, minus cash and cash equivalents — see the [Enterprise Value](/metrics/valuation-metrics/enterprise-value) page for the exact components.

**FAQ:**
### How is EV/Revenue different from P/S (price-to-sales)?

Price-to-sales compares market capitalization — the equity value alone — to revenue, ignoring debt and cash entirely. EV/Revenue compares the total enterprise value — equity plus net debt — to revenue. Two companies with identical P/S ratios can have very different EV/Revenue multiples if one carries significant debt and the other holds a large net cash position, making EV/Revenue the more capital-structure-aware comparison of the two.

### What is a "good" EV/Revenue multiple?

There is no universal answer — it varies enormously by industry and growth rate. Software and other high-margin, high-growth businesses regularly trade at high-single-digit or double-digit multiples, while low-margin businesses like retailers or distributors often trade below 1x. EV/Revenue is best used to compare similar companies within the same industry, or the same company against its own historical range, rather than as an absolute threshold.

### Why might EV/Revenue differ between platforms?

The most common source of variation is how enterprise value is constructed — specifically, what counts as debt (operating leases, minority interest, preferred stock) and how cash is treated. GeminIQ builds enterprise value from as-filed balance sheet components rather than a normalized template, so the individual inputs are visible and traceable to the original filing.

#### Free Cash Flow Yield
source: https://www.geminiq.com/metrics/valuation-metrics/free-cash-flow-yield

**Definition:**
Free cash flow yield measures a company's free cash flow as a percentage of its market capitalization. It is the cash-flow equivalent of earnings yield (inverse of P/E) and represents the return investors would receive if the company distributed all of its free cash flow to shareholders. FCF yield is widely regarded as one of the most useful single-number valuation metrics because it combines operating efficiency, capital discipline, and market pricing into one figure.

**Formula:**
FCF Yield = Free Cash Flow (TTM) / Market Capitalization

Where FCF = Operating Cash Flow − Capital Expenditures

**What is a good free cash flow yield?**
Above 5% is generally attractive and suggests the market may be undervaluing the company's cash generation. Between 3% and 5% is moderate. Below 2% is expensive unless justified by high growth. The 10-year Treasury yield is a useful comparison point — if a company's FCF yield is below the risk-free rate, you need to believe strongly in future growth to justify the price.

### Why is FCF yield often preferred over P/E for valuation?

FCF yield is based on actual cash generation after all necessary capital spending, which is harder to manipulate than accounting earnings. It also incorporates capital discipline — a company that generates the same earnings as a peer but requires less capex will have a higher FCF yield.

### Why might FCF yield differ between platforms?

Differences in how capex is defined and how market cap is calculated are the main sources. GeminIQ uses as-filed capex and period-end market cap using basic shares.

**How GeminIQ Calculates This Metric:**
GeminIQ divides TTM free cash flow (operating cash flow minus capex) by market cap at the filing period end. All inputs are from SEC filings.

**FAQ:**
### What is a good free cash flow yield?

Above 5% is generally attractive and suggests the market may be undervaluing the company's cash generation. Between 3% and 5% is moderate. Below 2% is expensive unless justified by high growth. The 10-year Treasury yield is a useful comparison point — if a company's FCF yield is below the risk-free rate, you need to believe strongly in future growth to justify the price.

### Why is FCF yield often preferred over P/E for valuation?

FCF yield is based on actual cash generation after all necessary capital spending, which is harder to manipulate than accounting earnings. It also incorporates capital discipline — a company that generates the same earnings as a peer but requires less capex will have a higher FCF yield.

### Why might FCF yield differ between platforms?

Differences in how capex is defined and how market cap is calculated are the main sources. GeminIQ uses as-filed capex and period-end market cap using basic shares.

#### Market Capitalization
source: https://www.geminiq.com/metrics/valuation-metrics/market-capitalization

**Definition:**
Market capitalization is the total market value of a company's outstanding shares of stock, calculated by multiplying the stock price by the number of shares outstanding. It represents the market's current consensus on what the entire company is worth and is the starting point for nearly all valuation analysis.

Market cap is used to categorize companies by size: mega-cap (above $200B), large-cap ($10B-$200B), mid-cap ($2B-$10B), small-cap ($300M-$2B), and micro-cap (below $300M). These size categories affect which funds can invest in a stock, how liquid the shares are, and what benchmark the company is measured against.

**Formula:**
Market Capitalization = Stock Price × Basic Shares Outstanding

**How GeminIQ Calculates This Metric:**
GeminIQ multiplies the closing stock price on the filing period end date by the period-end basic shares outstanding from the SEC filing. This ensures market cap is calculated on the same share count basis used for all per-share metrics, maintaining internal consistency. The stock price is sourced from market data for the trading day closest to the filing period end date.

**FAQ:**
### Why does GeminIQ use period-end basic shares for market cap?

Using period-end basic shares (rather than diluted shares or a different date's count) ensures that market cap is on the same basis as EPS, cash flow per share, and all other per-share metrics on GeminIQ. This prevents apples-to-oranges comparisons when using market cap in ratio calculations like P/E, P/B, and P/S.

### Is market cap the same as enterprise value?

No. Market cap values only the equity portion of the company. Enterprise value adds net debt (total debt minus cash) to market cap, representing the total cost to acquire the entire business including assuming its debt and gaining access to its cash.

### Why might market cap differ between platforms?

Differences arise from the stock price date used and the share count source. Some platforms use real-time prices, others use period-end prices. Share counts can differ depending on whether the platform uses basic vs. diluted shares and whether it uses the SEC-reported count or a more recent estimate. GeminIQ uses the period-end price and basic shares from the filing.

#### PEG Ratio
source: https://www.geminiq.com/metrics/valuation-metrics/peg-ratio

**Definition:**
The PEG ratio divides a company's P/E ratio by its earnings growth rate, popularized by Peter Lynch as a shorthand for judging whether a growth stock's valuation is reasonable relative to how fast it is growing. The intuition: a P/E of 20 on a company growing earnings 20% annually (PEG of 1.0) is a materially different proposition than a P/E of 20 on a company growing 5% annually (PEG of 4.0), even though the two companies have identical P/E ratios.

Lynch generally considered a PEG below 1.0 attractive — the market is pricing the stock at a discount to its growth rate — and a PEG above 2.0 a sign the growth premium has become excessive. The PEG ratio is a heuristic, not a valuation model: it assumes a roughly linear relationship between P/E and growth that doesn't hold precisely, it says nothing about how sustainable the growth rate is, and it becomes unreliable or meaningless when earnings growth is negative, near zero, or driven by a low prior-year base rather than genuine business improvement.

**Formula:**
PEG Ratio = P/E (TTM) / EPS Growth Rate (TTM, 1Y)

**What Is a Good PEG Ratio?**
The conventional reading is that a PEG ratio below 1.0 means the stock's P/E is low relative to its earnings growth, around 1.0 is fairly valued, and well above 1.0 is expensive for its growth. GeminIQ's data shows why that rule needs care: about 34% of US companies with a market capitalization above $2 billion have a negative or undefined PEG because their earnings shrank or turned to a loss, and about 39% show a PEG below 1.0.

Many of those low readings are not bargains. GeminIQ's PEG uses trailing one-year EPS growth, and a company whose earnings rebound from a depressed year can post growth of several hundred percent, which drives its PEG toward zero even though that pace cannot continue. For that reason GeminIQ does not publish a typical PEG range; the distribution is dominated by one-off growth rates.

Use the PEG ratio as a screen rather than a verdict. Check that the growth behind it is sustained over several years, that earnings are positive, and that the company's P/E is reasonable for its industry before treating a low PEG as a sign of value.

**How GeminIQ Calculates This Metric:**
GeminIQ computes the PEG ratio as trailing twelve-month P/E divided by trailing-twelve-month EPS growth over the prior year, both sourced from as-filed SEC data — see [P/E Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) and [EPS Growth](/metrics/growth-metrics/earnings-per-share-growth) for how each input is calculated. The growth rate is expressed as a whole number (e.g., 20 for 20% growth) rather than a decimal, matching Lynch's original convention.

**FAQ:**
### What is a good PEG ratio?

Conventionally, below 1.0 suggests the P/E is low relative to earnings growth and above 1.0 suggests the opposite. Treat it as a screen, not a verdict: about 34% of US companies above $2 billion in market cap have a negative or undefined PEG, and many very low readings come from one-year earnings rebounds that will not repeat.

### Why does the PEG ratio use EPS growth instead of revenue growth?

The PEG ratio was designed to test whether the premium the market pays for earnings (via the P/E ratio) is justified by how fast those same earnings are growing — so it pairs an earnings-based price multiple with an earnings-based growth rate. Revenue growth can diverge significantly from earnings growth (through margin changes, share buybacks, or one-time items), which is why GeminIQ's screener also exposes revenue growth as its own filterable field for building a more complete GARP screen alongside the PEG ratio.

### What does a negative or undefined PEG ratio mean?

A negative PEG ratio usually results from negative earnings growth (a shrinking or newly-loss-making earnings base) rather than a mathematically meaningful "cheap" signal, and should generally be excluded from screens rather than interpreted at face value. The same caution applies to a very low positive growth rate in the denominator, which can produce an extremely high PEG ratio from a small, possibly noisy, growth figure.

### Why might PEG ratios differ between platforms?

PEG ratios diverge most often because of differences in the growth rate used — trailing vs. forward growth, GAAP EPS vs. adjusted/non-GAAP EPS, and one-year vs. multi-year growth windows all produce different denominators for the same company. GeminIQ computes both P/E and EPS growth from as-filed GAAP figures rather than adjusted or forward estimates, so the PEG ratio reflects the company's own reported results.

#### Price-to-Book Ratio (P/B)
source: https://www.geminiq.com/metrics/valuation-metrics/price-to-book-ratio

**Definition:**
The price-to-book ratio divides market capitalization by total shareholders' equity (book value). It measures how much investors are paying relative to the company's net asset value on the balance sheet. A P/B of 1.0 means the stock trades at exactly its book value. Below 1.0 may indicate undervaluation or asset quality concerns. Above 1.0 means the market believes the company's assets are worth more than their accounting value — due to intangible assets, brand value, growth potential, or earning power not captured on the balance sheet.

**Formula:**
Price-to-Book = Market Capitalization / Total Shareholders' Equity

**What is a good P/B ratio?**
Below 1.0 is considered value territory. Between 1.0 and 3.0 is moderate for most industries. Above 5.0 is common for asset-light businesses like software and services where most of the value is in intangible assets not on the balance sheet. Financial companies are traditionally valued relative to book, with P/B near 1.0-1.5 considered fair value.

### Why do some companies have very high P/B ratios?

Companies with strong brands, intellectual property, or network effects often have minimal tangible assets on the balance sheet relative to their earning power. A software company may have $2B in book equity but $50B in market cap because the value is in its code, customers, and market position — none of which appear as assets on the balance sheet.

### Why might P/B differ between platforms?

Differences in how shareholders' equity is defined — whether it includes minority interests, preferred equity, or accumulated other comprehensive income — directly change P/B. GeminIQ uses Total Shareholders' Equity as reported.

### What does a P/B ratio below 1 mean?

The market values the company at less than the net assets on its balance sheet. That can mean the stock is undervalued, or that investors expect the assets to be written down or to earn less than their cost of capital. It is most common among banks, insurers, and asset-heavy cyclical companies.

### Which is better, P/E or P/B?

They answer different questions. P/E compares price with earnings and works best for profitable, steadily earning companies. P/B compares price with net assets and works best for banks, insurers, and other asset-heavy businesses whose balance sheets reflect their value. Asset-light companies with large intangible value are poorly served by P/B.

**How GeminIQ Calculates This Metric:**
GeminIQ divides market cap by total equity from the balance sheet as filed with the SEC.

**FAQ:**
### What is a good P/B ratio?

Below 1.0 is considered value territory. Between 1.0 and 3.0 is moderate for most industries. Above 5.0 is common for asset-light businesses like software and services where most of the value is in intangible assets not on the balance sheet. Financial companies are traditionally valued relative to book, with P/B near 1.0-1.5 considered fair value.

### Why do some companies have very high P/B ratios?

Companies with strong brands, intellectual property, or network effects often have minimal tangible assets on the balance sheet relative to their earning power. A software company may have $2B in book equity but $50B in market cap because the value is in its code, customers, and market position — none of which appear as assets on the balance sheet.

### Why might P/B differ between platforms?

Differences in how shareholders' equity is defined — whether it includes minority interests, preferred equity, or accumulated other comprehensive income — directly change P/B. GeminIQ uses Total Shareholders' Equity as reported.

### What does a P/B ratio below 1 mean?

The market values the company at less than the net assets on its balance sheet. That can mean the stock is undervalued, or that investors expect the assets to be written down or to earn less than their cost of capital. It is most common among banks, insurers, and asset-heavy cyclical companies.

### Which is better, P/E or P/B?

They answer different questions. P/E compares price with earnings and works best for profitable, steadily earning companies. P/B compares price with net assets and works best for banks, insurers, and other asset-heavy businesses whose balance sheets reflect their value. Asset-light companies with large intangible value are poorly served by P/B.

#### Price-to-Cash-Flow Ratio (P/CF)
source: https://www.geminiq.com/metrics/valuation-metrics/price-to-cash-flow-ratio

**Definition:**
Price-to-cash-flow divides market cap by trailing twelve-month operating cash flow. It is an alternative to P/E that uses cash generated from operations rather than accounting earnings. Cash flow is harder to manipulate than earnings, making P/CF a useful check on whether a stock's P/E-based valuation is supported by actual cash generation.

**Formula:**
P/CF = Market Capitalization / Operating Cash Flow (TTM)

**What is a good P/CF ratio?**
A P/CF below 10 is generally considered attractive. Between 10 and 20 is moderate. Above 20 is expensive unless justified by high growth. As with all valuation ratios, compare within the same industry.

### Why might P/CF differ between platforms?

Operating cash flow can differ if the platform adjusts for certain items. GeminIQ uses Operating Cash Flow as reported on the cash flow statement.

**How GeminIQ Calculates This Metric:**
GeminIQ divides market cap by TTM operating cash flow from the cash flow statement in SEC filings.

**FAQ:**
### When is P/CF more useful than P/E?

P/CF is more useful for capital-intensive businesses where depreciation is a large non-cash charge that depresses earnings relative to cash flow. It is also useful when comparing companies with different depreciation policies or when earnings are distorted by non-cash items.

### What is a good P/CF ratio?

A P/CF below 10 is generally considered attractive. Between 10 and 20 is moderate. Above 20 is expensive unless justified by high growth. As with all valuation ratios, compare within the same industry.

### Why might P/CF differ between platforms?

Operating cash flow can differ if the platform adjusts for certain items. GeminIQ uses Operating Cash Flow as reported on the cash flow statement.

#### Price-to-Earnings Ratio (P/E)
source: https://www.geminiq.com/metrics/valuation-metrics/price-to-earnings-ratio

**Definition:**
The price-to-earnings ratio, or P/E ratio, divides a company's market capitalization by its trailing twelve-month net income. It tells you how much investors are willing to pay for each dollar of the company's annual earnings. A P/E of 20 means investors are paying $20 for every $1 of annual earnings, or equivalently, the company's earnings yield (the inverse) is 5%.

P/E is the most widely used valuation metric and the starting point for nearly all investment analysis, but it has significant limitations. It does not account for growth (a high P/E may be justified if earnings are growing rapidly), debt levels (two companies with the same P/E but different leverage have different risk profiles), or earnings quality (companies can manage earnings through accounting choices).

P/E is undefined when earnings are negative and can be misleading when earnings are near zero (producing extremely high ratios) or depressed by one-time charges.

**Formula:**
P/E Ratio = Market Capitalization / Net Income (TTM)

**What Is a Good P/E Ratio?**
There is no single good P/E ratio, but there is a normal range. Among US companies with a market capitalization above $2 billion and positive trailing earnings, the median P/E is 21.4, and the middle half trade between 14.0 and 35.9. For companies above $10 billion the median rises to 24.7. About 19% of companies above $2 billion have zero or negative earnings, so their P/E is not meaningful.

| Industry | Median | Middle 50% |
| --- | --- | --- |
| Insurance | 12.1 | 8.5 – 16.2 |
| Banks | 12.3 | 10.8 – 14.2 |
| Oil & gas | 12.6 | 7.5 – 24.5 |
| Telecom & media | 15.0 | 6.7 – 33.4 |
| Transportation | 19.8 | 13.3 – 40.4 |
| Pharma & biotech | 20.1 | 12.8 – 49.9 |
| Food & beverage | 20.7 | 14.5 – 34.3 |
| Retail | 20.7 | 13.9 – 32.2 |
| Utilities | 21.0 | 16.3 – 25.5 |
| REITs | 24.4 | 15.0 – 38.5 |
| Software & IT services | 27.0 | 15.6 – 55.4 |
| Industrial manufacturing | 27.4 | 18.5 – 44.7 |
| Medical devices | 28.4 | 21.1 – 44.8 |
| Semiconductors & hardware | 43.2 | 24.7 – 72.2 |

Banks and insurers trade at the lowest multiples because their earnings are cyclical and tied to credit and interest rates, while semiconductor and software companies trade at the highest because investors are paying for expected growth. A P/E of 15 can be expensive for a bank and cheap for a chip designer, which is why the comparison that matters is against direct peers and the company's own history.

A low P/E is not automatically a bargain. Earnings at a cyclical peak make the ratio look cheap just before profits fall, and one-time gains can inflate trailing earnings. Figures are GeminIQ calculations across US companies that file with the SEC, using each company's latest reported period as of September 2026. The middle 50% runs from the 25th to the 75th percentile. The industry table groups companies by SIC code and includes those above $300 million in market capitalization.

**How GeminIQ Calculates This Metric:**
GeminIQ divides market cap (price × basic shares) by TTM net income from SEC filings.

**FAQ:**
### What is a good P/E ratio?


For profitable US companies above $2 billion in market cap, the median P/E is 21.4 and the middle half trade between 14.0 and 35.9. Banks and insurers typically trade near 12, while semiconductor and software companies trade far higher. A good P/E is one that is reasonable relative to direct peers and the company's own growth and history.

### Why is P/E sometimes misleading?

P/E does not account for growth, leverage, or cash on the balance sheet. A company with a P/E of 30 growing earnings at 25% annually is arguably cheaper than a company with a P/E of 15 growing at 3%. P/E also breaks down when earnings are negative or distorted by one-time items.

### Why might P/E ratios differ between platforms?

P/E depends on both the share price (which varies by timing) and net income (which can differ by definition). Some platforms use diluted shares, which produces a higher market cap and a higher P/E. GeminIQ uses period-end basic shares and TTM net income from the filing.

### Is a P/E ratio of 40 or 50 too high?

It is high for most companies. A P/E of 40 is above the 75th percentile (35.9) for profitable US companies above $2 billion in market cap. It can still be reasonable for a business growing earnings quickly, such as a semiconductor company, where the industry median is 43.2. A P/E of 50 or more needs sustained high growth to justify it.

### What does a negative P/E ratio mean?

A negative P/E means the company lost money over the last twelve months. The ratio is not meaningful in that case, so GeminIQ and most platforms show it as not meaningful rather than as a number. Price-to-sales or EV/revenue are the usual substitutes for unprofitable companies.

#### Price-to-Sales Ratio (P/S)
source: https://www.geminiq.com/metrics/valuation-metrics/price-to-sales-ratio

**Definition:**
Price-to-sales divides market cap by trailing twelve-month revenue. It is useful for valuing companies that are not yet profitable, where P/E is undefined. P/S treats all revenue dollars equally regardless of profitability, so a low P/S does not necessarily mean a stock is cheap — a company with a 2% net margin at a P/S of 0.5 may be less attractive than a company with a 25% margin at a P/S of 5.

**Formula:**
P/S = Market Capitalization / Revenue (TTM)

**What is a good P/S ratio?**
SaaS companies: 5-15x is common for high-growth names. Consumer brands: 1-3x. Retail and grocery: 0.2-0.8x. The appropriate P/S depends entirely on the margin profile — high-margin businesses justify higher P/S ratios because a larger share of each revenue dollar converts to profit.

### Why might P/S differ between platforms?

Revenue definitions can vary if the aggregator reclassifies items. GeminIQ uses as-filed revenue from SEC filings.

### Is a lower price-to-sales ratio better?

A lower P/S means you pay less for each dollar of revenue, but it is only cheaper if that revenue converts to profit. A retailer at 0.5 times sales with a 2% net margin is trading at about 25 times earnings. Always read P/S alongside the company's margins.

### What is the difference between P/S and EV/Revenue?

P/S divides market capitalization by revenue, so it ignores debt and cash. EV/Revenue divides enterprise value, which adds debt and subtracts cash, by revenue. EV/Revenue is the better comparison between companies with different balance sheets, since revenue is earned for all capital providers, not just shareholders.

**How GeminIQ Calculates This Metric:**
GeminIQ divides market cap by TTM revenue from SEC filings.

**FAQ:**
### When is P/S most useful?

P/S is most useful for early-stage companies that are not yet profitable, where P/E cannot be calculated. It is also useful for comparing companies with similar margin profiles within the same industry. It should always be paired with margin analysis — a low P/S on a low-margin business may not be attractive.

### What is a good P/S ratio?

SaaS companies: 5-15x is common for high-growth names. Consumer brands: 1-3x. Retail and grocery: 0.2-0.8x. The appropriate P/S depends entirely on the margin profile — high-margin businesses justify higher P/S ratios because a larger share of each revenue dollar converts to profit.

### Why might P/S differ between platforms?

Revenue definitions can vary if the aggregator reclassifies items. GeminIQ uses as-filed revenue from SEC filings.

### Is a lower price-to-sales ratio better?

A lower P/S means you pay less for each dollar of revenue, but it is only cheaper if that revenue converts to profit. A retailer at 0.5 times sales with a 2% net margin is trading at about 25 times earnings. Always read P/S alongside the company's margins.

### What is the difference between P/S and EV/Revenue?

P/S divides market capitalization by revenue, so it ignores debt and cash. EV/Revenue divides enterprise value, which adds debt and subtracts cash, by revenue. EV/Revenue is the better comparison between companies with different balance sheets, since revenue is earned for all capital providers, not just shareholders.


---

## Section 4c: Accounting Terms & Definitions
source: https://www.geminiq.com/financial-definitions

Plain-English definitions of income statement, balance sheet, and cash flow line items and financial ratios, each tied to the US-GAAP element companies report to the SEC.

#### Accounts & Notes Receivable
source: https://www.geminiq.com/financial-definitions/accounts-and-notes-receivable
Accounts and notes receivable is the amount a company expects to collect within the next year (or its operating cycle, if longer) for goods it has delivered and services it has performed in the ordinary course of business. It is reported net of the allowance for credit losses, so the balance reflects what the company actually expects to collect rather than the gross amount billed.

Accounts receivable are the ordinary open invoices a company extends to customers on credit. Notes receivable are the same kind of claim documented in a formal written promise to pay, often with a stated interest rate and maturity date. Balances due after more than a year are classified as noncurrent and are not part of this figure.

#### Accounts Payable
source: https://www.geminiq.com/financial-definitions/accounts-payable
Accounts payable is the amount a company owes its suppliers and vendors for goods and services it has already received but not yet paid for, as of the balance-sheet date. It is usually backed by an invoice and is expected to be paid within the company's normal credit terms, so it is reported as a current liability.

Accounts payable covers ordinary operating purchases such as inventory, raw materials, utilities, and outside services. It does not include borrowed money, wages owed to employees, taxes, or other costs the company has incurred but not yet been billed for. Those appear under debt or accrued liabilities.

#### Accounts Receivable, Net
source: https://www.geminiq.com/financial-definitions/accounts-receivable-net
Accounts receivable, net is the amount customers owe a company for goods and services it has already delivered on credit, after subtracting the allowance for credit losses the company expects never to collect. It is reported as a current asset when collection is expected within one year or the operating cycle, whichever is longer.

The net figure is gross receivables minus the allowance. It excludes formal notes and loans the company holds, amounts owed by non-customers, and receivables that fall due after more than a year, which are reported separately.

#### Accrued Liabilities
source: https://www.geminiq.com/financial-definitions/accrued-liabilities
Accrued liabilities are expenses a company has incurred but not yet paid, and in most cases not yet been billed for, as of the balance-sheet date. They are recorded so that costs land in the period they relate to, even when the cash leaves later. Amounts due within a year or the operating cycle are reported as current liabilities.

Typical accruals include wages, bonuses, and payroll taxes earned by employees, interest that has built up on debt, rent, utilities, warranty costs, and taxes other than those shown separately. Because no invoice exists, many accruals rest on management's estimates.

#### Accrued Taxes
source: https://www.geminiq.com/financial-definitions/accrued-taxes
Accrued taxes are taxes a company owes for periods already completed but has not yet paid as of the balance-sheet date. The balance is mainly income taxes currently due to federal, state, and foreign governments, and may also include sales, payroll, property, and excise taxes the company has incurred or collected but not yet remitted.

Accrued taxes are a current liability when payment is due within a year. They represent tax actually owed now. Deferred tax liabilities, by contrast, are taxes expected to become payable in future years because of timing differences between book and tax accounting.

#### Accumulated Depreciation
source: https://www.geminiq.com/financial-definitions/accumulated-depreciation
Accumulated depreciation is the total depreciation a company has charged against its property, plant, and equipment since those assets were placed in service, net of amounts removed when assets were sold or retired. It is a contra-asset: it is subtracted from the original cost of PP&E to give net PP&E, the carrying amount shown on the balance sheet.

The figure grows each period by that period's depreciation expense and falls when fully or partly depreciated assets leave the books. For natural-resource companies it usually also includes depletion, and it can include amortization of leasehold improvements and finance-lease assets.

#### Accumulated Other Comprehensive Income
source: https://www.geminiq.com/financial-definitions/accumulated-other-comprehensive-income
Accumulated other comprehensive income (AOCI) is the running total of a company's other comprehensive income, reported as a separate component of shareholders' equity on the balance sheet. It holds the after-tax gains and losses that have been recognized but kept out of net income, and it is shown as accumulated other comprehensive loss when the balance is negative.

AOCI does to other comprehensive income what retained earnings does to net income: each period's OCI is added to it, and amounts reclassified into net income are taken out.

#### Acquisition of Fixed & Intangible Assets
source: https://www.geminiq.com/financial-definitions/acquisition-of-fixed-and-intangible-assets
Acquisition of fixed and intangible assets is the total cash a company spent during a period to buy or improve long-lived operating assets, both physical assets such as property, plant, and equipment and intangible assets such as software, licenses, patents, and other rights. It is an outflow in the investing section of the cash flow statement.

It is a broader measure than property and equipment purchases alone. It captures companies whose investment in technology and intellectual property matters as much as their spending on physical capacity.

#### Acquisition of Fixed Productive Assets
source: https://www.geminiq.com/financial-definitions/acquisition-of-fixed-productive-assets
Acquisition of fixed productive assets is the cash a company paid during a period to buy, build, or improve physical long-lived assets it uses to produce goods and deliver services, such as land, buildings, machinery, vehicles, and computer hardware. It is an investing outflow on the cash flow statement and is the narrowest common definition of capital expenditures.

It excludes intangible assets such as software and licenses, and it excludes assets obtained by acquiring an entire business.

#### Acquisition of Intangible Assets
source: https://www.geminiq.com/financial-definitions/acquisition-of-intangible-assets
Acquisition of intangible assets is the cash a company paid during a period to obtain assets without physical form, such as patents, trademarks, licenses, broadcast or spectrum rights, customer lists, and software, when they are bought individually rather than as part of a business acquisition. It also commonly includes cash spent developing software for internal use that qualifies for capitalization. It is an outflow in the investing section of the cash flow statement.

Goodwill is excluded. It can arise only when a company acquires an entire business.

#### Additional Paid-In Capital
source: https://www.geminiq.com/financial-definitions/additional-paid-in-capital
Additional paid-in capital is the amount shareholders have paid a company for its stock above the stock's par or stated value, together with other increases in equity that come from transactions in the company's own shares. It is a component of stockholders' equity and is often abbreviated APIC.

Par value is usually a nominal amount, often a fraction of a cent per share, so nearly all the money raised in a share issuance lands in APIC rather than in the common stock account. APIC also moves with stock-based compensation, the exercise of employee options, and certain conversions of debt into equity.

#### After-Tax Interest Expense
source: https://www.geminiq.com/financial-definitions/after-tax-interest-expense
Formula: After-Tax Interest Expense = Interest Expense × (1 − Effective Tax Rate)
After-tax interest expense is a company's interest expense reduced by the income tax savings that the interest deduction produces, calculated as interest expense multiplied by one minus the effective tax rate. It shows the true cost of borrowing to the company once the tax benefit of deducting interest is taken into account.

Because interest is generally deductible, every dollar of interest lowers taxable income and therefore lowers the tax bill. After-tax interest expense strips that saving out, leaving the net burden that debt places on earnings. It is not a line item companies report. It is calculated from figures reported in SEC filings.

#### Allowance for Doubtful Accounts
source: https://www.geminiq.com/financial-definitions/allowance-for-doubtful-accounts
The allowance for doubtful accounts is a reserve a company sets against its receivables for the portion it does not expect to collect. It is a contra-asset: it is deducted from gross accounts receivable so that the balance sheet shows receivables at the amount the company actually expects to receive. Under current US GAAP it is called the allowance for credit losses.

The allowance is an estimate, not a record of specific defaults. It rises when the company records credit-loss expense and falls when it writes off accounts it has given up on collecting.

#### Asset Impairment Charge
source: https://www.geminiq.com/financial-definitions/asset-impairment-charge
An asset impairment charge is a noncash expense a company records when the carrying amount of an asset on its balance sheet is no longer recoverable and must be written down, usually to fair value. On the cash flow statement it is added back to net income in the operating section, because the write-down reduced earnings without any cash leaving the company.

Impairments can apply to property and equipment, goodwill, other intangible assets, right-of-use lease assets, and investments. The cash was spent earlier, when the asset was bought or the business was acquired.

#### Assets Held for Sale (Current)
source: https://www.geminiq.com/financial-definitions/assets-held-for-sale
Assets held for sale (current) are long-lived assets, or groups of assets and related liabilities called disposal groups, that a company has decided to sell and expects to sell within one year. Once assets meet the held-for-sale criteria, they are removed from their usual captions, such as property, plant and equipment, and reported together as a single current asset line.

The line can hold an individual building or piece of equipment, or an entire business unit the company is divesting. If the business being sold qualifies as a discontinued operation, its assets are usually shown here as well.

#### Basic Weighted Average Shares Outstanding
source: https://www.geminiq.com/financial-definitions/basic-weighted-average-shares
Basic weighted average shares outstanding is the average number of common shares a company had outstanding during a reporting period, with each share counted in proportion to the fraction of the period it was actually outstanding. It is the denominator of basic earnings per share.

Weighting by time keeps earnings per share fair when the share count changes mid-period. Shares issued halfway through a year count as half a share for that year, and shares repurchased and retired stop counting from the date they were bought back.

#### Beta
source: https://www.geminiq.com/financial-definitions/beta
Formula: Covariance of Stock Returns with Market Returns / Variance of Market Returns
Beta, or stock beta, measures how much a stock's price tends to move relative to the overall market. It is the slope of a regression of the stock's periodic returns against the returns of a market index, so a beta of 1.0 means the stock has historically moved in line with the market, above 1.0 means it has swung more, and below 1.0 means it has swung less.

Beta captures systematic risk, the part of a stock's volatility tied to broad market movements. It does not measure risk specific to the company, such as a failed product or a lawsuit, which tends to average out in a diversified portfolio.

#### Book Value per Share
source: https://www.geminiq.com/financial-definitions/book-value-per-share
Formula: Total Common Equity / Shares Outstanding
Book value per share (BVPS) is the common shareholders' equity on a company's balance sheet divided by the number of common shares outstanding. It is the accounting value of the net assets that belong to each common share: what would be left per share if every asset were sold and every liability paid at the amounts on the books.

It is an accounting measure, not a market one. The stock's price is set by trading and can sit far above or below book value.

#### Capital Expenditures
source: https://www.geminiq.com/financial-definitions/capital-expenditures
Capital expenditures are the cash a company spends during a period to buy, build, or improve long-lived physical assets, such as buildings, machinery, equipment, and technology infrastructure, that it uses to run its business rather than to resell. CapEx appears as an outflow in the investing section of the cash flow statement.

Because these assets serve the business for many years, their cost is capitalized on the balance sheet and expensed gradually through depreciation, instead of hitting the income statement all at once.

#### Capital (Finance) Leases – Total
source: https://www.geminiq.com/financial-definitions/capital-leases-total
Capital (finance) leases – total is the full balance-sheet liability a company owes under its finance leases, combining the portion due within the next year and the portion due later. The liability equals the present value of the lease payments still to be made, discounted at the rate implicit in the lease or the company's incremental borrowing rate.

Under ASC 842 these leases are called finance leases; before that standard, US GAAP called them capital leases. They are leases that effectively transfer control of an asset to the lessee, which is why they are treated much like a purchase financed with debt.

#### Capital Yield
source: https://www.geminiq.com/financial-definitions/capital-yield
Formula: (Ending Share Price − Beginning Share Price) / Beginning Share Price
Capital yield is the percentage change in a stock's price over a period, measured against the price at the start of that period. It captures the part of an investor's return that comes from the shares becoming more or less valuable, as opposed to the income received from dividends.

Capital yield is also called capital gains yield or price return. It is negative when the share price falls over the period, which means an investor who held throughout suffered a capital loss.

#### Capitalized Software Costs
source: https://www.geminiq.com/financial-definitions/capitalized-software-costs
Capitalized software costs are software development costs a company records as an asset instead of expensing immediately, and then amortizes over the software's expected life. They arise in two different situations with different rules: software a company develops to sell, lease, or market to customers, and software it develops for its own internal use.

Costs that are not capitalized are expensed as incurred, usually as research and development. How much a company capitalizes therefore changes both its reported expenses and its assets.

#### Cash & Cash Equivalents
source: https://www.geminiq.com/financial-definitions/cash-and-cash-equivalents
Cash and cash equivalents is the money a company holds in currency and bank deposits it can withdraw on demand, plus short-term, highly liquid investments so close to maturity that their value is practically certain. It is the first line of current assets on most balance sheets and the most liquid resource a company has.

Cash equivalents typically include Treasury bills, commercial paper, and money market funds. As a general rule only investments with an original maturity of three months or less, measured from the date the company bought them, qualify. Longer-dated securities are reported as short-term or long-term investments instead.

#### Cash, Cash Equivalents & Short-Term Investments
source: https://www.geminiq.com/financial-definitions/cash-and-short-term-investments
Cash, cash equivalents and short-term investments is the combined total of a company's cash, its cash equivalents, and the marketable securities it expects to sell or hold to maturity within the next year. It gives a fuller picture of liquid resources than cash alone, because many companies park surplus funds in securities that do not qualify as cash equivalents.

Short-term investments are usually Treasury and agency notes, corporate bonds, certificates of deposit, and similar instruments with maturities beyond three months at purchase. They may be classified as trading, available-for-sale, or held-to-maturity, and are reported as current assets.

#### Cash Flow to Firm
source: https://www.geminiq.com/financial-definitions/cash-flow-to-firm
Formula: Cash from Operating Activities + Interest Expense × (1 − Tax Rate)
Cash flow to firm is a company's operating cash flow with the after-tax cost of interest added back, giving the cash generated by operations before any payment to lenders or shareholders. It is commonly calculated as cash from operating activities plus interest expense multiplied by one minus the tax rate.

Unlike free cash flow to firm, it does not subtract capital expenditures. It measures the business's operating cash generation on a basis that does not depend on how much debt the company carries. It is not a GAAP line item and is calculated from figures reported in SEC filings.

#### Cash Flow to Net Income
source: https://www.geminiq.com/financial-definitions/cash-flow-to-net-income
Formula: Cash from Operating Activities / Net Income
Cash flow to net income divides a company's cash from operating activities by its net income for the same period. It shows how many dollars of operating cash the business generated for every dollar of profit it reported, and it is one of the simplest tests of whether reported earnings are backed by cash.

A ratio above 1.0 means operating cash flow exceeded net income. A ratio below 1.0 means the company booked more profit than it collected in cash from its operations during the period.

#### Cash for Acquisition of Subsidiaries
source: https://www.geminiq.com/financial-definitions/cash-for-acquisition-of-subsidiaries
Cash for acquisition of subsidiaries is the cash a company paid during a period to gain control of other businesses, which then become consolidated subsidiaries. It is an outflow in the investing section of the cash flow statement and is usually reported net of the cash the acquired businesses held on the acquisition date.

Only the cash part of the price appears here. Shares issued, debt assumed, and contingent payments not yet made are part of the purchase price but are not cash outflows in the period.

#### Cash for Joint Ventures
source: https://www.geminiq.com/financial-definitions/cash-for-joint-ventures
Cash for joint ventures is the cash a company invested during a period in joint ventures and other affiliates it does not control, including initial purchases of an ownership stake, later capital contributions, and advances to those entities. It is an outflow in the investing section of the cash flow statement.

These investments are typically accounted for under the equity method, which applies when a company has significant influence, often presumed at an ownership stake of 20 to 50 percent, or shares control with other partners.

#### Cash from Debt
source: https://www.geminiq.com/financial-definitions/cash-from-debt
Cash from debt is the total cash a company received from new borrowings during a period, including both long-term debt, such as bonds, notes, and term loans, and short-term debt, such as commercial paper and draws on credit lines. It is a gross inflow in the financing section of the cash flow statement.

It shows only money borrowed, not money repaid. To see whether total debt went up or down, set it against repayments of debt.

#### Cash from Divestitures
source: https://www.geminiq.com/financial-definitions/cash-from-divestitures
Cash from divestitures is the cash a company received during a period from selling a business, such as a subsidiary, division, product line, or segment, or from selling an interest in an affiliate. It is an inflow in the investing section of the cash flow statement and is typically reported net of any cash the sold business held when it left the group.

It covers sales of operating businesses. Sales of individual assets, such as equipment or a single patent, are reported separately.

#### Cash from Financing Activities
source: https://www.geminiq.com/financial-definitions/cash-from-financing-activities
Cash from financing activities, also called cash flow from financing activities, is the net cash a company raised from, or returned to, its lenders and owners during a period. It includes borrowing and repaying debt, issuing and repurchasing shares, and paying dividends. It is the third section of the cash flow statement.

A positive figure means the company brought in more capital than it paid out. A negative figure means it returned capital, through debt repayment, buybacks, or dividends, on a net basis.

#### Cash from Investing Activities
source: https://www.geminiq.com/financial-definitions/cash-from-investing-activities
Cash from investing activities, also called cash flow from investing activities, is the net cash a company spent on, or received from, long-term assets and investments during a period. It covers buying and selling property and equipment, acquiring and selling businesses, purchasing and selling securities, and making and collecting loans. It is the second section of the cash flow statement.

For most healthy companies the figure is negative, because they are spending to maintain and grow their asset base. A positive figure usually means asset sales or investment maturities exceeded new spending.

#### Cash from Long-Term Debt
source: https://www.geminiq.com/financial-definitions/cash-from-long-term-debt
Cash from long-term debt is the cash a company received during a period from borrowings that, when taken on, were due more than one year out, or beyond the operating cycle if that is longer. Typical sources are bond and note offerings, term loans, and draws on multi-year credit facilities. It is reported as an inflow in the financing section of the cash flow statement.

The classification is based on the debt's maturity when it was issued, not on how much time is left, so a five-year note stays in this category even as it nears repayment.

#### Cash from Operating Activities
source: https://www.geminiq.com/financial-definitions/cash-from-operating-activities
Cash from operating activities, better known as operating cash flow, is the net cash a company generated from, or used in, its core business during a period, after paying for things like inventory, wages, rent, interest, and taxes, and before any spending on long-term investments or any financing transactions. It is the first of the three sections of the cash flow statement.

A positive figure means the day-to-day business brought in more cash than it consumed. It is often called operating cash flow, or CFO.

#### Cash from (Repurchase of) Equity
source: https://www.geminiq.com/financial-definitions/cash-from-repurchase-of-equity
Formula: Increase in Capital Stock − Decrease in Capital Stock
Cash from (repurchase of) equity is the net cash a company raised from, or returned to, shareholders through transactions in its own stock during a period. It equals cash received from issuing shares, including employee option exercises, minus cash paid to buy back shares. A positive value means the company was a net issuer of equity; a negative value, shown in parentheses, means it was a net repurchaser.

It does not include dividends, which are a separate financing outflow.

#### Cash from Short-Term Debt
source: https://www.geminiq.com/financial-definitions/cash-from-short-term-debt
Cash from short-term debt is the cash a company received during a period from borrowings that, when taken on, were due within one year or within the operating cycle if that is longer. Common sources include commercial paper, bank overdrafts, short-term bank loans, and draws on short-term credit lines. It appears in the financing section of the cash flow statement.

Many companies report this line net of repayments, so it can represent either the gross amount borrowed or the net change in short-term borrowings.

#### Cash & Equivalents per Share
source: https://www.geminiq.com/financial-definitions/cash-per-share
Formula: Cash and Cash Equivalents / Shares Outstanding
Cash and equivalents per share is a company's cash and cash equivalents divided by the number of common shares outstanding. It shows how much of each share's price is backed by cash the company holds at the balance-sheet date.

The measure uses gross cash. It does not subtract debt, so a company can have high cash per share and still owe far more than it holds.

#### Cash to Shareholders
source: https://www.geminiq.com/financial-definitions/cash-to-shareholders
Formula: Dividends Paid + Repurchases of Common Stock − Proceeds from Issuance of Common Stock
Cash to shareholders is the total amount of cash a company returned to its stockholders during a period through dividends and share repurchases, net of any cash it raised by issuing new shares. It is calculated from figures reported in SEC filings and measures how much money actually flowed from the company to its owners.

The figure is positive when distributions exceed new stock issuance. It can be negative for a company that raised more equity than it paid out, which is common among younger, fast-growing businesses.

#### Operating Cash Flow to Average Current Liabilities
source: https://www.geminiq.com/financial-definitions/cfo-to-average-current-liabilities
Formula: Cash from Operating Activities / ((Current Liabilities at Start of Period + Current Liabilities at End of Period) / 2)
Operating cash flow to average current liabilities divides the cash a company generated from its operations over a period by the average of its current liabilities at the start and end of that period. It measures how well the business's own cash generation covers the obligations that fall due within a year.

A ratio of 1.0 means a year of operating cash flow equals the typical level of current liabilities the company carried. Unlike the current ratio, which compares two balance-sheet snapshots, this measure uses a flow of cash earned over time.

#### Operating Cash Flow to CapEx
source: https://www.geminiq.com/financial-definitions/cfo-to-capex
Formula: Cash from Operating Activities / Capital Expenditures
Operating cash flow to CapEx divides the cash a company generated from its operations by the cash it spent on capital expenditures in the same period. It shows how many times over the business could fund its investment in property, plant, and equipment from its own operating cash, without borrowing or issuing stock.

A ratio above 1.0 means operations produced more cash than the company reinvested in physical assets, leaving money for debt repayment, dividends, buybacks, or acquisitions. A ratio below 1.0 means capital spending exceeded operating cash flow and the shortfall had to be financed some other way.

#### Operating Cash Flow to Total Liabilities
source: https://www.geminiq.com/financial-definitions/cfo-to-total-liabilities
Formula: Cash from Operating Activities / Total Liabilities
Operating cash flow to total liabilities divides the cash a company generated from its operations by everything it owes, both short-term and long-term. It measures how much of the company's total obligations a year of operating cash could cover, and it is a cash-based gauge of long-term solvency.

A ratio of 0.25, for example, means operating cash flow equals a quarter of total liabilities, implying roughly four years of cash generation to cover all obligations if nothing else changed. Higher values indicate greater capacity to service and reduce what the company owes.

#### Change in Accounts Payable
source: https://www.geminiq.com/financial-definitions/change-in-accounts-payable
Change in accounts payable is the operating cash flow adjustment for how much the company's unpaid bills to suppliers grew or shrank during a period. An increase in payables is added to net income, because the company recorded costs it has not yet paid in cash. A decrease is subtracted, because the company paid down more supplier bills than it took on.

The "Inc (Dec)" label reflects that a liability works the opposite way from an asset: a rise in payables increases operating cash flow.

#### Change in Accounts Receivable
source: https://www.geminiq.com/financial-definitions/change-in-accounts-receivable
Change in accounts receivable is the adjustment in the operating section of the cash flow statement that reflects how much the amount customers owe the company grew or shrank during the period. An increase in receivables is subtracted from net income, because the company booked revenue it has not yet collected in cash. A decrease is added back, because the company collected more cash than it billed.

The label "(Inc) Dec" signals this sign convention: a rise in receivables appears as a negative number and a fall appears as a positive one.

#### Net Change in Fixed & Intangible Assets
source: https://www.geminiq.com/financial-definitions/change-in-fixed-and-intangible-assets
Formula: Disposal of Fixed & Intangible Assets − Acquisition of Fixed & Intangible Assets
Net change in fixed and intangible assets is the net cash a company spent on long-lived operating assets during a period: cash paid to buy property, plant, equipment, software, and other intangibles, minus cash received from selling such assets. It is a component of the investing section of the cash flow statement and is often referred to as net capital expenditures.

For a company that is investing, the figure is negative. It turns positive only when asset sales exceed new purchases.

#### Change in Inventories
source: https://www.geminiq.com/financial-definitions/change-in-inventories
Change in inventories is the operating cash flow adjustment for the growth or reduction in the goods a company holds for sale or for use in production during a period. When inventory rises, the increase is subtracted from net income, because the company spent cash buying or making goods that have not yet been sold and expensed. When inventory falls, the decrease is added back.

The line covers raw materials, work in process, and finished goods together. It shows how much cash was tied up in, or released from, stock on hand.

#### Change in Non-Cash Working Capital
source: https://www.geminiq.com/financial-definitions/change-in-non-cash-working-capital
Formula: Sum of the operating changes in receivables, inventories, prepaid assets, payables, and other operating assets and liabilities
Change in non-cash working capital, often reported simply as the change in working capital, is the total cash effect of movements in a company's operating current assets and liabilities, excluding cash itself and debt, during a period. It combines the individual adjustments for receivables, inventories, prepaid assets, payables, accrued liabilities, and other operating items in the operating section of the cash flow statement.

A negative figure means the company tied up cash in working capital, for example by building inventory or extending more credit to customers. A positive figure means working capital released cash.

#### Change in Other Operating Assets & Liabilities
source: https://www.geminiq.com/financial-definitions/change-in-other-operating-assets-and-liabilities
Change in other operating assets and liabilities is the catch-all working capital adjustment in the operating section of the cash flow statement. It captures the net cash effect of movements in operating balances that the company does not break out on their own line, such as accrued expenses, deferred revenue, other current assets, and miscellaneous operating liabilities.

Like the other working capital lines, increases in operating assets reduce cash flow and increases in operating liabilities add to it. Because this line nets many items together, it can be positive or negative in any period.

#### Change in Prepaid Assets
source: https://www.geminiq.com/financial-definitions/change-in-prepaid-assets
Change in prepaid assets is the operating cash flow adjustment for the rise or fall in amounts a company has paid in advance for goods or services it will receive later, such as insurance premiums, rent paid ahead of time, software subscriptions, and advance deposits to suppliers. An increase is subtracted from net income, because cash went out before the related expense was recorded. A decrease is added back, because the expense is now being recognized without new cash leaving.

It is typically one of the smaller working capital lines, but it can swing noticeably around annual renewals and large supplier deposits.

#### Common Equity to Total Assets
source: https://www.geminiq.com/financial-definitions/common-equity-to-total-assets
Formula: Total Common Equity / Total Assets
Common equity to total assets divides the book value belonging to common shareholders by the company's total assets. It shows what share of the company's assets is financed by its common owners rather than by creditors, preferred shareholders, or minority investors in its subsidiaries.

A higher percentage means the company relies less on borrowed money and other obligations. The remainder of the assets is funded by liabilities and by any preferred or noncontrolling equity.

#### Common Stock
source: https://www.geminiq.com/financial-definitions/common-stock
Common stock, as a balance-sheet line, is the par or stated value of all common shares a company has issued. It is the legal-capital portion of what shareholders paid for their shares; any amount paid above par is recorded separately as additional paid-in capital.

Because par values are usually tiny, often a penny or a fraction of a cent per share, the common stock line is typically small even at companies that have raised large sums. It changes only when shares are issued, retired, or split in ways that affect total par. Shares bought back and held in treasury normally remain in this figure, with their cost deducted elsewhere in equity.

#### Comprehensive Income
source: https://www.geminiq.com/financial-definitions/comprehensive-income
Formula: Net Income + Other Comprehensive Income (OCI)
Comprehensive income is the total change in a company's equity during a period from everything except transactions with its owners. It equals net income plus other comprehensive income (OCI), the gains and losses that accounting standards keep out of net income, such as currency translation adjustments and unrealized gains or losses on certain debt securities.

Investments by shareholders and distributions to them, such as share issuances, buybacks, and dividends, are excluded. What remains is the full after-tax result of the company's activities and of changes in the value of what it holds.

#### Contract Assets
source: https://www.geminiq.com/financial-definitions/contract-assets
A contract asset is a company's right to payment for goods or services it has already delivered to a customer, when that right still depends on something other than the passage of time, such as finishing the rest of the contract or reaching a milestone. It arises when revenue has been recognized ahead of the company's unconditional right to bill.

Contract assets are common in long-term construction, engineering, defense, and custom software work, where revenue is recognized as the work progresses but billing follows a contractual schedule.

#### Cost of Goods & Services Sold
source: https://www.geminiq.com/financial-definitions/cost-of-goods-and-services-sold
Cost of goods and services sold, usually called cost of goods sold (COGS), is the total cost of making the products a company sold and delivering the services it performed during a period. It covers direct materials, direct labor, production overhead, and the direct cost of service delivery, and it leaves out selling, administrative, and research costs.

It is a slightly narrower measure than cost of revenue. It is limited to goods and services, so costs tied to financial services or other revenue-generating activities, such as interest expense at a finance arm, fall outside it.

#### Cost of Revenue
source: https://www.geminiq.com/financial-definitions/cost-of-revenue
Cost of revenue is the total direct cost of producing the goods a company sold and delivering the services it provided during a period. It includes costs such as materials, direct labor, manufacturing overhead, and the costs of delivering services, and it excludes general costs of running the business such as selling, administrative, and research expenses.

Revenue minus cost of revenue equals gross profit, the first measure of how profitable a company's core offering is before overhead.

#### Currency Conversion Rate
source: https://www.geminiq.com/financial-definitions/currency-conversion-rate
The currency conversion rate is the exchange rate used to restate a company's financial figures from the currency they were reported in into another currency, usually US dollars, so that companies reporting in different currencies can be compared. It expresses how many units of the target currency one unit of the reporting currency is worth.

It matters mainly for companies whose statements are not presented in dollars, such as foreign private issuers filing annual reports on Form 20-F. For a US company that reports in dollars, the conversion rate to dollars is simply 1.0.

#### Decrease in Capital Stock
source: https://www.geminiq.com/financial-definitions/decrease-in-capital-stock
Decrease in capital stock is the cash a company paid during a period to buy back its own shares, whether common or preferred. Share repurchases, also called buybacks, can be made in the open market, through accelerated repurchase agreements with a bank, by tender offer, or by redeeming preferred stock. The amount is an outflow in the financing section of the cash flow statement.

Repurchased shares are either retired or held as treasury stock. Either way, the shares outstanding fall and cash leaves the company.

#### Decrease in Long-Term Investments
source: https://www.geminiq.com/financial-definitions/decrease-in-long-term-investments
Decrease in long-term investments is the cash a company received during a period when longer-term investments were sold, matured, were called or prepaid by the issuer, or were otherwise collected. Typical sources are bonds and notes reaching maturity, sales of equity stakes, and repayments on investment-type loans. It is an inflow in the investing section of the cash flow statement.

It reflects the full cash received, including any gain or loss relative to what the company paid.

#### Deferred Income Taxes
source: https://www.geminiq.com/financial-definitions/deferred-income-taxes
Deferred income taxes on the cash flow statement is the portion of the period's income tax expense (or benefit) that will be paid (or recovered) in future periods rather than now. Because it is part of the tax expense in net income but involved no cash payment this period, a deferred tax expense is added back in the operating section, and a deferred tax benefit is subtracted.

It arises from temporary differences between when income and expenses are recognized for financial reporting and when they count for tax purposes.

#### Deferred Revenue
source: https://www.geminiq.com/financial-definitions/deferred-revenue
Deferred revenue is cash a company has received, or has an unconditional right to receive, for goods or services it has not yet delivered. Because the company still owes the customer something, the amount is recorded as a liability, not revenue. It moves into revenue as the company fulfills its obligation.

Common examples are annual software subscriptions billed up front, gift cards, maintenance contracts, and customer deposits. The part expected to be earned within a year is a current liability, and the rest is noncurrent.

#### Deferred Tax Liabilities
source: https://www.geminiq.com/financial-definitions/deferred-tax-liabilities
A deferred tax liability (DTL) is income tax a company expects to pay in future years on income it has already recognized in its financial statements but has not yet reported on its tax returns. Deferred tax liabilities arise from temporary differences, where an item hits book income earlier, or tax deductions come earlier, than the other way round.

The most common source is depreciation. Tax rules often allow faster depreciation than the straight-line method used in financial reports, so taxable income runs below book income in an asset's early years. The tax saved now is expected to reverse later, and the liability records that future payment.

#### Depreciation & Amortization
source: https://www.geminiq.com/financial-definitions/depreciation-and-amortization
Depreciation and amortization (D&A) is the expense a company records during a period to spread the cost of its long-lived assets over the years they are used, depreciation for physical assets such as buildings and equipment, and amortization for intangible assets with finite lives such as customer relationships, patents, and capitalized software. On the cash flow statement it is added back to net income, because the expense reduced earnings but no cash was paid in the period.

The cash was spent when the asset was bought, and that outflow appears in investing activities as capital expenditures or acquisitions.

#### Depreciation Expense
source: https://www.geminiq.com/financial-definitions/depreciation-expense
Depreciation expense is the portion of the cost of a company's physical long-lived assets, such as buildings, machinery, vehicles, and computer equipment, that it charges against earnings in a period to reflect using those assets up. It spreads an asset's cost, less any expected salvage value, over the years the asset is expected to be useful.

Depreciation is a non-cash charge. The cash left the business when the asset was bought and was recorded then as a capital expenditure. Depreciation simply moves that cost from the balance sheet to the income statement over time.

#### Derivative & Hedging Liabilities
source: https://www.geminiq.com/financial-definitions/derivative-and-hedging-liabilities
Derivative and hedging liabilities are the fair value of derivative contracts that are currently in a loss position for the company, meaning it would have to pay to exit them at the balance-sheet date. Typical examples are interest-rate swaps, foreign-currency forwards and options, and commodity futures used to hedge fuel, metals, or energy costs.

A derivative is a contract whose value depends on an underlying price or rate and that can be settled net, usually without exchanging the full notional amount. Whether it shows up as an asset or a liability depends on which side of the contract is winning on the reporting date, so the same contract can move between the two from one quarter to the next.

#### Diluted Weighted Average Shares Outstanding
source: https://www.geminiq.com/financial-definitions/diluted-weighted-average-shares
Diluted weighted average shares outstanding is the basic weighted average share count plus the additional common shares that would exist if a company's dilutive securities, such as stock options, warrants, restricted stock units, and convertible debt or preferred stock, had been turned into common stock. It is the denominator of diluted earnings per share.

It answers a conservative question: how much of the period's earnings would each share represent if every security that could reasonably become common stock already had?

#### Discontinued Operations
source: https://www.geminiq.com/financial-definitions/discontinued-operations
Discontinued operations is the after-tax income or loss from a part of a company that has been sold, spun off, or classified as held for sale, when that disposal represents a strategic shift with a major effect on the company's operations and financial results. It is reported as a single line below income from continuing operations.

The line combines two things: the discontinued unit's own operating results for the period, and any gain or loss on disposing of it, including write-downs to fair value less costs to sell. Separating them from continuing results lets investors see what the remaining business earns.

#### Disposal of Fixed & Intangible Assets
source: https://www.geminiq.com/financial-definitions/disposal-of-fixed-and-intangible-assets
Disposal of fixed and intangible assets is the total cash a company received during a period from selling long-lived operating assets, both physical assets such as buildings, equipment, and vehicles and intangible assets such as licenses, patents, and software. It is an inflow in the investing section of the cash flow statement.

It covers individual assets or groups of assets sold outside the normal course of business. Proceeds from selling an entire business or subsidiary are reported separately as divestitures.

#### Disposal of Fixed Productive Assets
source: https://www.geminiq.com/financial-definitions/disposal-of-fixed-productive-assets
Disposal of fixed productive assets is the cash a company received during a period from selling physical long-lived assets used in its operations, such as land, buildings, machinery, vehicles, and equipment. It is an inflow in the investing section of the cash flow statement.

It includes only physical assets. Sales of intangible assets and of entire businesses are reported on other lines.

#### Disposal of Intangible Assets
source: https://www.geminiq.com/financial-definitions/disposal-of-intangible-assets
Disposal of intangible assets is the cash a company received during a period from selling assets that have no physical form, such as patents, trademarks, licenses, spectrum rights, customer lists, and software, when they are sold on their own rather than as part of a business. It is an inflow in the investing section of the cash flow statement.

Goodwill is excluded, because it cannot be sold separately from the business it belongs to.

#### Dividends Paid
source: https://www.geminiq.com/financial-definitions/dividends-paid
Dividends paid is the cash a company distributed to its shareholders as dividends during a period. It is reported as an outflow in the financing section of the cash flow statement and can include dividends on common stock, dividends on preferred stock, and distributions that subsidiaries pay to their noncontrolling (minority) owners.

It reflects cash actually paid, which can differ from the dividends the board declared in the same period.

#### EBIT
source: https://www.geminiq.com/financial-definitions/ebit
Formula: Net Income + Income Tax Expense + Interest Expense
EBIT, or earnings before interest and taxes, is a company's profit before deducting interest on its debt and income taxes. It is calculated from figures reported in SEC filings, most simply by adding interest expense and income tax expense back to net income.

Removing interest and taxes gives a view of earnings that is largely independent of how a company is financed and where it pays tax. That makes EBIT useful for comparing businesses with very different amounts of debt.

#### EBITA
source: https://www.geminiq.com/financial-definitions/ebita
Formula: EBIT + Amortization of Intangible Assets
EBITA, or earnings before interest, taxes, and amortization, is EBIT with amortization of intangible assets added back. It is calculated from figures reported in SEC filings and sits between EBIT and EBITDA: it removes the amortization charge but still deducts depreciation of physical assets.

The measure exists mainly to neutralize acquisitions. When a company buys another business, it records intangible assets such as customer relationships and technology and amortizes them for years afterward. EBITA strips out that charge, so a company that grew by acquisition can be compared with one that grew internally.

#### EBITDA Margin
source: https://www.geminiq.com/financial-definitions/ebitda-margin
Formula: EBITDA / Revenue
EBITDA margin is earnings before interest, taxes, depreciation, and amortization expressed as a percentage of revenue. It shows how much of each dollar of sales remains after operating costs, excluding the non-cash charges for depreciation and amortization and before financing costs and income taxes.

Because EBITDA is not a GAAP line item, EBITDA margin is calculated from figures reported in SEC filings rather than read directly from the income statement.

#### EBITDA Minus CapEx
source: https://www.geminiq.com/financial-definitions/ebitda-minus-capex
Formula: EBITDA − Capital Expenditures
EBITDA minus CapEx is EBITDA less the capital expenditures a company made during the same period. It is calculated from figures reported in SEC filings and approximates the operating earnings left over after the business pays to maintain and expand its physical assets.

It corrects EBITDA's best-known blind spot. EBITDA adds back depreciation as if long-lived assets were free, while this measure charges the business for the cash it actually spent on property and equipment in the period.

#### EBITDA per Share
source: https://www.geminiq.com/financial-definitions/ebitda-per-share
Formula: EBITDA / Shares Outstanding
EBITDA per share is earnings before interest, taxes, depreciation, and amortization divided by the number of common shares outstanding. It shows how much operating profit, before non-cash depreciation and amortization charges and before financing and tax costs, the business generates for each share.

EBITDA is not a GAAP line item, so EBITDA per share is an analyst-derived figure rather than one companies report on the face of their financial statements.

#### EBITDA
source: https://www.geminiq.com/financial-definitions/ebitda
Formula: EBIT + Depreciation & Amortization
EBITDA, or earnings before interest, taxes, depreciation, and amortization, is a company's profit with interest expense, income taxes, and depreciation and amortization all added back. It is calculated from figures reported in SEC filings and is widely used as a rough proxy for the cash earnings a business generates from its operations.

By removing financing costs, taxes, and the non-cash charges tied to past investment, EBITDA puts companies with different debt loads, tax positions, and asset ages on a more comparable footing.

#### Effect of Foreign Exchange Rates on Cash
source: https://www.geminiq.com/financial-definitions/effect-of-foreign-exchange-rates
The effect of foreign exchange rates on cash is the line on the cash flow statement that shows how much a company's cash balance rose or fell during a period purely because currency exchange rates moved. It applies to cash, cash equivalents, and restricted cash held in currencies other than the company's reporting currency.

It is not a cash flow in the usual sense. No money came in or went out; the same foreign-currency balance is simply worth more or less when translated into dollars.

#### Equity Before Minority Interest
source: https://www.geminiq.com/financial-definitions/equity-before-minority-interest
Equity before minority interest is the stockholders' equity that belongs to the parent company's own shareholders, leaving out the share of consolidated subsidiaries owned by outside investors. It includes preferred and common stock, additional paid-in capital, retained earnings, accumulated other comprehensive income, and treasury stock, but excludes noncontrolling interest.

When a parent consolidates a subsidiary it does not fully own, it reports all of the subsidiary's assets and liabilities. The slice of the subsidiary's equity owned by others is noncontrolling interest, formerly called minority interest. Removing it leaves the equity the parent's shareholders actually own.

#### EV/Cash Flow to Firm
source: https://www.geminiq.com/financial-definitions/ev-to-cash-flow-to-firm
Formula: Enterprise Value / Cash Flow to Firm (trailing twelve months)
EV/Cash Flow to Firm divides a company's enterprise value by the operating cash flow available to all of its capital providers, lenders and shareholders alike. It shows how many years of that cash flow the market is paying for the whole business, and it is the enterprise-level counterpart of price-to-cash-flow.

Cash flow to firm starts from cash from operating activities and adds back after-tax interest expense. The add-back matters because interest is paid to lenders, whose claim is part of enterprise value. Capital spending is not deducted, which is the difference between this ratio and EV/Free Cash Flow to Firm.

#### Extraordinary Items & Accounting Changes
source: https://www.geminiq.com/financial-definitions/extraordinary-items-and-accounting-changes
Extraordinary items and accounting changes is the combined after-tax effect on net income of two historical categories: extraordinary gains or losses, and the cumulative effect of changes in accounting principle. Both were once reported as separate lines below income from continuing operations so they would not distort the view of recurring earnings.

Neither category is used in current US GAAP financial statements in the way it once was. For recent periods this field is normally zero, and it matters mainly when working with older filings.

#### Finished Goods
source: https://www.geminiq.com/financial-definitions/finished-goods
Finished goods are completed products a company holds and has ready to sell to customers. For a manufacturer they are the last of three inventory stages, after raw materials and work in process. For a retailer or distributor, which buys products ready to sell, nearly all of its inventory is finished goods, often called merchandise.

Finished goods are carried at cost, which for a manufacturer includes the materials, labor, and factory overhead absorbed in making them. If their expected selling price falls below that cost, the carrying amount is written down.

#### Free Cash Flow to Equity
source: https://www.geminiq.com/financial-definitions/free-cash-flow-to-equity
Formula: Cash from Operating Activities − Capital Expenditures + Net Cash from Debt
Free cash flow to equity is the cash a company generates that is available to its common shareholders after paying operating expenses, interest, taxes, and capital expenditures, and after accounting for net borrowing from or repayment to lenders. It is commonly calculated as cash from operating activities minus capital expenditures, plus new debt issued, minus debt repaid.

It is a measure of what the company could pay out as dividends and buybacks without drawing down cash or issuing shares. It is not a GAAP line item and is calculated from figures reported in SEC filings.

#### Free Cash Flow to Firm
source: https://www.geminiq.com/financial-definitions/free-cash-flow-to-firm
Formula: Cash from Operating Activities + Interest Expense × (1 − Tax Rate) − Capital Expenditures
Free cash flow to firm is the cash a company's operations generate after taxes and capital expenditures but before any payments to its capital providers, meaning it is the cash available to both lenders and shareholders together. A common way to calculate it from the cash flow statement is operating cash flow plus after-tax interest expense, minus capital expenditures.

Because it is measured before financing costs, it does not depend on how the company is financed. It is not a GAAP line item and is calculated from figures reported in SEC filings.

#### Goodwill
source: https://www.geminiq.com/financial-definitions/goodwill
Goodwill in accounting is the part of an acquisition's purchase price that cannot be assigned to any specific asset the buyer received. When one company acquires another, it records each identifiable asset and liability at fair value. Whatever the buyer paid above the net of those fair values is recorded as goodwill.

Goodwill stands for benefits that cannot be separately identified, such as an assembled workforce, expected synergies, and the value of the acquired business as a going concern. It appears on the balance sheet only through acquisitions. A company cannot record goodwill it builds internally.

#### Gross Profit
source: https://www.geminiq.com/financial-definitions/gross-profit
Formula: Revenue − Cost of Revenue
Gross profit is revenue minus the direct costs of producing the goods and services a company sold during a period. It shows how much a company earns from its core offering before paying for selling, administration, research, interest, and taxes.

Gross profit is the first profit subtotal on a multi-step income statement. Divided by revenue, it gives gross margin, the percentage of each sales dollar that remains after covering production and delivery costs.

#### Income Before Extraordinary Items Less Minority Interest & Preferred Dividends
source: https://www.geminiq.com/financial-definitions/income-before-extraordinary-items-to-common
Formula: Income Before Extraordinary Items − Minority Interest − Preferred Dividends
Income before extraordinary items less minority interest and preferred dividends is the portion of a company's earnings that belongs to its common shareholders, measured before any extraordinary gains or losses and before the cumulative effect of accounting changes. It starts from income before those items and subtracts the share owed to noncontrolling (minority) owners of subsidiaries and the dividends owed to preferred shareholders.

It is the numerator for earnings per share before extraordinary items, a measure that let investors see common-shareholder earnings without rare events and accounting catch-up adjustments.

#### Income (Loss) from Continuing Operations
source: https://www.geminiq.com/financial-definitions/income-from-continuing-operations
Income (loss) from continuing operations is a company's after-tax profit or loss from the businesses it still owns and intends to keep running. It includes all revenue, expenses, non-operating items, and income taxes for those businesses, and it excludes the results of any operation reported as discontinued.

On the income statement it is the subtotal just above discontinued operations. For most companies in most years, with nothing discontinued, it equals net income.

#### Income (Loss) Including Minority Interest
source: https://www.geminiq.com/financial-definitions/income-including-minority-interest
Income (loss) including minority interest is the total after-tax profit or loss of a company and all the subsidiaries it consolidates, before any of it is divided between the parent's shareholders and the outside owners of partly owned subsidiaries. It is also called consolidated net income.

Minority interest is the older name for what US GAAP now calls noncontrolling interest. Subtracting the noncontrolling holders' share from this figure gives net income attributable to the parent, the number most people mean by net income.

#### (Income) Loss from Affiliates
source: https://www.geminiq.com/financial-definitions/income-loss-from-affiliates
(Income) loss from affiliates is a company's share of the profit or loss earned by businesses it holds a significant but non-controlling stake in, such as joint ventures and associated companies accounted for under the equity method. The company does not consolidate these businesses. Instead, it records its percentage of their results as a single line on its own income statement.

The brackets around "Income" follow a cost-style sign convention: in this field, a share of affiliate profits is shown as a negative number because it reduces the company's net costs, and a share of affiliate losses is shown as a positive number.

#### Income Tax Expense (Benefit)
source: https://www.geminiq.com/financial-definitions/income-tax-expense
Income tax expense (benefit) is the total tax on income that a company recognizes for a period on its continuing operations, combining the tax it owes for the period with the change in its deferred taxes. A benefit, shown as a negative expense, arises when the company records a tax credit, usually because of a pretax loss or a tax refund or release.

It is often labeled the provision for income taxes. Subtracting it from pretax income gives income from continuing operations.

#### Increase in Capital Stock
source: https://www.geminiq.com/financial-definitions/increase-in-capital-stock
Increase in capital stock is the cash a company received during a period from issuing its own shares, including common and preferred stock sold in public or private offerings, shares issued when employees exercise stock options or buy through a stock purchase plan, and treasury shares reissued for cash. It is an inflow in the financing section of the cash flow statement.

Only cash proceeds count. Shares issued in exchange for a business, for services, or on conversion of debt are noncash transactions and do not appear here.

#### Increase in Long-Term Investments
source: https://www.geminiq.com/financial-definitions/increase-in-long-term-investments
Increase in long-term investments is the cash a company spent during a period buying investments it expects to hold beyond the current operating cycle, such as longer-dated bonds and notes, equity securities of other companies, and other financial assets. It is an outflow in the investing section of the cash flow statement.

These purchases move cash into other assets rather than consuming it. The company still owns the value, now in the form of securities.

#### Incremental Operating Margin
source: https://www.geminiq.com/financial-definitions/incremental-operating-margin
Formula: (Operating Income − Prior-Period Operating Income) / (Revenue − Prior-Period Revenue)
Incremental operating margin is the change in operating income between two periods divided by the change in revenue over the same periods. It shows how much of each additional dollar of sales turned into additional operating profit, rather than how profitable the business is on average.

An incremental margin above the company's ordinary operating margin means profitability is expanding as revenue grows.

#### Interest & Dividends Payable
source: https://www.geminiq.com/financial-definitions/interest-and-dividends-payable
Interest and dividends payable is the combined amount a company owes, as of the balance-sheet date, for interest that has built up on its borrowings but not yet been paid and for dividends its board has declared but not yet distributed to shareholders. Both are normally settled within a few months, so they are reported as current liabilities.

The two pieces arise differently. Interest accrues automatically with the passage of time under the terms of a loan or bond. A dividend becomes a liability only when the board formally declares it; before that date, a company has no obligation to pay one, however regular its dividend history.

#### Interest Expense, Net
source: https://www.geminiq.com/financial-definitions/interest-expense-net
Formula: Interest Expense − Interest Income
Interest expense, net is a company's interest expense on its borrowings minus the interest income it earns on its cash and investments. It measures the net cost of the company's debt after crediting the return on its own cash holdings.

A positive figure means the company pays more interest than it earns. A negative figure, which is common among cash-rich companies with little debt, means its interest income exceeds its interest expense.

#### Interest Expense
source: https://www.geminiq.com/financial-definitions/interest-expense
Interest expense is the cost a company recognizes during a period for the money it has borrowed. It covers interest on bonds, loans, credit lines, and similar obligations, along with the gradual amortization of any debt discount and issuance costs, and the interest component of finance lease payments.

It is recognized as the interest accrues, not when the cash is paid. A company can therefore report interest expense in a quarter with no interest payment, and vice versa.

#### Interest Income
source: https://www.geminiq.com/financial-definitions/interest-income
Interest income is the interest a company earns during a period on interest-bearing assets it holds, such as cash deposits, money market funds, government and corporate bonds, and loans or notes it has made to others. It is recognized as it is earned over time, not when payment is received.

For most companies it is a non-operating item that reflects the return on idle cash. For banks, lenders, and finance subsidiaries, it is the main source of revenue.

#### Inventories
source: https://www.geminiq.com/financial-definitions/inventories
Inventory, reported on the balance sheet as inventories, consists of goods a company holds for sale in the ordinary course of business, products still being made for sale, and materials and supplies that will be used up in production. They are reported as a current asset at cost, reduced where necessary to what the company expects to recover when the goods are sold.

For a manufacturer, inventories combine raw materials, work in process, and finished goods. For a retailer or distributor, they are mainly merchandise bought for resale. Service businesses and software companies often carry little or none.

#### Inventory Adjustments
source: https://www.geminiq.com/financial-definitions/inventory-adjustments
Inventory adjustments are the reserves a company deducts from the gross cost of its inventory to arrive at the net carrying amount on the balance sheet. The two main types are the LIFO reserve, which converts inventory costed on another basis to its LIFO value, and valuation reserves for goods that are obsolete, damaged, slow-moving, or worth less than they cost.

The adjustments are usually shown as a negative figure. Adding them back to net inventory gives the gross amount, typically on a FIFO or current-cost basis, before the reserves are applied.

#### Inventory Write-Down
source: https://www.geminiq.com/financial-definitions/inventory-write-down
An inventory write-down is a loss recorded when inventory is worth less than the cost on the company's books, because goods have become obsolete, damaged, slow-moving, or cheaper to replace. The carrying amount of the inventory is reduced and the loss is charged to earnings, usually within cost of goods sold.

A write-off is the extreme case, removing the full cost of inventory that has no remaining value. Both are non-cash charges: the cash was spent when the inventory was bought or made.

#### Investment Income
source: https://www.geminiq.com/financial-definitions/investment-income
Investment income is the interest and dividends a company earns on securities it holds outside its core operations, such as Treasury bills, corporate bonds, money market funds, and shares of other companies. For most businesses it is non-operating income, reported below operating income.

It measures the return on cash and investments the company is holding rather than on the products or services it sells. Interest income, covered separately, is the larger part for most companies; dividend income is the rest.

#### Loans Receivable, Net
source: https://www.geminiq.com/financial-definitions/loans-receivable-net
Loans receivable, net is the amount of loans a company holds as investments, after subtracting the allowance for credit losses and adjusting for unearned fees, discounts, premiums, and deferred costs. For a bank or other lender it is usually the largest asset on the balance sheet and the main source of interest income.

The figure covers loans the company intends to hold for the foreseeable future or to maturity, such as commercial, real estate, and consumer loans. Loans it plans to sell are reported separately as held for sale, and the allowance deducted represents the losses the lender expects over the life of the portfolio.

#### Long-Term Borrowings
source: https://www.geminiq.com/financial-definitions/long-term-borrowings
Long-term borrowings are the interest-bearing money a company has borrowed that is not due for repayment until more than a year after the balance-sheet date. They include bonds and notes, term loans from banks, drawn amounts under revolving credit facilities classified as long-term, mortgages, and similar obligations.

The figure is the noncurrent portion only. Principal falling due within the next year is moved into current liabilities as current maturities of long-term debt. Lease obligations are usually excluded from borrowings and counted separately, which is the main difference between this figure and a broader long-term debt total.

#### Long-Term Debt to Capital
source: https://www.geminiq.com/financial-definitions/long-term-debt-to-capital
Formula: Long-Term Debt / (Total Debt + Total Shareholders' Equity)
Long-term debt to capital, or the long-term debt to capital ratio, divides a company's long-term debt by its total capital, meaning the combined total of its debt and shareholders' equity. It shows what percentage of the permanent funding behind the business comes from borrowings that are not due within the next year.

A higher percentage means the company leans more heavily on long-term borrowing to finance itself. A company with no long-term debt scores zero, and one funded mostly by bonds and term loans may score well above 50%.

#### Long-Term Debt
source: https://www.geminiq.com/financial-definitions/long-term-debt
Long-term debt is the total of a company's debt obligations that fall due more than one year after the balance-sheet date, typically combining long-term borrowings such as bonds, notes, and term loans with the noncurrent portion of finance lease obligations. It is reported among noncurrent liabilities.

Principal due within the next year is excluded and shown instead as current maturities within current liabilities, where it counts toward short-term debt. Long-term debt plus short-term debt equals total debt.

#### Long-Term Deferred Tax Assets
source: https://www.geminiq.com/financial-definitions/long-term-deferred-tax-assets
Long-term deferred tax assets are future reductions in income taxes a company expects to realize more than a year out, because of deductible temporary differences and tax carryforwards it has already accumulated. They are reported as a noncurrent asset, after any valuation allowance.

They arise when the company has recognized an expense in its financial statements before the tax return allows the deduction, as with warranty reserves, accrued compensation, or lease liabilities, or when it has unused tax losses and credits that can offset future taxable income.

#### Long-Term Derivative & Hedging Assets
source: https://www.geminiq.com/financial-definitions/long-term-derivative-and-hedging-assets
Long-term derivative and hedging assets are the fair value of derivative contracts that are in a gain position for the company and are expected to settle more than a year after the balance-sheet date. Typical examples are long-dated interest-rate swaps, cross-currency swaps, and multi-year commodity hedges.

A derivative becomes an asset when market movements have made the contract favorable to the company, meaning a counterparty would have to pay it to close the position. Contracts, or portions of them, due to settle within a year are reported in current assets instead.

#### Long-Term Finance Lease Liabilities
source: https://www.geminiq.com/financial-definitions/long-term-finance-leases
Long-term finance lease liabilities are the portion of a company's finance lease obligations due more than one year after the balance-sheet date, measured at the present value of the remaining lease payments. They are reported among noncurrent liabilities, and the portion due within a year is shown separately in current liabilities.

Finance leases, known as capital leases before ASC 842, are leases that effectively give the company control of an asset for most of its useful life, so they are accounted for much like buying the asset with borrowed money. The noncurrent liability is the principal still owed beyond the coming year.

#### Long-Term Investments & Receivables
source: https://www.geminiq.com/financial-definitions/long-term-investments-and-receivables
Long-term investments and receivables is the combined total of the financial assets a company holds beyond the next year: investments it intends to keep for longer than one operating cycle, plus amounts owed to it that are not due for more than a year, such as long-term notes, loans, and customer receivables. Receivables are included net of their allowance for credit losses.

Grouping the two gives a single measure of a company's noncurrent claims on other parties, separate from its physical assets like property and equipment and from intangibles like goodwill.

#### Long-Term Investments
source: https://www.geminiq.com/financial-definitions/long-term-investments
Long-term investments are financial assets a company intends to hold for longer than one year or its operating cycle. They include debt securities with later maturities, stakes in other companies, investments accounted for by the equity method, and similar holdings that are not expected to be turned into cash in the near term.

They are reported as noncurrent assets. Securities the company plans to sell within a year, or that mature within a year, are classified as short-term investments instead, and cash equivalents are reported separately.

#### Long-Term Receivables
source: https://www.geminiq.com/financial-definitions/long-term-receivables
Long-term receivables are amounts owed to a company that are not due for collection until more than one year, or more than one operating cycle, after the balance-sheet date. They include customer receivables on extended payment terms, long-term notes and loans receivable, and installment and lease receivables, reported net of the allowance for credit losses.

They are noncurrent assets. When part of a long-term receivable falls due within the coming year, that portion moves into current receivables.

#### Minority Interest (Income Statement)
source: https://www.geminiq.com/financial-definitions/minority-interest-income-statement
Minority interest on the income statement is the portion of a company's consolidated net income or loss that belongs to outside shareholders of subsidiaries the company controls but does not wholly own. It is subtracted from consolidated net income to arrive at net income attributable to the parent company's shareholders.

US GAAP now calls this net income attributable to noncontrolling interest. SFAS 160, now part of ASC 810, replaced the older term minority interest, which remains common in financial data.

#### Miscellaneous Long-Term Assets
source: https://www.geminiq.com/financial-definitions/miscellaneous-long-term-assets
Miscellaneous long-term assets are the noncurrent assets left over after every named category has been counted, meaning items that are not property and equipment, investments, long-term receivables, intangibles, goodwill, deferred tax assets, or derivatives. They are expected to provide benefit, or be realized, more than a year after the balance-sheet date.

The contents vary by company but often include long-term prepaid expenses, deposits, capitalized contract costs, cash surrender value of life insurance, restricted cash held for long-term purposes, and deferred charges. Individually these items are usually too small to warrant their own line.

#### Miscellaneous Long-Term Liabilities
source: https://www.geminiq.com/financial-definitions/miscellaneous-long-term-liabilities
Miscellaneous long-term liabilities are the noncurrent obligations left over after every named category has been counted, meaning amounts due after one year that are not long-term debt, lease liabilities, deferred taxes, pension obligations, deferred revenue, or other separately reported items. They are the residual catch-all within a company's long-term liabilities.

Typical contents include long-term portions of accrued expenses, deposits held from customers, deferred compensation, uncertain tax positions, legal and environmental reserves, and asset retirement obligations when a company does not show them on their own line.

#### Miscellaneous Short-Term Assets
source: https://www.geminiq.com/financial-definitions/miscellaneous-short-term-assets
Miscellaneous short-term assets are the current assets left over after every named category has been counted, meaning items expected to be realized or used up within a year that are not cash, investments, receivables, inventory, prepaid expenses, or other separately reported assets. They are the residual catch-all within current assets.

The contents vary by company and are often not itemized at all. They can include short-term deposits, income tax refunds receivable, the current portion of capitalized contract costs, short-term derivative positions, and other small balances that do not merit their own line.

#### Miscellaneous Short-Term Liabilities
source: https://www.geminiq.com/financial-definitions/miscellaneous-short-term-liabilities
Miscellaneous short-term liabilities are the current obligations left over after every named category has been counted, meaning amounts due within a year that are not accounts payable, accrued expenses, short-term debt, current lease liabilities, taxes payable, deferred revenue, or other separately reported items. They are the residual catch-all within current liabilities.

Typical contents include customer deposits, amounts owed under legal settlements, short-term derivative liabilities, dividends declared but unpaid, and other small balances that a company does not list on their own line.

#### Net Cash from Acquisitions & Divestitures
source: https://www.geminiq.com/financial-definitions/net-cash-from-acquisitions-and-divestitures
Formula: Cash from Divestitures − Net Cash Paid for Acquisitions
Net cash from acquisitions and divestitures is the combined cash effect of a company buying and selling businesses during a period: cash received from selling subsidiaries, divisions, and interests in affiliates, minus cash paid to acquire businesses and affiliate stakes, each typically net of the cash the businesses held. It sits within the investing section of the cash flow statement.

A negative figure means the company was a net buyer of businesses. A positive figure means it raised more from sales than it spent on purchases.

#### Net Cash from Debt
source: https://www.geminiq.com/financial-definitions/net-cash-from-debt
Formula: Cash from Debt − Repayments of Debt
Net cash from debt is the difference between the cash a company raised from new borrowings and the cash it spent repaying principal during a period. A positive figure means the company borrowed more than it repaid; a negative figure means it paid down debt on a net basis.

It combines short-term and long-term borrowing activity into one number and is sometimes called net borrowing or net debt issuance.

#### Net Cash from Discontinued Operations
source: https://www.geminiq.com/financial-definitions/net-cash-from-discontinued-operations
Net cash from discontinued operations is the cash generated or used during a period by a business the company has sold, spun off, or classified as held for sale, when that business qualifies as a discontinued operation. It separates the cash flows of the exiting business from those of the operations the company is keeping.

It can be reported as one total or split into operating, investing, and financing pieces. Either way, it helps readers judge the cash-generating ability of the business that will remain.

#### Net Cash Paid for Acquisitions
source: https://www.geminiq.com/financial-definitions/net-cash-paid-for-acquisitions
Net cash paid for acquisitions is the cash a company spent during a period to acquire businesses and interests in affiliates, after subtracting the cash those businesses held on the date they were acquired. It is an outflow in the investing section of the cash flow statement.

The "net" refers to the cash acquired. The measure reflects the buyer's true cash cost: the price paid in cash less the cash that came with the target.

#### Net Change in Cash
source: https://www.geminiq.com/financial-definitions/net-change-in-cash
Formula: Cash from Operating Activities + Cash from Investing Activities + Cash from Financing Activities + Effect of Exchange Rates on Cash
Net change in cash is the total increase or decrease in a company's cash, cash equivalents, and restricted cash over a period. It equals the sum of cash from operating, investing, and financing activities plus the effect of exchange rate changes on cash held in foreign currencies, and it links the beginning and ending cash balances shown at the bottom of the cash flow statement.

It answers the simplest question the statement is built to answer: how much more or less cash the company had at the end of the period than at the start.

#### Net Change in Long-Term Investments
source: https://www.geminiq.com/financial-definitions/net-change-in-long-term-investments
Formula: Decrease in Long-Term Investments − Increase in Long-Term Investments
Net change in long-term investments is the net cash effect of a company's purchases and sales of longer-term investments during a period: cash received from sales, maturities, and collections, minus cash spent on new purchases. It is a component of the investing section of the cash flow statement.

A negative figure means the company put more cash into investments than it took out. A positive figure means it drew down its investment holdings on a net basis.

#### Net Debt to Capital
source: https://www.geminiq.com/financial-definitions/net-debt-to-capital
Formula: Net Debt / (Net Debt + Total Shareholders' Equity)
Net debt to capital divides a company's net debt, meaning total borrowings minus cash and cash equivalents, by the sum of that net debt and shareholders' equity. It shows what percentage of the company's net funding comes from lenders once available cash is credited against debt.

The ratio ranges from 0% for a company whose cash exactly offsets its debt to 100% for one financed entirely by net borrowing. It turns negative when cash exceeds debt, which signals a net cash position.

#### Net Debt/EBIT
source: https://www.geminiq.com/financial-definitions/net-debt-to-ebit
Formula: (Total Debt − Cash and Cash Equivalents) / EBIT (trailing twelve months)
Net debt/EBIT divides a company's net debt, its total borrowings minus cash and cash equivalents, by its trailing twelve-month earnings before interest and taxes. It estimates how many years of current operating earnings the company would need to repay its debt after using the cash it already holds.

A multiple of 2.0x means net debt equals two years of EBIT. A negative multiple usually means the company holds more cash than debt, though it can also result from negative EBIT, so the sign has to be read carefully.

#### Net Deferred Tax Liabilities
source: https://www.geminiq.com/financial-definitions/net-deferred-tax-liabilities
Formula: Deferred Tax Liabilities − Deferred Tax Assets (net of valuation allowance)
Net deferred tax liabilities are a company's deferred tax liabilities minus its deferred tax assets, after the valuation allowance. The result shows the company's overall deferred tax position: a positive figure means it expects to owe more tax in future years because of past timing differences than it expects to save, and a negative figure means the reverse.

Deferred taxes arise from temporary differences between the income a company reports in its financial statements and the income it reports on its tax returns. Liabilities come from items taxed later than they are booked; assets come from items deducted later than they are expensed, and from unused tax losses and credits.

#### Net Extraordinary Losses (Gains)
source: https://www.geminiq.com/financial-definitions/net-extraordinary-losses-gains
Net extraordinary losses (gains) is the after-tax amount of gains or losses that a company classified as extraordinary under the accounting rules in effect before 2016, meaning items that were both unusual in nature and infrequent in occurrence. The label puts losses first, so a net extraordinary loss is shown as a positive number and a net gain as a negative one.

Extraordinary items were reported separately, below income from continuing operations and discontinued operations, so they would not distort the view of recurring earnings. The category no longer exists in US GAAP.

#### Net Income Available to Common Shareholders
source: https://www.geminiq.com/financial-definitions/net-income-available-to-common
Formula: Net Income Attributable to Parent − Preferred Dividends − Other Adjustments
Net income available to common shareholders is the part of a company's net income that belongs to its common stockholders after every prior claim on earnings has been deducted. It starts from net income attributable to the parent and subtracts preferred dividends and other amounts owed to holders of senior or participating securities.

It is the numerator of basic earnings per share, which makes it the most direct measure of what the period's profit means for common shareholders.

#### Net Income (Cash Flow Statement)
source: https://www.geminiq.com/financial-definitions/net-income-cash-flow
Net income on the cash flow statement is the profit or loss figure that opens the operating section under the indirect method, serving as the starting point from which noncash items and working capital changes are added or subtracted to arrive at cash from operating activities.

It is usually the company's consolidated net income, which includes the share of profit belonging to noncontrolling (minority) interests. That can make it larger than the net income attributable to the parent's shareholders shown at the bottom of the income statement.

#### Net Income (GAAP)
source: https://www.geminiq.com/financial-definitions/net-income-gaap
Net income (GAAP) is a company's total profit or loss for a period after every expense, loss, interest charge, and income tax recognized under US generally accepted accounting principles, attributable to the parent company's shareholders. It includes the results of both continuing and discontinued operations and excludes the share of earnings belonging to noncontrolling owners of subsidiaries.

It is the bottom line of the income statement and the starting point for earnings per share, return on equity, and the price-to-earnings ratio.

#### Non-Cash Items
source: https://www.geminiq.com/financial-definitions/non-cash-items
Non-cash items are the total adjustments in the operating section of the cash flow statement for income and expenses that affected net income without any cash changing hands in the period. They are added back (for noncash expenses and losses) or subtracted (for noncash income and gains) to move from net income toward cash from operating activities.

Typical members of this group are depreciation and amortization, stock-based compensation, deferred income taxes, impairment charges, and gains or losses on selling assets or investments. Changes in working capital are usually shown separately.

#### Non-Operating (Income) Loss
source: https://www.geminiq.com/financial-definitions/non-operating-income-loss
Non-operating (income) loss is the net total of gains, losses, income, and expenses that come from activities outside a company's core business operations, such as investment gains, foreign exchange results, and income from securities. It sits between operating income and pretax income on the income statement.

The brackets around "Income" follow an expense-style sign convention: in this field, net non-operating income is shown as a negative number because it reduces the company's net costs, and a net non-operating loss is shown as a positive number.

#### Noncontrolling Interest
source: https://www.geminiq.com/financial-definitions/noncontrolling-interest
Noncontrolling interest is the portion of a consolidated subsidiary's equity that is owned by investors other than the parent company. When a parent controls a subsidiary without owning all of it, it includes 100 percent of the subsidiary's assets and liabilities in its own statements, and noncontrolling interest records the outside owners' share of the subsidiary's net assets.

It was long called minority interest. The term changed to noncontrolling interest with SFAS 160, now part of ASC 810, which also moved the balance into equity rather than presenting it between liabilities and equity.

#### Notes Receivable, Net
source: https://www.geminiq.com/financial-definitions/notes-receivable-net
Notes receivable, net is the amount owed to a company under formal written promises to pay, known as promissory notes, after subtracting the allowance for credit losses. A note typically states a principal amount, an interest rate, and a maturity date, which makes it a more formal and usually longer-dated claim than an ordinary customer invoice.

Notes can come from customers who convert overdue accounts or finance large purchases, from loans to franchisees, suppliers, employees, or affiliates, or from selling a business or asset in exchange for a note. The portion due within a year is a current asset; the rest is noncurrent.

#### Number of Employees
source: https://www.geminiq.com/financial-definitions/number-of-employees
Number of employees is the count of people a company employs, as disclosed in its annual report. It is usually stated as of the end of the fiscal year and gives a direct measure of the size of a company's workforce.

It is not an accounting figure and does not appear in the financial statements. Companies report it in the narrative business section of the Form 10-K, typically alongside a discussion of their workforce.

#### Operating Expenses
source: https://www.geminiq.com/financial-definitions/operating-expenses
Operating expenses are the recurring costs a company incurs to run its business that are not directly tied to producing the goods and services it sells. They typically include selling, general and administrative expense, research and development, and other operating costs, and they are subtracted from gross profit to arrive at operating income.

Different filers draw the line in different places. Some present operating expenses excluding cost of revenue, while others present a single total of costs and expenses that includes it.

#### Operating Income per Share
source: https://www.geminiq.com/financial-definitions/operating-income-per-share
Formula: Operating Income / Shares Outstanding
Operating income per share is a company's operating income divided by its number of common shares outstanding. It shows how much profit the core business produced for each share before interest, income taxes, and non-operating gains and losses.

Because it stops above interest and tax, it lets investors compare the operating performance of companies with different capital structures and tax positions on a per-share basis.

#### Operating Income (Loss)
source: https://www.geminiq.com/financial-definitions/operating-income
Formula: Revenue − Cost of Revenue − Operating Expenses
Operating income (loss) is the profit or loss a company earns from its core business activities, calculated as revenue minus cost of revenue and all operating expenses. It measures what the business itself produces before interest, non-operating gains and losses, and income taxes.

It is often called operating profit or income from operations. Divided by revenue, it gives operating margin, one of the most widely compared profitability measures.

#### Other Adjustments
source: https://www.geminiq.com/financial-definitions/other-adjustments
Other adjustments are the amounts, apart from ordinary preferred dividends, that a company adds to or subtracts from net income attributable to the parent to arrive at net income available to common shareholders. They capture claims on earnings by holders of securities other than common stock, and certain equity transactions that ASC 260 treats as affecting common shareholders' earnings.

For most companies the field is zero. It becomes meaningful for companies with participating securities, redeemable preferred stock, or unusual preferred stock transactions.

#### Other Comprehensive Income
source: https://www.geminiq.com/financial-definitions/other-comprehensive-income
Other comprehensive income (OCI) is the set of gains and losses that accounting standards require to bypass net income and be recorded directly in equity. It is reported after tax for each period and, added to net income, makes up comprehensive income.

The usual components are foreign currency translation adjustments, unrealized gains and losses on available-for-sale debt securities, gains and losses on derivatives designated as cash flow hedges, and remeasurements of defined benefit pension and other postretirement plans.

#### Other Equity
source: https://www.geminiq.com/financial-definitions/other-equity
Other equity is the part of stockholders' equity that falls outside the main captions of common stock, additional paid-in capital, retained earnings, treasury stock, and preferred stock. It is a residual grouping that collects the remaining components of shareholders' equity into one figure.

The largest item in it is usually accumulated other comprehensive income, which holds gains and losses that bypass the income statement, such as foreign-currency translation adjustments, certain pension adjustments, unrealized gains and losses on available-for-sale debt securities, and the effective portion of cash-flow hedges. Other items can include unearned compensation for employee stock ownership plans and other capital adjustments.

#### Other Financing Activities
source: https://www.geminiq.com/financial-definitions/other-financing-activities
Other financing activities is the residual line in the financing section of the cash flow statement. It holds the net cash from financing transactions that the company does not present separately from its main debt, equity, and dividend lines.

Common contents include taxes paid on behalf of employees for shares withheld when equity awards vest, principal payments on finance leases, debt issuance costs, contributions from or distributions to noncontrolling owners, and payments of deferred or contingent acquisition consideration.

#### Other Intangible Assets
source: https://www.geminiq.com/financial-definitions/other-intangible-assets
Other intangible assets are identifiable non-physical assets a company owns, other than goodwill, reported net of accumulated amortization and impairment. They include patents, trademarks and brand names, customer relationships, licenses, franchise rights, developed technology, and similar rights that can be separated from the business or arise from contracts or law.

Most of these assets come onto the balance sheet through acquisitions, where each identifiable intangible is recorded at fair value. Intangibles a company develops internally, such as its own brands or research, are generally expensed as incurred and so do not appear, with limited exceptions such as certain software costs.

#### Other Inventory
source: https://www.geminiq.com/financial-definitions/other-inventory
Other inventory is the part of a company's inventory that does not fall into the standard classes of raw materials, work in process, or finished goods. It is most often supplies, such as maintenance materials, spare parts, packaging, and fuel used in production or operations, and can also include inventoried costs on long-term contracts and other categories specific to the company.

Like the rest of inventory, it is a current asset carried at cost, less any write-down needed when its value falls below cost.

#### Other Investing Activities
source: https://www.geminiq.com/financial-definitions/other-investing-activities
Other investing activities is the residual line in the investing section of the cash flow statement. It captures the net cash from investing transactions that the company does not present on their own lines, such as small loans made or collected, insurance proceeds for damaged property, deposits on future asset purchases, and settlements of certain hedges tied to investments.

It can be an inflow or an outflow in any period, and it is usually small compared with capital expenditures and acquisitions.

#### Other Long-Term Assets
source: https://www.geminiq.com/financial-definitions/other-long-term-assets
Other long-term assets are noncurrent assets that do not belong in any of the main balance-sheet captions, such as property and equipment, long-term investments, goodwill, or intangible assets. They are expected to benefit the company, or be realized, more than a year after the balance-sheet date.

The line commonly holds a mix of items, including long-term prepaid expenses and deposits, capitalized costs of obtaining customer contracts, noncurrent derivative assets, pension plan surpluses, restricted cash held for long-term purposes, and deferred tax assets when a company does not present them separately. Its contents differ widely from one company to the next.

#### Other Long-Term Liabilities
source: https://www.geminiq.com/financial-definitions/other-long-term-liabilities
Other long-term liabilities are obligations a company does not expect to settle within the next year (or its operating cycle, if longer) and that it does not report under a more specific noncurrent caption such as long-term debt, deferred income taxes, or pension liabilities. It is a catch-all line that gathers the remaining noncurrent obligations into one amount.

The contents vary widely from company to company. Common examples include uncertain tax positions, asset retirement obligations, long-term legal or environmental reserves, deferred compensation owed to employees, long-term customer deposits, and the noncurrent portion of liabilities that a filer chooses not to show on their own line.

#### Other Non-Cash Adjustments
source: https://www.geminiq.com/financial-definitions/other-non-cash-adjustments
Other non-cash adjustments is the residual line in the operating section of the cash flow statement for income and expense items that affected net income without moving cash, but that the company does not show on their own line. It is added to or subtracted from net income along with the named noncash items, such as depreciation and stock-based compensation.

Items that commonly end up here include amortization of debt issuance costs, noncash lease cost, changes in fair value of certain instruments, foreign currency remeasurement gains and losses, and provisions that have not yet been paid.

#### Other Non-Operating (Income) Loss
source: https://www.geminiq.com/financial-definitions/other-non-operating-income-loss
Other non-operating (income) loss is the net amount of non-operating gains, losses, income, and expenses that a company does not report on any more specific line. It is the catch-all for results outside the core business once interest, investment income, and other named items have been shown separately.

The label uses an expense-style sign convention. Net other non-operating income is shown as a negative number, because it reduces net costs, and a net other non-operating loss is shown as a positive number.

#### Other Operating Expense
source: https://www.geminiq.com/financial-definitions/other-operating-expense
Other operating expense is the total of operating costs that are part of a company's normal business but do not fall under cost of revenue, selling, general and administrative expense, research and development, or another specific operating line. It is deducted in arriving at operating income.

Its contents vary by company and by period. It can include restructuring and severance costs, asset impairments, losses on disposing of operating assets, and other charges tied to running the business.

#### Other Operating Income
source: https://www.geminiq.com/financial-definitions/other-operating-income
Other operating income is income that arises from a company's normal business operations but is not part of its main revenue and is not reported on a more specific line. It is added in arriving at operating income, rather than being reported below it with non-operating items.

Typical examples include gains on selling equipment or other operating assets, royalty or licensing income outside the main business, government grants related to operations, and insurance recoveries on operating losses.

#### Other Payables & Accruals
source: https://www.geminiq.com/financial-definitions/other-payables-and-accruals
Other payables and accruals are the short-term obligations a company owes for costs it has already incurred, other than the ordinary trade invoices it owes suppliers. They cover expenses that have built up but have not been paid, such as wages, bonuses, payroll taxes, interest, rent, utilities, and warranty or rebate obligations, along with amounts payable to parties other than trade vendors.

An accrual is recorded because the cost belongs to the current period even though no bill has arrived or payment is not yet due. Together with trade accounts payable, these items make up total payables and accruals.

#### Other Receivables, Net
source: https://www.geminiq.com/financial-definitions/other-receivables-net
Other receivables, net, are amounts owed to a company by parties other than its customers for ordinary sales, reported after subtracting any allowance for amounts it does not expect to collect. They arise from transactions outside the normal selling cycle, such as tax refunds due, insurance claims, amounts owed by suppliers under rebate programs, proceeds due from the sale of an asset, and advances to employees.

The balance usually refers to amounts expected within a year and sits among current assets. Longer-dated items of the same kind are reported with noncurrent assets.

#### Other Short-Term Assets
source: https://www.geminiq.com/financial-definitions/other-short-term-assets
Other short-term assets are current assets that a company does not report under a more specific caption such as cash, short-term investments, receivables, inventory, or prepaid expenses. They are resources the company expects to turn into cash, sell, or use up within a year (or its operating cycle, if longer), gathered into a single residual line.

What goes into the line varies by company. Common examples include contract assets, deposits, income taxes receivable, short-term derivative assets, restricted cash, and deferred costs expected to be expensed within the year.

#### Other Short-Term Liabilities
source: https://www.geminiq.com/financial-definitions/other-short-term-liabilities
Other short-term liabilities are obligations a company expects to settle within a year (or its operating cycle, if longer) that it does not report under a more specific current caption such as accounts payable, accrued expenses, short-term debt, or deferred revenue. The line collects the remaining current obligations into one amount.

Its contents differ from company to company. Typical items include customer deposits, dividends declared but unpaid, current derivative liabilities, amounts owed on acquisitions, current portions of legal or restructuring reserves, and short-term operating lease liabilities when they are not shown separately.

#### Payables & Accruals
source: https://www.geminiq.com/financial-definitions/payables-and-accruals
Payables and accruals are the short-term amounts a company owes for goods, services, and costs it has already received or incurred but has not yet paid for. The total combines trade accounts payable, which are invoices owed to suppliers, with accrued liabilities, which are expenses recognized before a bill arrives or payment falls due, such as wages, interest, taxes, and utilities.

The balance is a current liability. It represents credit the company receives from suppliers, employees, and others in the normal course of operating, not money it has borrowed.

#### Pension Liabilities
source: https://www.geminiq.com/financial-definitions/pension-liabilities
Pension liabilities are the amount by which a company's promised retirement benefits under its defined benefit plans exceed the assets set aside to pay them, as recognized on the balance sheet. The figure is the unfunded portion of the obligation: the estimated present value of benefits employees have earned, minus the fair value of the plan's investments.

Many companies report pension liabilities together with other postretirement benefits, such as retiree health care, which are measured the same way. Defined contribution plans, like a 401(k), create no such liability once the company has made its contributions.

#### Preferred Dividends
source: https://www.geminiq.com/financial-definitions/preferred-dividends
Preferred dividends are the dividends a company owes or pays to holders of its preferred stock for a period. On the income statement they are subtracted from net income to arrive at net income available to common shareholders, because preferred holders have a claim on earnings that ranks ahead of common stock.

Preferred dividends are a distribution of profit to equity holders, not an operating or financing expense, so they do not reduce net income itself. They reduce only the earnings attributed to common shareholders.

#### Preferred Equity & Hybrid Capital
source: https://www.geminiq.com/financial-definitions/preferred-equity-and-hybrid-capital
Preferred equity and hybrid capital is the carrying amount of securities a company has issued that rank ahead of common stock but behind debt, together with instruments that combine features of both debt and equity. Preferred stock typically pays a fixed or formula-based dividend and has priority over common shareholders for dividends and in a liquidation, but usually carries limited or no voting rights.

"Hybrid capital" is not a US GAAP caption. It is an analyst grouping for instruments such as convertible preferred stock and other securities with both debt-like and equity-like terms, placed alongside preferred stock because they sit between creditors and common owners.

#### Prepaid Expenses
source: https://www.geminiq.com/financial-definitions/prepaid-expenses
Prepaid expenses are amounts a company has paid in advance for goods or services it will receive in a later period, recorded as an asset until the benefit is used. Common examples are insurance premiums, rent paid ahead of the lease period, software subscriptions, maintenance contracts, and advertising paid for before it runs.

As each month of coverage or service passes, the company moves that portion of the prepayment from the balance sheet to the income statement as an expense. Prepayments that will be used within a year are current assets.

#### Pretax Income
source: https://www.geminiq.com/financial-definitions/pretax-income
Pretax income is a company's profit or loss from continuing operations before income tax expense. It reflects every item of revenue and expense for the ongoing business, including interest and non-operating gains and losses, but not taxes on income or the results of discontinued operations.

It is also called income before taxes or earnings before tax (EBT). Subtracting income tax expense from it gives income from continuing operations.

#### Property, Plant & Equipment (Gross)
source: https://www.geminiq.com/financial-definitions/property-plant-and-equipment-gross
Property, plant and equipment (gross), or gross PP&E, is the total original cost of the physical, long-lived assets a company uses to run its business, before subtracting accumulated depreciation. It includes land, buildings, machinery, equipment, vehicles, furniture, computer hardware, leasehold improvements, and construction in progress, all measured at what the company paid to acquire or build them.

Assets held for resale are not included; those are inventory. Gross PP&E minus accumulated depreciation equals net PP&E, the carrying value reported on most balance sheets.

#### Property, Plant & Equipment, Net
source: https://www.geminiq.com/financial-definitions/property-plant-and-equipment-net
Property, plant and equipment, net (net PP&E), is the carrying value of a company's long-lived physical operating assets after subtracting the depreciation, depletion, and amortization accumulated since they were acquired. It covers assets such as land, buildings, machinery, equipment, and construction in progress that the company uses to produce goods and services rather than to sell.

Net PP&E is the figure most balance sheets show on the face of the statement. It represents the portion of the assets' original cost that has not yet been expensed.

#### Raw Materials
source: https://www.geminiq.com/financial-definitions/raw-materials
Raw materials are the inputs a manufacturer has bought and is holding to use in production but has not yet started converting into products. Examples include steel, chemicals, resin, lumber, electronic components, and agricultural commodities, recorded at cost as part of inventory.

Raw materials are the first of the three stages of manufacturing inventory. Once materials enter production they become work in process, and once production is complete they become finished goods.

#### Repayments of Debt
source: https://www.geminiq.com/financial-definitions/repayments-of-debt
Repayments of debt is the total cash a company paid during a period to reduce the principal of its borrowings, both short-term and long-term. It includes scheduled maturities, early redemptions and tender offers for bonds, and payments on term loans and credit lines. It is a cash outflow in the financing section of the cash flow statement.

It covers principal only. Interest paid on the same debt is an operating outflow under US GAAP.

#### Repayments of Long-Term Debt
source: https://www.geminiq.com/financial-definitions/repayments-of-long-term-debt
Repayments of long-term debt is the cash a company paid during a period to reduce the principal of borrowings that were originally due more than one year out, such as bonds, notes, mortgages, and term loans. It includes scheduled maturities, required amortization payments, early redemptions, and bond repurchases in the open market or through tender offers.

It is a cash outflow in the financing section of the cash flow statement. Because the classification is based on original maturity, repaying the current portion of a long-term loan still belongs here.

#### Repayments of Short-Term Debt
source: https://www.geminiq.com/financial-definitions/repayments-of-short-term-debt
Repayments of short-term debt is the cash a company paid during a period to settle borrowings that were originally due within one year or within the operating cycle if longer, such as commercial paper, short-term bank loans, and draws on credit lines. It is a cash outflow in the financing section of the cash flow statement.

It is shown only when a company reports its short-term borrowings gross. Many companies instead report a single net figure for short-term debt, in which case repayments are not visible on their own.

#### Research & Development
source: https://www.geminiq.com/financial-definitions/research-and-development
Research and development (R&D) expense is what a company spends during a period on work aimed at discovering new knowledge or turning that knowledge into new or significantly improved products, services, or processes. It covers the salaries of scientists and engineers, lab supplies, contract research, and the share of facilities and equipment used for R&D work.

Under US GAAP most research and development is expensed as incurred, so the full cost reduces current-period operating income even though the benefits may arrive years later.

#### Retained Earnings
source: https://www.geminiq.com/financial-definitions/retained-earnings
Retained earnings are the total profits a company has earned since it began that it has kept in the business instead of paying out to shareholders as dividends. When cumulative losses and distributions exceed cumulative profits, the balance turns negative and is reported as an accumulated deficit.

Retained earnings are a component of stockholders' equity, not a pile of cash. The earnings they represent may have been spent long ago on equipment, acquisitions, debt repayment, or share buybacks.

#### Revenue per Share
source: https://www.geminiq.com/financial-definitions/revenue-per-share
Formula: Revenue / Shares Outstanding
Revenue per share is a company's total revenue for a period divided by its number of common shares outstanding. It shows how much in sales the business generates for each share, regardless of whether those sales are profitable.

It is also called sales per share. Because revenue is positive even when a company loses money, the measure works for businesses where earnings-based ratios cannot be used.

#### Revenue
source: https://www.geminiq.com/financial-definitions/revenue
Revenue is the total amount a company earns from its business activities during a period, chiefly from selling goods and providing services, net of discounts, returns, and allowances. It is the top line of the income statement, before any costs are subtracted.

Revenue goes by several names. US companies often say sales or net sales, and turnover is the common term in the UK and parts of Europe. Total revenue can also include interest, rental, and other income when those are part of how a company earns money.

#### Right-of-Use Asset
source: https://www.geminiq.com/financial-definitions/right-of-use-asset
A right-of-use (ROU) asset is a lessee's right to use a leased asset, such as an office, store, warehouse, or piece of equipment, for the lease term. Under ASC 842, a company that leases an asset records a right-of-use asset on its balance sheet together with a lease liability for the payments it owes.

Before ASC 842, operating leases stayed off the balance sheet and appeared only as rent expense and a footnote. The standard brought them on, so a company that leases most of its property now reports both the asset and the obligation.

#### Sales & Services Revenue
source: https://www.geminiq.com/financial-definitions/sales-and-services-revenue
Sales and services revenue, often simply called sales revenue, is the income a company earns from selling its products and performing services for customers during a period, after deducting discounts, returns, and allowances. It covers the core commercial activity of the business and excludes interest, investment, rental, and other incidental income.

For most industrial, retail, and technology companies it equals total revenue. It differs for companies that also earn meaningful revenue from lending, leasing, or other activities outside contracts with customers.

#### Sales per Employee
source: https://www.geminiq.com/financial-definitions/sales-per-employee
Formula: Revenue / Number of Employees
Sales per employee, also called revenue per employee, divides a company's revenue for a period by the number of people it employs. It shows how much revenue the business generates for each member of its workforce and is one of the simplest measures of labor productivity.

A higher figure generally means a company produces more sales with fewer people, which often points to automation, a high-value product, or an asset-light business model. A lower figure is typical of labor-intensive industries such as restaurants, retail, and services.

#### Selling, General & Administrative Expense
source: https://www.geminiq.com/financial-definitions/selling-general-and-administrative
Selling, general and administrative expense (SG&A) is the combined cost of selling a company's products and services and of running the business as a whole, other than the direct costs of production and, usually, research and development. It covers items such as sales staff pay and commissions, advertising, corporate salaries, rent for offices, legal and accounting fees, and technology used outside production.

SG&A is typically the largest operating expense after cost of revenue. It is subtracted from gross profit on the way to operating income.

#### Share Capital & Additional Paid-In Capital
source: https://www.geminiq.com/financial-definitions/share-capital-and-apic
Share capital and additional paid-in capital (APIC) is the total amount a company has received from shareholders in exchange for its stock, as recorded in stockholders' equity. Share capital is the par or stated value of the shares issued, and APIC is everything received above that nominal amount. Together they are often called contributed capital.

Par value is usually a token amount, such as a fraction of a cent per share, so for most companies nearly all of the capital raised from shareholders sits in APIC.

#### Shareholder Yield, Excluding Debt
source: https://www.geminiq.com/financial-definitions/shareholder-yield-ex-debt
Formula: (Dividends Paid + Repurchases of Common Stock − Proceeds from Issuance of Common Stock) / Market Capitalization
Shareholder yield excluding debt measures the cash a company returned to its stockholders through dividends and net share repurchases as a percentage of its market capitalization. It combines dividend yield and net buyback yield into one figure, showing what shareholders received relative to the market value of their stake.

Unlike the financing-cash-flow version of shareholder yield, it leaves out debt entirely. Borrowing and repayment do not affect the result, so it reflects only cash flowing between the company and its equity holders.

#### Shareholder Yield (Cash Flow from Financing)
source: https://www.geminiq.com/financial-definitions/shareholder-yield
Formula: −(Cash from Financing Activities) / Market Capitalization
Shareholder yield based on cash flow from financing measures the net cash a company paid out through its financing activities, including dividends, share buybacks, and net debt repayment, as a percentage of its market capitalization. It takes the whole financing section of the cash flow statement, reverses its sign so that net outflows are positive, and divides by the company's market value.

A positive yield means the company sent more cash to shareholders and lenders than it raised from them. A negative yield means it was a net raiser of capital during the period, through new borrowing or stock issuance.

#### Shares Outstanding
source: https://www.geminiq.com/financial-definitions/shares-outstanding
Shares outstanding is the number of a company's common shares currently held by investors, including insiders and institutions, as of a specific date. It equals the shares the company has issued minus any it has bought back and holds in treasury.

Shares outstanding is a point-in-time count. It differs from the weighted-average share count used in earnings per share, which averages the number outstanding across a reporting period.

#### Short-Term Borrowings
source: https://www.geminiq.com/financial-definitions/short-term-borrowings
Short-term borrowings are debt a company took on with an original term of one year or less, such as commercial paper, bank loans and notes payable, drawings on short-term credit lines, and bank overdrafts. They are interest-bearing obligations reported among current liabilities.

Short-term borrowings do not include long-term debt that is simply coming due within the next year. Those current maturities are a separate item, and the two together make up the broader short-term debt figure.

#### Short-Term Debt
source: https://www.geminiq.com/financial-definitions/short-term-debt
Short-term debt is all of a company's interest-bearing debt due within the next year (or its operating cycle, if longer). It combines short-term borrowings, such as commercial paper, bank loans, and credit-line drawings, with the current maturities of long-term debt, and often includes the current portion of finance lease obligations.

The measure answers a practical question: how much borrowed money must the company repay or refinance in the coming twelve months? It sits within current liabilities and is the near-term half of total debt.

#### Short-Term Deferred Tax Assets
source: https://www.geminiq.com/financial-definitions/short-term-deferred-tax-assets
Short-term deferred tax assets are the portion of a company's deferred tax assets that was classified as current on the balance sheet, representing expected future reductions in income taxes tied to items that would reverse within a year. A deferred tax asset arises when a company has recognized an expense or loss for accounting purposes before it can deduct it on its tax return, or holds tax loss and credit carryforwards it expects to use.

Current classification of deferred taxes has been eliminated for US GAAP filers, so this line now appears mainly in historical balance sheets. Today all deferred tax assets and liabilities are reported as noncurrent.

#### Short-Term Derivative & Hedging Assets
source: https://www.geminiq.com/financial-definitions/short-term-derivative-and-hedging-assets
Short-term derivative and hedging assets are the fair value of derivative contracts that are currently in a company's favor and expected to be settled or realized within one year. They include forwards, futures, swaps, and options a company uses to hedge exposures such as foreign currency, interest rates, and commodity prices, as well as any derivatives it holds for other purposes.

A derivative is an asset when the company would receive value if the contract were settled at the balance sheet date, and a liability when it would have to pay.

#### Short-Term Finance Lease Liabilities
source: https://www.geminiq.com/financial-definitions/short-term-finance-leases
Short-term finance lease liabilities are the portion of a company's finance lease obligations that is due within the next year. A finance lease is one in which the lessee effectively acquires the use of an asset for most of its life or value, so the arrangement is accounted for much like buying the asset with borrowed money.

The liability is the present value of the remaining lease payments, and the current portion is the principal expected to be paid over the next twelve months. Before ASC 842, these were called capital leases.

#### Short-Term Investments
source: https://www.geminiq.com/financial-definitions/short-term-investments
Short-term investments are financial investments a company expects to sell, collect, or have mature within one year that do not qualify as cash equivalents. They typically include Treasury bills, certificates of deposit, commercial paper, corporate and government bonds, and money market holdings with maturities too long to count as cash, along with equity securities held for liquidity.

Most companies hold them to earn a return on cash they do not need immediately, while keeping it available on short notice.

#### Sustainable Growth Rate
source: https://www.geminiq.com/financial-definitions/sustainable-growth-rate
Formula: Return on Equity × (1 − Dividend Payout Ratio)
The sustainable growth rate is the fastest a company can grow its sales and earnings using only the profits it retains, without issuing new stock and without changing its financial leverage. It is calculated by multiplying return on equity by the retention ratio, which is the share of earnings not paid out as dividends.

A company earning a 15% return on equity and paying out a third of its profits has a sustainable growth rate of 10%. Growing faster than that requires new equity, more borrowing relative to equity, or better margins or asset efficiency.

#### Tangible Assets
source: https://www.geminiq.com/financial-definitions/tangible-assets
Formula: Total Assets − Goodwill − Other Intangible Assets
Tangible assets are a company's total assets minus goodwill and other intangible assets. The figure keeps physical assets, such as property, equipment, and inventory, along with financial assets such as cash, investments, and receivables, and removes non-physical assets such as acquired brands, customer relationships, patents, and goodwill.

Tangible assets is a derived measure, not a line item companies report. It is calculated from figures reported in SEC filings.

#### Tangible Book Value per Share
source: https://www.geminiq.com/financial-definitions/tangible-book-value-per-share
Formula: (Total Common Equity − Goodwill − Other Intangible Assets) / Shares Outstanding
Tangible book value per share (TBVPS) is common shareholders' equity minus goodwill and other intangible assets, divided by the number of common shares outstanding. It estimates the net value per share of the assets a company could more readily sell or use to repay creditors, excluding items that have no physical form.

It is a stricter version of book value per share, and it is always equal to or lower than it.

#### Tangible Common Equity Ratio
source: https://www.geminiq.com/financial-definitions/tangible-common-equity-ratio
Formula: (Common Equity − Goodwill − Other Intangible Assets) / (Total Assets − Goodwill − Other Intangible Assets)
The tangible common equity ratio divides a company's tangible common equity by its tangible assets. Tangible common equity is shareholders' equity minus preferred stock, goodwill, and other intangible assets, and tangible assets are total assets minus the same goodwill and intangibles. It measures how much loss-absorbing capital common shareholders provide against the company's physical and financial assets.

The ratio is used mainly for banks and other financial institutions, where it offers a conservative view of capital strength. A higher percentage means a larger cushion before common shareholders' capital would be wiped out.

#### Tangible Common Equity
source: https://www.geminiq.com/financial-definitions/tangible-common-equity
Formula: Total Common Equity − Goodwill − Other Intangible Assets
Tangible common equity (TCE) is the portion of a company's shareholders' equity that belongs to common stockholders after removing preferred equity, goodwill, and other intangible assets. It estimates the book value that would remain for common shareholders if assets that cannot be readily sold, such as acquisition goodwill and acquired intangibles, were worth nothing.

TCE is not a GAAP line item. It is calculated from figures reported in SEC filings, and when a company presents it in an earnings release or filing, the SEC's non-GAAP rules apply.

#### Total Assets
source: https://www.geminiq.com/financial-definitions/total-assets
Total assets is the sum of everything a company owns or controls that is expected to provide future economic benefit, as recorded on its balance sheet at a specific date. It includes current assets such as cash, receivables, and inventory, and noncurrent assets such as property and equipment, investments, intangible assets, and goodwill.

Under the accounting equation, total assets always equals total liabilities plus total equity. It measures the size of the resources a company has to work with, however they were financed.

#### Total Cash Common Dividends
source: https://www.geminiq.com/financial-definitions/total-cash-common-dividends
Total cash common dividends is the total amount of cash dividends a company declared to its common shareholders during a period. It measures how much of the company's earnings the board chose to return to common stockholders in cash, excluding dividends on preferred stock and dividends paid in additional shares.

Dividends are not an expense. They are a distribution of profit to owners, so they do not reduce net income. They reduce retained earnings when declared and cash when paid.

#### Total Common Equity
source: https://www.geminiq.com/financial-definitions/total-common-equity
Formula: Total Stockholders' Equity (attributable to parent) − Preferred Equity
Total common equity is the portion of a company's shareholders' equity that belongs to its common stockholders. It equals the parent company's total stockholders' equity minus the carrying value of any preferred stock, and it includes common stock, additional paid-in capital, retained earnings, and accumulated other comprehensive income, net of treasury stock.

For a company with no preferred stock, total common equity is the same as stockholders' equity attributable to the parent. Common equity is what investors mean by book value when they compare it with market value.

#### Total Current Assets
source: https://www.geminiq.com/financial-definitions/total-current-assets
Total current assets is the sum of the assets a company expects to convert into cash, sell, or use up within one year or its normal operating cycle, whichever is longer. It typically includes cash and cash equivalents, short-term investments, accounts receivable, inventory, prepaid expenses, and other current assets.

Current assets are the resources available to cover short-term obligations, which makes this total the starting point for most liquidity analysis.

#### Total Current Liabilities
source: https://www.geminiq.com/financial-definitions/total-current-liabilities
Total current liabilities is the sum of the obligations a company expects to settle within one year or its normal operating cycle, whichever is longer. It typically includes accounts payable, accrued expenses, short-term borrowings, the current portion of long-term debt and lease liabilities, income taxes payable, deferred revenue, and other current liabilities.

Current liabilities are the claims that current assets are expected to pay, which is why the two totals are compared in nearly every liquidity measure.

#### Total Debt to Capital
source: https://www.geminiq.com/financial-definitions/total-debt-to-capital
Formula: Total Debt / (Total Debt + Total Shareholders' Equity)
Total debt to capital, commonly called the debt-to-capital ratio, divides a company's total debt by its total capital, which is the sum of that debt and shareholders' equity. It shows what percentage of the money invested in the business, by lenders and owners combined, comes from borrowing.

The ratio runs from 0% for a debt-free company toward 100% for one financed almost entirely by debt. A value of 40% means lenders provide 40 cents of every dollar of capital and shareholders provide the other 60.

#### Total Debt/EBIT
source: https://www.geminiq.com/financial-definitions/total-debt-to-ebit
Formula: Total Debt / EBIT (trailing twelve months)
Total debt/EBIT divides a company's total debt by its trailing twelve-month earnings before interest and taxes. It estimates how many years of current operating earnings the company would need to repay all of its borrowings, without counting any cash it holds.

A multiple of 4.0x means total debt equals four years of EBIT. Higher multiples indicate heavier leverage relative to the earnings available to service debt.

#### Total Debt to Enterprise Value
source: https://www.geminiq.com/financial-definitions/total-debt-to-enterprise-value
Formula: Total Debt / Enterprise Value, where Enterprise Value = Market Capitalization + Short-Term Debt + Long-Term Debt − Cash and Cash Equivalents
Total debt to enterprise value divides a company's total debt by its enterprise value. It shows what share of the market value of the whole business is financed by borrowing, making it a measure of leverage based on market values rather than book values.

A low ratio means most of the company's value belongs to equity holders. A high ratio means lenders have a large claim on the business relative to what the market thinks it is worth, which leaves less cushion for shareholders if that value falls.

#### Total Equity
source: https://www.geminiq.com/financial-definitions/total-equity
Total equity is the owners' residual claim on a company's assets after all liabilities are subtracted: total assets minus total liabilities, excluding any temporary equity. It includes the equity of the parent company's shareholders, meaning preferred and common stock, additional paid-in capital, retained earnings, accumulated other comprehensive income, and treasury stock, plus noncontrolling interests in subsidiaries.

Total equity is also called shareholders' equity, stockholders' equity, or book value. It is an accounting measure, not the market value of the company.

#### Total Intangible Assets
source: https://www.geminiq.com/financial-definitions/total-intangible-assets
Total intangible assets is the combined carrying value of a company's non-physical, long-lived assets, including goodwill and identifiable intangibles such as patents, trademarks, customer relationships, licenses, technology, and franchise rights. Finite-lived intangibles are shown net of accumulated amortization, and all intangibles are shown net of any impairment.

Most recorded intangibles come from acquisitions. Intangibles a company develops internally, such as its own brand or research, are generally expensed as incurred and do not appear on the balance sheet.

#### Total Liabilities & Equity
source: https://www.geminiq.com/financial-definitions/total-liabilities-and-equity
Total liabilities and equity is the final line on the right-hand, or financing, side of a balance sheet. It adds together everything the company owes, any temporary equity such as redeemable preferred stock, and shareholders' equity, including noncontrolling interests. By construction it always equals total assets.

The figure answers the question of how a company's assets are financed: some portion by creditors and other obligations, and the rest by owners.

#### Total Liabilities
source: https://www.geminiq.com/financial-definitions/total-liabilities
Total liabilities is the sum of every obligation a company has recognized on its balance sheet at a given date, both those due within a year and those due later. It includes debt, accounts payable, accrued expenses, deferred revenue, lease liabilities, deferred income taxes, pension obligations, and other liabilities.

Total liabilities is broader than debt. It captures everything the company owes to lenders, suppliers, employees, customers, tax authorities, and others, not just borrowed money.

#### Total Noncurrent Assets
source: https://www.geminiq.com/financial-definitions/total-noncurrent-assets
Formula: Total Assets − Total Current Assets (when not reported directly)
Total noncurrent assets is the sum of the assets a company does not expect to convert into cash, sell, or use up within one year or its normal operating cycle, whichever is longer. It typically includes property, plant and equipment, operating lease right-of-use assets, long-term investments, goodwill and other intangible assets, long-term receivables, deferred tax assets, and other long-term assets.

These are the assets a company uses to operate over many years, as opposed to the working assets that turn over within the operating cycle.

#### Total Noncurrent Liabilities
source: https://www.geminiq.com/financial-definitions/total-noncurrent-liabilities
Formula: Total Liabilities − Total Current Liabilities (when not reported directly)
Total noncurrent liabilities is the sum of the obligations a company does not expect to settle within one year or its normal operating cycle, whichever is longer. It typically includes long-term debt, noncurrent lease liabilities, deferred income taxes, pension and other postretirement obligations, long-term deferred revenue, and other long-term liabilities.

These obligations represent the company's longer-dated financing and commitments, as opposed to the payables and short-term debt that come due in the current cycle.

#### Treasury Stock
source: https://www.geminiq.com/financial-definitions/treasury-stock
Treasury stock is a company's own previously issued shares that it has bought back and holds rather than cancels. On the balance sheet it appears as a deduction from stockholders' equity, usually at the price the company paid to repurchase the shares.

Treasury shares are issued but not outstanding. They carry no voting rights, receive no dividends, and are excluded from earnings per share, but the company can reissue them later, for example to satisfy employee stock awards.

#### TTM After-Tax Interest Expense
source: https://www.geminiq.com/financial-definitions/ttm-after-tax-interest-expense
Formula: TTM After-Tax Interest Expense = TTM Interest Expense × (1 − TTM Effective Tax Rate)
TTM after-tax interest expense is the interest a company incurred over the trailing twelve months, reduced by the tax saving that deducting it produces, calculated as TTM interest expense multiplied by one minus the TTM effective tax rate. It gives a current, full-year view of what debt costs the company after taxes.

Trailing twelve months (TTM) means the four most recent fiscal quarters combined. Using a rolling year rather than the last fiscal year keeps the figure up to date with each new 10-Q while still covering a full twelve months, so seasonal swings between quarters wash out.

#### TTM Capital Expenditures
source: https://www.geminiq.com/financial-definitions/ttm-capital-expenditures
Formula: TTM Capital Expenditures = Sum of capital expenditures over the four most recent quarters
TTM capital expenditures are the total cash a company spent on property, plant, and equipment over the trailing twelve months, the four most recent fiscal quarters. The figure gives an up-to-date, full-year view of how much the company is investing in its physical asset base.

Capital spending is often lumpy. A company may concentrate projects in certain quarters, or finish a large build-out in the middle of a fiscal year. Adding up four quarters smooths that timing while still reflecting the latest 10-Q, which a single quarter or the last annual report cannot do.

#### TTM Cash Flow from Financing
source: https://www.geminiq.com/financial-definitions/ttm-cash-flow-from-financing
Formula: TTM Cash Flow from Financing = Sum of net cash from financing activities over the four most recent quarters
TTM cash flow from financing is the net cash a company raised from, or returned to, its lenders and shareholders over the trailing twelve months. It combines the financing section of the cash flow statement for the four most recent fiscal quarters into a single, current, full-year figure.

A positive value means the company brought in more money from borrowing and issuing stock than it paid out. A negative value means it spent more on repaying debt, buying back shares, and paying dividends than it raised, which is typical of a mature, cash-generating business.

#### TTM Cash Flow to Firm
source: https://www.geminiq.com/financial-definitions/ttm-cash-flow-to-firm
Formula: TTM Cash Flow to Firm = TTM Cash from Operating Activities + TTM Interest Expense × (1 − TTM Effective Tax Rate)
TTM cash flow to firm is the operating cash a company generated over the trailing twelve months before any payments to lenders, commonly calculated as TTM operating cash flow plus TTM after-tax interest expense. It measures the cash the business produces for all of its capital providers, debt and equity together, before it spends anything on new capital assets.

It is not a figure companies report and not a GAAP line item. It is calculated from figures reported in SEC filings, and definitions vary somewhat between analysts and data providers.

#### TTM Cash from Operations
source: https://www.geminiq.com/financial-definitions/ttm-cash-from-operations
Formula: TTM Cash from Operations = Sum of net cash from operating activities over the four most recent quarters
TTM cash from operations is the net cash a company's day-to-day business generated over the trailing twelve months, the four most recent fiscal quarters. It is the operating section of the cash flow statement rolled into a current, full-year total.

It starts from net income, adds back noncash charges such as depreciation and stock-based compensation, and adjusts for changes in working capital like receivables, inventory, and payables. The result is the cash the business actually produced, as opposed to the profit it reported.

#### TTM Cost of Revenue
source: https://www.geminiq.com/financial-definitions/ttm-cost-of-revenue
Formula: TTM Cost of Revenue = Sum of cost of revenue over the four most recent quarters
TTM cost of revenue is the total direct cost of the goods a company sold and the services it delivered over the trailing twelve months, the four most recent fiscal quarters. It pairs with TTM revenue to give a current, full-year view of gross profit and gross margin.

Cost of revenue covers costs such as materials, direct labor, production overhead, and the costs of delivering services. It leaves out selling, administrative, and research expenses, which sit lower on the income statement.

#### TTM Dividends Paid
source: https://www.geminiq.com/financial-definitions/ttm-dividends-paid
Formula: TTM Dividends Paid = Sum of cash dividends paid over the four most recent quarters
TTM dividends paid is the total cash a company paid out as dividends over the trailing twelve months, the four most recent fiscal quarters. It is taken from the financing section of the cash flow statement and shows how much cash the company actually distributed to shareholders over the latest full year.

It measures cash that left the company, not dividends declared. A dividend declared near the end of a quarter but paid in the next one shows up in the quarter it is paid.

#### TTM EBIT
source: https://www.geminiq.com/financial-definitions/ttm-ebit
Formula: TTM EBIT = TTM Net Income + TTM Income Tax Expense + TTM Interest Expense
TTM EBIT is a company's earnings before interest and taxes over the trailing twelve months, the four most recent fiscal quarters. It measures the profit the business produced from its operations and other activities before paying lenders and tax authorities, on a current, full-year basis.

EBIT is not a US GAAP line item. When a company does not report it, EBIT is calculated from figures reported in SEC filings by adding income tax expense and interest expense back to net income.

#### TTM EBITDA
source: https://www.geminiq.com/financial-definitions/ttm-ebitda
Formula: TTM EBITDA = TTM EBIT + TTM Depreciation & Amortization
TTM EBITDA is a company's earnings before interest, taxes, depreciation, and amortization over the trailing twelve months, the four most recent fiscal quarters. It approximates the operating profit the business generated over the latest full year before financing costs, taxes, and the noncash charges that spread the cost of long-lived assets over time.

EBITDA is not a US GAAP measure. It is calculated from figures reported in SEC filings, and companies that present it must follow SEC non-GAAP rules.

#### TTM Free Cash Flow to Firm
source: https://www.geminiq.com/financial-definitions/ttm-free-cash-flow-to-firm
Formula: TTM FCFF = TTM Cash from Operating Activities + TTM Interest Expense × (1 − TTM Effective Tax Rate) − TTM Capital Expenditures
TTM free cash flow to the firm (FCFF) is the cash a company generated over the trailing twelve months that is available to all of its capital providers, lenders and shareholders together, after it has paid operating costs, taxes, and capital expenditures. It is commonly calculated as TTM operating cash flow plus TTM after-tax interest expense minus TTM capital expenditures.

It is often called unlevered free cash flow, because it measures the business's cash generation as if it carried no debt. It is not a GAAP line item and is calculated from figures reported in SEC filings.

#### TTM Interest Expense
source: https://www.geminiq.com/financial-definitions/ttm-interest-expense
Formula: TTM Interest Expense = Sum of interest expense over the four most recent quarters
TTM interest expense is the total interest cost a company recognized on its income statement over the trailing twelve months, the four most recent fiscal quarters. It gives a current, full-year measure of what the company's borrowing costs, and it updates with every quarterly filing.

Interest expense includes interest on bonds, loans, and credit lines, along with amortization of debt discounts and issuance costs. Interest that a company capitalizes into the cost of assets it is building is not included, since that interest is added to the asset rather than expensed.

#### TTM Minority Interest
source: https://www.geminiq.com/financial-definitions/ttm-minority-interest
Formula: TTM Minority Interest = Sum of net income attributable to noncontrolling interest over the four most recent quarters
TTM minority interest is the portion of a company's consolidated net income over the trailing twelve months that belongs to outside owners of its subsidiaries rather than to the parent company's shareholders. It sums the income statement's noncontrolling-interest line for the four most recent fiscal quarters.

When a parent controls a subsidiary but owns less than all of it, it consolidates all of the subsidiary's revenue, expenses, and profit, then assigns the outside owners their share. That share is subtracted from consolidated net income to reach net income attributable to the parent.

#### TTM Net Income Available to Common Shareholders
source: https://www.geminiq.com/financial-definitions/ttm-net-income-available-to-common
Formula: TTM Net Income Available to Common = TTM Net Income Attributable to Parent − TTM Preferred Dividends and Other Adjustments
TTM net income available to common shareholders is the profit left for a company's common stockholders over the trailing twelve months, after every expense, tax, the share belonging to noncontrolling interests, and dividends on preferred stock have been deducted. It is the numerator used to calculate earnings per share.

For most companies it is close or equal to net income. The gap matters for companies with preferred stock, participating securities, or large noncontrolling interests, whose claims come ahead of the common shareholders'.

#### TTM Net Income
source: https://www.geminiq.com/financial-definitions/ttm-net-income
Formula: TTM Net Income = Sum of net income over the four most recent quarters
TTM net income is a company's bottom-line profit over the trailing twelve months, the four most recent fiscal quarters, after all expenses, interest, taxes, and discontinued operations. It is the most widely used current measure of how much a company earned over a full year.

Because it rolls forward with each 10-Q, TTM net income always reflects the latest reported quarter while still covering a complete year, which removes the seasonality that makes a single quarter hard to read.

#### TTM Net Share Repurchases
source: https://www.geminiq.com/financial-definitions/ttm-net-share-repurchases
Formula: TTM Net Share Repurchases = TTM Payments for Repurchase of Stock − TTM Proceeds from Issuance of Stock
TTM net share repurchases is the cash a company spent buying back its own stock over the trailing twelve months, minus the cash it received from issuing new shares over the same period. It measures how much cash the company returned to shareholders through buybacks after offsetting stock sold to employees and investors.

A positive figure means the company bought back more stock than it issued, which usually shrinks the share count. A negative figure means it raised more from issuing shares than it spent on repurchases.

#### TTM Operating Income
source: https://www.geminiq.com/financial-definitions/ttm-operating-income
Formula: TTM Operating Income = Sum of operating income over the four most recent quarters
TTM operating income is the profit a company earned from its core business over the trailing twelve months, the four most recent fiscal quarters, after deducting operating expenses from operating revenue. It shows how profitable the company's day-to-day operations were over the latest full year, before interest, taxes, and non-operating gains or losses.

Operating income sits between gross profit and pretax income. It reflects cost of revenue and operating costs such as selling, general, and administrative expenses and research and development, but not financing costs or investment income.

#### TTM Revenue per Share
source: https://www.geminiq.com/financial-definitions/ttm-revenue-per-share
Formula: TTM Revenue per Share = TTM Revenue ÷ Shares Outstanding
TTM revenue per share is a company's total revenue over the trailing twelve months divided by its shares outstanding. It expresses the latest full year of sales on a per-share basis, showing how much revenue each share represents.

Revenue per share is the building block of the price-to-sales ratio: dividing the share price by TTM revenue per share gives the same result as dividing market capitalization by TTM revenue.

#### TTM Sales
source: https://www.geminiq.com/financial-definitions/ttm-sales
Formula: TTM Sales = Sum of revenue over the four most recent quarters
TTM sales is a company's total revenue over the trailing twelve months, the four most recent fiscal quarters. It is the most current full-year measure of how much business a company does, and it updates with every quarterly filing.

Sales and revenue mean the same thing here: the amounts a company earned from selling goods, providing services, and its other ordinary business activities, net of discounts, returns, and allowances.

#### Work in Process
source: https://www.geminiq.com/financial-definitions/work-in-process
Work in process (also called work in progress) is inventory that a manufacturer has started producing but not yet finished. Its cost includes the raw materials already put into production plus the direct labor and manufacturing overhead applied to those units so far.

Work in process is the middle stage of manufacturing inventory. It begins when raw materials enter production and ends when the units are complete and move into finished goods. The term "work in progress" is often used for the same thing.


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## Section 4d: SEC Filings Glossary
source: https://www.geminiq.com/glossary

Definitions of SEC forms, filing rules, filer status categories, and EDGAR/XBRL terms, written from the SEC's own rule text and form instructions.

#### Accelerated Filer
source: https://www.geminiq.com/glossary/accelerated-filer
An accelerated filer is an SEC-reporting company with a public float of at least $75 million but less than $700 million, measured on the last business day of its second fiscal quarter, that files its annual and quarterly reports on a shorter schedule than smaller issuers.

It is the middle tier of the filer-status system in Exchange Act Rule 12b-2, sitting between large accelerated filers above and non-accelerated filers below. Public float here means the worldwide market value of voting and non-voting common equity held by non-affiliates.

#### Accession Number
source: https://www.geminiq.com/glossary/accession-number
An accession number is the unique identifier the SEC assigns to each individual submission made through EDGAR. While a Central Index Key (CIK) identifies the filer, the accession number identifies one specific filing by that filer — a particular 10-K, 10-Q, 8-K, or any other document submitted on a particular date. It is the precise reference used to locate and cite an exact filing in EDGAR.

A typical accession number looks like 0000320193-23-000106, written as three segments separated by hyphens.

#### Amended Filings (/A)
source: https://www.geminiq.com/glossary/amended-filings
An amended filing is a revised version of a document already submitted to the SEC, identified by the suffix "/A" after the form type, as in 10-K/A, 10-Q/A, or 8-K/A. Under Exchange Act Rule 12b-15, amendments are filed under cover of the original form, marked with the letter A, and must set out the complete text of every item being amended.

An /A does not by itself mean the numbers were wrong. Amendments range from adding a missing exhibit to fully restating financial statements, so the scope is what matters.

#### CIK (Central Index Key)
source: https://www.geminiq.com/glossary/cik-central-index-key
The Central Index Key (CIK), often called a CIK number, is the unique number the SEC assigns to every filer in the EDGAR system — including public companies, mutual funds, and individuals such as corporate insiders. The CIK is the canonical identifier used to look up, group, and link every filing a given entity has ever submitted. Because it is permanent and unambiguous, the CIK is more reliable than a company name or ticker symbol, both of which can change over time or be shared across entities.

For example, Apple Inc. is identified in EDGAR by CIK 0000320193, regardless of any change to its name, ticker, or stock listing.

#### Critical Audit Matters (CAMs)
source: https://www.geminiq.com/glossary/critical-audit-matters
A critical audit matter (CAM) is an issue from the audit of a company's financial statements that the auditor communicated, or was required to communicate, to the audit committee, that relates to accounts or disclosures material to the financial statements, and that involved especially challenging, subjective, or complex auditor judgment. CAMs are described in the auditor's report under a section titled "Critical Audit Matters," as required by PCAOB auditing standard AS 3101.

CAMs are the part of the audit report that tells investors where the auditor found the accounts hardest to get comfortable with.

#### DEF 14A
source: https://www.geminiq.com/glossary/def-14a
DEF 14A is the SEC form code for a company's definitive proxy statement, the document filed ahead of its annual shareholder meeting whenever shareholders will vote on any matter. It sets out what is on the ballot — typically the election of directors, ratification of the outside auditor, an advisory vote on executive pay, and any shareholder or management proposals — and gives shareholders the information needed to vote, whether in person or by proxy.

The proxy statement is also the primary public disclosure of how a company pays its named executive officers and how its board is structured.

#### DEI (Document and Entity Information)
source: https://www.geminiq.com/glossary/dei-document-and-entity-information
DEI (Document and Entity Information) is the standardized XBRL taxonomy used to tag the metadata about a filing and the entity that submitted it. While the US-GAAP taxonomy covers the numbers in the financial statements, the DEI taxonomy covers the descriptive facts on the cover page and document context — items such as the registrant's name, Central Index Key, document type, fiscal year and period focus, the period-end date, the trading symbol, and the public float. These tags tell software what the document is, who filed it, and what period it covers.

DEI tagging is required on the cover pages of periodic reports, which is what makes a filing's basic identifying details machine-readable.

#### EDGAR
source: https://www.geminiq.com/glossary/edgar
SEC EDGAR (Electronic Data Gathering, Analysis, and Retrieval) is the U.S. Securities and Exchange Commission's official electronic system for collecting, validating, indexing, and disseminating the disclosure documents that public companies, funds, and certain individuals are required to file. Every 10-K, 10-Q, 8-K, registration statement, proxy statement, and insider-trading form filed with the SEC is submitted through EDGAR and made available to the public, free of charge, at sec.gov.

EDGAR is the authoritative primary source for U.S. public-company financial disclosure. Because filers submit directly to the SEC and the documents are published without an intermediary, EDGAR data reflects exactly what a company reported, with no third-party normalization or reclassification.

#### Emerging Growth Company (EGC)
source: https://www.geminiq.com/glossary/emerging-growth-company
An emerging growth company (EGC) is a company whose gross revenues for its latest completed fiscal year were under $1.235 billion, a status that lets a newly public company phase into some of the SEC's more demanding reporting requirements rather than meeting all of them at once.

The definition sits in Exchange Act Rule 12b-2. Unlike filer status, which is built on public float, EGC status turns on revenue and on how long ago the company first sold common equity in a registered offering.

#### Financial Restatement
source: https://www.geminiq.com/glossary/financial-restatement
A financial restatement, or restatement of financial statements, is the revision of previously issued financial statements to correct an error. When a company's board, audit committee, or authorized officers conclude that earlier statements should no longer be relied upon because of an error, as addressed in FASB ASC Topic 250, the company must disclose that conclusion on Form 8-K under Item 4.02 and then issue corrected statements.

#### Fiscal Year End
source: https://www.geminiq.com/glossary/fiscal-year-end
A company's fiscal year end is the last day of the annual accounting period it reports on, and it is the date from which SEC annual and quarterly reporting deadlines are counted. Many companies use December 31, but a fiscal year can close on whatever date the company adopts.

Exchange Act Rule 12b-2 defines the fiscal year as the company's annual accounting period, and says that if no closing date has been adopted, the fiscal year is the calendar year ending December 31.

#### Foreign Private Issuer (FPI)
source: https://www.geminiq.com/glossary/foreign-private-issuer
A foreign private issuer (FPI) is a company incorporated or organized outside the United States that is not a foreign government and is not so closely tied to the U.S. that the SEC treats it as domestic — a status that lets it file annual reports on Form 20-F and furnish interim information on Form 6-K instead of filing 10-Ks, 10-Qs, and 8-Ks.

The term is defined in Exchange Act Rule 3b-4 and, in matching terms, in Securities Act Rule 405.

#### Form 10-K
source: https://www.geminiq.com/glossary/form-10-k
Form 10-K is the comprehensive annual report that U.S. public companies file with the SEC. It is the most detailed periodic disclosure a company produces, covering a complete fiscal year and including audited financial statements. Because it is audited and comprehensive, the 10-K is the authoritative annual snapshot of a company's financial condition, results of operations, and risks — the primary document investors and analysts rely on for fundamental analysis.

The financial statements in a 10-K are tagged in XBRL, which is what makes the data usable for structured, cross-company analysis.

#### Form 10-Q
source: https://www.geminiq.com/glossary/form-10-q
Form 10-Q is the quarterly report that U.S. public companies file with the SEC for each of the first three quarters of their fiscal year. It provides a condensed, unaudited update on the company's financial position and results between annual reports. Because it is filed every quarter, the 10-Q is the main source of timely, in-period financial data, giving investors a regular cadence of updates on revenue, earnings, and the balance sheet.

The financial statements in a 10-Q are tagged in XBRL, making the quarterly data usable for structured analysis alongside annual figures.

#### Form 10
source: https://www.geminiq.com/glossary/form-10
Form 10 is the general registration statement a company files with the SEC to register a class of securities under Section 12(b) or 12(g) of the Securities Exchange Act of 1934 when no other form is prescribed. Registering under the Exchange Act makes the company a reporting company, obligated from then on to file 10-Ks, 10-Qs, and 8-Ks.

Form 10 is not an offering document. It registers a class of securities for ongoing reporting and trading rather than registering a sale of new securities, which is the job of Securities Act forms such as the S-1.

#### Form 12b-25
source: https://www.geminiq.com/glossary/form-12b-25
Form 12b-25 is the notice a public company files with the SEC when it cannot file a periodic report, such as a 10-K, 10-Q, or 20-F, by its deadline. On EDGAR it appears as NT 10-K, NT 10-Q, or NT 20-F, where NT stands for notification of late filing. Filed on time, it buys a short grace period and requires the company to explain why the report is late.

For investors, an NT filing is an event in itself: a company that misses a scheduled report is telling the market something went wrong in its close process.

#### Form 13F
source: https://www.geminiq.com/glossary/form-13f
Form 13F, the source of the 13F filings investors track, is the quarterly report the SEC requires from institutional investment managers who exercise investment discretion over $100 million or more in Section 13(f) securities. Filed under Section 13(f) of the Securities Exchange Act of 1934, it discloses what a manager held in U.S. equities as of the last trading day of the prior calendar quarter.

Once a manager crosses the $100 million threshold, it must keep filing for that quarter and the following three, even if its assets later fall back below the threshold.

#### Form 144
source: https://www.geminiq.com/glossary/form-144
Form 144 is the notice a person files with the SEC when they plan to sell restricted or control securities in reliance on Rule 144 under the Securities Act of 1933 and the sale is above a size threshold. It announces an intended sale, not a completed one, which makes it an early signal that an affiliate such as an officer, director, or large holder expects to sell.

The notice is required when sales over any three-month period exceed 5,000 shares or units, or an aggregate sale price of $50,000. Smaller sales need no Form 144.

#### Form 15
source: https://www.geminiq.com/glossary/form-15
Form 15 is the short SEC filing a company uses to end the Exchange Act Section 12(g) registration of a class of its securities, or to give notice that its duty to file periodic reports under Section 13(a) or 15(d) has been suspended. Put simply, it is how a company stops being an SEC reporting company, often called deregistering or going dark.

The form itself is brief: the company checks the rule it relies on and states its approximate number of holders of record.

#### Form 20-F
source: https://www.geminiq.com/glossary/form-20-f
Form 20-F is the annual report that a foreign private issuer, a non-U.S. company that meets the test in Exchange Act Rule 3b-4, files with the SEC in place of a Form 10-K. The same form also serves as the registration statement when such a company first registers a class of securities under Section 12 of the Securities Exchange Act of 1934.

For investors in American depositary shares or U.S.-listed foreign companies, the 20-F is the core annual disclosure document: audited financial statements plus a narrative description of the business, its risks, and its results.

#### Form 3
source: https://www.geminiq.com/glossary/form-3
Form 3 is the one-time SEC filing a person makes on becoming a company insider (a director, an officer, or a holder of more than 10% of a registered class of equity), disclosing every security of that company they own at that moment. It is required by Section 16(a) of the Securities Exchange Act of 1934 and Rule 16a-3, and it sets the baseline that every later Form 4 and Form 5 changes from.

A Form 3 is required even when the new insider owns nothing. In that case the filer states that no securities are beneficially owned.

#### Form 4
source: https://www.geminiq.com/glossary/form-4
Form 4 is the SEC filing that officers, directors, and owners of more than 10% of a company's registered equity must submit whenever their holdings change through a purchase, sale, grant, or option exercise. Formally the Statement of Changes in Beneficial Ownership, it is required under Section 16 of the Securities Exchange Act of 1934 and is generally due within two business days of the transaction.

Because that reporting window is so short, Form 4 filings are close to a real-time record of what a company's insiders are doing with their own shares.

#### Form 40-F
source: https://www.geminiq.com/glossary/form-40-f
Form 40-F is the annual report and Exchange Act registration form available to large, established Canadian companies, letting them satisfy U.S. SEC reporting largely with the disclosure documents they already prepare under Canadian securities law. Rather than rebuilding their disclosure around U.S. items, eligible companies file their Canadian annual information form, audited annual financial statements, and management's discussion and analysis under a 40-F cover.

It is the Canadian counterpart to Form 20-F, and the two are the main annual filings for foreign issuers listed in the United States.

#### Form 424B
source: https://www.geminiq.com/glossary/form-424b
Form 424B is the EDGAR label for a prospectus filed under Rule 424(b) of the Securities Act of 1933: the final version of a prospectus, or a supplement to one, used after a registration statement has become effective. It is where the actual terms of an offering, including the price, the number of shares or principal amount, and the underwriters, are formally put on the record.

A registration statement such as an S-1 or S-3 makes an offering legally possible. The 424B shows what was actually sold and on what terms.

#### Form 5
source: https://www.geminiq.com/glossary/form-5
Form 5 is the annual SEC filing in which a company's Section 16 insiders (directors, officers, and more-than-10% holders) catch up on ownership changes that were not reported on a Form 4 during the year. It is due within 45 days after the end of the company's fiscal year, under Rule 16a-3(f).

Most insider activity is reported on Form 4 within days, so Form 5 is a year-end sweep rather than a primary source. A filer owes nothing if every reportable item was already disclosed before the due date.

#### Form 6-K
source: https://www.geminiq.com/glossary/form-6-k
Form 6-K is the report a foreign private issuer furnishes to the SEC to pass along material information it has published outside the United States, such as quarterly results, press releases, and shareholder meeting materials. It is required by Exchange Act Rules 13a-16 and 15d-16 and fills the gap between a foreign company's annual reports on Form 20-F or Form 40-F.

The 6-K is often described as the foreign counterpart to the 8-K, but its trigger is different. Instead of a fixed list of reportable events, it mirrors whatever the company makes public at home.

#### Form 8-K Items
source: https://www.geminiq.com/glossary/form-8-k-items
Form 8-K items are the numbered event categories, such as Item 1.01 or Item 5.02, that tell a reader exactly what kind of event a current report discloses. Every 8-K lists the item or items it responds to, so the item number alone identifies whether a filing is about an acquisition, an earnings release, an auditor change, or a departing executive.

The items are grouped into nine sections, and the first digit of each item number is its section.

#### Form 8-K
source: https://www.geminiq.com/glossary/form-8-k
Form 8-K is the "current report" that U.S. public companies file with the SEC to disclose material events as they happen, between the scheduled annual (10-K) and quarterly (10-Q) reports. Rather than following a fixed calendar, an 8-K is event-driven: a company files one whenever something significant occurs that investors should know about promptly. This makes the 8-K the mechanism for timely, real-time disclosure of developments that can move a stock between periodic filings.

#### Form D
source: https://www.geminiq.com/glossary/form-d
Form D is the brief notice a company files with the SEC after it sells securities in a private offering that is exempt from registration under Regulation D (Rules 504 or 506) or Section 4(a)(5) of the Securities Act of 1933. It is a notice, not a registration statement: it tells regulators and the public that an unregistered offering is under way, without the audited financials or detailed disclosure of a prospectus.

Because private funds and companies of every size file it, Form D is one of the few public windows into private capital raising.

#### Form S-1
source: https://www.geminiq.com/glossary/form-s-1
Form S-1 is the registration statement a company files with the SEC before offering securities to the public for the first time, most commonly ahead of an initial public offering. It discloses the business, its financial history, the terms of the offering, and the risks of investing.

A company that is already public generally uses a different form, such as Form S-3, for follow-on offerings. The S-1 is specifically the first-time registration.

#### Form S-3
source: https://www.geminiq.com/glossary/form-s-3
Form S-3 is the simplified registration statement that an established public company can use to register securities for sale under the Securities Act of 1933, relying on the reports it already files with the SEC instead of repeating that information. Because it incorporates the company's 10-K, 10-Q, and 8-K filings by reference, an S-3 is far shorter than a Form S-1.

It is the usual vehicle for a shelf registration, in which a company registers securities in advance and sells them later in one or more takedowns when conditions suit it.

#### Form S-4
source: https://www.geminiq.com/glossary/form-s-4
Form S-4 is the registration statement a company files with the SEC when it will issue new securities as payment in a business combination, most often a merger or acquisition in which the target's shareholders receive the buyer's stock. Because those shareholders are effectively being offered a new investment, the securities must be registered under the Securities Act of 1933, and the S-4 is the form built for that purpose.

When the deal needs a shareholder vote, the S-4 prospectus is usually combined with the proxy statement, producing a single document that both solicits the vote and offers the shares.

#### Form S-8
source: https://www.geminiq.com/glossary/form-s-8
Form S-8 is the registration statement a public company files with the SEC to register shares it will issue to employees under an employee benefit plan, such as a stock option, restricted stock, or employee stock purchase plan. Registering the shares under the Securities Act of 1933 lets employees receive and later sell them freely instead of holding restricted stock.

An S-8 does not raise capital from outside investors. It registers the pool of shares a company expects to hand out as compensation, which makes it a useful marker of future dilution from stock-based pay.

#### Inline XBRL
source: https://www.geminiq.com/glossary/inline-xbrl
Inline XBRL (iXBRL) is a format that embeds machine-readable XBRL tags directly inside the human-readable HTML document of an SEC filing. Rather than submitting a separate data exhibit alongside the filing, a company files a single document that is simultaneously a readable web page and a fully tagged dataset.

The numbers a person reads and the data a machine extracts are therefore guaranteed to be the same figures. Inline XBRL is now the required format for the financial statements in 10-K and 10-Q filings.

#### Internal Control over Financial Reporting (ICFR)
source: https://www.geminiq.com/glossary/internal-control-over-financial-reporting
Internal control over financial reporting (ICFR) is the set of processes a public company uses to provide reasonable assurance that its financial reporting is reliable and that its external financial statements are prepared in accordance with GAAP. The SEC defines it in Exchange Act Rule 13a-15(f) as a process designed under the supervision of the principal executive and principal financial officers and carried out by the board, management, and other personnel.

#### Large Accelerated Filer
source: https://www.geminiq.com/glossary/large-accelerated-filer
A large accelerated filer is an SEC-reporting company whose public float — the worldwide market value of its common equity held by non-affiliates — was $700 million or more on the last business day of its second fiscal quarter, and which therefore faces the SEC's fastest deadlines for annual and quarterly reports.

The category is defined in Exchange Act Rule 12b-2. It is the top tier of a three-level system that also includes accelerated filers and non-accelerated filers, and a company declares its tier with a check box on the cover of every 10-K and 10-Q.

#### Management's Discussion and Analysis (MD&A)
source: https://www.geminiq.com/glossary/management-discussion-and-analysis
Management's Discussion and Analysis (MD&A) is the narrative section of a 10-K or 10-Q in which a company's management explains, in its own words, what drove the reported financial results, how its liquidity and capital resources stand, and which known trends or uncertainties could make past results a poor guide to the future. Its content is governed by Item 303 of Regulation S-K.

The SEC's stated aim for MD&A is to let investors see the business the way management sees it. Where the financial statements report what happened, MD&A is supposed to explain why.

#### Material Weakness
source: https://www.geminiq.com/glossary/material-weakness
A material weakness is a deficiency, or a combination of deficiencies, in a company's internal control over financial reporting that creates a reasonable possibility that a material misstatement in its annual or interim financial statements will not be prevented or caught in time. The term is defined in Exchange Act Rule 12b-2.

It is the most severe category of control problem. It does not mean the financial statements are wrong, but it means the company's controls cannot be counted on to stop them from being wrong.

#### Non-Accelerated Filer
source: https://www.geminiq.com/glossary/non-accelerated-filer
A non-accelerated filer is any SEC-reporting company that does not meet the conditions to be an accelerated filer or a large accelerated filer, and so receives the longest standard deadlines for its annual and quarterly reports: 90 days for a Form 10-K and 45 days for a Form 10-Q.

Rule 12b-2 under the Exchange Act defines the two accelerated categories in detail; non-accelerated status is simply what is left over. It is one of the check boxes on the cover of every 10-K and 10-Q.

#### Period of Report vs. Filing Date
source: https://www.geminiq.com/glossary/period-of-report
The period of report is the date an SEC filing speaks to — the end of the fiscal year or quarter a 10-K or 10-Q covers, or the date of the event an 8-K reports — while the filing date is the day the document actually reached the SEC. The gap between them can run weeks or months.

Mixing them up means misreading financial data in time: a quarter's results describe the business as of its period end, but the market only learned them on the filing date.

#### Regulation G
source: https://www.geminiq.com/glossary/regulation-g
Regulation G is the SEC rule, codified at 17 CFR 244.100 through 244.102, that governs how public companies present non-GAAP financial measures whenever they publicly disclose them. A company that releases a figure such as adjusted earnings or EBITDA must also present the most directly comparable GAAP measure and a reconciliation between the two, and the non-GAAP presentation must not be misleading.

#### Regulation S-K
source: https://www.geminiq.com/glossary/regulation-s-k
Regulation S-K is the SEC's master set of disclosure rules, codified at 17 CFR Part 229, for the non-financial statement portions of registration statements, periodic reports, proxy statements, tender offer documents, and other filings. Each topic is a numbered Item, and forms such as the 10-K, 10-Q, and S-1 mostly work by instructing companies to "furnish the information required by" a given S-K Item.

#### Regulation S-X
source: https://www.geminiq.com/glossary/regulation-s-x
Regulation S-X is the body of SEC rules, codified at 17 CFR Part 210, that sets the form and content of the financial statements companies must include in registration statements, annual and quarterly reports, and proxy statements. Where GAAP governs how transactions are measured, Regulation S-X governs which financial statements must be filed, for which periods, how current they must be, and what they must show.

Under Rule 1-01, "financial statements" for these purposes include the notes and related schedules, not only the primary statements.

#### Risk Factors (Item 1A)
source: https://www.geminiq.com/glossary/risk-factors
Risk Factors is the section of a 10-K, 10-Q, or registration statement in which a company describes the material factors that make an investment in it, or in the securities being offered, speculative or risky. The content is governed by Item 105 of Regulation S-K, and in the annual report it appears as Item 1A of Form 10-K.

Each risk must sit under its own subcaption that describes it, and the company must explain how that risk would affect the business or the securities rather than just naming it.

#### Rule 10b5-1 Trading Plan
source: https://www.geminiq.com/glossary/rule-10b5-1-plan
A Rule 10b5-1 trading plan is a pre-arranged, written instruction for buying or selling a company's stock, set up before the person has any material nonpublic information, that lets trades carried out under it be defended as not being made "on the basis of" inside information.

The rule, 17 CFR 240.10b5-1, treats a trade as made "on the basis of" material nonpublic information whenever the trader was aware of that information at the time. The plan structure in paragraph (c) is an affirmative defense to that standard, commonly used by executives who sell shares on a set schedule.

#### Schedule 13D
source: https://www.geminiq.com/glossary/schedule-13d
Schedule 13D is the SEC filing required of any investor who acquires beneficial ownership of more than 5% of a public company's outstanding voting shares and has an intent to influence control of the company. Under current SEC rules it must generally be filed within five business days of crossing the threshold.

Because it can signal activist intent, a new Schedule 13D is closely watched and often moves the target company's stock.

#### Schedule 13G
source: https://www.geminiq.com/glossary/schedule-13g
Schedule 13G is the abbreviated beneficial ownership disclosure available to an investor who crosses 5% ownership of a public company's outstanding voting shares but holds the position passively, without intent to influence or control the company. It requires less disclosure than a Schedule 13D.

It is the more common filing among index funds, mutual funds, and other institutional holders that accumulate large stakes purely as investments.

#### Schedule TO
source: https://www.geminiq.com/glossary/schedule-to
Schedule TO is the disclosure document filed with the SEC by anyone making a tender offer for a public company's equity securities, a public offer to buy shares directly from holders, usually at a fixed price and within a set window. It is filed under Section 14(d)(1) of the Securities Exchange Act of 1934 for an offer by an outside party, and under Section 13(e)(1) for an offer by the company itself or its affiliate to repurchase its own shares.

On EDGAR the two variants appear separately, as SC TO-T for a third-party offer and SC TO-I for an issuer offer.

#### Exhibits (Item 601)
source: https://www.geminiq.com/glossary/sec-filing-exhibits
Exhibits are the supporting documents attached to an SEC registration statement or periodic report, such as a company's charter, material contracts, list of subsidiaries, officer certifications, and XBRL data files. Item 601 of Regulation S-K sets out which exhibits each form requires and assigns every exhibit type a standard number, so Exhibit 21 is always the subsidiary list and Exhibit 31 is always the officer certification, whatever the company.

#### Section 16 Insider
source: https://www.geminiq.com/glossary/section-16
A Section 16 insider, often called a Section 16 officer, is a director or officer of a company with a class of equity registered under Section 12 of the Securities Exchange Act of 1934, or a beneficial owner of more than 10% of such a class, who must publicly report holdings and trades in the company's equity and is subject to the short-swing profit rules of Section 16(b).

Section 16(a) is the reporting obligation, carried out on Forms 3, 4, and 5. Section 16(b) is the profit-recovery provision aimed at insiders who buy and sell, or sell and buy, within a short window.

#### SIC Code
source: https://www.geminiq.com/glossary/sic-code
A Standard Industrial Classification (SIC) code is the numeric industry code, up to four digits long, that the SEC attaches to each company in EDGAR to describe its type of business — for example, 7372 for prepackaged software, 3674 for semiconductors, or 2834 for pharmaceutical preparations.

The code appears in the company information EDGAR publishes alongside every filing, and the SEC maintains the official list of codes and industry titles it uses on sec.gov.

#### Smaller Reporting Company (SRC)
source: https://www.geminiq.com/glossary/smaller-reporting-company
A smaller reporting company (SRC) is an issuer with a public float below $250 million, or with annual revenues below $100 million and either no public float or a float below $700 million, that may use the SEC's scaled-down disclosure requirements in its registration statements and periodic reports.

The definition appears in both Exchange Act Rule 12b-2 and Item 10(f) of Regulation S-K. Investment companies, asset-backed issuers, and majority-owned subsidiaries of a parent that is not itself an SRC are excluded.

#### SOX 302 and 906 Certifications
source: https://www.geminiq.com/glossary/sox-certifications
SOX 302 and 906 certifications are the personal statements that a public company's principal executive officer and principal financial officer sign and attach to each 10-K and 10-Q, vouching for the accuracy of the report and the company's controls. The SEC implements the Section 302 certification through Exchange Act Rule 13a-14(a), filed as Exhibit 31; the Section 906 certification is required by 18 U.S.C. 1350 and Rule 13a-14(b), and is furnished as Exhibit 32.

#### US-GAAP Taxonomy
source: https://www.geminiq.com/glossary/us-gaap-taxonomy
The US-GAAP taxonomy is the standardized XBRL dictionary of U.S. Generally Accepted Accounting Principles reporting concepts that public companies use to tag the financial statements in their SEC filings. It defines thousands of elements — revenue, cost of goods sold, net income, total assets, stockholders' equity — each with a precise definition, data type, and reference to the underlying accounting standard.

It is the base taxonomy anchoring the XBRL data in nearly every 10-K and 10-Q, developed by the FASB and approved each year by the SEC.

#### XBRL Taxonomy
source: https://www.geminiq.com/glossary/xbrl-taxonomy
An XBRL taxonomy is the standardized dictionary of reporting concepts that XBRL tags refer to. It defines each reportable element — "Revenues," "Net Income (Loss)," "Total Assets" — along with its precise meaning, data type, valid relationships, labels, and references to accounting standards. Tagging a number in a filing means linking it to a specific taxonomy element.

The most widely used taxonomy for U.S. public-company financial statements is the U.S. GAAP Financial Reporting Taxonomy, maintained by the FASB and approved annually by the SEC.

#### XBRL
source: https://www.geminiq.com/glossary/xbrl
XBRL (eXtensible Business Reporting Language) is an open, XML-based standard for tagging financial data so that software can read and process it. Instead of reporting "Net income: $96,995 million" only as text on a page, XBRL attaches a machine-readable tag identifying what the value represents, the period it covers, the entity, the currency, and the precision.

The SEC requires public companies to submit the financial statements in their 10-K and 10-Q filings in XBRL format, which is what makes large-scale fundamental analysis from SEC filings possible.


---

## Section 5: Why Direct SEC Data Matters
source: https://www.geminiq.com/blog/third-party-financial-data-problems

### Third-Party Financial Data Problems: What Gets Lost
Most financial platforms don't pull their data from the SEC. They license it from a middleman that has already decided which numbers matter — and which to throw away. Here's what gets lost in translation, with documented examples.

If you use any of the popular financial research platforms available today, there's a good chance you're not looking at SEC data. You're likely looking at data licensed from a third-party aggregator that has already ingested the raw SEC filing and transformed it into a standardized template.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=third-party-financial-data-problems)**

These aggregators ingest raw SEC filings and normalize them into templates designed for cross-company comparability. The intent is practical: make it easy to compare Apple's income statement to Microsoft's, or screen 10,000 stocks on the same set of metrics.

But standardization has a cost. Every time a data vendor normalizes a filing, it makes decisions about how to translate the company's own reporting into a generic template. Non-standard line items get reclassified. Company-specific labels get replaced with uniform ones. Distinct financial instruments get merged into generic buckets. The result is data that's clean, consistent, and comparable — but no longer the data the company actually reported.

For investors who build models, audit assumptions, or run quantitative strategies on SEC filing data, this gap matters more than most people realize.

> **A note on how GeminIQ handles "cleaning":** When we describe processing raw filings, we mean correcting known XBRL tagging errors (misapplied tags, duplicate entries from amended filings), not reclassifying what a company reported. We do not change Apple's "Vendor Non-Trade Receivables" into "Other Current Assets." The line items, labels, and values stay exactly as filed. This is the core difference.

---

## The Data Pipeline Most Investors Don't Know About

Here's how financial data typically reaches you:

## Step 1: The company files with the SEC

A company files its 10-K or 10-Q with the SEC via EDGAR. The filing includes XBRL-tagged financial data — every number carries a standardized identifier assigned by the SEC.

## Step 2: An aggregator ingests and normalizes the filing

A third-party data aggregator ingests the filing and maps it into their proprietary template schema. Line items that don't fit the template get consolidated, reclassified, or dropped.

## Step 3: Platforms license the processed data

Retail research platforms license this processed data from the aggregator and display it through their own interfaces.

By the time the number appears on your screen, it has been through two layers of processing — the aggregator's normalization and the platform's formatting. Neither layer is visible to you. There's no audit trail. There's no way to verify whether the number you see matches what's actually in the filing.

This isn't a theoretical problem. It's a practical one that affects how you model businesses, calculate metrics, and make investment decisions. We've documented specific examples.

---

## Documented Discrepancies: What the Data Actually Shows

Before exploring the broader categories of data loss, here are four documented examples comparing what the SEC filing says to what one widely-used retail aggregator displays — two from [Apple's](/stocks/AAPL) FY2025 10-K (filed October 31, 2025) and two from other large filers:

**1. Repurchase of Common Stock — Cash Flow Statement (10-K page 33)**
- As filed: Repurchases of common stock — **$90,711M**
- Platform display: Repurchase of Common Stock — **$96,671M**
- What happened: The platform combined "Repurchases of common stock" ($90,711M) with "Payments for taxes related to net share settlement of equity awards" ($5,960M) and labeled the merged result under a single line item. $90,711 + $5,960 = $96,671. These are two distinct cash outflows with separate XBRL tags and different economic meanings — one is a buyback program, one is a payroll tax obligation on equity compensation.

**2. Commercial Paper (Net) — Home Depot FY2025 10-K, Cash Flow Statement**
- As filed: net proceeds from/(repayments of) commercial paper — **+$4,148M**, reported as a single net line
- Platform display: dissolved into separate gross "debt issued" and "debt repaid" buckets, with no single net commercial-paper line
- What happened: A single net commercial-paper figure was recast into gross issuance and repayment buckets. Because the filing reports a *net* number, this reconstruction can invert the economic direction entirely in a year when the company is a net repayer — turning a paydown into apparent new borrowing.

**3. Other Current Liabilities — Carvana FY2025 10-K, Balance Sheet**
- As filed: Other current liabilities — **$134M**
- Platform display: Other Current Liabilities — **$296M**
- What happened: Under the identical label, the platform's bucket absorbs lease and other obligations the filing reports elsewhere — roughly 2.2× the as-filed figure. The same pattern hits Carvana's other non-current liabilities: **$15M** as filed versus **$2,243M** displayed, under the same name.

**4. Other Non-Current Liabilities — Balance Sheet (10-K page 40)**
- As filed: Other non-current liabilities — **$41,549M**
- Platform display: Other Non-Current Liabilities — **$29,946M**
- What happened: The platform subtracted Capital Leases ($11,603M) from the line and still labeled it identically to the 10-K. $29,946 + $11,603 = $41,549. An $11.6 billion gap under the exact same name.

These aren't theoretical edge cases. They are documented discrepancies in widely held companies' most recent annual filings — where a line item carrying the exact same label as the SEC source shows a materially different number.

### Verify It Yourself in 2 Minutes

1. Open Apple's FY2025 10-K at investor.apple.com in the SEC Filings section and select the most recent Annual Report.
2. Navigate to page 40, the Consolidated Balance Sheet.
3. Find "Other non-current liabilities". The as-filed value is **$41,549M**.
4. Open your current financial data platform and find the same line for Apple FY2025.
5. Compare the two numbers.

If they match, great. If they don't, you've just found a normalization discrepancy. This is exactly what XBRL traceability is designed to prevent.

---

## What Else Gets Lost in Normalization

### 1. Company-Specific Line Items Disappear

Every company reports its financials using labels that reflect its actual business. Apple's balance sheet includes a line item called **"Vendor Non-Trade Receivables"** — a $33.2 billion asset representing payments owed back to Apple by its outsourced manufacturing partners who buy components on Apple's behalf. This line item carries the XBRL tag `NontradereceivablesCurrent` and is specific to Apple's component consignment model.

On a normalized template, this line item typically gets folded into a generic bucket like "Other Receivables" or "Other Current Assets." The $33.2 billion doesn't disappear — but its identity does. An analyst pulling "Accounts Receivable" from a third-party API would see $39.8 billion (the trade receivables), missing the $33.2 billion vendor receivable entirely. That's a 46% undercount of Apple's total receivables picture that directly impacts working capital analysis, [cash conversion cycle](/blog/cash-conversion-cycle-formula-explained) calculations, and any model that depends on understanding Apple's actual balance sheet structure.

On [GeminIQ](/), Vendor Non-Trade Receivables appears as its own line item with its XBRL tag — exactly as Apple filed it.

### 2. Distinct Debt Structures Get Merged

Apple's balance sheet separates its debt into three distinct instruments: **Commercial Paper**, **current Term Debt**, and **non-current Term Debt**. Each carries its own XBRL tag, because each represents a fundamentally different type of obligation.

Commercial paper is unsecured short-term promissory notes rolling continuously with maturities under nine months. Current term debt is the portion of Apple's fixed-rate notes maturing within 12 months. Non-current term debt is long-term fixed-rate bonds stretching out to 2062.

On a normalized template, these three instruments often get merged into two generic buckets — "Short-Term Debt" and "Long-Term Debt" — or sometimes just one "Total Debt" figure. An analyst modeling Apple's refinancing risk needs to know that commercial paper rolls continuously at market rates (and can be pulled if credit markets seize), while term debt is a fixed obligation coming due on a specific schedule.

GeminIQ preserves all three as separate line items with their individual XBRL tags — because that's how Apple reported them.

### 3. Cash Flow Granularity Gets Smoothed

Apple's cash flow statement includes "Vendor non-trade receivables" as a separate working capital adjustment. On normalized templates, this gets rolled into a generic "Changes in working capital" or "Other operating activities" bucket. The working capital adjustment tells you whether Apple's manufacturing partners are paying down component consignment obligations or building them up — a signal about supply chain dynamics that disappears in normalization.

### 4. Balance Sheet Reclassifications Create Silent Errors

As the documented examples above show, normalization doesn't just merge line items — it can actively reclassify them while keeping the same label. When a platform subtracts capital lease obligations from "Other Non-Current Liabilities" but keeps the label unchanged, an analyst comparing that platform's number to the 10-K will find an $11.6 billion gap with no explanation. This is the most dangerous type of normalization error because it looks correct at a glance.

These are not obscure edge cases. They're standard features of the most widely followed stock in the world. If normalization loses granularity on Apple, imagine what it does to a mid-cap industrial with a balance sheet structure that doesn't fit the standard template at all.

---

## Why "Close Enough" Isn't Good Enough

The standard defense of normalized data is that it's "close enough" — the numbers are approximately right, and the standardization makes comparison easier. For screening or high-level scanning, that's often true.

But four common analytical workflows break down when the data is only close enough:

**Metric calculation.** [ROIC](/blog/roic-return-on-invested-capital-explained) requires [Invested Capital](/metrics/calculated-values/invested-capital), which depends on how you define Operating Assets and Operating Liabilities. If the underlying balance sheet has been normalized — with Apple's $33.2 billion vendor non-trade receivables reclassified into a generic bucket, and its three debt instruments merged into two — the Invested Capital calculation inherits those reclassifications. Every financial ratio downstream carries the same inherited imprecision.

**Cross-checking and auditing.** If you calculate a metric directly from the 10-K and get a different number from the platform, which is right? Without XBRL tag-level traceability, there's no way to trace the platform's number back to its source. As documented above, a platform can show "Other Non-Current Liabilities" at $29,946M while the 10-K shows $41,549M — an $11.6 billion gap under the exact same label. Without auditability, you'd never catch it.

**Quantitative strategies.** Systematic investors who backtest strategies on historical financial data need the data to reflect what was actually filed. If an aggregator retroactively reclassifies a line item when updating its template — which happens — historical data changes, backtests break, and signals shift without any underlying economic change.

**Quarter-over-quarter analysis.** 10-Q filings are where inflection points appear first. Quarterly shifts in margins, working capital, or debt structure emerge from precise quarterly data. If the data has been smoothed, merged, or rounded by an aggregator, the inflection point gets dulled — and you see it later than investors working directly from the source.

---

## The XBRL Layer Most Platforms Ignore

Here's the part that surprises most people: the SEC already solved this problem.

Since 2009, every public company has been required to tag its financial data with **XBRL** (eXtensible Business Reporting Language) identifiers when filing with EDGAR. Each number in the filing carries a specific tag — like `Revenues` for revenue, `OperatingIncomeLoss` for operating income, or `NontradereceivablesCurrent` for Apple's vendor receivables — that uniquely identifies what the number represents.

These tags are the SEC's own data standard. They're machine-readable. They map directly to the company's as-filed reporting structure. And they create a verifiable link between any data point and the exact line item in the original filing.

Yet most financial platforms discard this layer entirely.

Third-party aggregators each maintain their own proprietary taxonomy. When they normalize a filing, they map the SEC's XBRL tags into their proprietary schema — and the original tag identifiers don't survive the translation. By the time the data reaches a retail platform, the XBRL provenance is gone. You see a number. You don't see where it came from or which specific filing data point produced it.

This is the gap that [GeminIQ](/) was built to fill.

---

## How GeminIQ Does It Differently

GeminIQ doesn't license data from any third-party aggregator. We build our own ingestion pipelines directly from SEC EDGAR and preserve the as-filed reporting structure — with every data point's [XBRL tag intact](/features#financial-statements).

**Every number is the filing.** Apple's revenue on GeminIQ is $416,161,000,000 because that's the value tagged `Revenues` in Apple's FY2025 10-K. It wasn't mapped, translated, or reclassified. It's the number the company reported, carrying the tag the SEC assigned, linked to the filing it came from.

**Every line item is preserved as-filed.** Apple's Vendor Non-Trade Receivables appears on GeminIQ as its own line item — not collapsed into a generic bucket. Apple's three distinct debt instruments (Commercial Paper, current Term Debt, non-current Term Debt) remain separate with their individual tags. The filing structure is the data structure.

**Every metric is computed from raw inputs.** GeminIQ calculates [90+ financial KPIs](/features#calculated-metrics) — ROIC, ROE, margins, growth rates, [Altman Z-Score](/blog/altman-z-score-financial-distress), and more — directly from the XBRL-tagged source data. When GeminIQ shows Apple's FY2025 [gross margin](/metrics/margin-metrics/gross-profit-margin) of 46.9%, you can trace it: Gross Profit ($195,201,000,000, tag `GrossProfit`) divided by Total Revenue ($416,161,000,000, tag `Revenues`). Both inputs link to the filing. The math is transparent.

**17+ years of quarterly history, structured and ready.** Not just annual snapshots — every quarterly 10-Q and annual 10-K, going back more than 17 years for every SEC filer. You can chart Apple's gross margin trajectory from 2009 to today, quarter by quarter, and spot the exact moment trends began shifting.

**Verification takes seconds, not hours.** Every data point on GeminIQ is labeled using the XBRL tag. Copy the tag and search the original filing on EDGAR. The number matches — because it was never transformed.

**[See what as-filed data actually looks like →](/stocks/AAPL)**

---

## What This Enables That Normalized Data Can't

When every number is traceable to its source, several analytical capabilities become possible that simply don't work on normalized data:

**Auditable screening.** GeminIQ's [Advanced Screener](/features#screener) filters across 100+ metrics with up to 10 stackable conditions. When you find a company that passes your screen, every number behind that result traces to a specific XBRL tag in the source filing. Screen for companies with expanding gross margins, accelerating revenue, and declining debt ratios — and know that every input in the screen matches the 10-K.

**Interactive financial visualizations.** GeminIQ's [Interactive Visualizations](/features#visualizations) let you chart any financial line item or calculated metric across every quarter going back 17+ years. Line, bar, or area charts. Log or linear scaling. When Apple's gross margin ticks up in the most recent quarter, the visualization shows this in context against the entire margin history — making it immediately clear whether it's noise or an inflection.

**Post-earnings behavioral analysis.** GeminIQ's proprietary [Earnings Market Reaction Heatmap](/features#price-variance) tracks how a stock performed 1 through 12 months after every filing. For Apple, 88% of annual filings over the past 16 years were followed by positive 12-month returns, with a median gain of approximately 30%. Layering this behavioral data on top of auditable financial data creates an analytical edge that normalized platforms can't replicate.

**Insider and institutional context.** GeminIQ's [insider transaction timeline](/features#insider-transactions) and [institutional ownership trends](/features#institutional-ownership) sit alongside the financial data on every company page. Track insider buying and selling patterns alongside the financial data to spot when insiders are acting on information that hasn't yet shown up in the numbers.

**Custom analytical frameworks.** GeminIQ's [Custom Tables](/features#custom-tables) let you build reusable data templates that pull exactly the line items you care about — including company-specific items that normalized platforms strip out. Build a template for Apple that includes Vendor Non-Trade Receivables alongside trade receivables, or one that separates Commercial Paper from Term Debt. Save it. Easily apply it to any company within the GeminIQ database.

---

## The Side-by-Side Comparison

Here's what the same Apple data looks like on a normalized platform vs. GeminIQ (FY2025 10-K):

| What You're Looking For | Normalized Platform | GeminIQ |
|---|---|---|
| Apple's total receivables | $39.8B ("Accounts Receivable") | $39.8B trade + $33.2B vendor non-trade = $73.0B, both with XBRL tags |
| Debt breakdown | "Short-term: ~$20.3B, Long-term: $78.3B" | CP: $8.0B, Current term: $12.4B, NC term: $78.3B — three instruments, three tags |
| Other non-current liabilities | $29.9B (capital leases removed, same label) | $41.5B — as filed, no adjustments |
| Cash flow: stock repurchases | $96.7B (buybacks + equity tax payments merged) | $90.7B buybacks + $5.96B tax payments — two separate line items |
| Quarterly gross margin trend | Annual or trailing figures; quarterly may lag | Every quarter for 17+ years, charted with visualization tools |
| Source verification | "Source: [data provider]" — no further traceability | Click any number → see XBRL tag → verify in original filing on EDGAR |
| Metric calculation transparency | Black box — no visibility into inputs | Every metric shows its formula and source XBRL inputs |
| Company-specific line items | Reclassified into generic buckets | Preserved as-filed with original labels |
| Insider transaction context | Not typically integrated | Timeline of every Form 4 transaction alongside financial data |
| Post-filing price reactions | Not available | Heatmap showing 1 to 12-month returns after every filing |
| Institutional ownership trends | Separate platform or data source | Integrated with financial data on every company page |

---

## Who This Matters For

If you're scanning 500 stocks looking for ideas, normalized data from a third-party API is probably fine. The approximation is close enough, and the standardization makes comparison fast.

But if you're doing any of the following, the data source matters:

- **Building financial models** where the inputs need to match the 10-K
- **Running quantitative strategies** that depend on historical data consistency
- **Auditing a thesis** before committing capital
- **Analyzing company-specific balance sheet structures** that don't fit a standard template
- **Tracking quarter-over-quarter inflections** in margins, cash flow, or working capital
- **Layering behavioral signals** (insider activity, institutional flows, post-filing price reactions) on top of fundamentals
- **Teaching yourself fundamental analysis** and wanting to learn from the actual filing, not a vendor's interpretation of it

For these workflows, normalized data isn't just imprecise — it's an invisible source of error that compounds with every calculation you layer on top.

---

## Frequently Asked Questions

### What is XBRL and why does it matter for financial data accuracy?
XBRL (eXtensible Business Reporting Language) is the tagging system the SEC requires companies to use when filing. Every number in a 10-K or 10-Q carries a specific XBRL identifier that links it back to its exact meaning in the filing. When a platform preserves these tags, you can verify any data point against the original document. When a platform discards them in favor of a proprietary taxonomy, that traceability is permanently lost.

### Why do so many financial platforms show different numbers for the same company?
Most retail research platforms don't source data directly from the SEC. They license processed data from third-party aggregators who have already normalized the filings into a standardized template. Because aggregators make their own methodological choices — how to classify lease obligations, whether to combine certain cash flow lines, how to handle company-specific instruments — two platforms using the same underlying aggregator can display the same reclassification simultaneously, and both can differ from the actual filing.

### Why does data normalization cause discrepancies rather than fix them?
Normalization is designed for comparability across thousands of companies, not fidelity to any individual filing. When an aggregator maps Apple's three distinct debt instruments into two generic categories, or combines a buyback program with a payroll tax payment under a single label, the intent is to make Apple look like every other company in the template. The result can be a number that's internally consistent but economically misleading — like labeling a net repayment as "debt issued," or showing an $11.6 billion gap under the exact same line item name.

### How far back does GeminIQ's historical data go?
GeminIQ provides 17+ years of quarterly financial data, going back to approximately 2009 when XBRL tagging was first required for large accelerated filers under SEC mandate. This covers the full market cycles most long-term investors need for meaningful analysis.

### What's the difference between GeminIQ's 90+ calculated metrics and 100+ screener metrics?
GeminIQ automatically calculates 90+ financial KPIs — ratios, growth rates, efficiency metrics, and valuation measures like ROIC, Altman Z-Score, and gross margin — directly from XBRL-sourced data. The 100+ screener metrics include both these calculated KPIs and the underlying raw financial line items, giving you the full range of inputs to screen against.

### How quickly is new filing data available on GeminIQ?
New filings are processed overnight (T+1), meaning clean, structurally accurate datasets are available by the time the market opens the day after a filing goes live on EDGAR.

---

## The Bottom Line

Third-party financial data platforms deliver genuine value through their interfaces — broad coverage, fast search, and easy comparisons are real benefits. But normalization is a tradeoff, not a free lunch. Every time a data aggregator translates a filing into a template, it makes choices about what to keep, what to consolidate, and what to reclassify. Those choices are invisible to you. And every metric, screen, and model you build on that data inherits them — with no way to verify whether the foundation matches the filing.

As the four documented examples above show, this isn't abstract. It's an $11.6 billion gap under the same label. A net commercial-paper line recast as gross issuance. A buyback merged with a tax payment. On some of the most heavily analyzed companies on the market.

GeminIQ takes a different approach: go directly to the source, preserve the source, and let the analyst decide what matters. Every number traceable. Every metric transparent. Every filing structured with its XBRL tags intact — across 17+ years of history, updated automatically, with the insider, institutional, and behavioral data that turns raw filings into investment insight.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=third-party-financial-data-problems)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Section 6: Hidden Information in SEC Filings
source: https://www.geminiq.com/blog/what-investors-miss-in-sec-filings

### Hidden Information in SEC Filings: What Most Investors Overlook (2026)
The most valuable information in a 10-K isn't in the headline numbers. It's in the balance sheet shifts, cash flow adjustments, insider patterns, and post-filing price reactions that most investors scroll past. Here's how to find it.

When [Apple](/stocks/AAPL) reports $416.2 billion in revenue and $112.0 billion in net income, every financial website on the internet publishes those numbers within minutes. They're not hidden. They're not hard to find. And they're not where the analytical edge lives.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-investors-miss-in-sec-filings)**

The edge lives in the details that the headline numbers obscure — the balance sheet changes that signal where cash is actually going, the cash flow adjustments that reveal how much of "earnings" is actually cash, the insider transaction patterns that span a decade, and the behavioral data that shows how the market historically reacts to each filing.

This information is all public. It's all in the SEC filings. But it takes effort to extract — which is why most investors never see it.

In this guide, we'll walk through five types of hidden information using [Apple's](/stocks/AAPL) actual SEC data, and show how [GeminIQ](/) surfaces them automatically.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-investors-miss-in-sec-filings)**

---

## 1. Balance Sheet Changes That Tell the Real Story

The income statement tells you how a company performed during a period. The balance sheet tells you what changed underneath — and it often reveals more.

Most investors check revenue, earnings, and margins. Far fewer compare the balance sheet line by line against the prior year. But the shifts between FY2024 and FY2025 on [Apple's](/stocks/AAPL) balance sheet tell a story that the income statement alone can't:

**Current Marketable Securities dropped 47%** — from $35.2 billion to $18.8 billion. That's $16.4 billion in liquid securities that Apple either sold, let mature, or moved. A headline reader sees "cash went up." A balance sheet reader asks: why did Apple shift its investment portfolio so dramatically?

**Inventories fell 22%** — from $7.3 billion to $5.7 billion. For a hardware company, declining inventory heading into the holiday quarter can mean two things: either supply chain efficiency improved, or the company is drawing down stock ahead of a product transition. The 10-K's Item 7 (MD&A) tells you Apple announced iPhone 17 and Apple Watch Series 11 in the fourth quarter — context that explains the inventory drawdown as a transition effect.

**Accounts Receivable jumped 19%** — from $33.4 billion to $39.8 billion, while revenue grew only 6.4%. When receivables grow faster than revenue, it can mean the company is extending more credit, customers are paying slower, or the revenue mix shifted toward higher-receivable channels. This is the kind of divergence that signals potential cash collection risk — and it only shows up if you read the balance sheet.

**Other Current Liabilities dropped 15%** — from $78.3 billion to $66.4 billion. That's an $11.9 billion decrease. What drove it? The 10-K notes reveal that Income Taxes Payable fell from $26.6 billion to $13.0 billion — a $13.6 billion drop largely driven by the settlement of the European Commission State Aid obligation that Apple paid out of escrow in FY2025. Without reading the balance sheet and the notes together, you'd miss this entirely.

**Shareholders' equity grew 30%** — from $57.0 billion to $73.7 billion. Apple's accumulated deficit shrank from $(19.2B) to $(14.3B). For a company that has been running an accumulated deficit for years due to massive buybacks exceeding retained earnings, this reversal is notable — net income of $112.0 billion finally exceeded the combined drain from buybacks and dividends, rebuilding the equity base. And by Q1 FY2026, the accumulated deficit has already shrunk further to just $(2.2B), putting Apple on track to eliminate it entirely.

Every one of these data points is in the 10-K. None of them are in the earnings headline.

> **GeminIQ Tip:** GeminIQ extracts every balance sheet line item from every quarterly and annual filing, [tagged with its XBRL identifier](/features#financial-statements), across 17+ years of history. You can build a [Custom Table](/features#custom-tables) that tracks specific balance sheet items over time and spot these shifts visually — without manually comparing two PDFs side by side.

---

## 2. Cash Flow Adjustments That Reveal Earnings Quality

Net income is an accounting concept. Cash flow is what actually happened. The gap between them — visible only in the cash flow statement — is one of the most important signals in fundamental analysis.

Apple reported $112.0 billion in net income in FY2025. It generated $111.5 billion in operating cash flow. On the surface, they're nearly identical — which suggests high [earnings quality](/blog/earnings-quality-accruals-analysis). But the adjustments that bridge the gap are worth examining:

**Share-based compensation: $12.9 billion.** This is a real economic cost (it dilutes existing shareholders), but it's a non-cash expense that gets added back in the cash flow statement. [Apple's](/stocks/AAPL) SBC has grown from $10.8 billion in FY2023 to $12.9 billion in FY2025 — a 19% increase in two years. For earnings quality analysis, the question is: how much of [Apple's](/stocks/AAPL) "earnings" represents cash vs. stock-based promises to employees?

**Depreciation and amortization: $11.7 billion.** Another non-cash add-back. Compare this to capital expenditures of $12.7 billion: Apple is spending slightly more on new assets than it's depreciating on existing ones, which means the asset base is growing — consistent with the company's expansion into data centers and manufacturing infrastructure.

**Other current and non-current liabilities: $(11.1 billion).** This is cash that went out the door to reduce liabilities — primarily the State Aid tax payment mentioned earlier. This line item turned operating cash flow from what would have been $122.6 billion into the reported $111.5 billion. A one-time drag.

**Other current and non-current assets: $(9.2 billion).** Cash absorbed by growing non-current assets — likely related to long-term supply agreements and prepayments. This is Apple locking in future component supply, visible only in the cash flow adjustments.

The point: Apple's earnings quality is genuinely high, but the cash flow statement reveals over $24 billion in non-cash adjustments (SBC + D&A) and nearly $20 billion in working capital movements that tell you where the cash actually went. These details are invisible if you only look at net income.

> **GeminIQ Tip:** GeminIQ's [Calculated Metrics](/features#calculated-metrics) include free cash flow, free cash flow per share, operating cash flow margin, and payout ratio — all computed directly from the XBRL-tagged cash flow statement. For [Apple](/stocks/AAPL) FY2025: free cash flow of $98.8 billion, FCF per share of $6.61, and a payout ratio of 13.8%. But the real capital return story is bigger: [Apple](/stocks/AAPL) returned $106.1 billion to shareholders through buybacks ($90.7B) and dividends ($15.4B) — approximately 95% of net income — while still generating enough cash to fund operations, invest in infrastructure, and reduce debt.

---

## 3. The Insider Transaction Pattern Nobody Talks About

SEC Form 4 filings track every purchase and sale of company stock by executives, directors, and major shareholders. Most investors check whether insiders are "buying or selling." But the real insight comes from looking at the pattern across years — not individual transactions.

GeminIQ's [insider transaction data](/features#insider-transactions) for [Apple](/stocks/AAPL) spans from 2008 to present and reveals a striking pattern: across 435 total transactions, there have been **only 4 open-market purchases** — ever.

All four purchases were by board members, not executives: Robert Iger bought 2,670 shares in November 2011 at $374.91 and 1,780 shares in November 2012 at $563.63. Susan Wagner bought 3,800 shares across two transactions in July 2015 at approximately $123 per share.

That's it. No [Apple](/stocks/AAPL) executive — not Tim Cook, not any SVP, not any CFO — has ever bought [Apple](/stocks/AAPL) stock on the open market in the entire dataset. The remaining 431 transactions are all sales, overwhelmingly driven by RSU vesting and the tax withholding that follows.

What does this tell you? Two things. First, Apple compensates its executives so heavily in equity that they never need to buy — the RSU pipeline is their primary acquisition mechanism. Second, a pattern of zero executive purchases means that if an executive ever *did* buy on the open market, it would be an extremely strong signal — precisely because it has never happened before. The absence of signal is itself informative.

<center><sup>GeminIQ Insider Transactions (SEC Form 4) for Apple, showing the monthly purchase and sale pattern and the transaction table sourced directly from Form 4 filings.</sup></center>

---

## 4. Post-Filing Price Reactions Over 16 Years

Here's a question most financial platforms can't answer: after Apple files its annual 10-K, what does the stock typically do over the next 12 months?

GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) tracks the stock's performance 1 to 12 months after every filing. For Apple's 16 annual 10-K filings from 2009 to 2024, the data reveals a clear pattern:

**14 out of 16 filings (88%) were followed by positive 12-month returns.** The median 12-month post-filing return is approximately 30%.

**The worst 12-month return was -17.0%** — following the FY2012 10-K (filed October 2012), which preceded Apple's first major revenue deceleration after the iPhone 5 cycle.

**Post-filing dips have historically been buying opportunities.** The FY2018 10-K saw Apple drop 11.1% in the first month and 21.5% by month three (the late-2018 selloff). But by month 12, the stock was up 14.4%. The FY2016 10-K showed a 4.3% drop in month one, then returned 33.7% over 12 months. The FY2015 10-K dropped 18.2% by month three, but the 12-month return was only -3.5% — nearly a full recovery.

**The strongest 12-month returns followed years of negative sentiment.** FY2019's 10-K (filed October 2019, amid trade war fears) was followed by an 82.3% return over 12 months. FY2009's 10-K was followed by a 48.1% gain.

This pattern — short-term post-filing weakness followed by 12-month recovery — is the kind of behavioral data that only becomes visible when you track every filing systematically over a decade and a half. No single 10-K tells you this. The aggregate filing history does.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Apple, showing cumulative post-filing returns at the one-, two-, and three-month marks across 16 years of filings.</sup></center>

**[Explore Apple's full Earnings Market Reaction Heatmap on GeminIQ →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-investors-miss-in-sec-filings)**

---

## 5. Institutional Ownership Trends That Confirm (or Contradict) Your Thesis

Individual investor sentiment is noisy. Institutional ownership — tracked through [13F filings](/blog/how-to-read-13f-filing) — shows what professional capital is actually doing with its money, quarter by quarter.

GeminIQ's [Institutional Ownership](/features#institutional-ownership) data for Apple reveals a decade-long accumulation trend. From 57.4% of outstanding shares held by institutions in FY2014, ownership has fluctuated in a band between roughly 50% and 60%. As of September 2025, institutional investors held **58.5%** of Apple's shares — and the most recent data point (December 2025) shows that figure rising to **61.1%**, the highest level in the dataset.

But the noise within the trend is where the insight lives.

**Q4 2022: institutional ownership dropped to 49.4%** — the lowest point since 2015. This coincided with the tech selloff and rising interest rates. Within 12 months, institutional ownership rebounded to 53.6%. Apple's stock rose 12.9% in the 12 months following the FY2022 10-K filing, then 29.6% in the 12 months after the FY2023 10-K — a clear recovery trajectory.

**The share count is shrinking while institutional ownership percentage holds steady.** Apple's split-adjusted outstanding shares have declined from roughly 23 billion in FY2014 to 14.8 billion in FY2025 — a 36% reduction from buybacks. Throughout that period, institutional ownership percentage has remained in a band between roughly 50% and 60%, even as the total float contracted dramatically. This means institutions have been trimming their absolute share counts roughly in proportion to buybacks, but *not* exiting — effectively maintaining their proportional stake while Apple shrinks the denominator.

This is the kind of structural insight that emerges from tracking ownership alongside buyback activity over time. It doesn't appear in any single quarterly filing, but the longitudinal pattern tells a clear story: professional capital isn't selling Apple — Apple is buying itself.

<center><sup>GeminIQ 13F Institutional Holdings tracker (SEC Form 13F) for Apple, showing the institutional ownership percentage trend aggregated from quarterly Form 13F filings.</sup></center>

---

## The Information Is Public. The Analysis Shouldn't Be Manual.

Every data point in this article came from public SEC filings. The balance sheet changes, the cash flow adjustments, the insider transactions, the post-filing price reactions, the institutional ownership trends — all of it is freely available on EDGAR.

The problem isn't access. It's extraction. Reading two 100-page PDFs side by side to spot balance sheet shifts. Downloading 428 Form 4 filings to count how many were purchases vs. sales. Manually tracking stock prices after each of 16 annual filings to build a reaction heatmap. Cross-referencing 13F data with outstanding share counts to understand institutional concentration.

That's what [GeminIQ](/) automates.

Every financial statement is extracted directly from EDGAR with its XBRL tags intact. Every calculated metric traces to its source inputs. The insider timeline, institutional ownership trends, and Earnings Market Reaction Heatmap are built from primary sources and updated automatically. The [Stock Screener](/features#screener) lets you filter across 100+ metrics with up to 10 stackable conditions — all running on data you can verify in the original filing.

The hidden information in SEC filings isn't hidden because it's secret. It's hidden because extracting it manually takes hours. GeminIQ makes it visible in seconds.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-investors-miss-in-sec-filings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025) and Q1 FY2026 10-Q (filed January 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193).

---

## Section 7: How to Read a 10-K
source: https://www.geminiq.com/blog/how-to-read-10-k

### How to Read a 10-K Annual Report: A Value Investor's Guide (2026)
Every public company in the U.S. files a 10-K with the SEC every year. It's the single most important document for understanding a business — and most investors never read one. Here's how to change that, using Apple's FY2025 filing as our example.

The 10-K is the annual report that every U.S.-listed company files with the Securities and Exchange Commission. It's not the glossy shareholder letter your broker sends you. It's the real thing — audited financial statements, detailed risk disclosures, management's own analysis of the business, and the raw data that drives every valuation model worth building.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-k)**

Warren Buffett reads hundreds of them a year. If you're serious about value investing, you should be reading them too.

In this guide, we'll walk through how to read a 10-K section by section, using **[Apple's](/stocks/AAPL) fiscal year 2025 filing** (filed October 31, 2025) as our working example. We'll also show you how [GeminIQ](/) automatically extracts, structures, and visualizes the data inside these filings — so you spend less time copying numbers into spreadsheets and more time analyzing them.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-k)**

---

## What Is a 10-K Filing?

A 10-K is a comprehensive annual report filed by every company registered with the SEC. Unlike the 10-Q (quarterly) or 8-K (current events), the 10-K gives you the full picture: three years of audited financial statements, detailed segment breakdowns, risk factors, management's discussion of results, and notes that explain the accounting behind every number.

The key word is **audited**. The financial statements in a 10-K are reviewed and signed off by an independent accounting firm — in Apple's case, Ernst & Young. This is the highest standard of reliability you'll get from any corporate financial data source.

Every 10-K follows the same structure mandated by the SEC, which means once you know how to read one, you can read any of them. Here's the roadmap:

- **Part I** — Business description, risk factors, properties
- **Part II** — Financial data: MD&A, financial statements, and notes
- **Part III** — Governance, compensation (usually in the [proxy statement](/blog/what-is-def-14a))
- **Part IV** — Exhibits and signatures

For value investors, the real meat is in Part I (Item 1 and Item 1A) and Part II (Items 7 and 8). That's where we'll focus.

---

## Step 1: Understand the Business (Item 1)

Before you touch a single number, read Item 1. This is where the company tells you — in plain English — what it does, how it makes money, and how it's structured.

In [Apple's](/stocks/AAPL) FY2025 10-K, Item 1 reveals a few things that matter for valuation. [Apple](/stocks/AAPL) reports revenue across five geographic segments: Americas, Europe, Greater China, Japan, and Rest of Asia Pacific. It breaks product revenue into four hardware categories (iPhone, Mac, iPad, Wearables/Home/Accessories) plus Services.

This is important because Services revenue — which hit **$109.2 billion** in FY2025, up 14% year-over-year — carries a **75.4% [gross margin](/metrics/margin-metrics/gross-profit-margin)** compared to just **36.8%** for Products. As Services becomes a larger share of the mix, it structurally improves the overall margin profile. A value investor who only looks at the top-line revenue number misses this entirely.

Item 1 also tells you that 60% of Apple's sales flow through indirect channels (carriers and resellers), and that a "significant majority" of manufacturing is outsourced to partners in China, India, Japan, South Korea, Taiwan, and Vietnam. That's a supply chain concentration risk that directly intersects with the tariff discussion in FY2025.

> **GeminIQ Tip:** On GeminIQ, every line item from Apple's 10-K is extracted automatically and tagged with its [XBRL identifier](/features#financial-statements) — including the segment and product breakdowns. You don't need to manually pull these numbers from the PDF. They're structured, searchable, and ready to visualize the moment the filing hits EDGAR.

---

## Step 2: Read the Risk Factors (Item 1A)

Most investors skip Item 1A because it reads like a legal disclaimer. That's a mistake.

The risk factors section tells you what *management themselves* believe could materially hurt the business. Read it not for the boilerplate (every company warns about "macroeconomic conditions"), but for the **specific, new, or evolving risks** that weren't in last year's filing.

In Apple's FY2025 10-K, the tariff disclosure is the standout. The filing describes new U.S. tariffs imposed beginning in the second quarter of 2025 on imports from China, India, Japan, South Korea, Taiwan, Vietnam, and the EU — essentially every country in Apple's manufacturing supply chain. The filing notes that the "ultimate impact remains uncertain" and that the U.S. Department of Commerce has initiated an investigation into semiconductor imports, including "downstream products that contain semiconductors" — which describes every Apple product.

This is the kind of risk that directly impacts gross margins. Apple's Products gross margin percentage actually *decreased* in FY2025 despite higher revenue, "primarily due to a different mix of products and tariff costs." You'd find that detail in Item 7 (MD&A), but the risk factor in Item 1A gives you the forward-looking framework for understanding it.

The other risk worth flagging: Apple's licensing relationship with Google. The filing discloses that on September 2, 2025, a U.S. District Court ordered remedies after finding Google violated antitrust laws — and notes that if certain proposed remedies are implemented, they "could materially adversely affect the Company's ability to earn revenue from such licensing arrangements." Google's search licensing fees are widely estimated to represent a significant portion of Apple's Services revenue.

---

## Step 3: Follow the Money in the MD&A (Item 7)

Item 7 — Management's Discussion and Analysis — is where the CEO and CFO explain, in their own words, what happened during the year and why. This section bridges the gap between the narrative in Item 1 and the raw numbers in Item 8.

For [Apple's](/stocks/AAPL) FY2025, the MD&A shows:

- **Total net sales** grew 6% to **$416.2 billion**, driven by iPhone (up 4%), Mac (up 12%), and Services (up 14%)
- **Greater China** was the only segment that declined, falling 4% to $64.4 billion — primarily due to lower iPhone sales
- **Total gross margin** expanded to **46.9%** from 46.2%, driven by the Services mix shift, even as Products margins compressed from tariff costs
- **R&D spending** rose 10% to **$34.6 billion**, representing 8% of revenue — a sign of continued heavy investment
- The company repurchased **$89.3 billion** of its own stock and paid **$15.4 billion** in dividends

The MD&A also reveals that Apple's effective tax rate dropped from 24.1% in FY2024 to 15.6% in FY2025. Why? Because FY2024 included a one-time $10.2 billion charge from the European Commission's State Aid Decision. Stripping that out, the underlying tax rate is more stable — and understanding this adjustment is essential for building a forward earnings estimate.

> **GeminIQ Tip:** GeminIQ's [Calculated Metrics](/features#calculated-metrics) automatically compute over 90 financial KPIs from the raw filing data — including ROIC, free cash flow per share, and growth rates — so you don't have to build your own spreadsheet. For Apple FY2025, GeminIQ shows an ROIC of 78.5% (reflecting Apple's massive capital efficiency relative to its small invested capital base), an ROE of 171.4%, and free cash flow of $98.8 billion.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-k)**

---

## Step 4: Analyze the Financial Statements (Item 8)

This is the core of the 10-K. Item 8 contains three audited financial statements — and each tells you something different about the business.

### The Income Statement: How the Company Makes Money

Start at the top with revenue and work your way down to net income. For Apple FY2025:

| Line Item | FY2025 | FY2024 | Change |
|-----------|--------|--------|--------|
| Total Net Sales | $416.2B | $391.0B | +6% |
| Cost of Sales | $221.0B | $210.4B | +5% |
| Gross Margin | $195.2B | $180.7B | +8% |
| Operating Income | $133.1B | $123.2B | +8% |
| Net Income | $112.0B | $93.7B | +19.5% |
| Diluted EPS | $7.46 | $6.08 | +22.7% |

The 22.7% EPS growth is faster than the 19.5% net income growth — because Apple repurchased 402 million shares during the year, reducing the share count. This is the buyback effect, and it's a core part of Apple's capital return strategy.

### The Balance Sheet: What the Company Owns and Owes

The balance sheet is a snapshot of financial health. Key items for Apple as of September 27, 2025:

- **Cash and marketable securities:** $132.4 billion
- **Total debt:** $98.7 billion ($90.7B term debt + $8.0B commercial paper)
- **Total assets:** $359.2 billion
- **Total shareholders' equity:** $73.7 billion (up from $57.0B — the accumulated deficit is shrinking)
- **[Current ratio](/metrics/liquidity-ratios/current-ratio):** 0.89 (current liabilities exceed current assets — typical for Apple's asset-light model)

A current ratio below 1.0 would concern you with most companies. For Apple, it's structural — the company generates $111.5 billion in annual operating cash flow and carries $132.4 billion in liquid assets. The low current ratio reflects Apple's efficient working capital management, not financial distress.

### The Cash Flow Statement: Where the Cash Actually Goes

The cash flow statement is the value investor's favorite — it shows you actual cash movement, stripped of accounting adjustments.

- **Operating cash flow:** $111.5 billion
- **Capital expenditures:** $12.7 billion (up 35% — Apple is investing in manufacturing and data center infrastructure)
- **Free cash flow:** $98.8 billion
- **Stock repurchases:** $90.7 billion
- **Dividends:** $15.4 billion

Apple returned **$106.1 billion** to shareholders in FY2025 through buybacks and dividends — more than its free cash flow of $98.8 billion. The difference was funded from existing cash and marketable securities. This level of capital return is only sustainable for a business generating Apple's level of cash flow.

> **GeminIQ Tip:** On GeminIQ, all three financial statements are presented exactly as the company filed them — [preserving every line item](/features#financial-statements), every segment, and every XBRL tag. You can build [Custom Tables](/features#custom-tables) that pull specific metrics across multiple years and save them as reusable templates. Build your Apple income statement comparison once, then apply it to any company in seconds.

---

## Step 5: Don't Skip the Notes

The Notes to Consolidated Financial Statements (starting on page 34 of Apple's 10-K) are where the real analytical depth lives. This is where you find:

- **Revenue recognition policies** — Apple defers revenue on bundled services (iCloud, Siri, Maps) and recognizes it over time. As of September 2025, Apple had $13.7 billion in deferred revenue, with 66% expected to be recognized within a year.
- **Segment detail** — Note 13 breaks operating income by geographic segment. Americas generated $72.5B in operating income, Europe $47.7B, Greater China $26.9B. The corporate segment shows $(42.6B) — that's where R&D and G&A sit.
- **Tax complexity** — Note 7 reveals $23.2 billion in gross unrecognized tax benefits. The European State Aid Decision created a $10.2 billion charge in FY2024 that reversed in FY2025's effective rate — if you didn't read the notes, you'd mismodel the tax rate going forward.
- **Debt maturity schedule** — Note 9 shows $12.4 billion in term debt maturing in 2026, $10.1B in 2027, $9.3B in 2028. This is your forward-looking view of refinancing risk and interest expense.

These details don't appear in any screener or dashboard that normalizes the data. They're only in the filing itself — or on a platform like GeminIQ that preserves the as-filed structure.

---

## Step 6: Go Beyond the 10-K

The 10-K tells you what the company reported. But as a value investor, you also want to know what the market did with that information — and what insiders are doing with their own shares.

### Insider Transactions

GeminIQ's [Insider Transaction Tracking](/features#insider-transactions) shows that Apple's executives have been consistent net sellers of stock through equity compensation vesting. In October 2025 alone, CEO Tim Cook sold 129,963 shares at $256.22, SVP Deirdre O'Brien sold 43,013 shares at $257.72, and CFO Kevan Parekh sold 4,199 shares at $247.37.

For Apple, this selling pattern is routine — executives receive RSUs that vest and are partially sold to cover tax obligations. What a value investor looks for is *unusual* buying, which would signal that insiders see the stock as undervalued relative to their private knowledge. GeminIQ's visual sentiment timeline helps you distinguish between routine compensation sales and conviction-driven transactions at a glance.

<center><sup>GeminIQ Insider Transactions (SEC Form 4) for Apple, showing the monthly purchase and sale history and the sortable transaction table pulled directly from Form 4 filings — the open-market activity a 10-K narrative never surfaces.</sup></center>
**[Explore Apple's data now — no account needed →](/stocks/AAPL)**

### Institutional Ownership

GeminIQ's [Institutional Ownership](/features#institutional-ownership) data shows that institutional investors held approximately **57.5%** of Apple's outstanding shares as of March 2025, up from 55.2% a year earlier. Rising institutional ownership alongside rising share prices suggests professional capital is accumulating, not distributing — a constructive signal for value investors evaluating market sentiment.

<center><sup>GeminIQ 13F Institutional Holdings tracker (SEC Form 13F) for Apple, showing the institutional ownership percentage over time aggregated from quarterly 13F filings.</sup></center>
**[Explore Apple's data now — no account needed →](/stocks/AAPL)**

### Earnings Market Reaction

GeminIQ's proprietary [Earnings Market Reaction Heatmap](/features#price-variance) tracks how Apple's stock performed 1, 2, 3, 6, and 12 months after each filing. For the FY2024 10-K (filed November 1, 2024), Apple gained 3.2% in the first month, 3.3% after three months, dropped 10.9% after six months (coinciding with the tariff announcements), and recovered to gain 15.1% after twelve months.

This behavioral data helps you understand how the market historically reacts to Apple's reported results — and whether post-filing pullbacks have historically been buying opportunities or signals of fundamental deterioration. No other platform tracks this filing-to-price relationship.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Apple, showing cumulative post-filing returns at the one-, two-, and three-month marks measured from each filing date.</sup></center>
**[Explore Apple's data now — no account needed →](/stocks/AAPL)**

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-k)**

---

## Finding Your Next 10-K to Read

Once you're comfortable reading Apple's 10-K, the natural next step is finding other companies worth the same level of analysis. GeminIQ's [Stock Screener](/features#screener) lets you filter across 100+ financial metrics — all derived from XBRL-tagged SEC data — with up to 10 stackable conditions. Screen for companies with [ROIC](/blog/roic-return-on-invested-capital-explained) above 15%, gross margins above 40%, and revenue growth above 8% to find businesses with Apple-like quality characteristics, then dive into their 10-Ks armed with the same analytical framework.

Every number on GeminIQ traces directly to its XBRL tag in the source SEC filing. You can verify any metric in under 30 seconds. No normalization, no aggregation, no black boxes — just the data the company reported, structured for analysis.

---

## Start Reading 10-Ks the Smarter Way

The 10-K is the most important document in a value investor's toolkit. But manually extracting data from 100+ page PDFs, building spreadsheet models from scratch, and cross-referencing insider activity across multiple sources takes hours per company.

GeminIQ automates the data extraction, calculates the metrics, visualizes the trends, and tracks the behavioral signals — all built on direct SEC EDGAR data with XBRL traceability for every number. So you can spend your time doing what actually generates returns: analyzing businesses and making decisions.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-k)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Section 8: How to Read a 10-Q
source: https://www.geminiq.com/blog/how-to-read-10-q

### How to Read a 10-Q: A Step-by-Step Guide for Investors (2026)
The 10-K gets all the attention, but the 10-Q is where earnings surprises, margin shifts, and red flags show up first. Here's how to read one efficiently — using Apple's Q1 FY2026 filing as our walkthrough.

Public companies file a 10-K once a year. They file a **10-Q three times a year** — after each of the first three fiscal quarters. (The fourth quarter gets folded into the 10-K.) That means 10-Qs are where new information surfaces between annual reports: revenue acceleration or deceleration, margin compression, balance sheet deterioration, new legal risks, and management's own quarter-by-quarter commentary on performance.

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Most value investors read the annual 10-K carefully and then skim — or skip — the quarterly filings. That's a mistake. If you know where to look, a 10-Q can be read in under 30 minutes, and it tells you things the annual report won't show for months.

In this guide, we'll break down how to read a 10-Q using [Apple's](/stocks/AAPL) **Q1 FY2026 filing** (quarter ending December 27, 2025) as our working example, with comparisons against the prior year quarter. We'll also show how [GeminIQ](/) structures this quarterly data automatically — so you can skip the manual extraction and go straight to analysis.

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---

## 10-Q vs. 10-K: What's Different?

Before diving in, it helps to understand what a 10-Q is *not*. A 10-Q is shorter (typically 30–60 pages vs. 100+ for a 10-K), and the financial statements are **unaudited** — reviewed by the company's independent accountant, but not subjected to the full audit procedures applied to the annual filing. The 10-Q also omits several sections that appear in the 10-K: the full business description (Item 1), the complete risk factors section (Item 1A), and the detailed notes on accounting policies.

What the 10-Q *does* include is everything you need to assess how the business performed in the most recent quarter: condensed financial statements with year-over-year comparisons, management's quarterly discussion and analysis, updated risk disclosures (only material changes), and any material legal or regulatory developments. Think of the 10-Q as a delta — it tells you what changed since the last filing.

Here's a simple framework for reading one in under 30 minutes, broken into five steps.

---

## Minute 1–5: Start with the Income Statement

Open the 10-Q and go directly to the Condensed Consolidated Statements of Operations. This is the quarterly income statement. It shows the current quarter alongside the same quarter from the prior year, giving you an immediate year-over-year comparison.

For [Apple's](/stocks/AAPL) Q1 FY2026 (the holiday quarter ending December 27, 2025):

| Line Item | Q1 FY2026 | Q1 FY2025 | Change |
|-----------|-----------|-----------|--------|
| Total Net Sales | $143.8B | $124.3B | +15.7% |
| Cost of Sales | $74.5B | $66.0B | +12.9% |
| Gross Margin | $69.2B | $58.3B | +18.8% |
| R&D Expense | $10.9B | $8.3B | +31.7% |
| SG&A Expense | $7.5B | $7.2B | +4.4% |
| Operating Income | $50.9B | $42.8B | +18.7% |
| Net Income | $42.1B | $36.3B | +15.9% |
| Diluted EPS | $2.84 | $2.40 | +18.3% |

In five minutes, you already know the quarter's story: revenue accelerated to 15.7% growth (up from 6.4% for the full fiscal year 2025), [gross margin](/metrics/margin-metrics/gross-profit-margin)s expanded because revenue grew faster than costs, and EPS grew even faster than net income thanks to continued share buybacks reducing the denominator.

Two things to flag for deeper analysis: R&D spending surged 31.7%, which is unusually high for Apple and signals a significant step-up in investment — the MD&A attributes this to increases in infrastructure-related costs, headcount-related expenses, and engineering program costs. And EPS growth of 18.3% outpacing net income growth of 15.9% tells you the buyback program is adding roughly 2–3 percentage points of EPS accretion per year.

> **GeminIQ Tip:** On GeminIQ, every quarterly line item is [extracted automatically from the filing](/features#financial-statements) with its XBRL tag preserved. You don't need to manually build a Q-over-Q comparison table — GeminIQ structures 17+ years of quarterly data for every SEC filer, ready for trend analysis the moment the filing hits EDGAR.

---

## Minute 5–10: Check the Gross Margin Trend

Gross margin is the single most important line item for value investors reading a 10-Q. It tells you whether the company's pricing power and cost structure are holding, improving, or deteriorating — quarter by quarter.

For Apple's Q1 FY2026:

- **Gross margin percentage:** 48.2% ($69.2B / $143.8B)
- **Prior year Q1:** 46.9% ($58.3B / $124.3B)
- **Full year FY2025:** 46.9%

Gross margin expanded approximately 130 basis points year-over-year. That's significant. The Q1 FY2026 MD&A breaks this down further: Products gross margin rose from 39.3% to 40.7%, driven by a different mix of products but partially offset by tariff costs. Services gross margin climbed from 75.0% to 76.5%, driven by a different mix of services. Both segments expanded — an uncommon occurrence that signals broad-based margin improvement.

In [Apple's](/stocks/AAPL) FY2025 10-K, management noted that Products gross margin was under pressure from tariff costs. A Q1 FY2026 expansion to 40.7% suggests that either the tariff headwind has been partially offset by pricing, or the product mix shifted toward higher-margin hardware (iPhone Pro models drove the quarter, per the MD&A). Meanwhile, the Services mix shift continues to pull the overall blended margin higher — Services now carry 76.5% gross margins vs. 40.7% for Products.

This is exactly the kind of inflection a quarterly filing catches before the annual report. The 10-K gives you the full-year average. The 10-Q shows you the trajectory.

> **GeminIQ Tip:** GeminIQ's [Interactive Visualizations](/features#visualizations) let you chart gross margin percentage across every quarter going back 17+ years — with line, bar, or area charts, log or linear scaling, and z-score normalization. You can spot margin inflections visually in seconds rather than building a spreadsheet.

<center><sup>GeminIQ Visualizations for Apple, charting the Gross Profit margin trend across recent quarters so a sequential inflection is visible at a glance.</sup></center>

---

## Minute 10–15: Read the Cash Flow Statement

The quarterly cash flow statement shows you where cash actually went during the quarter — and it often tells a different story than the income statement.

For Apple's Q1 FY2026:

- **Operating cash flow:** $53.9B (vs. $29.9B in Q1 FY2025 — up 80%)
- **Capital expenditures:** $2.4B
- **Free cash flow:** $51.6B
- **Stock repurchases:** $24.7B
- **Dividends paid:** $3.9B
- **Debt repayment:** $2.2B term debt + $5.9B commercial paper (net)
- **Cash taxes paid:** $3.4B (vs. $18.7B in Q1 FY2025)

The standout number here is cash taxes paid: $3.4 billion vs. $18.7 billion in the prior year quarter. That's an 82% drop. Why? Because Q1 FY2025 included a massive payment related to the European Commission State Aid Decision — a one-time $15.8 billion obligation that [Apple](/stocks/AAPL) settled by releasing escrowed funds. If you didn't know about that one-time item (disclosed in [Apple's](/stocks/AAPL) FY2024 10-K), you'd misread Q1 FY2025's depressed operating cash flow as a normal baseline and overstate the improvement in Q1 FY2026.

This is the value of reading 10-Qs in sequence. Each quarter builds context for the next one.

Operating cash flow of $53.9 billion in a single quarter — enough to fund the entire buyback program and dividend with $25.3 billion left over — confirms the cash generation machine is running at full capacity.

---

## Minute 15–20: Scan the Balance Sheet for Changes

The quarterly balance sheet is a snapshot, not a flow statement. Read it by looking for meaningful changes from the prior quarter-end or year-end.

Key balance sheet items as of December 27, 2025 (vs. September 27, 2025 year-end):

| Item | Dec 2025 | Sep 2025 | Change |
|------|----------|----------|--------|
| Cash & Equivalents | $45.3B | $35.9B | +$9.4B |
| Total Current Assets | $158.1B | $148.0B | +$10.1B |
| Total Assets | $379.3B | $359.2B | +$20.1B |
| Commercial Paper | $2.0B | $8.0B | -$6.0B |
| Current Term Debt | $11.8B | $12.4B | -$0.5B |
| Non-Current Term Debt | $76.7B | $78.3B | -$1.6B |
| Total Debt | $90.5B | $98.7B | -$8.1B |
| Total Shareholders' Equity | $88.2B | $73.7B | +$14.5B |
| Current Ratio | 0.97 | 0.89 | Improving |

Several things jump out. Total debt dropped $8.1 billion in a single quarter, driven primarily by a $6.0 billion net reduction in commercial paper (from $8.0 billion to $2.0 billion) alongside $2.2 billion in term debt maturities. This is [Apple](/stocks/AAPL) actively deleveraging. Shareholders' equity grew $14.5 billion, driven by the $42.1 billion in net income exceeding the $29.1 billion returned through buybacks ($25.2B repurchased) and dividends and dividend equivalents ($3.9B). [Apple's](/stocks/AAPL) accumulated deficit — which had been a talking point for years — shrank dramatically from $(14.3B) to just $(2.2B) and is on track to turn positive within the next quarter.

The [current ratio](/metrics/liquidity-ratios/current-ratio) improved from 0.89 to 0.97. It's still below 1.0, but trending in the right direction. For a company generating $54 billion in quarterly operating cash flow, this ratio is about working capital efficiency, not solvency risk.

> **GeminIQ Tip:** GeminIQ's [Custom Tables](/features#custom-tables) let you build a quarterly balance sheet comparison template once and apply it to any company. Pick the line items that matter to your thesis, save the template, and run it across any SEC filer instantly — with every number traceable to its XBRL tag.

---

## Minute 20–25: Read the MD&A (Quickly)

The MD&A section in a 10-Q is shorter than its 10-K counterpart, but it contains management's own explanation of what happened during the quarter. Read it for three things:

**1. Segment performance.** [Apple's](/stocks/AAPL) Q1 FY2026 shows how the holiday quarter performed across all five geographic segments:

| Segment | Q1 FY2026 | Q1 FY2025 | Change |
|---------|-----------|-----------|--------|
| Americas | $58.5B | $52.6B | +11% |
| Europe | $38.1B | $33.9B | +13% |
| Greater China | $25.5B | $18.5B | +38% |
| Japan | $9.4B | $9.0B | +5% |
| Rest of Asia Pacific | $12.1B | $10.3B | +18% |

The standout: Greater China surged 38% year-over-year — a dramatic reversal from FY2025's full year when Greater China was the only declining segment. The MD&A attributes this entirely to higher iPhone sales. This is a thesis-changing data point for anyone who had been bearish on [Apple's](/stocks/AAPL) China exposure.

**2. Product and Services mix.** The MD&A breaks down that iPhone revenue surged 23% to $85.3B (driven by Pro models), while Mac declined 7% and Wearables dipped 2%. Services grew 14% to $30.0B. For a company where Services margins are nearly double Products margins, this mix data is essential for margin modeling.

**3. Forward-looking commentary.** The Q1 FY2026 MD&A contains significant discussion of tariff uncertainty, including a new Section 232 semiconductor investigation that was announced in January 2026. The MD&A explicitly notes that tariff costs partially offset Products gross margin improvement — a signal that the tariff headwind is real but manageable so far.

Don't try to read every word of the MD&A. Scan the segment and product tables first, read the commentary around any segment that surprised you, and move on.

---

## Minute 25–30: Check for Red Flags

Use the final five minutes to scan three sections for anything that warrants further investigation:

**Legal proceedings.** [Apple's](/stocks/AAPL) 10-K disclosed ongoing antitrust litigation from the DOJ, DMA investigations in the EU, and the Epic Games injunction. The 10-Q updates any material developments. In Q1 FY2026, the 10-Q discloses several significant updates: the European Commission fined [Apple](/stocks/AAPL) €500 million in the DMA Article 5(4) investigation ([Apple](/stocks/AAPL) has appealed), and issued preliminary findings in a second DMA investigation that could result in fines up to 10% of worldwide net sales. On the Epic Games front, the Ninth Circuit issued an order in December 2025 upholding parts of the district court's injunction while allowing [Apple](/stocks/AAPL) to charge a commission on link-out purchases — a partial win for [Apple](/stocks/AAPL), though the case remains active. These legal risks, collectively, have meaningful implications for Apple's App Store economics and Services revenue trajectory.

**Risk factor updates.** Unlike the 10-K, the 10-Q only discloses *material changes* to risk factors — not the full list. If a new risk factor appears in the 10-Q, pay attention. It means something has changed since the annual filing that management considers significant enough to disclose.

**Insider transactions and institutional ownership.** These won't be in the 10-Q itself, but you should check them after reading the filing. On GeminIQ, you can see that Apple's [insider transaction timeline](/stocks/AAPL) shows consistent executive selling through equity compensation vesting. As of Q1 FY2026, the 10-Q's "Other Information" section discloses that CFO Kevan Parekh and SVP Deirdre O'Brien both adopted new Rule 10b5-1 trading plans during the quarter — routine compensation-related activity, not conviction-driven exits.

GeminIQ's [Institutional Ownership](/features#institutional-ownership) data shows institutional investors have been steadily increasing their positions in Apple, a trend that has accelerated alongside the company's improving financial profile. Rising institutional ownership alongside rising prices suggests professional capital is accumulating, not distributing.

**[Check Apple's latest insider activity and institutional trends on GeminIQ →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-10-q)**

---

## After the 10-Q: What Happened Next?

Reading the 10-Q tells you what the company reported. But value investors also want to know how the market reacted — and whether historical patterns suggest a buying opportunity.

GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) tracks exactly how a stock performed 1 to 12 months after each quarterly and annual filing. Over time, this heatmap reveals behavioral patterns: does the market tend to underreact to strong quarters? Are post-filing dips typically buying opportunities? For Apple, the historical data shows that 10-Q filings with double-digit revenue growth have consistently been followed by positive 12-month returns — the kind of pattern you can't see from a single filing but becomes obvious when you track every filing systematically.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Apple, showing cumulative post-filing returns at the one-, two-, and three-month marks measured from the 10-Q filing date.</sup></center>

---

## Finding More Companies Worth the Deep Read

Once you can read an Apple 10-Q in 30 minutes, the skill transfers to any company. But you need a way to find which companies are worth the time.

GeminIQ's [Stock Screener](/features#screener) lets you filter across 100+ financial metrics — all derived from XBRL-tagged SEC data — with up to 10 stackable conditions using precise logic (less than, greater than, between). Screen for companies with accelerating revenue growth, expanding gross margins, and strong [free cash flow yield](/blog/free-cash-flow-yield-explained) to surface the next quarterly filing worth reading. Every screener result links to auditable source data, so when you pull up the 10-Q, the numbers match.

---

## Stop Reading PDFs. Start Analyzing Quarters.

A 10-Q shouldn't take an hour to read. The bottleneck isn't comprehension — it's extraction. Copying numbers from a PDF into a spreadsheet, building quarter-over-quarter comparisons manually, and cross-referencing insider activity across multiple sources is where the time disappears.

GeminIQ automates the extraction, structures every quarterly filing with XBRL traceability, calculates the metrics, and tracks the behavioral signals — so your 30 minutes are spent analyzing, not transcribing.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s Q1 FY2026 10-Q (filed January 30, 2026, fiscal quarter ending December 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-Q).

---

## Section 9: Complete Guide to SEC Filings
source: https://www.geminiq.com/blog/sec-filings-guide

### SEC Filings Explained: 10-K, 10-Q, 8-K, DEF 14A, S-1, Form 4
Every SEC filing type explained for investors — what each one contains, when it's filed, what to look for, and how to use it in your investment research. Organized by importance, with examples from real filings.

The SEC requires public companies to file specific documents at specific times, and each document serves a different purpose. The 10-K gives you the annual audited picture. The 10-Q updates it quarterly. The 8-K tells you something just happened. The DEF 14A shows you how management is compensated and what shareholders are voting on. The S-1 is the company's debut. And Form 4 tells you what insiders are doing with their own shares.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filings-guide)**

If you understand what each filing contains and when to read it, you have access to the same primary source material that professional analysts use — for free.

This guide covers the six most important SEC filing types for investors, organized by how frequently you'll use them and what to look for in each one.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filings-guide)**

---

## The 10-K: The Annual Audit (Most Important)

**What it is:** The comprehensive annual report that every SEC-registered company must file within 60 days (large accelerated filers) to 90 days (smaller reporting companies) after its fiscal year ends.

**What it contains:** Three years of audited financial statements (income statement, balance sheet, cash flow statement), a full business description, risk factors, management's discussion and analysis (MD&A), notes to the financial statements, segment reporting, and information about controls and procedures.

**When to read it:** When evaluating a new investment, when the annual filing drops for a company you own, and when building or updating a financial model.

**What to look for:**

The 10-K is the foundation of fundamental analysis. For a step-by-step walkthrough, see our detailed guide: [How to Read a 10-K: A Value Investor's Guide](/blog/how-to-read-10-k). The key sections:

**Item 1 (Business Description)** tells you how the company makes money, its competitive position, and its operating structure. This is where you learn that Apple generates 60% of sales through indirect channels, or that a pharmaceutical company depends on a single drug for 70% of revenue.

**Item 1A (Risk Factors)** is where management discloses what they believe could materially hurt the business. Read this not for boilerplate warnings about macroeconomic conditions, but for new or evolving risks that weren't in the prior year's filing. Apple's FY2025 10-K introduced detailed tariff risk disclosures covering imports from China, India, Japan, South Korea, Taiwan, Vietnam, and the EU — an entirely new risk factor with direct margin implications.

**Item 7 (MD&A)** bridges narrative and numbers. Management explains what happened during the year: which segments grew, which contracted, what drove margin changes, and what one-time items affected the results. This is where Apple disclosed that its effective tax rate dropped from 24.1% to 15.6% due to the reversal of a $10.2 billion European Commission charge — a detail essential for forward earnings modeling.

**Item 8 (Financial Statements and Notes)** is the core. The three financial statements give you the numbers. The notes give you the context — revenue recognition policies, debt maturity schedules, segment operating income, tax rate reconciliations, and deferred revenue detail that don't appear anywhere else.

**The auditor's opinion** at the front of Item 8 tells you whether the independent accountant found the statements fairly presented. A clean (unqualified) opinion is standard. Anything else — qualified, adverse, or a going concern paragraph — is a significant red flag.

> **GeminIQ Tip:** GeminIQ extracts every data point from every 10-K with its [XBRL tag intact](/features#financial-statements), calculates [90+ KPIs](/features#calculated-metrics) from the tagged data, and makes the filing data available within one business day of the filing hitting EDGAR. You can go from a fresh 10-K to a fully structured analysis — with metrics, charts, and verification links — without ever opening the PDF.

---

## The 10-Q: The Quarterly Update (Most Frequent)

**What it is:** The quarterly report filed after each of the first three fiscal quarters. (The fourth quarter is covered by the 10-K.) Due within 40 days (large accelerated filers) to 45 days (all others) after quarter-end.

**What it contains:** Condensed (unaudited) financial statements with year-over-year quarterly comparisons, abbreviated MD&A, any material changes to risk factors, and updates on legal proceedings.

**When to read it:** Every quarter, for every company you own or are actively evaluating. The 10-Q is where inflection points appear first — margin shifts, revenue acceleration or deceleration, working capital changes, and new legal risks.

**What to look for:**

For a detailed walkthrough, see our guide: [How to Read a 10-Q in Under 30 Minutes](/blog/how-to-read-10-q). The priority items:

**[Gross margin](/metrics/margin-metrics/gross-profit-margin) trend.** Compare the current quarter's gross margin percentage to both the prior year quarter and the sequential quarter. Apple's Q1 FY2026 gross margin expanded to 48.2% from 46.9% in the prior year — a 130 basis point improvement that signaled broad-based margin expansion across both Products and Services.

**Cash flow statement.** Quarterly cash flow often tells a different story than the income statement. Apple generated $53.9 billion in Q1 FY2026 operating cash flow — up 80% from Q1 FY2025 — partly because the prior year included a $15.8 billion one-time European Commission tax payment. Without reading both quarters, you'd misjudge the trend.

**Balance sheet changes.** Read the quarterly balance sheet as a delta: what changed since the prior quarter-end? Apple reduced total debt by $8.1 billion in a single quarter in Q1 FY2026, driven primarily by paying down $6.0 billion in commercial paper. That's an active deleveraging signal visible only in the quarterly data.

**Risk factor updates.** Unlike the 10-K, the 10-Q only discloses material changes to risk factors. If a new risk factor appears, it means something has changed since the annual filing that management considers significant.

> **GeminIQ Tip:** GeminIQ structures 17+ years of quarterly data for every SEC filer, with [Interactive Visualizations](/features#visualizations) that let you chart any line item or metric quarter by quarter — making inflection points visible immediately.

---

## The 8-K: The Breaking News Filing

**What it is:** A current report filed when a material event occurs. Companies must file an 8-K within four business days of the triggering event.

**What it contains:** The nature and details of the event. The SEC defines specific item types that require an 8-K.

**When to read it:** When you see a news headline about a company and want the primary source, not the media's interpretation.

**What to look for:**

The most common 8-K item types for investors:

**Item 2.02 — Results of Operations (Earnings Release).** The earnings press release is furnished (not filed) as an exhibit to an 8-K. This is typically the first official release of quarterly results — before the 10-Q is filed. The press release often contains "adjusted" or "non-GAAP" figures that differ from the as-filed GAAP financials in the 10-Q.

**Item 1.01 — Entry into a Material Definitive Agreement.** Major contracts, credit facilities, mergers, or joint ventures. This is where you find the terms of a new acquisition or debt arrangement before they're summarized in the next 10-K.

**Item 2.01 — Completion of Acquisition or Disposition.** Confirmation that a previously announced deal has closed, with the financial details.

**Item 5.02 — Departure of Directors or Officers.** C-suite changes. An unexpected CEO departure or CFO replacement can materially affect the investment thesis.

**Item 2.05 — Costs Associated with Exit Activities.** Restructuring announcements — layoffs, facility closures, and the expected charges.

**Item 2.06 — Material Impairments.** Goodwill write-downs and asset impairments that signal the company has acknowledged a business is worth less than it paid.

**Item 7.01 / 8.01 — Regulation FD Disclosure / Other Events.** The catch-all for material information that doesn't fit the other categories — investor day presentations, updated guidance, significant legal developments.

The key distinction: 8-K earnings releases are "furnished," not "filed." Furnished items are not subject to the same legal liability standard as filed items, which is why companies use the earnings press release to present non-GAAP metrics they might not include in the formal 10-Q. The GAAP numbers in the 10-Q — filed later — are the auditable standard.

---

## The DEF 14A (Proxy Statement): Who Gets Paid and How

**What it is:** The definitive [proxy statement](/blog/what-is-def-14a) filed before the company's annual shareholder meeting. It's required for any meeting where shareholders will vote.

**What it contains:** Executive compensation details, board composition and independence, shareholder proposals, and any items that require a shareholder vote (director elections, equity plan approvals, say-on-pay votes, mergers).

**When to read it:** When you want to understand management incentive alignment, compensation structure, or governance quality.

**What to look for:**

**Executive compensation tables.** The Summary Compensation Table shows total compensation for each Named Executive Officer (NEO) — base salary, stock awards, option awards, non-equity incentive plan compensation, and "all other compensation." For Apple's most recent proxy, CEO Tim Cook's total compensation was predominantly stock-based — a structure that ties his economic interest directly to the stock price.

**Compensation structure design.** Look at what metrics drive incentive pay. Is management incentivized on revenue growth, EPS, [ROIC](/blog/roic-return-on-invested-capital-explained), total shareholder return, or something else? The metrics management is compensated on reveal what management is optimizing for — which may or may not align with what you care about as a shareholder.

**Related-party transactions.** The proxy discloses any material transactions between the company and its directors, officers, or their families.

**Shareholder proposals.** Proposals from institutional investors on governance reforms, environmental disclosures, or compensation practices. The vote results (reported in an 8-K after the meeting) show the balance of power between management and shareholders.

**Board composition.** Director biographies, committee memberships, and independence classifications. The audit committee composition is particularly important — independent directors with financial expertise are the oversight layer for the financial statements you're relying on.

---

## The S-1: The IPO Filing

**What it is:** The registration statement filed when a company plans to offer securities to the public for the first time. It's also used for follow-on offerings (sometimes on Form S-3 for seasoned issuers).

**What it contains:** Everything the 10-K contains, plus additional disclosures required for first-time registrants: the company's founding story, use of proceeds from the offering, capitalization table, dilution analysis, and a description of every class of securities.

**When to read it:** When evaluating an IPO or a recently public company.

**What to look for:**

**Use of proceeds.** This section tells you what the company plans to do with the money it raises. "General corporate purposes" is the red flag — it means management wants maximum flexibility but isn't making specific commitments. Specific uses — retire debt, fund R&D, build manufacturing capacity — give you a basis for evaluating whether the capital raise creates value.

**Capitalization table.** The cap table shows every class of equity — common stock, preferred stock, warrants, options, convertible instruments — and their respective rights. For venture-backed companies, the preferred stock liquidation preferences can mean that common shareholders (the shares you'd buy in the IPO) are subordinate to venture investors in a downside scenario.

**Pre-IPO financial history.** The S-1 contains financial statements covering the company's history as a private entity. These are your only window into pre-public performance. Pay attention to revenue growth trajectories, margin trends, and whether the company was profitable before going public.

**Risk factors.** The S-1 risk factors section is typically the most comprehensive version — because the company has the most legal incentive to disclose everything before the offering.

**Lock-up agreements.** Insiders and pre-IPO shareholders are typically restricted from selling for 90–180 days after the IPO. The lock-up expiration can create significant selling pressure if insiders have large unrealized gains.

---

## Form 4: What Insiders Are Doing with Their Shares

**What it is:** A disclosure filed by company insiders (officers, directors, and 10%+ shareholders) within two business days of any purchase, sale, grant, or exercise of company securities.

**What it contains:** The specific transaction — buy, sell, option exercise, gift, or plan-based acquisition — with the exact date, number of shares, and price.

**When to read it:** On an ongoing basis for companies you own. Insider transaction patterns are among the most underutilized data sources available to individual investors.

**What to look for:**

**Open-market purchases.** An insider buying shares with their own money on the open market is the strongest insider signal. It means they chose to allocate personal capital to the stock at the current price — a fundamentally different decision than receiving RSUs through a compensation plan.

**Patterns over time, not individual transactions.** A single Form 4 showing an executive selling 5,000 shares means very little. But tracking every Form 4 across a decade reveals structural patterns. For Apple, GeminIQ's [insider transaction data](/features#insider-transactions) shows 435 total transactions with only 4 open-market purchases — ever. All four were by board members. This means any executive purchase would be a departure from 17 years of established pattern — an extremely strong signal precisely because it has never happened.

**10b5-1 plan disclosures.** Executives who set up pre-planned trading schedules (10b5-1 plans) do so to avoid insider trading scrutiny. The plan's existence is disclosed in the Form 4 footnotes or in the 10-Q's "Other Information" section. Routine plan-based sales are different from discretionary sales — the distinction matters for interpreting the transaction.

**Cluster buying or selling.** When multiple insiders buy (or sell) within a short window, the signal is amplified. Cluster buying by several directors ahead of an earnings report is a stronger indicator than a single transaction.

> **GeminIQ Tip:** GeminIQ's [Insider Transaction Timeline](/features#insider-transactions) visualizes every Form 4 transaction alongside the stock price, with a sentiment indicator that distinguishes purchases from sales and plan-based transactions from discretionary ones. The pattern across years is immediately visible — without downloading hundreds of individual Form 4 filings.

---

## How the Filings Work Together

No single filing tells the complete story. The six filing types form an integrated information system:

The **10-K** establishes the annual baseline. The **10-Q** updates it three times a year with quarterly inflections. The **8-K** fills the gaps with material events as they happen. The **DEF 14A** reveals whether management's incentives are aligned with shareholder interests. The **S-1** tells you the company's origin story and pre-public financial history. And **Form 4** shows you what the people with the most information — insiders — are doing with their own capital.

GeminIQ structures the data from 10-K, 10-Q, and Form 4 filings automatically — with XBRL-tagged financial statements, calculated metrics, insider transaction timelines, and the [Earnings Market Reaction Heatmap](/features#price-variance) that tracks post-filing stock performance across 17+ years. The [Stock Screener](/features#screener) lets you filter across 100+ metrics to find companies worth the deep-dive — and then every filing data point is there, tagged and traceable, ready for analysis.

---

## Frequently Asked Questions

### Where can I find SEC filings for free?
All SEC filings are publicly available at sec.gov/edgar. You can search by company name, ticker, or CIK number. Filings are also available on most companies' investor relations pages. GeminIQ structures the financial data from 10-K and 10-Q filings automatically — extracting, tagging, and visualizing the data so you don't need to read the PDFs manually.

### What is the difference between "filed" and "furnished" with the SEC?
Filed documents carry full legal liability under the Securities Exchange Act. Furnished documents (like earnings press releases attached to 8-Ks) are subject to a lower liability standard. This matters because companies use furnished documents to present non-GAAP adjusted figures that wouldn't appear in the formally filed 10-Q.

### How quickly are filings available after submission?
Most filings appear on EDGAR within minutes of submission. GeminIQ processes new 10-K and 10-Q filings overnight (T+1), making structured XBRL-tagged data available by the time the market opens the following day.

### What is a 10-K/A or 10-Q/A?
The "/A" suffix indicates an amended filing — the company is correcting or supplementing a previously filed document. Amendments can range from minor typographical fixes to material restatements of financial results. GeminIQ handles amendments by preserving the most current version of the data while flagging when amendments have occurred.

### What is a Schedule 13D or 13G?
These are filed by investors who acquire more than 5% of a company's outstanding shares. A 13D is the "activist" filing — it indicates the investor may seek to influence the company (board seats, strategic changes, buybacks). A 13G is the "passive" filing — the investor holds the shares for investment only. Transitions from 13G to 13D are significant — they signal the investor's intentions have changed from passive to active.

### What is Form 144?
Filed by insiders and affiliates who intend to sell restricted or control securities. It signals upcoming sales before they happen — a leading indicator that complements the Form 4 filings that report sales after execution.

---

## The Bottom Line

SEC filings are the primary source material for fundamental analysis. Every financial data platform, every analyst report, every earnings summary traces back to these documents. The investors who read them have an informational advantage — not because the filings are secret, but because most investors never look past the platform's processed version.

You don't need to read every filing for every company. But you should be reading the 10-K and 10-Q for every company you own, scanning 8-Ks for material events, and monitoring Form 4s for insider transaction patterns. The proxy statement is worth an annual read for your largest positions.

GeminIQ makes this process efficient by structuring the 10-K and 10-Q data automatically — preserving every line item with its XBRL tag, calculating 90+ metrics from the source data, and integrating insider transactions, institutional ownership, and post-filing price reactions into a single research platform.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filings-guide)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025) and Q1 FY2026 10-Q (filed January 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193).

---

## Section 9a: What Is XBRL?
source: https://www.geminiq.com/blog/what-is-xbrl

### What Is XBRL? How SEC Tagging Affects Your Investment Data (2026)
XBRL is the SEC-mandated tagging system that gives every number in a 10-K or 10-Q a machine-readable identifier. Most financial platforms strip it out. Here's what it is, why the SEC requires it, and why it matters for your investment analysis.

XBRL (eXtensible Business Reporting Language) is the data standard the SEC requires every public company to use when filing financial statements. Each number in a 10-K or 10-Q — revenue, operating income, total debt, share-based compensation — carries a specific XBRL tag that identifies exactly what that number represents and links it back to the original filing. It is the single most important data layer for verifying financial data accuracy, and most investors have never heard of it.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-xbrl)**

If you've ever wondered why two financial platforms show different numbers for the same company, XBRL — or more precisely, the decision to discard it — is the answer.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-xbrl)**

---

## The Problem XBRL Was Built to Solve

Before 2009, public company financial data was trapped in PDFs. If you wanted to compare Apple's revenue to Microsoft's, you opened two filings, found the income statements, and typed the numbers into a spreadsheet. Multiply that by a few hundred companies and an entire career, and you start to understand why the SEC decided the system needed to change.

The SEC's solution was to require every filer to tag its financial data with standardized, machine-readable identifiers — XBRL tags — so that any number in any filing could be extracted, compared, and verified programmatically. The mandate rolled out in phases: large accelerated filers began tagging in 2009, and by 2012 all public companies were required to file with XBRL.

The idea was simple. If [Apple's](/stocks/AAPL) revenue carries the tag `Revenues` and Microsoft's carries the same tag, a computer can pull both numbers, compare them, and know they represent the same concept — without a human manually cross-referencing two PDFs. And if [Apple](/stocks/AAPL) reports a line item that only [Apple](/stocks/AAPL) reports — like its $33.2 billion in Vendor Non-Trade Receivables — that line item gets its own tag (`NontradereceivablesCurrent`) that links it to the exact concept in [Apple's](/stocks/AAPL) filing.

The SEC built the taxonomy. Companies apply the tags. Every number has a verifiable identity.

So why does your financial data platform show you something different than the filing?

---

## How XBRL Tags Work in Practice

Every financial data point in an SEC filing carries three pieces of XBRL information:

**1. The tag itself.** This is the standardized identifier from the US GAAP XBRL taxonomy — a controlled vocabulary maintained by the Financial Accounting Standards Board (FASB). [Apple's](/stocks/AAPL) revenue is tagged `Revenues`. Its operating income is tagged `OperatingIncomeLoss`. Its gross profit is tagged `GrossProfit`. Each tag has a formal definition that describes exactly what the number represents.

**2. The context.** This specifies the time period and entity the number applies to. [Apple's](/stocks/AAPL) FY2025 revenue tag carries a context indicating it covers the 12 months ending September 27, 2025, for entity CIK 0000320193 ([Apple](/stocks/AAPL) Inc.). Quarterly figures carry a different context specifying the three-month period.

**3. The value.** The actual number — $416,161,000,000 for [Apple's](/stocks/AAPL) FY2025 revenue. This is what appears in the filing, carried with full precision.

Together, these three elements create a verifiable chain: any data point can be traced from the number on your screen → to the XBRL tag → to the specific line item in the specific filing for the specific period. This is what traceability means.

When a company has a line item that doesn't fit the standard US GAAP taxonomy, it can create an extension tag — a custom identifier that describes the company-specific concept. Apple's Vendor Non-Trade Receivables uses such a tag. These extensions are documented in the filing and carry the same machine-readable properties as standard tags.

The system works. The tags are public. The taxonomy is comprehensive. Every number has a verifiable identity.

The problem starts when someone decides to throw all of this away.

---

## Where the XBRL Layer Disappears

The vast majority of financial research platforms don't source data directly from SEC EDGAR. They license processed data from third-party aggregators — companies whose business is ingesting raw filings, normalizing them into a standardized template, and selling the result.

When an aggregator normalizes a filing, it maps the SEC's XBRL tags into its own proprietary taxonomy. [Apple's](/stocks/AAPL) three distinct debt instruments (Commercial Paper, current Term Debt, non-current Term Debt) — each with its own XBRL tag — get merged into two generic buckets: "Short-Term Debt" and "Long-Term Debt." [Apple's](/stocks/AAPL) Vendor Non-Trade Receivables gets folded into "Other Current Assets." The XBRL tags that identified these line items are replaced with the aggregator's own internal identifiers.

By the time the data reaches you through a retail platform, the XBRL provenance is gone. You see a number. You see a label. But the verifiable link between that number and the specific line item in the original filing has been severed.

This matters because without XBRL traceability, you cannot:

**Verify a number against the filing.** If a platform shows [Apple's](/stocks/AAPL) "Other Non-Current Liabilities" at $29.9 billion, but the 10-K shows $41.5 billion under the same label, you have no way to trace the discrepancy. (This is a [documented example](/blog/third-party-financial-data-problems) — the aggregator subtracted $11.6 billion in capital leases and kept the label.)

**Identify company-specific line items.** If an aggregator maps [Apple's](/stocks/AAPL) Vendor Non-Trade Receivables into a generic bucket, you cannot see the $33.2 billion asset at all — it's been subsumed into a category that obscures its identity and economic meaning.

**Audit metric calculations.** If a platform shows ROIC of 42% and you calculate 85% from the filing, there's no way to determine which inputs the platform used or why they differ. With XBRL-tagged inputs, you can trace every component.

**Trust historical consistency.** Aggregators update their taxonomies over time. When they reclassify a line item, historical data can change retroactively — meaning a backtest you ran last month produces different results today, with no underlying economic change.

> **GeminIQ Tip:** On GeminIQ, every financial data point preserves its [XBRL tag](/features#financial-statements). Search the same tag on EDGAR to verify the match. The number on GeminIQ is the number in the filing — because it was never translated through a proprietary taxonomy.

---

## Why XBRL Matters for Five Specific Investment Workflows

### 1. Building Financial Models

Every financial model is only as accurate as its inputs. If your model's revenue line comes from a platform that merged two revenue streams, your margin calculation inherits that merge. If your [invested capital](/metrics/calculated-values/invested-capital) uses a debt figure that combined three instruments into two, your ROIC is wrong before you write the first formula. XBRL-tagged inputs mean the data feeding your model matches the filing — no silent reclassifications.

### 2. Screening and Quantitative Analysis

GeminIQ's [Stock Screener](/features#screener) filters across 100+ metrics with up to 10 stackable conditions. Every metric behind the screen — [ROIC](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield), [Debt-to-Equity](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), [Gross Margin](/metrics/margin-metrics/gross-profit-margin) — is computed from XBRL-tagged source data. When a company passes your screen, you can verify every input in the original filing. On a normalized platform, you can't.

### 3. Quarter-over-Quarter Trend Analysis

Inflection points in margins, working capital, and debt structure emerge from precise quarterly data. If an aggregator smooths or merges line items, the inflection gets dulled. GeminIQ's [Interactive Visualizations](/features#visualizations) chart any XBRL-tagged line item or calculated metric across 17+ years of quarterly history — with the granularity the company actually reported.

### 4. Cross-Checking Platform Data Against Filings

If you've ever compared a platform's number to the 10-K and found a discrepancy, XBRL is how you resolve it. With the tag, you can identify the exact line item in the filing and determine whether the platform normalized, merged, or reclassified the data. Without the tag, you're guessing.

### 5. Teaching and Learning Fundamental Analysis

If you're learning to analyze financial statements, you should be learning from the actual filing — not a vendor's interpretation of it. XBRL tags serve as a built-in glossary: each tag carries a formal definition from the FASB taxonomy that explains what the number represents. This makes XBRL-tagged data inherently more educational than normalized data.

---

## How GeminIQ Preserves the XBRL Layer

GeminIQ doesn't license data from third-party aggregators. The platform ingests filings directly from SEC EDGAR, preserves every XBRL tag, and structures the data for analysis without reclassification.

**Every number is the filing.** [Apple's](/stocks/AAPL) FY2025 revenue on GeminIQ is $416,161,000,000 because that is the value tagged `Revenues` in the 10-K. It was not mapped into a proprietary taxonomy.

**Every line item is preserved as-filed.** [Apple's](/stocks/AAPL) Vendor Non-Trade Receivables, Commercial Paper, current Term Debt, and non-current Term Debt all appear as separate line items — because that is how [Apple](/stocks/AAPL) reported them. The [financial statements](/features#financial-statements) on GeminIQ reflect the company's own reporting structure, not a template.

**Every metric traces to its inputs.** GeminIQ calculates [90+ financial KPIs](/features#calculated-metrics) — ROIC, ROE, margins, growth rates, [Altman Z-Score](/blog/altman-z-score-financial-distress), and more — directly from XBRL-tagged data. When GeminIQ shows [Apple's](/stocks/AAPL) gross margin of 46.9%, you can see the formula: Gross Profit ($195,201,000,000, tag `GrossProfit`) divided by Revenue ($416,161,000,000, tag `Revenues`). Both inputs link to the filing.

**17+ years of quarterly history.** Every quarterly 10-Q and annual 10-K going back to when XBRL tagging was first mandated for each filer — structured, tagged, and ready to chart.

**[See what XBRL-tagged financial data looks like →](/stocks/AAPL)**

---

## The Brief History of XBRL and SEC Mandates

XBRL was developed in the late 1990s as an open standard for electronic business reporting. The SEC began exploring it in the early 2000s through voluntary filing programs and officially mandated XBRL tagging in December 2008 through Rule 33-9002.

The rollout was phased by filer size. Large accelerated filers (companies with $5 billion+ in public float) began tagging in June 2009. Accelerated filers followed in 2010, and all remaining filers were required to tag by 2012. Initially, only the face of the financial statements required tagging. Starting in 2011, the SEC extended the requirement to the footnotes and schedules — the detail tagging phase — requiring companies to tag individual values within the notes to the financial statements.

In 2018, the SEC took the next step and mandated Inline XBRL (iXBRL), which embeds the XBRL tags directly within the human-readable HTML filing. This means the tags and the numbers live in the same document — you can read the filing as a web page and the machine can read the tags simultaneously. The Inline XBRL transition completed for all filers by 2021.

Today, every public company 10-K and 10-Q filed with the SEC carries embedded XBRL tags for every financial data point — face financials and notes alike. The data standard is mature, comprehensive, and designed for exactly the kind of verification that most financial platforms don't offer.

---

## Frequently Asked Questions

### What does XBRL stand for?
XBRL stands for eXtensible Business Reporting Language. It is an open data standard based on XML that allows financial data to be tagged with standardized, machine-readable identifiers. The SEC requires all public companies to use XBRL when filing financial statements.

### Is XBRL data free to access?
Yes. All XBRL-tagged data is publicly available through SEC EDGAR. The SEC provides bulk data downloads, an API (the CompanyFacts API), and the full text of every filing with embedded Inline XBRL tags. The challenge isn't access — it's structuring the raw data into a format suitable for analysis.

### Why don't most financial platforms use XBRL tags?
Most retail platforms license pre-processed data from third-party aggregators rather than building their own ingestion pipelines from EDGAR. Aggregators replace XBRL tags with proprietary identifiers during normalization, and the original tags don't survive the translation. Building and maintaining a direct EDGAR ingestion pipeline that preserves XBRL fidelity is technically complex — which is why most platforms outsource the data layer entirely.

### What is Inline XBRL?
Inline XBRL (iXBRL) is the current filing format required by the SEC. It embeds XBRL tags directly within the human-readable HTML filing, so the same document serves both human readers and machines. Before Inline XBRL, companies filed separate XBRL instance documents alongside their HTML filings, creating synchronization issues. Inline XBRL solved this by putting tags and content in one file.

### How does XBRL help with data accuracy?
XBRL creates a verifiable chain between any data point and the original filing. If a platform preserves the XBRL tag, you can trace any number — revenue, operating income, a specific balance sheet line item — back to the exact concept in the exact filing for the exact period. This makes it possible to audit platform data against the source. Without XBRL tags, there is no audit trail.

### How far back does XBRL-tagged data go?
The earliest XBRL-tagged filings date to 2009, when the SEC mandate took effect for large accelerated filers. GeminIQ provides 17+ years of XBRL-tagged quarterly data, covering the full history of the mandate.

---

## The Bottom Line

The SEC built XBRL to solve the financial data verification problem. Every public company tags every number in every filing with a machine-readable identifier that creates an auditable link to the source. The standard is mature, the data is free, and the infrastructure works.

Yet the majority of financial platforms strip this layer out during normalization — replacing it with proprietary taxonomies that sever the connection between the number on your screen and the number in the filing. The result is data you cannot verify, metrics you cannot trace, and discrepancies you cannot explain.

GeminIQ preserves the XBRL layer because it was designed for investors who need to trust their data. Every number traceable. Every metric transparent. Every filing structured exactly as the company reported it — across 17+ years of history, with the [screener](/features#screener), [visualizations](/features#visualizations), [insider tracking](/features#insider-transactions), and [institutional ownership](/features#institutional-ownership) data that turns raw filings into investment insight.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-xbrl)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Section 9c: The Data Pipeline
source: https://www.geminiq.com/blog/how-financial-data-reaches-investors

### How Financial Data Reaches Investors: What Gets Lost
Your financial data passes through at least two layers of processing before you see it. Here's the complete pipeline — from SEC EDGAR filing to your screen — with a step-by-step breakdown of where information is lost at each stage.

The number you see on your financial research platform is not the number the company filed with the SEC. It has been through at least two layers of processing — a third-party aggregator's normalization and the platform's display formatting — and at each layer, information was removed, reclassified, or merged. The number might still be approximately right. But "approximately right" is a different standard than "matches the filing," and the gap between them is invisible to you.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-financial-data-reaches-investors)**

Here's how the pipeline actually works, stage by stage, with documented examples of what gets lost at each step.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-financial-data-reaches-investors)**

---

## The Four-Stage Pipeline

Most investors think there's a direct line between a company's SEC filing and the data on their screen. There isn't. The typical path has four stages, and each one introduces changes.

### Stage 1: The Company Files with EDGAR

A public company prepares its 10-K or 10-Q, has it audited (for annual filings) or reviewed (for quarterly filings), and submits it to the SEC through the EDGAR system. Since 2018, filings are submitted in Inline XBRL format — meaning every financial data point is embedded with a machine-readable tag that identifies exactly what that number represents.

At this stage, the data is as clean as it gets. The numbers reflect the company's own reporting structure, using labels the company chose to describe its business. Apple's balance sheet at this stage includes "Vendor Non-Trade Receivables" as its own line item at $33.2 billion, three distinct debt instruments (Commercial Paper, current Term Debt, non-current Term Debt), and every cash flow adjustment in granular detail.

**What exists at Stage 1:**
- Every line item the company reported, with its original label
- XBRL tags linking every number to a standardized or extension concept
- Full notes to the financial statements with detail-tagged data
- The company's own reporting structure and classification decisions

**What gets lost at Stage 1:** Nothing. This is the source of truth.

### Stage 2: The Aggregator Ingests and Normalizes

Within hours of a filing hitting EDGAR, third-party data providers ingest it. Their job is to take thousands of filings from thousands of companies — each with its own reporting structure, its own labels, and its own line items — and map them all into a single standardized template.

This is where the most consequential changes happen.

**Normalization decisions the aggregator makes:**

**Merging line items.** Apple reports three distinct debt instruments. The aggregator's template has two debt categories (short-term and long-term) or sometimes just one (total debt). The three instruments get combined. The individual XBRL tags — `CommercialPaper`, `LongTermDebtCurrent`, `LongTermDebtNoncurrent` — are replaced with the aggregator's proprietary identifiers.

**Reclassifying line items.** Apple's "Vendor Non-Trade Receivables" doesn't fit the aggregator's template. It gets folded into "Other Current Assets" or "Other Receivables." The $33.2 billion is still in the data somewhere, but its identity — what it represents, why Apple reports it separately — is gone.

**Combining cash flow items.** Apple's cash flow statement separates "Repurchases of common stock" ($90.7 billion) from "Payments for taxes related to net share settlement of equity awards" ($6.0 billion). The aggregator combines them into a single "Repurchase of Common Stock" line at $96.7 billion. Two cash outflows with different economic meanings become one number.

**Relabeling without changing the label.** The most dangerous normalization: the aggregator subtracts capital lease obligations from "Other Non-Current Liabilities" but keeps the label "Other Non-Current Liabilities." The filing shows $41.5 billion. The aggregator shows $29.9 billion. Same label. $11.6 billion gap. No indication that anything changed.

**Adjusting for "comparability."** Some aggregators reclassify items they believe are mistagged or inconsistently reported. The intent is to make cross-company comparisons more uniform. The effect is that the data no longer represents what the company filed — it represents the aggregator's opinion of how the company should have filed.

**What exists at Stage 2:**
- A standardized template that works across thousands of companies
- Numbers that are approximately correct in aggregate but may differ materially from individual filings
- The aggregator's proprietary taxonomy (replacing XBRL tags)
- Cross-company comparability within the aggregator's framework

**What gets lost at Stage 2:**
- XBRL tag identifiers and the verifiable link to the source filing
- Company-specific line items that don't fit the template
- Granular debt, cash flow, and working capital breakdowns
- The ability to trace any number back to a specific filing data point

### Stage 3: The Platform Licenses the Data

Retail financial research platforms — the websites and apps you actually use — typically don't build their own data pipelines. They license the aggregator's processed output and build their interface on top of it.

At this stage, the platform makes its own display decisions: how to label columns, how to round numbers, which line items to show on the summary page versus hiding in a detail view, and how to present historical data. Some platforms add their own calculated metrics on top of the aggregator's data, which means the metric inherits every normalization decision the aggregator made — plus any errors in the platform's own calculation logic.

**What gets lost at Stage 3:**
- Any remaining granularity the aggregator preserved but the platform chose not to display
- Visibility into which aggregator was the source (most platforms don't disclose this)
- The ability to determine whether a displayed number was normalized, reclassified, or rounded

### Stage 4: You See the Number

By the time a data point appears on your screen, it has been through the company's filing process, the aggregator's normalization, and the platform's formatting. The number may be close to what was filed. It may be materially different. You have no way to tell, because the audit trail — the XBRL tag that linked the number to the filing — was stripped at Stage 2.

This is the pipeline that serves the vast majority of financial data consumed by individual investors today. It's not broken. It works well for high-level scanning and quick comparisons. But it was designed for breadth, not fidelity — and every analytical workflow that depends on fidelity inherits the gaps.

---

## A Documented Example Through All Four Stages

To make this concrete, here is one data point — Apple's "Other Non-Current Liabilities" — traced through each stage:

**Stage 1 (EDGAR filing):** Apple's FY2025 10-K, page 40, Consolidated Balance Sheet. "Other non-current liabilities" is reported at **$41,549,000,000**. XBRL tag: `OtherLiabilitiesNoncurrent`.

**Stage 2 (Aggregator):** The aggregator subtracts Capital Leases ($11,603M) from the line and maps the remainder — **$29,946M** — into its template under "Other Non-Current Liabilities." The XBRL tag is replaced with a proprietary identifier. The subtraction is not documented in the output.

**Stage 3 (Platform):** The retail platform displays **$29,946M** (or $29.9B) under the label "Other Non-Current Liabilities." No footnote. No indication of the adjustment.

**Stage 4 (Your screen):** You see "Other Non-Current Liabilities: $29.9B." You compare it to the 10-K, which says $41.5B. There's an $11.6 billion gap under the same label, and no way to explain it without independently discovering that the aggregator subtracted capital leases.

This is not a theoretical scenario. It is a [documented discrepancy](/blog/third-party-financial-data-problems) in the most analyzed company on earth, from its most recent annual filing.

---

## The Five Categories of Information Lost in the Pipeline

Based on our analysis of how aggregator normalization affects SEC filing data, information loss falls into five consistent categories:

### 1. Company-Specific Line Items

Every company reports using labels that describe its actual business. These labels are precise, intentional, and often carry economic meaning that generic categories cannot capture. When an aggregator folds Apple's $33.2 billion Vendor Non-Trade Receivables into "Other Current Assets," or combines a pharmaceutical company's milestone payment receivables into a generic bucket, the identity of the asset disappears. The number might survive, but the context that makes it analytically useful is gone.

### 2. Granular Instrument Breakdowns

Companies report distinct financial instruments separately because they represent different types of obligations with different risk profiles. Merging them destroys the granularity analysts need for refinancing risk analysis, interest rate exposure modeling, and liquidity assessment. Apple's Commercial Paper, current Term Debt, and non-current Term Debt are three instruments with different maturities, different rate structures, and different risk characteristics — information that vanishes when they become "Short-Term Debt" and "Long-Term Debt."

### 3. Cash Flow Decomposition

Cash flow statements contain the most granular view of where cash actually went during a period. When aggregators combine separate outflows (buybacks + tax payments on equity settlements), reclassify net proceeds as gross issuance, or merge working capital adjustments into generic buckets, the decomposition that reveals cash flow quality gets smoothed away.

### 4. Silent Reclassifications

The most analytically dangerous category: changes that keep the original label while altering the number. When "Other Non-Current Liabilities" shows $29.9 billion on a platform and $41.5 billion in the filing, under the exact same name, an analyst building a model has no reason to suspect a discrepancy — and no way to detect it without independently reading the filing.

### 5. XBRL Provenance

The loss of XBRL tags is not a loss of a single data point — it is the loss of the entire verification infrastructure. Without tags, you cannot audit any individual number, cannot trace metric calculations to their inputs, and cannot determine whether historical data has been retroactively reclassified.

---

## How GeminIQ Eliminates the Middle Layers

GeminIQ removes Stages 2 and 3 entirely. The pipeline is two stages:

**Stage 1:** The company files with EDGAR.

**Stage 2:** GeminIQ ingests the filing directly, preserves every XBRL tag, and presents the data exactly as filed — with [90+ calculated metrics](/features#calculated-metrics), [interactive visualizations](/features#visualizations), and a [screener](/features#screener) with 100+ filterable metrics all computed from the tagged source data.

No aggregator. No normalization. No proprietary taxonomy replacing the SEC's own data standard. When GeminIQ shows a number, it is the number the company filed, carrying the tag the SEC assigned, traceable to the original document on EDGAR.

> **GeminIQ Tip:** Every data point on GeminIQ displays its XBRL tag. Copy the tag, search for it in the original filing on EDGAR, and verify the match. This takes under 30 seconds. On a platform that discards XBRL tags, the same verification is functionally impossible.

**[See what the direct pipeline looks like →](/stocks/AAPL)**

---

## When Does the Pipeline Gap Actually Matter?

For high-level stock screening — scanning thousands of companies to find ideas — normalized data is often adequate. The approximation is close enough to surface interesting candidates, and the standardization makes comparison efficient.

But the pipeline gap matters whenever you move from scanning to analyzing:

**Financial modeling.** If your model inputs don't match the filing, every downstream calculation inherits the error. [ROIC](/blog/roic-return-on-invested-capital-explained), [free cash flow yield](/blog/free-cash-flow-yield-explained), return on equity — all depend on precise balance sheet and cash flow inputs.

**Quantitative backtesting.** If an aggregator retroactively reclassifies line items when updating its taxonomy, historical data changes. Backtests break. Signals shift without any underlying economic event.

**Auditing a position.** Before committing capital, you want to verify the numbers. If the platform's data doesn't trace to the filing, verification requires manually reading the 10-K and building your own comparison — hours of work that XBRL traceability makes unnecessary.

**Quarter-over-quarter inflection analysis.** Margin shifts, working capital changes, and debt structure movements emerge from precise quarterly data. If the pipeline smoothed or merged line items, the inflection gets dulled.

GeminIQ's [Advanced Screener](/features#screener) lets you find companies worth analyzing. The XBRL-tagged [financial statements](/features#financial-statements) let you analyze them with data you can trust. And the [Custom Tables](/features#custom-tables), [Earnings Market Reaction Heatmap](/features#price-variance), [Insider Transaction Timeline](/features#insider-transactions), and [Institutional Ownership](/features#institutional-ownership) data let you layer behavioral signals on top of verified fundamentals.

---

## Frequently Asked Questions

### Why do platforms use third-party aggregators instead of pulling directly from EDGAR?
Building and maintaining a direct EDGAR ingestion pipeline that preserves XBRL fidelity is technically complex. It requires parsing thousands of filings with different structures, handling XBRL extension tags, managing historical data across taxonomy changes, and cleaning known tagging errors without reclassifying what the company reported. Most platforms choose to license pre-processed data because it is faster and cheaper to integrate.

### Can I access SEC EDGAR data myself?
Yes. All SEC filings are publicly available at sec.gov/edgar. The SEC also provides bulk data through the CompanyFacts API. The challenge is structuring the raw data into a format suitable for analysis — which is the engineering work that GeminIQ performs automatically for every filer.

### How do I know if my current platform normalizes the data?
Compare any data point on your platform to the same line item in the original filing. Start with a company-specific line item like Apple's Vendor Non-Trade Receivables ($33.2 billion in FY2025). If it appears as its own line on your platform, the data may be sourced directly. If it's been folded into a generic category, the platform is using normalized data. Our [Third-Party Data Miss guide](/blog/third-party-financial-data-problems) provides a step-by-step verification walkthrough.

### Does GeminIQ normalize any data?
GeminIQ corrects known XBRL tagging errors — misapplied tags, duplicate entries from amended filings, and similar technical issues. It does not reclassify what a company reported. Apple's Vendor Non-Trade Receivables stays as Vendor Non-Trade Receivables. The line items, labels, and values remain exactly as filed.

### How quickly does new filing data appear on GeminIQ?
New filings are processed overnight (T+1), meaning structured, XBRL-tagged data is available by the time the market opens the day after a filing goes live on EDGAR.

### Does this pipeline problem affect all companies equally?
No. Companies with straightforward reporting structures — simple balance sheets, standard line items — lose less in normalization. Companies with complex or unusual reporting — multi-instrument debt structures, company-specific assets, non-standard working capital items — lose the most. The irony is that the companies where normalization strips the most information are often the companies where that information matters most for analysis.

---

## The Bottom Line

Financial data doesn't flow directly from the SEC to your screen. It passes through aggregators who normalize it for comparability, then through platforms who format it for display. At each step, information is removed — company-specific line items, granular instrument breakdowns, cash flow decomposition, and the XBRL tags that make verification possible.

This pipeline was built for efficiency and breadth. It works well for its intended purpose. But every investment decision you make using this data inherits its limitations — with no way to see them, no way to measure them, and no way to correct for them.

GeminIQ takes the direct path: EDGAR to your screen, with every XBRL tag intact.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-financial-data-reaches-investors)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Section 9d: Earnings Reaction Patterns
source: https://www.geminiq.com/blog/stock-price-reaction-after-earnings

### How Stocks React After Earnings: 17-Year Filing Study
We analyzed 578 SEC filings across 7 companies and 17 years of financial and market data. The finding that will change how you read earnings: the filings with the strongest fundamentals produced the weakest subsequent returns. Here's the full data.

After a company files its 10-K or 10-Q with the SEC, what happens to the stock? Not the day-of earnings reaction — every financial website tracks that. The question is what happens over the following one, two, three, six, and twelve months. And the more important question: does the quality of the filing — the revenue growth, the margin trajectory, the earnings trend — predict where the stock goes next?

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-price-reaction-after-earnings)**

We analyzed 578 filings across 7 companies — Apple, Microsoft, JPMorgan Chase, Johnson & Johnson, Caterpillar, UnitedHealth Group, and Deckers Outdoor — spanning 17 years of post-filing return data and fundamental financial data from GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) and [XBRL-tagged financial statements](/features#financial-statements).

The headline finding: **companies that filed declining revenue produced a median 12-month return of +26.7%. Companies that filed revenue growth above 5% produced a median of +14.4%.** The relationship between filing quality and subsequent returns is not what most investors expect — and understanding why is the key to using post-filing data correctly.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-price-reaction-after-earnings)**

---

## The Aggregate Pattern: Time Favors Holders

Across all 116 annual 10-K filings in our dataset, the probability of positive returns increases monotonically with time:

| Time After Filing | % Positive | Median Return |
|---|---|---|
| 1 month | 53% | +0.6% |
| 3 months | 64% | +3.5% |
| 6 months | 70% | +7.6% |
| 12 months | 75% | +14.9% |

At the one-month mark, annual filings are essentially a coin flip — 53% positive. By twelve months, three out of four filings are followed by positive returns, with a median gain of +14.9% and a mean of +18.7%.

But this aggregate conceals the most interesting finding in the data — which becomes visible only when you layer the fundamentals.

---

## The Counterintuitive Finding: Weak Filings, Strong Returns

The natural assumption is that companies filing strong earnings should produce better subsequent stock returns than companies filing weak earnings. The data shows the opposite.

### Revenue Growth vs. 12-Month Return

| Revenue Growth at Filing | Filings | Median 12M | Mean 12M | % Positive |
|---|---|---|---|---|
| Revenue declined | 18 | **+26.7%** | +29.9% | 83% |
| Revenue grew >5% | 55 | +14.4% | +17.4% | 82% |

Companies that filed declining revenue generated nearly double the median 12-month return of companies that filed solid revenue growth. And the positive hit rate was virtually identical — 83% vs. 82%.

### "Good" vs. "Bad" Earnings

Defining "good" as both revenue growth and EPS growth positive, and "bad" as either declining:

| Earnings Quality | Filings | Median 12M | Mean 12M | % Positive |
|---|---|---|---|---|
| Good (rev + EPS grew) | 53 | +13.9% | +17.3% | 79% |
| Bad (rev or EPS declined) | 31 | **+16.7%** | +22.2% | 81% |

"Bad" earnings produced higher median returns, higher mean returns, and a higher positive hit rate than "good" earnings.

### The "Double Beat" Paradox

The most counterintuitive result: filings where revenue grew AND gross margins expanded — the strongest possible fundamental signal — produced the weakest subsequent returns.

| Filing Quality | Filings | Median 12M | Mean 12M | % Positive |
|---|---|---|---|---|
| Revenue growth + margin expansion | 36 | +11.7% | +12.5% | 69% |
| Everything else | 48 | **+23.0%** | +24.0% | 88% |

Filings that weren't "double beats" outperformed by 11 percentage points in median return and were positive 88% of the time vs. 69%.

### Why This Happens

The explanation is not that weak fundamentals cause strong returns. It's that post-filing returns are driven by the gap between expectations and reality — not by the absolute quality of the filing.

When a company files declining revenue, the market has usually already priced in the decline. The stock has been sold down ahead of the filing. If the decline isn't as bad as feared, or if the balance sheet is stronger than expected, or if the company provides a credible path to recovery, the filing becomes the catalyst for repricing upward. The bad news was the expectation; the filing confirming "not as bad as feared" is the surprise.

Conversely, when a company files strong revenue growth and expanding margins, the market has often priced in the strength. The stock has already rallied ahead of the filing. Even excellent results may merely confirm what was expected — producing modest post-filing drift rather than a meaningful move.

This is why the [Earnings Market Reaction Heatmap](/features#price-variance) exists alongside XBRL-tagged [financial statements](/features#financial-statements) and [calculated metrics](/features#calculated-metrics) on GeminIQ. The filing tells you what happened. The heatmap tells you what the market did with that information. Neither is complete without the other.

---

## Apple: The Case Study in Fundamentals vs. Returns

Apple's 17-year filing history is the perfect illustration. Here are the fundamentals alongside the heatmap for every annual filing:

| FY | Revenue | Rev Growth | EPS Growth | Gross Margin | GM Change | ROIC | 12M Return |
|---|---|---|---|---|---|---|---|
| 2011 | $108.2B | +66% | +82% | 40.5% | +1.1pp | 48% | **+75.5%** |
| 2012 | $156.5B | +45% | +59% | 43.9% | +3.4pp | 52% | **-17.0%** |
| 2013 | $170.9B | +9% | -10% | 37.6% | -6.2pp | 30% | +37.4% |
| 2015 | $233.7B | +28% | +43% | 40.1% | +1.5pp | 35% | -3.5% |
| 2016 | $215.6B | -8% | -10% | 39.1% | -1.0pp | 24% | **+33.7%** |
| 2019 | $260.2B | -2% | -0.4% | 37.8% | -0.5pp | 30% | **+82.3%** |
| 2020 | $274.5B | +6% | +11% | 38.2% | +0.4pp | 38% | +35.8% |
| 2021 | $365.8B | +33% | +71% | 41.8% | +3.5pp | 62% | **+1.0%** |
| 2023 | $383.3B | -3% | +0.1% | 44.1% | +0.8pp | 64% | +29.6% |
| 2024 | $391.0B | +2% | -0.8% | 46.2% | +2.1pp | 64% | +15.1% |

Three milestone cases tell the story:

**FY2012: The best earnings Apple ever filed produced its worst return.** Revenue surged 45%, EPS grew 59%, gross margins expanded 3.4 percentage points to 43.9%, and ROIC was 52%. On every fundamental metric, this was Apple at peak performance. The 12-month return: **-17.0%** — the worst in the entire 17-year dataset. The market had priced in the iPhone-driven supercycle. Peak earnings became peak stock.

**FY2021: Monster results, flat stock.** Revenue exploded 33%, EPS grew 71%, gross margins expanded 3.5 percentage points, and ROIC jumped from 38% to 62%. The most impressive year-over-year improvement in Apple's recent history. The 12-month return: **+1.0%**. The pandemic-driven acceleration was already reflected in the stock price.

**FY2019: Declining revenue, best return ever.** Revenue fell 2%, EPS was essentially flat, and gross margins contracted 0.5 percentage points. This was Apple's weakest filing since FY2016. The 12-month return: **+82.3%** — the best in the dataset by a wide margin. The market had oversold Apple on trade war fears and iPhone demand concerns. The "weak" filing was actually better than feared.

The pattern is unmistakable: Apple's strongest fundamentals corresponded to its weakest subsequent returns, and vice versa. The filing data was essential for understanding the business. The heatmap data was essential for understanding the stock.

> **GeminIQ Tip:** Apple's Earnings Market Reaction Heatmap is available on [GeminIQ](/stocks/AAPL), showing every filing's 1-through-12-month return alongside the [XBRL-tagged financial statements](/features#financial-statements) and [90+ calculated metrics](/features#calculated-metrics) that provide the fundamental context. You can see both the fundamentals and the market's reaction in one view.

---

## The Seven-Company Scorecard

Here is the complete 10-K summary for each company, ranked by median 12-month post-filing return:

| Company | Sector | Filings | Med 1M | Med 3M | Med 6M | Med 12M | % Pos 12M | Best 12M | Worst 12M |
|---|---|---|---|---|---|---|---|---|---|
| AAPL | Technology | 17 | +0.5% | +3.6% | +6.1% | +30.5% | 88% | +82.3% | -17.0% |
| MSFT | Technology | 16 | +1.0% | +0.9% | +10.4% | +22.4% | 87% | +44.0% | -5.8% |
| UNH | Healthcare | 17 | +3.1% | +4.7% | +13.4% | +16.4% | 88% | +50.1% | -22.1% |
| CAT | Industrials | 17 | -1.1% | +4.7% | +2.4% | +13.8% | 69% | +76.8% | -26.9% |
| JPM | Financials | 17 | -1.8% | -3.2% | +3.9% | +13.6% | 62% | +53.3% | -18.1% |
| JNJ | Healthcare/Staples | 17 | +1.6% | +2.7% | +7.0% | +10.7% | 81% | +34.0% | -7.1% |
| DECK | Consumer (Mid-Cap) | 15 | +0.4% | +6.4% | +14.4% | +6.0% | 50% | +79.0% | -44.0% |

---

## Caterpillar: Where the Contrarian Signal Is Strongest

Caterpillar's data produces the most dramatic examples of weak fundamentals followed by exceptional returns — because the cyclical amplification of industrial earnings creates the widest expectation gaps.

| FY | Revenue | Rev Growth | EPS Growth | Gross Margin | ROIC | 12M Return |
|---|---|---|---|---|---|---|
| 2015 | $44.1B | -20% | -29% | 24.0% | 18% | **+49.0%** |
| 2016 | $38.5B | -13% | -103% (loss) | 26.5% | 0% | **+75.7%** |
| 2019 | $53.8B | -2% | +4% | 31.9% | 65% | **+45.5%** |
| 2024 | $64.8B | -3% | +10% | 38.0% | 57% | **+76.8%** |

Caterpillar's FY2016 is the most extreme example in the entire dataset: **revenue declined 13%, the company reported a net loss (EPS -103%), and ROIC collapsed to near zero.** Twelve months later, the stock was up 75.7% — the third-best 10-K return across all 7 companies and 17 years.

What happened? By the time CAT filed its FY2016 10-K, the market had already priced in the commodity downturn and global capex decline. The stock had been punished for two years. The 10-K confirmed the weakness — but the trough in CAT's cycle was already visible in the balance sheet. Working capital was being managed conservatively. Free cash flow remained positive at $4.5 billion. And the commodity cycle was beginning to turn.

In contrast, CAT's FY2011 filing — revenue surging 44%, EPS up 81%, ROIC at 45% — was followed by a -13.2% twelve-month return. Peak cycle earnings, peak stock.

The cycle plays out repeatedly: CAT FY2015 (-20% revenue → +49.0% return), FY2019 (-2% revenue filed just before COVID → +45.5%), and FY2024 (-3% revenue → +76.8%). Each time, the "weak" filing occurred at or near the trough, and the market repriced over the following year.

---

## Microsoft: Consistent Quality, Consistent Recovery

Microsoft's fundamental trajectory is the steadiest in the dataset — sixteen consecutive years of revenue growth (except FY2016), with operating margins expanding from 38.6% in FY2010 to 45.6% in FY2025 and ROIC easing from 38% to 32% as the business scaled.

| FY | Revenue | Rev Growth | EPS Growth | Op Margin | ROIC | 12M Return |
|---|---|---|---|---|---|---|
| 2016 | $85.3B | -9% | +42% | 23.7% | 15% | +29.8% |
| 2019 | $125.8B | +14% | +138% | 34.1% | 25% | **+44.0%** |
| 2021 | $168.1B | +18% | +40% | 41.6% | 34% | **-5.8%** |
| 2022 | $198.3B | +18% | +20% | 42.1% | 37% | +22.4% |
| 2024 | $245.1B | +16% | +22% | 44.6% | 34% | +18.2% |

The contrarian pattern appears here too: FY2021 — the strongest combination of growth and margin expansion in Microsoft's recent history (+18% revenue, +40% EPS, 41.6% operating margins) — produced the only negative 12-month return (-5.8%). Meanwhile, FY2016 — the only year revenue declined — was followed by a +29.8% return.

But Microsoft's most notable feature is its **83% dip-recovery rate**: five out of six times the stock was down three months after the 10-K filing, it recovered to positive territory by month twelve. This recovery rate is the highest in the dataset, reflecting the depth of analyst coverage and institutional ownership that efficiently prices MSFT over time.

---

## JPMorgan Chase: Financials Behave Differently

JPMorgan's fundamentals are structurally different from the other companies — as a bank, its "revenue" includes net interest income and noninterest revenue, and its "gross margin" reflects the spread business rather than product economics. But the filing-to-return relationship follows the same contrarian pattern.

JPM's strongest 12-month returns followed filings with pedestrian or weak fundamentals:

- **FY2015** (revenue -0.7%, net margin 24.0%): **+53.3%** twelve-month return
- **FY2016** (revenue flat, net margin 23.9%): **+31.2%**
- **FY2024** (revenue +12%, EPS +22%): **+21.5%** — but this was the second-strongest filing, confirming that even for JPM, the moderate-growth filings outperformed

JPM's unique feature is the **negative median first-month return (-1.8%)** — the weakest short-term post-filing behavior in the dataset. Bank 10-Ks are filed in February, into the macroeconomic uncertainty of a new year. The market takes months to validate whether the credit quality and margin trends in the filing will persist. By month six, the median turns positive (+3.9%), and by twelve months the pattern resolves favorably 62% of the time.

---

## Johnson & Johnson: The Stability Benchmark

JNJ's filing data demonstrates what the contrarian pattern looks like in a low-volatility defensive name. The one-month return range (-9.4% to +6.9%) and twelve-month range (-7.1% to +34.0%) are the narrowest in the dataset — roughly half the spread of AAPL.

The fundamental-return correlation tells the same story but in a muted register:

- **FY2024** (revenue +4%, EPS -58%): **+34.0%** — the best 12-month return in JNJ's dataset, following a filing with sharply declining earnings
- **FY2014** (revenue +4%, EPS +24%, margins expanding): **-1.8%** — flat to slightly negative despite strong fundamentals

JNJ's post-filing pattern is characteristic of the defensive sector: lower ceiling, higher floor, and the same contrarian relationship between filing quality and subsequent returns — just with smaller amplitude. For investors using GeminIQ's [Dividend Growth Screen](/screens/stock-screeners/dividend-growth), JNJ's heatmap provides reassurance: 81% positive at twelve months with a worst case of just -7.1%.

---

## UnitedHealth: What a Structural Break Looks Like

UNH carried one of the strongest track records in the dataset: 88% positive at twelve months, median +16.4%, with fifteen consecutive filings (FY2009–FY2023) producing only one marginally negative twelve-month return (-0.4% in FY2011).

The fundamentals supported the pattern — UNH grew revenue from $87 billion to $400 billion over the period, with operating margins holding steady near 8% and ROIC consistently around 17-21%. This was a textbook compounder.

Then FY2024 broke the pattern. The filing itself reported $400.3 billion in revenue (+8% growth) with 8.1% operating margins — solid numbers. The first-month return was +10.8%, which appeared to confirm the historical pattern. But the subsequent three months brought a -37.4% collapse, extending to -45.8% at six months and -22.1% at twelve months.

The fundamentals in the filing didn't predict this. The break came from outside: a CEO change, a DOJ investigation into billing practices, and a fundamental repricing of managed care regulatory risk. The filing's EPS decline of -35% was a signal — but the magnitude of the subsequent stock decline far exceeded what the filing data alone would suggest.

This is the essential lesson: post-filing patterns are base rates built on the assumption that the company's competitive position and regulatory environment remain structurally intact. When that assumption breaks — as it did for UNH in 2024 — the historical pattern is void. GeminIQ's [insider transaction timeline](/features#insider-transactions) and the filing's own [risk factors](/blog/how-to-read-10-k) provide the supplementary signals for detecting structural breaks before they show up in the stock price.

---

## Deckers Outdoor: Mid-Cap Amplification

Deckers (DECK) — the parent of HOKA and UGG — is the mid-cap in our dataset. Its twelve-month return range of -44.0% to +79.0% (a 123 percentage point spread) is roughly triple JNJ's range. Only 50% of DECK's annual filings were followed by positive twelve-month returns — essentially a coin flip.

The contrarian pattern is present but less reliable in mid-caps. DECK's best twelve-month returns (+79.0% in FY2022, +72.7% in FY2020) followed periods of negative sentiment. But its dip-recovery rate is just 20% — only 1 of 5 three-month dips recovered by month twelve, compared to 83% for Microsoft. The thinner analyst coverage and less efficient pricing mean that mid-cap dips are as likely to reflect genuine revaluation as temporary overreaction.

---

## The Contrarian Signal: What It Means for Your Research

The data across all seven companies tells a consistent story: **post-filing returns are not driven by the absolute quality of the filing. They are driven by the gap between what the market expected and what the filing revealed.**

This has three practical implications:

**1. The filing alone is not enough.** Reading the 10-K (see our guide: [How to Read a 10-K](/blog/how-to-read-10-k)) tells you what happened. But to assess whether the stock is likely to appreciate, you also need to know what the market already priced in. A "bad" filing that's better than feared (Apple FY2019, Caterpillar FY2016) can produce enormous returns. A "great" filing that merely confirms expectations (Apple FY2012, FY2021) can produce nothing — or worse.

**2. The heatmap provides the missing context.** GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows you the historical relationship between filings and returns for any company — across every quarter and every annual filing in the XBRL era. When a stock drops after a strong filing, the heatmap tells you whether similar drops have historically been buying opportunities or signals of further decline.

**3. Fundamental quality still matters — for the long term.** The contrarian signal operates on a twelve-month timeframe. Over the full 17-year period, the companies with the strongest fundamental trajectories (Apple, Microsoft, UnitedHealth) also produced the strongest cumulative returns. Quality compounds. But within any given filing cycle, the expectation gap dominates the return.

---

## How to Use Filing Data and the Heatmap Together

**Before the filing:** Check the heatmap. Understand the company's historical post-filing pattern. Apple at 88% positive is a very different base rate than DECK at 50%.

**Read the filing:** Use GeminIQ's [XBRL-tagged financial statements](/features#financial-statements) and [calculated metrics](/features#calculated-metrics) to assess the fundamentals: [revenue growth](/metrics/growth-metrics/revenue-growth), [margin trends](/metrics/margin-metrics/gross-profit-margin), [ROIC](/metrics/returns-and-profitability/return-on-invested-capital), [free cash flow](/metrics/valuation-metrics/free-cash-flow-yield). Is the business improving, stable, or deteriorating?

**Assess the expectation gap:** Compare the filing quality to what the market appeared to be pricing. A stock that dropped 20% ahead of the filing has a lower expectation bar than one that rallied 20%. Check [insider transactions](/features#insider-transactions) — are insiders buying the dip? Check [institutional ownership](/features#institutional-ownership) — is professional capital accumulating or distributing?

**Calibrate by company type:** For large-cap technology (AAPL, MSFT): the base rate is strong, dip-recovery is reliable, and weak filings after sell-offs have historically been buying opportunities. For cyclicals (CAT): the contrarian signal is the strongest but the timing is noisiest. For defensives (JNJ): the range is narrow and the outcomes are consistent. For mid-caps (DECK): the base rate is essentially a coin flip — require fundamental confirmation before acting.

**Use the screener to find opportunities.** GeminIQ's [Stock Screener](/features#screener) lets you filter for companies with strong underlying quality — high [ROIC](/metrics/returns-and-profitability/return-on-invested-capital), conservative [leverage](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), growing [free cash flow](/metrics/valuation-metrics/free-cash-flow-yield) — that may be temporarily mispriced after a "weak" filing. The [Buffett-Style Screen](/screens/stock-screeners/buffett-style) and [Quality Compounder Screen](/screens/stock-screeners/quality-compounder) identify the durable businesses where the contrarian signal is most reliable.

---

## Frequently Asked Questions

### Does this mean I should avoid companies with strong earnings?
No. The data shows that filing quality alone doesn't predict subsequent returns — expectations matter more. Companies with strong fundamentals compound value over years. But within any single filing cycle, a "strong" filing can produce flat or negative returns if the strength was already priced in. The heatmap helps you distinguish between the two.

### How far back does the Earnings Market Reaction Heatmap go?
The heatmap covers the full XBRL era — approximately 17 years of filing data, going back to 2009 for large accelerated filers.

### Does the heatmap track 10-Q filings as well as 10-Ks?
Yes. Every quarterly 10-Q and annual 10-K filing has its own entry in the heatmap. This analysis covers 116 annual filings and 462 quarterly filings across the 7 companies studied.

### Can post-filing return patterns predict future performance?
Past patterns establish base rates, not predictions. The heatmap is a tool for contextualizing current filing reactions against historical behavior. UNH's FY2024 experience — a broken 15-year positive streak — is the clearest reminder that base rates have limits.

### Why do mid-caps behave so differently from large-caps?
Thinner analyst coverage, lower institutional ownership, and less efficient price discovery. DECK's 12-month return standard deviation of 42.7% is roughly double any large-cap in our dataset. The expectation gap is wider and noisier, making the contrarian signal less reliable.

### Can I see this data — fundamentals and heatmap together — for any company on GeminIQ?
Yes. The Earnings Market Reaction Heatmap, XBRL-tagged financial statements, and 90+ calculated metrics are available on every company page on GeminIQ for every filing in the company's history.

---

## The Bottom Line

Across 578 filings and 17 years of data, the most important finding is not that stocks tend to go up after filings — they do (75% positive at twelve months). It's that **the quality of the filing does not predict the magnitude or direction of the subsequent return.** Revenue decliners outperformed revenue growers. "Bad" earnings outperformed "good" earnings. The strongest possible fundamental signal — revenue growth plus margin expansion — produced the weakest median return.

The explanation is straightforward: markets are forward-looking. By the time a filing lands, the results are partially or fully priced in. The post-filing return is driven by the gap between expectations and reality, not by the reality alone. And that gap is only measurable when you have both the fundamental data (what was filed) and the behavioral data (what the market did with it).

GeminIQ provides both: XBRL-tagged financial statements showing exactly what the company reported, alongside the Earnings Market Reaction Heatmap showing exactly how the market responded — for every filing, for every company, across 17+ years of history.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-price-reaction-after-earnings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Post-filing market reaction is measured from each filing's filed date. Methodology: [Filing Data Study Methodology](/blog/filing-data-study-methodology).

---

## Blog: Return on Invested Capital (ROIC) Formula and Benchmarks
source: https://www.geminiq.com/blog/roic-return-on-invested-capital-explained

### Return on Invested Capital (ROIC) Formula and Benchmarks
Return on Invested Capital (ROIC) measures after-tax operating profit per dollar of capital deployed — the single most important metric for evaluating long-term business quality. This guide covers the NOPAT formula, invested capital calculation, WACC spread, and benchmarks.

**Return on invested capital (ROIC) is NOPAT divided by invested capital — the after-tax operating profit a company earns on each dollar of debt and equity it has put to work.** A ROIC above the company's cost of capital, typically 7% to 12% for US companies, means the business creates value; across US companies above $2 billion in market capitalization, the median ROIC is about 9.7%.

Return on Invested Capital (ROIC) is the metric serious investors reach for when they want to know whether a business actually creates value — not whether it looks profitable, not whether revenue is growing, but whether the company earns more on every dollar it deploys than that dollar costs to obtain. Most investors have heard of it. Most financial websites display a number labeled ROIC. The problem is that ROIC is one of the most methodology-sensitive metrics in fundamental analysis, and the number on your favorite aggregator is almost certainly not calculated from the actual filing. The effective tax rate gets replaced with a flat statutory assumption. Excess cash stays in the denominator, dragging down returns for capital-light businesses sitting on large cash positions. Trailing twelve-month figures get swapped for stale fiscal-year snapshots. Each shortcut looks minor in isolation. Together they can move the calculated ROIC for the same company in the same period by ten percentage points or more. This guide covers the ROIC formula, the benchmarks, where the metric breaks — and how GeminIQ calculates it directly from XBRL-tagged filing data so the number you see is the number the company reported.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=roic-return-on-invested-capital-explained)**

---

## Table of Contents

- [ROIC Quick Reference](#roic-quick-reference)
- [What Is Return on Invested Capital?](#what-is-return-on-invested-capital)
- [The ROIC Formula](#the-roic-formula)
- [How to Calculate NOPAT](#how-to-calculate-nopat)
- [How to Calculate Invested Capital](#how-to-calculate-invested-capital)
- [ROIC Benchmarks: What Is a Good ROIC?](#roic-benchmarks-what-is-a-good-roic)
- [ROIC vs. WACC: The Value Creation Test](#roic-vs-wacc-the-value-creation-test)
- [ROIC vs. ROE vs. ROA: Why ROIC Wins](#roic-vs-roe-vs-roa-why-roic-wins)
- [Why ROIC Differs So Dramatically Across Platforms](#why-roic-differs-so-dramatically-across-platforms)
- [Real-World Examples: What High and Low ROIC Looks Like](#real-world-examples-what-high-and-low-roic-looks-like)
- [When ROIC Breaks — and What to Do About It](#when-roic-breaks-and-what-to-do-about-it)
- [How to Find High-ROIC Companies at Scale](#how-to-find-high-roic-companies-at-scale)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## ROIC Quick Reference

| Element | Detail |
| --- | --- |
| Formula | ROIC = NOPAT ÷ Invested Capital |
| NOPAT | Operating income × (1 − effective tax rate) |
| Invested Capital | Total debt + total equity − excess cash |
| Good ROIC | ≥ 15% sustained; the value test is ROIC > WACC |
| Where it breaks | Flat statutory tax rate, excess cash left in the denominator, stale fiscal-year figures used instead of TTM |

## What Is Return on Invested Capital?

Return on Invested Capital (ROIC) measures how efficiently a company converts the total capital entrusted to it — by both debt holders and equity holders — into after-tax operating profit. For every dollar of capital deployed in the business, ROIC tells you how many cents of operating profit that capital generates.

This is different from asking how profitable the company is, or how fast it is growing. A company can be profitable and growing while simultaneously destroying economic value — if the return it earns on each new dollar invested falls below what investors could earn elsewhere at similar risk. ROIC is the metric that catches this. It is why Charlie Munger argued that over the long run, the return an investor earns on a stock will roughly approximate the underlying business's ROIC. The compounding math is straightforward: a business that earns **20% ROIC** on retained earnings doubles the economic value of every dollar it keeps inside the business approximately every 3.6 years. A business earning **8% ROIC** takes roughly 9 years to do the same — and if the cost of capital is 9%, it never does it at all.

ROIC is not a valuation metric. It does not tell you whether the stock is cheap or expensive. It tells you whether the underlying business is worth compounding into, regardless of price. That is a different and, for long-term investors, more important question.

---

## The ROIC Formula

ROIC = NOPAT (TTM) ÷ Average [Invested Capital](/metrics/calculated-values/invested-capital)

Where:
- **NOPAT** = Net Operating Profit After Tax = EBIT × (1 − Effective Tax Rate)
- **Excess Cash** = Total Cash − Operating Cash (estimated as 2% of TTM Revenue, capped at total cash)
- **Invested Capital** = Total Equity + Total Debt − Excess Cash
- **Average Invested Capital** = (Invested Capital current period + Invested Capital same period prior year) ÷ 2

The trailing twelve-month (TTM) convention matters because it captures four full quarters of operating performance regardless of fiscal year boundaries — more representative than any single annual period for companies with seasonal or lumpy earnings patterns.

---

## How to Calculate NOPAT

Net Operating Profit After Tax (NOPAT) is the operating profit the business would generate if it had no debt — it strips out the tax benefit of interest expense and shows the after-tax earnings available to all capital providers. Two companies with identical operations but different leverage levels will show different net income, but identical NOPAT. That comparability is precisely the point.

**NOPAT = EBIT (TTM) × (1 − Effective Tax Rate)**

EBIT — Earnings Before Interest and Taxes — is either reported directly on the income statement or derived as Net Income + Income Tax Expense + Interest Expense. In XBRL-tagged SEC filings, the relevant line items are `OperatingIncomeLoss` (for operating income, which is equivalent to EBIT for most companies), `IncomeTaxExpense`, and `InterestExpense`.

The effective tax rate is where most platforms go wrong. A fixed **21% statutory rate** is commonly applied across every US public company because it is easy to implement at scale. The actual effective tax rate — derived by dividing income tax expense by pretax income from the filed 10-K or 10-Q — can differ substantially. Companies with significant foreign income, R&D tax credits, deferred tax assets, or loss carryforwards routinely report effective tax rates between **12% and 30%**. Applying the wrong rate to the same EBIT number produces a different NOPAT and therefore a different ROIC, sometimes by five percentage points or more for the same company in the same year.

GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) uses each company's actual filed effective tax rate, derived from the XBRL tags `IncomeTaxExpenseBenefit` and `IncomeLossFromContinuingOperationsBeforeIncomeTaxesExtraordinaryItemsNoncontrollingInterest`, rather than a fixed statutory assumption. When the effective rate cannot be reliably calculated — typically for loss-making periods or unusual tax situations — GeminIQ falls back to the 21% federal statutory rate with that caveat disclosed.

---

## How to Calculate Invested Capital

Invested capital is the total capital deployed in the business by both debt and equity investors, net of excess cash. There are two methodologically sound approaches to calculating it, and understanding the difference explains most of the platform-to-platform variation you will encounter.

**The Financing Approach (GeminIQ's Method):**

Invested Capital = Total Equity + Total Debt − Excess Cash

Where:
- **Total Debt** = Short-Term Debt + Long-Term Debt (XBRL tags: `ShortTermBorrowings` + `LongTermDebtNoncurrent`)
- **Total Equity** = Total Shareholders' Equity as reported (XBRL tag: `StockholdersEquity`)
- **Excess Cash** = Total Cash − Operating Cash Reserve, where the operating cash reserve is estimated as the smaller of total cash and 2% of trailing twelve-month revenue

The logic for subtracting excess cash is critical: cash sitting on the balance sheet above what the business needs for day-to-day operations is not invested in the business. Including it in invested capital would understate ROIC by artificially inflating the denominator with capital that is generating no operating return. A company sitting on **$50 billion in cash** against a **$20 billion operational capital base** is not actually deploying **$70 billion** in the business — and ROIC should not pretend it is.

**The Operating Approach (Alternative):**

Invested Capital = Net Working Capital + Net Fixed Assets + Other Long-Term Operating Assets

This approach builds invested capital from the asset side of the balance sheet, classifying each asset as either operating or financial. It can be more granular but requires judgment calls about how to classify items that vary across companies — goodwill treatment, operating lease right-of-use assets, deferred taxes. The financing approach sidesteps these judgment calls entirely by working from the funding side, which is why it is more robust when comparing companies that reclassify items across reporting periods.

Both approaches should produce similar results for the same company. When they diverge materially, the divergence itself is informative — it usually points to unusual balance sheet structure that warrants deeper investigation.

---

## ROIC Benchmarks: What Is a Good ROIC?

ROIC benchmarks are not universal — they must be interpreted against the company's cost of capital and its sector. That said, the following ranges apply broadly across US public companies.

A ROIC **below 8%** suggests the business may be earning less than its cost of capital for most companies in most industries. This does not automatically make it a bad business — capital-intensive industries like utilities, telecom infrastructure, and basic materials structurally operate at lower returns — but it flags a potential value-destruction situation that requires further analysis.

A ROIC **between 8% and 15%** is average. The business is likely covering its cost of capital, compounding at a modest rate, and not obviously destroying value — but it is not creating the kind of durable excess returns that drive long-term compounding.

A ROIC **above 15%** is strong and clears the estimated cost of capital for most US companies, which typically ranges from **7% to 12%** depending on beta, leverage, and capital structure. A business sustaining above-**15%** ROIC across a full economic cycle is demonstrating that its competitive position is real enough to defend against competitive erosion.

A ROIC **above 25%** is exceptional. Businesses that sustain returns above **25%** for five or more consecutive years typically possess a genuine economic moat — a durable structural advantage that allows them to earn returns well above what new entrants could achieve. The S&P 500 median ROIC across a full cycle runs roughly **10% to 12%**. Companies clearing **25%** are in the top quartile.

### What the Filing Data Shows

GeminIQ's own numbers put those ranges in context. Across US companies above $2 billion in market capitalization, excluding banks, insurers, and REITs, the median ROIC is **9.7%**, and the middle half fall between **3.1%** and **19.0%**. For companies above $10 billion the median rises to **12.1%**, and about **28%** of companies above $2 billion earn more than 15%.

| Industry | Median ROIC | Middle 50% |
| --- | --- | --- |
| Pharma & biotech | -43.9% | -89.9% – 0.0% |
| Medical devices | 3.7% | -8.4% – 11.9% |
| Software & IT services | 4.9% | -6.5% – 16.8% |
| Telecom & media | 5.5% | 0.0% – 8.6% |
| Utilities | 6.0% | 5.0% – 8.4% |
| Food & beverage | 7.4% | 2.5% – 15.2% |
| Oil & gas | 8.2% | 2.0% – 15.2% |
| Industrial manufacturing | 8.5% | 3.5% – 15.9% |
| Transportation | 8.8% | 1.7% – 15.2% |
| Semiconductors & hardware | 10.1% | 0.0% – 20.3% |
| Retail | 14.9% | 6.8% – 29.3% |

Banks, insurers, and REITs are left out because invested capital is not a meaningful base for them: deposits, policyholder funds, and property financing make up most of their capital. Figures are GeminIQ calculations from each company's latest reported period as of September 2026; the middle 50% runs from the 25th to the 75th percentile, and industries are grouped by SIC code for companies above $300 million in market capitalization.

The most important single-period benchmark is not a fixed percentage but the spread over the cost of capital. A **15% ROIC against a 9% cost of capital** produces a spread of 600 basis points — the company is creating **$0.06 of economic value for every dollar of invested capital**. A **25% ROIC against a 20% cost of capital** produces a spread of only 500 basis points, despite the higher absolute return. Spread matters as much as level.

---

## ROIC vs. WACC: The Value Creation Test

The ROIC vs. [WACC](/blog/how-to-calculate-wacc-from-10k) comparison is the clearest conceptual test of whether a business is creating or destroying shareholder value. WACC — the Weighted Average Cost of Capital — represents the blended required return of the company's debt and equity holders. It is the minimum return the business must earn just to break even in economic terms.

**WACC = (Weight of Equity × Cost of Equity) + (Weight of Debt × After-Tax Cost of Debt)**

When ROIC exceeds WACC, the business is generating returns above what investors could earn elsewhere at similar risk. Every dollar reinvested into the business creates positive economic value. When ROIC falls below WACC, the business is destroying economic value — even if it shows positive accounting profits. Growth makes this situation worse, not better, because each incremental dollar invested compounds the value destruction.

The spread between ROIC and WACC — (ROIC − WACC) — is arguably the clearest quantitative expression of competitive advantage available from public filings. A wide, persistent spread signals a moat. A narrowing spread signals competitive erosion. An industry where the median ROIC consistently hovers near WACC — airlines are the canonical example, having operated near or below cost of capital through most economic cycles — tells you that competition has structurally eliminated the ability to earn excess returns at the industry level, regardless of revenue growth.

WACC is estimated, not observed. Small differences in the assumed equity risk premium, beta, or debt cost can shift the calculated WACC by two or three percentage points. Treat ROIC vs. WACC as a directional framework, not a precise calculation, and apply additional margin for error when the spread is narrow.

---

## ROIC vs. ROE vs. ROA: Why ROIC Wins

Return on Equity (ROE) and Return on Assets (ROA) both measure profitability against a capital base. ROIC does the same thing but eliminates the two most common distortions that make the other metrics misleading.

ROE is computed as Net Income ÷ Average Shareholders' Equity. The problem is the denominator. A company that finances its operations primarily with debt will show a smaller equity base, and even modest earnings will produce a high ROE. Two businesses with identical operations — same revenue, same operating margin, same capital base — will show materially different ROEs if one carries **$5 billion in debt** and the other carries none, simply because the levered company has eroded its equity base through the interest burden. ROE cannot distinguish between operational excellence and financial engineering. ROIC can, because it includes total debt in the denominator and uses NOPAT — which strips out the tax benefit of interest — in the numerator.

ROA (Net Income ÷ Average Total Assets) partially addresses the leverage problem because total assets include debt-financed assets. But it carries its own distortion: total assets include excess cash, goodwill from acquisitions, and other financial assets that generate no operating return. A company that made a poor acquisition ten years ago and wrote down the goodwill to zero has a smaller asset base and therefore an artificially higher ROA. A company sitting on a large cash pile has a larger asset base and an artificially lower ROA. Neither distortion has anything to do with operating performance.

ROIC addresses both. It uses NOPAT to neutralize leverage effects on the numerator and uses invested capital — net of excess cash, built from the financing side — to create a denominator that reflects only the capital genuinely at work in the business.

The practical consequence: when ROE and ROIC diverge significantly for the same company, investigate the balance sheet. The divergence almost always points to leverage, cash accumulation, or share buybacks that have compressed equity without improving operations. The ROIC will tell you the honest version.

---

## Why ROIC Differs So Dramatically Across Platforms

Pull the same company's ROIC from three different financial data platforms and you will frequently see three meaningfully different numbers. This is not a data error. It is a methodology problem.

The main sources of divergence are the effective tax rate, the excess cash assumption, the debt definition, and whether the platform uses trailing twelve months or the most recent fiscal year. A platform applying a flat **21% statutory rate** to a company with a **14% effective tax rate** is overstating NOPAT — and therefore overstating ROIC. A platform that does not subtract excess cash from invested capital is inflating the denominator for capital-light businesses with large balance sheet cash positions and understating their ROIC. A platform that includes operating lease right-of-use assets in invested capital without a corresponding adjustment for lease liabilities is applying the operating approach inconsistently.

These are not corner cases. For major technology companies where effective tax rates frequently run well below the statutory rate, ROIC differences of **5 to 10 percentage points** between platforms using different methodology are common. For companies with large cash positions — pharmaceuticals, technology platform businesses — the excess cash treatment alone can shift the number by **3 to 7 percentage points**.

GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) uses the financing approach with each company's actual effective tax rate from its SEC filing, a 2%-of-revenue operating cash reserve to determine excess cash, and TTM figures that roll forward with each new quarterly filing. Every input is sourced directly from XBRL-tagged SEC data — no aggregator adjustments, no fixed-rate assumptions applied uniformly across the universe.

---

## Real-World Examples: What High and Low ROIC Looks Like

The contrast between a high-ROIC and low-ROIC business becomes clearest when you look at industries where the structural economics differ at the business model level.

[Costco](/stocks/COST) ($COST) is one of the most striking examples of capital efficiency in the S&P 500. The business operates on a **3.82% operating margin** (Q3 FY2026 10-Q, period ended May 10, 2026) — a number that screams commodity retail when pulled out of context. But the ROIC tells a completely different story. GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) shows the TTM figure at **33.4%**. The mechanism is the membership float: members pay upfront in cash, Costco recognizes that revenue over twelve months, and suppliers are paid on 30+ day terms using inventory that customers have already purchased. The invested capital base stays remarkably small relative to the revenue volume flowing through it. A **3.82%** operating margin business earning **33.4% ROIC** is not a broken screener result — it is the membership model in action. See the full breakdown in the [Costco 10-Q teardown](/blog/costco-stock-analysis-2026).

At the other end of the spectrum, the airline industry illustrates what ROIC near or below the cost of capital looks like across a full cycle. Airlines generate revenue, report operating income in good years, and attract capital through periods of apparent growth. But the structural economics — high fixed costs, commodity fuel inputs, intense fare competition, heavy debt loads from aircraft financing — push industry ROIC toward or below the cost of capital in most periods. Growing revenue in a business earning insufficient ROIC does not create value; it accelerates value destruction by deploying more capital at inadequate returns. The [GeminIQ Airline Intel Brief](/blog/airline-sector-stock-analysis) tracks these dynamics across the major carriers using raw SEC filing data.

These two examples illustrate why ROIC is more informative than net income, revenue growth, or operating margin in isolation. The question is never "is the business profitable?" It is "does the business earn more than its cost of capital on each dollar it deploys?"

---

## When ROIC Breaks — and What to Do About It

ROIC is the most important metric for evaluating long-term business quality, but it has failure modes that matter in practice.

Large impairments and restructuring charges can temporarily reduce invested capital by writing down the asset base — goodwill impairments being the most common example. When a company takes a **$10 billion goodwill write-down**, its equity falls by **$10 billion** (net of tax), and invested capital shrinks. NOPAT, derived from operating income which is usually unaffected by below-the-line impairments, stays constant. The resulting ROIC spikes upward — not because the business improved, but because the denominator shrank. This is the single most common source of ROIC distortion. Always confirm that the invested capital figure in any period where an impairment was taken is representative of the normal operating capital base before using the ROIC number to draw conclusions.

Negative invested capital renders ROIC undefined or meaningless. Some businesses — particularly those with negative book equity due to aggressive buyback programs or accumulated deficits — can produce negative invested capital under the financing approach. GeminIQ sets ROIC to null in these periods rather than displaying a mathematically valid but economically meaningless number.

Early-stage and pre-revenue companies are structurally incompatible with ROIC analysis. The metric requires both a meaningful NOPAT and a meaningful invested capital base. A company spending heavily on R&D with no revenue has neither, and computing ROIC from those inputs tells you nothing useful about the business's long-term economics.

Businesses in heavy investment cycles — building manufacturing capacity, laying infrastructure, expanding distribution — will show temporarily depressed ROIC because capex inflates the invested capital base before the new assets generate proportional returns. Context matters: a company whose ROIC temporarily compresses from **22% to 16%** during a period of deliberate capacity expansion is not the same story as a company whose ROIC has structurally declined to **16%** because competition has eroded its pricing power. The trend over three to five years is more informative than any single period. ROIC that holds above the cost of capital across a full cycle is the signal. Everything else is noise about timing.

---

## How to Find High-ROIC Companies at Scale

The value of understanding ROIC at the conceptual level is limited without a practical way to apply it across a large universe of companies. Calculating ROIC manually from SEC filings for even ten companies is a multi-hour exercise — sourcing EBIT, effective tax rates, short and long-term debt, equity, and cash positions from individual filings and then normalizing the TTM figures. That is time most investors do not have, and it is why most investors never look at ROIC beyond what an aggregator happens to display on a company page.

GeminIQ's [Stock Screener](/features#screener) lets you filter across the full US public company universe using ROIC as a primary screen — stacked with additional conditions on leverage, free cash flow conversion, margin consistency, or revenue growth — all running on data pulled directly from XBRL-tagged SEC filings. The [Quality Compounder screen](/screens/stock-screeners/quality-compounder) is specifically designed around ROIC persistence: it identifies businesses that have consistently earned returns above the cost of capital across multiple filing periods, not just one strong quarter.

The distinction between "high ROIC now" and "consistently high ROIC across a cycle" is the most important filter in quality investing. A single period of elevated returns can reflect a commodity price spike, a one-time working capital benefit, or a low-invested-capital period following an impairment. Consistent high ROIC across five or more years is far harder to fake — it requires a genuine, defensible competitive advantage. That is the screen that matters, and it is the one that requires clean, unprocessed data to run correctly.

---

## Frequently Asked Questions

### What is the difference between ROIC and ROE?
ROE measures net income as a percentage of shareholders' equity. ROIC measures NOPAT as a percentage of invested capital — which includes both equity and debt, and nets out excess cash. ROE can be artificially inflated by leverage: a company with very little equity (because it has borrowed heavily) will show high ROE even if its operational returns are mediocre. ROIC is immune to this distortion because it puts debt in the denominator. For evaluating business quality independently of capital structure, ROIC is the correct metric.

### What is a good ROIC for a long-term investor?
Above **15%** is strong for most industries and typically clears the estimated cost of capital. Above **25%** is exceptional and usually indicates a durable competitive advantage — a business that competition has not been able to successfully enter or erode. The most important benchmark is the spread over the cost of capital, not the absolute number. A **15% ROIC against a 9% cost of capital** is creating meaningful economic value; a **15% ROIC against a 14% cost of capital** barely is.

### Why does ROIC look different on different financial websites?
Primarily because of three methodology differences: the effective tax rate applied to calculate NOPAT, whether excess cash is subtracted from invested capital, and whether TTM or fiscal-year figures are used. Platforms that apply a fixed **21% statutory rate** and skip the excess cash adjustment will produce materially different results from platforms that use actual filed tax rates and a financing-approach capital definition. The gap can be **5 to 10 percentage points** for the same company in the same period.

### Does high ROIC mean the stock will outperform?
Not necessarily, and not in the short term. ROIC measures business quality, not valuation. A company with **35% ROIC** priced at 60x earnings may be a worse investment than a company with **18% ROIC** priced at 12x earnings, depending on growth expectations and the durability of the competitive advantage. ROIC is most powerful as a long-term quality filter and a reinvestment return benchmark — it tells you whether the business creates value as it grows, not whether the current price is right.

### Can ROIC be negative?
Mathematically yes, but it is rarely meaningful. Negative ROIC typically results from a negative NOPAT (operating losses) or a negative invested capital base — more common than it sounds for companies with aggressive buyback histories or accumulated deficits. GeminIQ treats negative invested capital as a null case for ROIC rather than displaying a number that would imply positive returns from a capital-deficient structure.

### How often does ROIC update on GeminIQ?
GeminIQ's [Calculated Metrics](/features#calculated-metrics) — including Return on Invested Capital — update with each new SEC filing. For large accelerated filers reporting quarterly 10-Qs, that means four updates per year. The TTM calculation rolls forward automatically with each new quarterly data point, so the figure always reflects the most current four quarters of operating performance rather than a stale annual snapshot.

### Is ROIC the same as ROI?

No. ROI measures the gain on one specific investment relative to its cost, and it can be applied to anything from a marketing campaign to a stock purchase. ROIC measures a whole company's after-tax operating profit relative to all the debt and equity capital invested in the business, which makes it a measure of business quality rather than of a single decision.

### What is the difference between ROIC and ROCE?

ROCE divides pre-tax operating profit (EBIT) by capital employed, usually total assets minus current liabilities. ROIC divides after-tax operating profit (NOPAT) by invested capital, equity plus debt less excess cash. ROCE is the simpler, pre-tax version; ROIC is closer to the return shareholders and lenders actually keep.

---

### Related Reading

- [Costco Stock Analysis: How 3.8% Margin Earns 33% ROIC](/blog/costco-stock-analysis-2026) — the definitive case study in how capital efficiency and business model structure produce ROIC that headline metrics completely miss.
- [Airline Sector Stock Analysis: Intel Brief](/blog/airline-sector-stock-analysis) — how ROIC near the cost of capital has historically translated into poor long-term equity returns across the major carriers.
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary) — full definitions of ROIC, ROE, ROA, WACC, NOPAT, and every other metric referenced in this guide.
- [What Investors Miss in SEC Filings](/blog/what-investors-miss-in-sec-filings) — why the inputs for a correct ROIC calculation are hiding in plain sight in every 10-K and 10-Q, and how to find them.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=roic-return-on-invested-capital-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Company data cited in this article is sourced from SEC filings publicly available on EDGAR: [Costco Wholesale (COST)](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=COST&type=10-K&dateb=&owner=include&count=10).</sup>

---

## Blog: WACC Formula: How to Calculate It From a 10-K, Step by Step
source: https://www.geminiq.com/blog/how-to-calculate-wacc-from-10k

### WACC Formula: How to Calculate It From a 10-K, Step by Step
WACC has no single filed number to pull from a 10-K — it has to be built from the cost of debt, the cost of equity, and the company's actual capital structure. This guide builds a complete WACC estimate from Apple's most recent 10-K, line by line, then checks the result against GeminIQ's pre-calculated ROIC.

**The WACC formula is WACC = (E/V × Re) + (D/V × Rd × (1 − Tc)), where E and D are the market values of equity and debt, V is their total, Re is the cost of equity, Rd the cost of debt, and Tc the tax rate.** It is the blended annual return a company's shareholders and lenders require, and the hurdle its return on invested capital has to clear.

Search "how to calculate WACC" and most results hand you the WACC formula and stop there — three terms, a multiplication sign, and no indication of where the numbers actually come from. That gap matters more than it looks. Unlike revenue or [gross margin](/metrics/margin-metrics/gross-profit-margin), WACC is not sitting on any line of any filing waiting to be read — it has to be built, one input at a time, from a mix of what a company reports and what the market is pricing outside the filing entirely. This guide builds a complete WACC estimate from [Apple's](/stocks/AAPL) most recently filed 10-K — FY2025 (filed October 31, 2025, fiscal year ending September 27, 2025). Every filed input traces to its exact GeminIQ figure; every market-sourced input is flagged as exactly that. This guide checks the final number against GeminIQ's pre-calculated [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) — the entire reason WACC gets built in the first place.

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---

## Table of Contents

- [Why WACC Doesn't Show Up on Any Platform — GeminIQ Included](#why-wacc-doesnt-show-up-on-any-platform-geminiq-included)
- [The WACC Formula: What Actually Goes Into the Number](#the-wacc-formula-what-actually-goes-into-the-number)
- [Step 1: Pull the Capital Structure Weights From the Filing](#step-1-pull-the-capital-structure-weights-from-the-filing)
- [Step 2: Build the Cost of Debt — Why the Income Statement Alone Isn't Enough](#step-2-build-the-cost-of-debt-why-the-income-statement-alone-isnt-enough)
- [Step 3: Estimate the Cost of Equity With CAPM](#step-3-estimate-the-cost-of-equity-with-capm)
- [Step 4: Combine the Weights and Costs Into a Single WACC](#step-4-combine-the-weights-and-costs-into-a-single-wacc)
- [Step 5: Set the WACC Against GeminIQ's Pre-Calculated ROIC](#step-5-set-the-wacc-against-geminiqs-pre-calculated-roic)
- [Why This Estimate Moves — and What Actually Holds Steady](#why-this-estimate-moves-and-what-actually-holds-steady)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## Why WACC Doesn't Show Up on Any Platform — GeminIQ Included

WACC is not a metric GeminIQ calculates or displays on a company page, and it never will be — not because the calculation is difficult, but because two of its three inputs are not company data at all. A cost of equity estimate needs a risk-free rate and an equity risk premium, both pulled from the broader market rather than the filing. Every platform that displays a single WACC number has quietly picked a beta, a risk-free rate, and a risk premium on the user's behalf. None of it is labeled — which parts came from the 10-K, and which came from an assumption baked into the backend, look identical on the page.

That is precisely the distinction that matters for [Return on Invested Capital (ROIC)](/blog/roic-return-on-invested-capital-explained), the metric WACC exists to be compared against. ROIC is entirely reconstructible from filed data — NOPAT and [invested capital](/metrics/calculated-values/invested-capital) both trace back to specific XBRL tags, which is why GeminIQ calculates it directly and consistently for every company in its database. WACC cannot make that same claim, and a platform that displays one anyway is asking to be trusted on an assumption it never shows you. Every number below is marked as filed or market-sourced. Half of this estimate comes from Apple's balance sheet. The other half is a defensible guess.

---

## The WACC Formula: What Actually Goes Into the Number

**WACC = (Weight of Equity × Cost of Equity) + (Weight of Debt × After-Tax Cost of Debt)**

Three components, each built from a different source. The weights come from the capital structure — how much of the company is financed by equity versus debt, which is filed, observable data. The cost of equity comes from the Capital Asset Pricing Model, which is market data — a risk-free rate, a beta, and an equity risk premium, none of which appear anywhere in a 10-K. The cost of debt sits in between: it starts from the company's own borrowing. But when a company doesn't break interest expense out as a standalone line item — the case here — that cost has to be estimated from how the market is currently pricing its debt instead. The next three sections build one component each — then combine them into a single number.

---

## Step 1: Pull the Capital Structure Weights From the Filing

### What Are Capital Structure Weights?

The weights in the WACC formula answer a simple question: of the total capital financing the business, what share comes from equity holders and what share comes from debt holders? Both weights trace directly to filed data — no market assumption required for this step.

**The Data:** [Apple's](/stocks/AAPL) FY2025 balance sheet reports three interest-bearing debt line items: Commercial Paper (`Commercial Paper`: **$7.979 Billion**), Term Debt, Current (`Long Term Debt Current`: **$12.350 Billion**), and Term Debt, Non-Current (`Long Term Debt Noncurrent`: **$78.328 Billion**). Summed directly from the filing, that's **$98.657 Billion** in total interest-bearing debt — consistent with how GeminIQ defines [Total Debt](/metrics/calculated-values/total-debt) as Short-Term Debt plus Long-Term Debt, inclusive of current maturities. Against that, Apple's market capitalization at fiscal year end stands at **$3.80 Trillion**. Total invested capital, using market value of equity plus Total Debt, comes to **$3.894 Trillion**:

**Weight of Equity = $3.7956T / $3.894T = 97.47%**
**Weight of Debt = $98.657B / $3.894T = 2.53%**

The imbalance is the story before any cost assumption even enters the picture. [Apple's](/stocks/AAPL) capital structure is financed almost entirely by equity — its **$98.66 Billion** in Total Debt is a rounding error against a **$3.80 Trillion** market capitalization. That single fact means whatever cost of debt Step 2 estimates will barely move the final WACC number. A precise cost of debt matters enormously for a heavily levered company. For Apple, the equity side of the formula is doing nearly all the work.

<center><sup>GeminIQ Financial Statements showing Apple's three debt line items — Commercial Paper (`Commercial Paper`: $7.979 Billion), Term Debt, Current (`Long Term Debt Current`: $12.350 Billion), and Term Debt, Non-Current (`Long Term Debt Noncurrent`: $78.328 Billion), summing to $98.657 Billion in Total Debt — against Market Capitalization of $3.80 Trillion. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** Using market value of equity rather than book value is deliberate. Book equity reflects accumulated accounting history; market cap reflects what investors are actually paying today to own that equity — the more relevant weight for a forward-looking cost of capital. The tradeoff is that market cap moves every trading day while the debt figure stays fixed until the next filing. A WACC weight calculated the day after a sharp price move will look different from one calculated a month later — even though nothing about the underlying business changed.

---

## Step 2: Build the Cost of Debt — Why the Income Statement Alone Isn't Enough

### What Is the Cost of Debt Formula?

**After-Tax Cost of Debt = Pre-Tax Cost of Debt × (1 − Effective Tax Rate)**

The textbook version of this calculation divides a company's interest expense by its total debt to find an effective borrowing rate, then tax-adjusts it because interest is deductible. That approach assumes the company breaks interest expense out as its own line on the income statement. Pulling Interest Expense directly from GeminIQ's [Financial Statements](/features#financial-statements) for [Apple](/stocks/AAPL) returns **$0.00**. That is not because Apple pays no interest on its **$98.66 Billion** in Total Debt — it is because Apple's income statement nets interest expense against interest income earned on its marketable securities portfolio into a single combined "Other Income/(Expense), Net" line. Apple never files a standalone Interest Expense tag at all.

**The Data:** With no clean interest expense line to divide by total debt, the more defensible approach prices the debt the way the market currently does. Apple's own outstanding notes yield to maturity becomes the proxy for its current cost of debt. Apple's shorter-dated fixed-rate notes are currently trading to yield just over **5.02%**, consistent with where investment-grade technology-company debt has generally priced relative to Treasuries through mid-2026. Tax-adjusting that figure uses GeminIQ's pre-calculated Effective Tax Rate of **15.61%** — built from Income Tax Expense of **$20.719 Billion** against Pre-Tax Income of **$132.729 Billion** — well below the **21%** statutory federal rate.

**Pre-Tax Cost of Debt (~5.02%) × (1 − 15.61%) = After-Tax Cost of Debt of ~4.24%**

<center><sup>GeminIQ Calculated Metrics showing Apple's Effective Tax Rate (15.61%), built from Income Tax Expense ($20.719 Billion, XBRL tag `Income Tax Expense Benefit`) divided by Pre-Tax Income ($132.729 Billion, XBRL tag `Income Loss From Continuing Operations Before Income Taxes Extraordinary Items Noncontrolling Interest`), against the 21% statutory federal rate. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** Companies that report a standalone interest expense line make this step mechanical — divide interest expense by total debt, tax-adjust, done. Companies like Apple — with investment portfolios large enough that interest income offsets interest expense into a single net line — force a choice. Either dig through the notes to the financial statements for a gross interest expense figure that isn't always disclosed, or price the debt from the market instead, as this guide does. Either method is defensible. What is not defensible is dividing a net "Other Income/(Expense)" figure by total debt and calling the result a cost of debt. That number conflates two entirely different things, and it will materially understate the true borrowing cost.

---

## Step 3: Estimate the Cost of Equity With CAPM

### What Is the Capital Asset Pricing Model?

**Cost of Equity = Risk-Free Rate + (Beta × Equity Risk Premium)**

This is the point in the calculation where filed data stops entirely. All three CAPM inputs are market-observed, not company-reported, and none of them appear in a 10-K under any XBRL tag. The risk-free rate is typically the yield on a long-dated Treasury security — currently around **4.46%** on the 10-year. A widely-cited market assumption puts the equity risk premium at roughly **5%** for U.S. equities. Beta measures how volatile a stock's returns are relative to the broader market, and it is the input with the least agreement across data providers. Market data providers currently estimate [Apple's](/stocks/AAPL) beta anywhere from roughly **0.83** to **1.10**, depending on the lookback window and methodology used.

**The Data:** Running the CAPM formula across that beta range rather than a single point estimate:

**Low end: 4.46% + (0.83 × 5.0%) = 8.61%**
**High end: 4.46% + (1.10 × 5.0%) = 9.96%**

The midpoint of that range, roughly **9.29%**, is the figure this guide carries forward — but the range itself is the more honest output. A **135-basis-point** spread in the cost of equity — driven entirely by which beta estimate gets chosen — is a larger swing than most of the balance-sheet-level judgment calls that show up elsewhere in fundamental analysis. And it happens before a single dollar of Apple's actual financials enters the equation.

**When it breaks:** Beta is calculated from historical price returns, which makes it backward-looking by construction. It can shift meaningfully depending on whether the lookback window is two years or five, and whether it's measured against daily, weekly, or monthly returns. A company that has recently changed its business mix, taken on new leverage, or entered a different risk profile than its trading history reflects will have a beta that describes its past more accurately than its present.

---

## Step 4: Combine the Weights and Costs Into a Single WACC

Every input is now in place. Capital structure weights come from the filed balance sheet. An after-tax cost of debt comes from market bond pricing and GeminIQ's pre-calculated effective tax rate. A cost of equity range comes from CAPM. Combining them:

**WACC = (97.47% × 9.29%) + (2.53% × 4.24%)**
**WACC = 9.05% + 0.11% = 9.16%**

Running the same combination across the full cost-of-equity range from Step 3 produces a WACC of roughly **8.50%** at the low end and **9.82%** at the high end. The **9.16%** headline figure sits almost exactly at the midpoint. Notice how little the debt term moves the outcome: at a **2.53%** weight, even a full percentage point of error in the cost of debt estimate would shift total WACC by roughly two to three basis points. The entire range in the final number comes from the cost of equity, not from anything on Apple's balance sheet — a direct consequence of how lightly Apple is levered.

---

## Step 5: Set the WACC Against GeminIQ's Pre-Calculated ROIC

The entire point of building a WACC estimate is the comparison it enables. Pulling GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) directly from the dashboard, [Apple's](/stocks/AAPL) ROIC (TTM) stands at **78.45%**. GeminIQ builds that figure from NOPAT of **$112.28 Billion** divided by Average Invested Capital of **$143.12 Billion** — both sourced automatically from as-filed data, with no market assumption required anywhere in the calculation. Against the **9.16%** WACC estimate built above, that produces a spread of roughly **69 percentage points** — among the widest of any large-cap company. It's consistent with a business earning dramatically more on every dollar of invested capital than that capital costs to raise.

That asymmetry is the whole argument for why WACC will never be a platform metric and ROIC always will be. One side of this comparison — **78.45%** — required zero judgment calls and updates automatically every filing. The other side — **9.16%**, with a defensible range of **8.50%** to **9.82%** — required a market bond yield, a Treasury rate, an equity risk premium assumption, and a choice among three plausible beta estimates. Both are legitimate numbers. Only one of them is a fact.

---

## Why This Estimate Moves — and What Actually Holds Steady

Rerun this walkthrough in three months and the answer will not be **9.16%**. The Treasury yield will have moved, Apple's stock price and therefore its market cap will have moved, its bond yields will have moved, and whichever beta estimate gets used may have shifted with a new trailing window. None of that instability lives in the filing — it lives entirely in the market-sourced half of the formula, exactly as Step 3 flagged.

What holds steady is the filed half: the capital structure weights and the effective tax rate will not change until the next filing posts. Both are traceable to the exact XBRL tag behind them at any point in between. That is the practical dividing line worth carrying out of this guide and into any other cost-of-capital estimate: half of WACC is auditable against a filing, and half of it is a defensible guess about the future. Treating both halves with the same confidence is where most WACC estimates go wrong before the math even starts.

---

## Frequently Asked Questions

### Why doesn't GeminIQ just calculate WACC and display it like ROIC?
Because two of its three inputs — the equity risk premium and beta — are not company data. GeminIQ calculates every metric from as-filed XBRL inputs with one transparent, published method per metric. WACC cannot meet that bar because a meaningful share of it is a market assumption, not a filed number. What GeminIQ does provide is every filed input this guide uses: Total Debt, Market Capitalization, and Effective Tax Rate, all sourced directly from the 10-K.

### Is the market-yield approach to cost of debt always necessary?
No. When a company reports a standalone interest expense line on its income statement, dividing that figure by total debt and tax-adjusting the result is simpler and uses entirely filed data. The market-yield approach in this guide is specifically necessary for companies like Apple that net interest expense against interest income into a single combined line — confirmed directly by GeminIQ's Interest Expense field returning **$0.00** for the period.

### Why use market value of equity instead of book value in the weights?
Book value of equity reflects historical accounting entries — retained earnings, paid-in capital, treasury stock — that can diverge substantially from what the market is actually paying for the business today. Market capitalization is the more theoretically correct weight for a forward-looking cost of capital because it reflects current investor pricing rather than accumulated accounting history.

### How sensitive is WACC to the beta assumption?
Very. In this walkthrough, a beta range of **0.83** to **1.10** — a spread that exists simply because different data providers use different lookback windows and methodologies — produced a **135-basis-point** range in the cost of equity and translated almost one-for-one into the final WACC range. For a lightly levered company like Apple, beta uncertainty is effectively the entire source of uncertainty in the final number.

### Does a wide ROIC-to-WACC spread guarantee the stock is a good investment?
No. A wide spread indicates the underlying business is creating substantial economic value with the capital it deploys — it says nothing about whether the current share price already reflects that quality. ROIC and WACC together answer whether a business is a good business; they do not answer whether it is a good price.

---

### What does a 5% WACC mean?

A 5% WACC means the company's investors, blended by how much capital each provides, require a 5% annual return. That is low, and usually reflects a large, stable company with cheap debt and low stock volatility; any investment returning more than 5% on capital adds value.

### Is a higher WACC good or bad?

For the company, a higher WACC is worse: it raises the return every project has to earn and lowers the present value of future cash flows in a valuation. It usually reflects higher risk, from a volatile stock, heavy borrowing, or expensive debt, rather than anything management chose deliberately.

### How do you calculate WACC in Excel?

Put the market value of equity, market value of debt, cost of equity, pre-tax cost of debt, and tax rate in five cells, then combine them: =E/(E+D)*Re + D/(E+D)*Rd*(1-T). The formula is simple; the work is in estimating the cost of equity and the market cost of debt, which the steps above cover.

### Related Reading

- [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained) — the full NOPAT and invested capital build, including the ROIC-vs-WACC value creation test this guide's final WACC number is meant to be checked against.
- [How to Calculate Financial Ratios From a 10-K: Step-by-Step](/blog/how-to-calculate-financial-ratios-10k) — the companion walkthrough using the same Apple FY2025 10-K, building four ratios entirely from filed data.
- [Discounted Cash Flow (DCF) Model: Step-by-Step Walkthrough](/blog/dcf-valuation-model-step-by-step) — where WACC is most commonly used as the discount rate, built here from NVIDIA's filing instead of Apple's.
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary) — full definitions of WACC, ROIC, CAPM, and every other term referenced in this guide.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Blog: Cash Conversion Cycle (CCC): Formula, Components, and Benchmarks
source: https://www.geminiq.com/blog/cash-conversion-cycle-formula-explained

### Cash Conversion Cycle (CCC): Formula, Components, and Benchmarks
The Cash Conversion Cycle (CCC) measures how many days a company takes to convert inventory investment into cash. This post explains the formula, breaks down DSO, DIO, and DPO, and shows how CCC reveals operational quality from SEC filing data.

**The cash conversion cycle (CCC) is the number of days it takes a company to turn cash spent on inventory back into cash collected from customers: CCC = DSO + DIO − DPO.** A shorter cycle means cash comes back faster, and a negative cycle means customers pay before the company pays its suppliers.

The income statement tells you whether a company made money. The Cash Conversion Cycle tells you whether the business model actually works. Margins and earnings per share are the metrics financial media covers on earnings day — the CCC is the efficiency metric that exposes how many days sit between a company spending cash on inventory and receiving cash from a customer. A business with thin margins and a negative CCC can generate more free cash flow than a high-margin competitor with a bloated working capital cycle. Most screeners do not surface it. Most analysts do not track it. But the raw inputs are in every SEC filing, in the receivables and inventory and payables accounts, waiting for the investor who knows what to do with them.

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## Table of Contents

- [What Is the Cash Conversion Cycle?](#what-is-the-cash-conversion-cycle)
- [The CCC Formula: DSO + DIO − DPO](#the-ccc-formula-dso--dio--dpo)
- [What Is Days Sales Outstanding (DSO)?](#what-is-days-sales-outstanding-dso)
- [What Is Days Inventory Outstanding (DIO)?](#what-is-days-inventory-outstanding-dio)
- [What Is Days Payables Outstanding (DPO)?](#what-is-days-payables-outstanding-dpo)
- [How to Calculate the Cash Conversion Cycle](#how-to-calculate-the-cash-conversion-cycle)
- [What Is a Good Cash Conversion Cycle?](#what-is-a-good-cash-conversion-cycle)
- [The Negative CCC: When Suppliers Finance Your Operations](#the-negative-ccc-when-suppliers-finance-your-operations)
- [What a Rising CCC Reveals Before the Income Statement Does](#what-a-rising-ccc-reveals-before-the-income-statement-does)
- [Why CCC Values Differ Between Platforms](#why-ccc-values-differ-between-platforms)
- [How GeminIQ Calculates the Cash Conversion Cycle](#how-geminiq-calculates-the-cash-conversion-cycle)

---

## What Is the Cash Conversion Cycle?

The Cash Conversion Cycle — abbreviated CCC — measures the number of days it takes a company to convert its investment in inventory and working capital into cash receipts from customers. It captures the full operational loop: from the moment a company pays for raw materials or goods, through storage or production, through the sale, and finally through the collection of cash from the buyer.

A shorter CCC means the business moves through this loop faster. Every day removed from the cycle is a day the company ties up less working capital — capital that can instead be reinvested in operations, returned to shareholders, or held as liquidity. A longer CCC means the company is holding cash in inventory that has not yet sold, or in receivables that have not yet been collected, or both.

The CCC is not a profitability metric. A company can report strong operating margins and still run a deteriorating CCC — booking revenue while collecting cash slowly and watching inventory build. The opposite is equally important: a business with thin margins but a tightly managed cycle may generate far more free cash flow per dollar of revenue than a high-margin competitor with poor working capital discipline. The post on [key financial metrics for value investors](/blog/financial-metrics-value-investors) covers this territory in depth. The margin is what the income statement shows. The cycle is what determines whether that margin becomes cash.

---

## The CCC Formula: DSO + DIO − DPO

The [Cash Conversion Cycle](/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle) is the sum of two collection metrics minus one payment metric:

**CCC = Days Sales Outstanding (DSO) + Days Inventory Outstanding (DIO) − Days Payables Outstanding (DPO)**

Each of the three components is derived from a turnover ratio, and each measures a distinct phase of the operating cycle. Understanding all three is required to interpret CCC correctly — because the same final number can result from very different underlying conditions.

---

### What Is Days Sales Outstanding (DSO)?

[Days Sales Outstanding (DSO)](/metrics/efficiency-and-turnover-ratios/days-sales-outstanding) measures how many days, on average, a company takes to collect payment after a sale has been made.

**Formula:** DSO = 365 ÷ [Receivables Turnover](/metrics/efficiency-and-turnover-ratios/receivables-turnover), where Receivables Turnover = TTM Revenue ÷ Average Accounts Receivable.

A DSO of **30 days** means the company collects from customers within a month of the sale, on average. A DSO of **90 days** means payment takes three months — during which time the company has recognized revenue on the income statement but has not yet touched the cash. B2C businesses with point-of-sale cash transactions naturally run DSO under **5 days**. B2B companies operating on net-30 or net-60 terms typically fall between **30 and 60 days**. Software companies with upfront annual billing can run DSO near zero.

**When it breaks:** Rising DSO across consecutive reporting periods signals that the company is either loosening credit standards to sustain sales volume — extending longer payment windows to customers who cannot otherwise afford to buy — or that existing customers are paying more slowly than before. Either condition points to a receivables quality problem that the income statement has not yet registered.

---

### What Is Days Inventory Outstanding (DIO)?

[Days Inventory Outstanding (DIO)](/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding) measures how many days, on average, a company holds inventory before it sells.

**Formula:** DIO = 365 ÷ [Inventory Turnover](/metrics/efficiency-and-turnover-ratios/inventory-turnover), where Inventory Turnover = TTM COGS ÷ Average Inventory.

A DIO of **30 days** means inventory cycles through in one month. A DIO of **120 days** means the company holds goods for four months before they convert to revenue — tying up significant capital in assets that have not yet earned their keep. Grocery retailers naturally run under **20 days** because they sell perishables. General merchandise typically falls between **45 and 90 days**. Heavy manufacturers and aerospace companies can legitimately carry DIO above **120 days** due to long production cycles, which makes cross-sector comparisons largely meaningless without industry context.

**When it breaks:** DIO rising faster than revenue growth is the earliest quantitative signal of demand deterioration. When a company is building inventory faster than it sells — before the imbalance appears as a revenue miss — DIO is the first metric to move. By the time management cuts guidance on an earnings call, the DIO has often been flashing for one or two quarters already.

---

### What Is Days Payables Outstanding (DPO)?

[Days Payables Outstanding (DPO)](/metrics/efficiency-and-turnover-ratios/days-payables-outstanding) measures how many days, on average, a company takes to pay its own suppliers.

**Formula:** DPO = 365 ÷ [Payables Turnover](/metrics/efficiency-and-turnover-ratios/payables-turnover), where Payables Turnover = TTM COGS ÷ Average Accounts Payable.

Unlike DSO and DIO, a higher DPO reduces the CCC — and is therefore generally favorable. A company that takes **60 days** to pay suppliers is using those **60 days** as interest-free financing: it received the goods, may have already sold them, and collected customer cash before ever paying the vendor. That is working capital leverage in its most direct form. DPO is highest at companies with significant purchasing scale, whose bargaining power enables extended payment terms with suppliers. DPO rising modestly over time reflects improving leverage. A sudden spike may instead indicate the company is stretching payments because it is struggling with cash — not negotiating from strength.

**When it breaks:** A falling DPO means the company is paying suppliers faster than before — either voluntarily or because suppliers are demanding quicker payment. If vendors are tightening terms, that signals deteriorating credit quality in the supply chain relationship. DPO compressing simultaneously with rising DSO and DIO is the working capital trifecta of operational stress, and it shows up in the balance sheet before it ever reaches the income statement.

---

## How to Calculate the Cash Conversion Cycle

The calculation draws from three financial statements — the income statement and two consecutive periods of balance sheet data — and requires five inputs: TTM revenue, TTM COGS, and average period balances for accounts receivable, inventory, and accounts payable.

Beginning with Receivables Turnover, divide TTM Revenue by the average of beginning and ending Accounts Receivable. Divide 365 by that figure to arrive at DSO. For DIO, divide TTM COGS by average Inventory to produce Inventory Turnover, then divide 365 by the result. For DPO, divide TTM COGS by average Accounts Payable to produce Payables Turnover, and divide 365 by that result. Apply the formula — CCC = DSO + DIO − DPO — and the output is the number of days in the operating cash cycle.

The multi-statement nature of this calculation is exactly where third-party platforms introduce error. Any platform that normalizes COGS, reclassifies receivables, or applies a non-standard payables definition produces a CCC that diverges from the as-filed figures. The [financial data normalization problem](/blog/financial-data-normalization-explained) that distorts earnings-based metrics hits working capital metrics even harder, because the inputs span multiple statements and multiple reporting periods. A discrepancy at the DSO level and another at the DIO level compound into a CCC that can differ by double digits from what the raw SEC filing supports — enough to change the operational quality conclusion entirely.

---

## What Is a Good Cash Conversion Cycle?

No universal CCC benchmark exists — the metric only makes sense in industry context. The table below gives the typical ranges by business model, and what drives each one:

| Industry / business model | Typical CCC | What drives it |
|---|---|---|
| Software & SaaS (annual prepay) | **Negative to ~0 days** | Billed in advance; almost no inventory |
| Digital platforms & marketplaces | **Negative to ~10 days** | Cash collected at transaction; payouts lag |
| Big-box & grocery retail | **Negative to 20 days** | Purchasing scale extends DPO past DIO |
| General retail & distribution | **20–60 days** | Inventory held against normal supplier terms |
| Restaurants & food service | **Negative to 15 days** | Cash sales, rapid inventory turns |
| Manufacturing & industrial | **60–120 days** | Long production cycles; DIO dominates |
| Apparel & consumer brands | **80–130 days** | Seasonal buys, long lead times |
| Semiconductors & hardware | **90–150 days** | Long fabrication cycles, high finished-goods stock |
| Pharmaceutical & biotech | **100+ days** | Raw material lead times, regulatory holding requirements |

Read these as orientation, not thresholds — a number outside its band is a question to investigate, not a verdict. Capital-light businesses — software companies with annual subscription billing, digital platforms with immediate payment collection — often carry CCCs near zero or negative. They bill in advance or collect cash at the point of transaction, meaning the revenue cycle barely generates any working capital float.

General retail and distribution businesses typically fall in the **20-to-60-day** range. Companies with significant purchasing scale can compress this further through DPO extension, sometimes reaching negative CCC territory despite holding physical inventory. Manufacturing and industrial companies routinely operate between **60 and 120 days**, with DIO dominating because production cycles are long by design. Pharmaceutical and biotech businesses can carry CCCs well above **100 days** due to raw material lead times and finished goods holding requirements.

The more actionable benchmark is the company's own historical trend. A CCC widening by **10 days** year-over-year in a business where it has been stable for several years warrants investigation — regardless of whether the absolute level appears acceptable by industry standards. The CCC is also a direct operational antecedent of free cash flow: every day removed from the cycle is working capital freed for other uses. Investors who track the [free cash flow yield](/blog/free-cash-flow-yield-explained) as a valuation anchor should trace it back to the operational discipline that generates it. The CCC is that discipline, measured in days.

---

## The Negative CCC: When Suppliers Finance Your Operations

The most powerful working capital position is a negative CCC. It means the company collects cash from customers before it has to pay its own suppliers — running on other people's money, structurally and at scale.

A negative CCC requires one or more of three conditions: very low DSO (customers pay in advance or at the point of transaction), very low DIO (inventory cycles so quickly it barely registers as a balance sheet item), or very high DPO (suppliers wait long enough that the company has already collected from customers before the payables come due).

Large-scale retailers with significant purchasing leverage have historically demonstrated this dynamic. When vendor payment terms run to **60-plus days** but customers pay at the register, the retailer holds a permanent cash float funded by the supply chain rather than by its own equity. Every dollar of inventory stocked is financed by the supplier, not the retailer. That structural advantage compounds with volume — more purchasing power extends DPO further, compressing the CCC further, creating an operational flywheel with no equivalent on the income statement.

For investors, a sustained negative CCC is not merely an operational data point. A business that requires negative working capital to grow does not need to raise external capital to fund ordinary operations — it generates more cash than it consumes as a function of scale. That distinction lives in the balance sheet's payables and receivables accounts, not in reported earnings. The [return on invested capital](/blog/roic-return-on-invested-capital-explained) framework is the valuation complement to this analysis: the CCC tells you how efficiently the cycle runs; ROIC tells you what that efficiency earns on capital deployed. The two metrics read the same operational quality from different angles.

---

## What a Rising CCC Reveals Before the Income Statement Does

The CCC is a leading indicator. By the time operational deterioration reaches the income statement as margin compression or a revenue miss, the CCC has often been signaling stress for one, two, or three reporting periods. Standard financial media does not read the footnotes. It reads the press release.

The typical deterioration sequence begins with inventory. Demand softens or a product cycle stalls. DIO rises as goods accumulate. Rather than cut prices immediately, management maintains revenue guidance while the imbalance builds. A few quarters later, markdowns begin and units shipped accelerate — the revenue miss arrives alongside a writedown. But the DIO told this story months earlier, in a balance sheet line that most investors never glanced at.

A parallel sequence runs through receivables. A company pushing sales by extending generous payment terms — or whose customers are paying more slowly because of their own financial stress — will show rising DSO before any of this registers as bad debt expense. Both dynamics live in raw balance sheet data filed directly with the SEC. They are visible to any investor who runs the working capital math from the source. The CCC is therefore a genuine informational advantage for investors willing to use it — not because the data is hidden, but because most participants never look.

---

## Why CCC Values Differ Between Platforms

Because the CCC is built from three separate turnover ratios — each requiring multiple inputs — any inconsistency in how those inputs are defined propagates through the entire calculation. A platform using fiscal year-end accounts receivable rather than the average of beginning and ending balances produces a systematically different DSO. A platform reclassifying items out of COGS produces a different DIO. A platform applying a broader or narrower payables definition shifts the DPO.

These discrepancies compound. A DSO off by **5 days** and a DIO off by **8 days** produce a CCC that diverges by **13 days** — enough to flip a company from appearing operationally sound to appearing stressed, or to mask genuine deterioration beneath a cleaner-looking headline number. This is not a rounding difference. It is a data lineage problem that originates the moment a third party normalizes the raw filing.

GeminIQ uses as-filed XBRL values for every CCC input — the same figures the company submitted to the SEC, with no normalization or reclassification applied. The TTM revenue and COGS figures come directly from the as-filed income statement. The average balance sheet values are calculated from two consecutive SEC filings, period-end to period-end. The CCC GeminIQ produces is the number you would arrive at by reading the raw EDGAR filings and running the math yourself.

---

## How GeminIQ Calculates the Cash Conversion Cycle

GeminIQ's pre-calculated [Cash Conversion Cycle](/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle) is derived directly from SEC EDGAR XBRL filings. The three underlying turnover ratios — [Receivables Turnover](/metrics/efficiency-and-turnover-ratios/receivables-turnover), [Inventory Turnover](/metrics/efficiency-and-turnover-ratios/inventory-turnover), and [Payables Turnover](/metrics/efficiency-and-turnover-ratios/payables-turnover) — each use TTM values and average balance sheet inputs calculated from two consecutive filing periods. No adjustments are applied.

All three CCC components — [Days Sales Outstanding (DSO)](/metrics/efficiency-and-turnover-ratios/days-sales-outstanding), [Days Inventory Outstanding (DIO)](/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding), and [Days Payables Outstanding (DPO)](/metrics/efficiency-and-turnover-ratios/days-payables-outstanding) — are individually available on the platform alongside the composite CCC. When the cycle shifts, you can see immediately which component is driving the change — a receivables problem, an inventory build, or a payables compression — without any additional calculation.

For investors screening on operational quality at the asset level, the [Efficient Asset Turnover screener](/screens/stock-screeners/efficient-asset-turnover) pairs naturally with CCC analysis. It surfaces companies generating high revenue per dollar of total assets alongside strong margins and return on assets — a complementary filter that captures the same operational discipline at the asset level that the CCC captures at the working capital level. Both metrics read from the same underlying operational reality, sourced from the same SEC filings, with no aggregator between you and the data.

## Frequently Asked Questions

### How is the cash conversion cycle calculated?

Add days sales outstanding (how long customers take to pay) to days inventory outstanding (how long inventory sits before it sells), then subtract days payables outstanding (how long the company takes to pay suppliers). Each component is expressed in days, so the result is the number of days cash is tied up in operations.

### What does CCC stand for in finance?

CCC stands for cash conversion cycle, also called the cash-to-cash cycle or net operating cycle. It measures how long a company's cash is tied up in inventory and receivables before it comes back as collected revenue, net of the time suppliers allow before being paid.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Free Cash Flow Yield Explained: How to Find Undervalued Stocks
source: https://www.geminiq.com/blog/free-cash-flow-yield-explained

### Free Cash Flow Yield Explained: How to Find Undervalued Stocks
Free cash flow yield measures how much cash a company generates relative to its market cap — a more manipulation-resistant valuation metric than P/E. This guide covers the formula, thresholds, when high FCF yield is a warning sign, and how to screen for it.

**Free cash flow yield is free cash flow divided by market capitalization — the cash a business generates each year per dollar of its stock's value.** A yield above 5% is broadly attractive, while a yield below 2% means paying roughly 50 times free cash flow.

The P/E ratio is the most widely reported valuation metric in financial media. It appears in every earnings headline, every analyst note, every stock comparison table. And it is built entirely on net income — an accounting figure that management teams have meaningful latitude to shape through depreciation schedules, amortization choices, one-time charges, and non-cash items. Free cash flow is not immune to all forms of manipulation, but it is substantially more resistant. Cash either moved through the bank account or it did not. Free cash flow yield converts that reality into a valuation multiple — expressing the cash a business generates as a percentage of the price you are paying for it. It is the metric that separates companies that merely look cheap from companies that actually are.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=free-cash-flow-yield-explained)**

---

## Table of Contents

- [What Is Free Cash Flow Yield?](#what-is-free-cash-flow-yield)
- [How Is Free Cash Flow Yield Calculated?](#how-is-free-cash-flow-yield-calculated)
- [Does a High Free Cash Flow Yield Mean a Stock Is Undervalued?](#does-a-high-free-cash-flow-yield-mean-a-stock-is-undervalued)
- [Why FCF Yield Is a More Reliable Valuation Metric Than P/E](#why-fcf-yield-is-a-more-reliable-valuation-metric-than-pe)
- [How to Interpret FCF Yield: The Thresholds That Matter](#how-to-interpret-fcf-yield-the-thresholds-that-matter)
- [When High FCF Yield Is a Warning Sign, Not a Buy Signal](#when-high-fcf-yield-is-a-warning-sign-not-a-buy-signal)
- [Why FCF Yield Numbers Differ Across Platforms](#why-fcf-yield-numbers-differ-across-platforms)
- [How to Find High FCF Yield Stocks Using GeminIQ](#how-to-find-high-fcf-yield-stocks-using-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is Free Cash Flow Yield?

Free cash flow yield is the ratio of a company's free cash flow to its market capitalization. It answers one of the most fundamental questions in investing: for every dollar you invest in a business at its current price, how many cents of real cash does that business generate each year?

Think of it as the cash-flow equivalent of earnings yield — which is itself the inverse of the P/E ratio. Where earnings yield divides net income by market cap, free cash flow yield divides actual cash generation by market cap. The result is expressed as a percentage: a **5% FCF yield** means the business generates **$5 of free cash for every $100 of market value**. A **2% FCF yield** means you are paying **50x free cash flow** for the business — and you need to believe strongly in its future growth to justify that price.

The metric gained serious traction in the early 2000s as analysts searched for valuation frameworks that had not failed catastrophically during the dot-com collapse. P/E multiples had expanded to absurd levels for companies that barely had revenue, let alone earnings. FCF yield, rooted in actual cash generation, became the corrective — and it has remained a core valuation tool for fundamental investors ever since. Academic research has generally found that high FCF yield is a positive predictor of subsequent equity returns, aligning with the intuition that paying less per dollar of cash is a sound long-term approach.

### How Is Free Cash Flow Yield Calculated?

The formula has two components: free cash flow and market capitalization.

**Free Cash Flow Yield = Free Cash Flow (TTM) ÷ Market Capitalization**

Where free cash flow itself equals:

**Free Cash Flow = Operating Cash Flow − Capital Expenditures**

Operating cash flow is the cash the business generates from its core operations, after working capital movements and before financing or investing activities. It comes directly from the cash flow statement in the company's 10-K or 10-Q, where it is tagged under the XBRL identifier `NetCashProvidedByUsedInOperatingActivities`. Capital expenditures — the cash the company spends on property, plant, equipment, and other long-lived assets — appears as a cash outflow in the investing activities section of the same statement, tagged as `PaymentsToAcquirePropertyPlantAndEquipment`.

Market capitalization is shares outstanding multiplied by the current stock price. Because market cap changes continuously while financial data updates only at filing dates, FCF yield is typically calculated using the most recent four quarters of cash flow data (trailing twelve months, or TTM) against a recent market price.

GeminIQ's [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield) metric calculates this directly from XBRL-tagged cash flow statement data in SEC filings, using as-filed operating cash flow and capital expenditure figures alongside period-end shares outstanding. Because the calculation uses as-filed numbers rather than normalized or adjusted inputs, it reflects the actual economics of the business as reported — not a version that a third-party aggregator decided was more representative.

---

## Does a High Free Cash Flow Yield Mean a Stock Is Undervalued?

Not on its own — but it is the single strongest starting signal, and here is the precise reason. A high free cash flow yield indicates potential undervaluation because it means the market is paying a low price for each dollar of cash the business produces. FCF yield is free cash flow divided by market capitalization, so a higher yield mathematically requires a lower price relative to cash generation — the market is valuing that cash stream cheaply compared to higher-priced peers.

The mechanism is direct:

- **The price sits in the denominator.** FCF yield = FCF ÷ market cap. Holding cash generation constant, the yield can only rise if the price (market cap) falls — so a high yield is, by construction, a low price per dollar of free cash.
- **You recover more cash per dollar invested.** An 8% FCF yield returns 8 cents of real cash annually for every dollar of market value, versus 2 cents at a 2% yield. The higher-yield business pays back its price in cash far faster.
- **It clears the risk-free hurdle with room to spare.** When the FCF yield sits well above the 10-year Treasury, the equity is throwing off a meaningful cash return over a government bond — the spread the market demands to hold a cheap, cash-generative business.

One caveat keeps this honest: a high FCF yield indicates _potential_ undervaluation, not proof of it. The same low price can reflect a market correctly anticipating that the cash flow will decline. A capex-cycle low, a business in secular decline, or a one-time working-capital release can each inflate the yield with no real bargain underneath — the situations covered in [When High FCF Yield Is a Warning Sign](#when-high-fcf-yield-is-a-warning-sign-not-a-buy-signal). Genuine undervaluation is a high FCF yield attached to durable, repeatable cash generation.

---

## Why FCF Yield Is a More Reliable Valuation Metric Than P/E

The core argument for preferring FCF yield over P/E comes down to one word: cash.

Net income is the product of accounting rules. A company that aggressively capitalizes software development costs will report higher current earnings than one that expenses them immediately — even if the two businesses are economically identical. A company using longer depreciation schedules on its equipment will report higher earnings than one using accelerated depreciation for the same asset base. Strategic tax timing can inflate earnings in specific periods. None of these choices affect cash.

Consider [Apple](/stocks/AAPL)'s FY2025 financial results as an illustration. The company reported net income of **$112.0 billion**. Its operating cash flow was **$111.5 billion** — nearly identical. But bridging those two numbers requires accounting for **$12.9 billion** in stock-based compensation (a non-cash expense added back in the cash flow statement), **$11.7 billion** in depreciation and amortization, and roughly **$25 billion** in working capital movements and one-time items. [Apple's](/stocks/AAPL) [earnings quality](/blog/earnings-quality-accruals-analysis) happens to be exceptional — the gap between net income and operating cash flow is small relative to the scale of the business. As a result, [Apple's](/stocks/AAPL) free cash flow of **$98.8 billion** (operating cash flow of **$111.5 billion** minus capital expenditures of **$12.7 billion**) closely tracks what the income statement shows. That alignment is not a feature of every company.

For businesses where the gap between net income and operating cash flow is wide — driven by large accrual items, aggressive accounting, or non-recurring benefits — the P/E ratio will significantly overstate the true earning power of the business. A company reporting **$500 million in net income** but generating only **$50 million in free cash flow** is priced very differently under FCF yield than under P/E. That difference matters for long-term returns.

The other advantage of FCF yield is that it incorporates capital discipline. Two companies can report identical earnings, but if one requires twice the capital expenditure to generate that income, it is a fundamentally worse business. Free cash flow captures that difference naturally. The company that earns the same operating profit but requires less investment to maintain and grow it will have a higher FCF yield at the same market cap — because its actual cash generation is higher. The P/E ratio obscures this distinction entirely. The FCF yield does not.

---

## How to Interpret FCF Yield: The Thresholds That Matter

Not every FCF yield number carries the same implication. The absolute level of the yield matters, and so does the context: the current interest rate environment, the quality of the underlying business, and whether the free cash flow is recurring or episodic.

**Above 5%** is broadly considered the floor of attractiveness for mature, profitable businesses. A **5% FCF yield** means you are paying **20x free cash flow** — which historically has been a zone where patient value investors have found durable returns. Companies consistently generating yields above **7% to 8%** deserve close examination: the market is either pricing in significant future deterioration, or it has not fully recognized the business's cash generation capability. One of those interpretations represents a potential opportunity. The other is a warning. Distinguishing between them is the analytical work that follows the screen.

**Between 3% and 5%** is a moderate zone. This range typically reflects established businesses with steady cash generation and no particularly concerning quality concerns. The question at this level is whether the growth trajectory justifies the modest premium over higher-yield alternatives.

**Below 2%** means you are paying more than **50x free cash flow**. At this level, the business must demonstrate significant future growth in free cash flow to justify the price. Companies in this range are not automatically overvalued — a high-quality compounder growing free cash flow at **20% annually** may be well worth **50x TTM FCF** if that growth proves durable. But the margin for error is thin, and the investor is paying almost entirely for the future rather than the present.

A practical calibration benchmark: compare the FCF yield to the prevailing risk-free rate. When the 10-year Treasury yield sits at a given level, an FCF yield below that level means you are receiving less cash-based return from the equity than from a government bond — and equities carry far more uncertainty. The FCF yield must exceed the risk-free rate by a meaningful margin to compensate for business risk and the uncertainty of future cash flows. When that spread compresses or disappears, the equity is doing little work for the additional risk it carries.

---

## When High FCF Yield Is a Warning Sign, Not a Buy Signal

A standard screener flags stocks above **5% FCF yield** as potentially undervalued. But high FCF yield is not automatically a buy signal — three specific situations produce elevated yields that do not reflect genuine value.

The first is the capex cycle trap. Capital-intensive businesses — mining, energy infrastructure, utilities, heavy manufacturing — have lumpy capital expenditure patterns. A company in a low-capex year following a major construction or expansion project will show an elevated FCF yield that does not reflect normalized business economics. Within a few years, maintenance and replacement capex will return, and the true normalized FCF yield is materially lower. The trailing TTM figure does not capture this dynamic. Always examine the capex trend over multiple periods, not a single year in isolation.

The second is the declining business case. A company in secular decline can generate excellent free cash flow precisely because it is harvesting its asset base rather than reinvesting in growth. Capital expenditures fall, working capital liquidates, and the FCF yield rises — even as revenue and competitive position erode. High FCF yield on a declining revenue base is a different investment thesis than high FCF yield on a stable or growing business. Any screening process that treats these two situations identically will surface poor candidates.

The third is the one-time working capital release. Operational changes — extended supplier payment terms, accelerated customer collections, inventory reduction programs — can temporarily inflate operating cash flow without reflecting any durable improvement in the business. These events produce a spike in FCF yield during the period they occur and then normalize in subsequent quarters. If FCF yield is significantly elevated relative to what the earnings picture would suggest for the same period, investigate the working capital movements before assuming the number is sustainable. The cash flow statement shows exactly where that cash came from — and whether it is likely to repeat.

GeminIQ's [Visualizations](/features#visualizations) feature lets you chart operating cash flow, net income, and capital expenditures across eight or more quarters for any company. The shape of those three lines over time tells a far more complete story than any single-period yield figure. The ideal FCF yield candidate shows operating cash flow consistently above net income — a signature of high earnings quality — alongside stable or declining capex and a yield that has remained elevated for multiple periods rather than appearing in one anomalous quarter.

---

## Why FCF Yield Numbers Differ Across Platforms

Free cash flow is one of the most definitionally variable metrics in financial analysis, and the differences across platforms can be material — not rounding errors, but multi-percentage-point divergences that lead to fundamentally different conclusions about the same company.

The primary source of disagreement is capex definition. The most precise approach — and the one GeminIQ uses — is to take capital expenditures exactly as reported on the cash flow statement: the cash paid to acquire property, plant, and equipment, as filed under the XBRL tag `PaymentsToAcquirePropertyPlantAndEquipment`. But aggregators make different choices. Some platforms add capitalized software development costs to the capex figure, which reduces the reported free cash flow for technology companies. Others include content acquisition spending, critical for streaming and media businesses. Some platforms sweep acquisition payments — which appear in the investing section of the cash flow statement alongside organic capex — into the free cash flow calculation. Each of these choices produces a different free cash flow figure, and therefore a different FCF yield.

The second source of variation is market cap timing. Market capitalization changes every trading day. Platforms that use end-of-period market cap will show a different FCF yield than platforms using the current price. For a company whose stock has moved significantly since its last filing date, the FCF yield on two platforms can differ by several full percentage points — not because the underlying data is wrong, but because the price reference point is different.

This is precisely the problem that makes aggregated financial data unreliable as a consistent screening foundation. When one financial website shows a **6.2% FCF yield** and a different platform shows **5.1%** for the same company in the same period, those are not errors — they are different definitional choices, none of which are labeled as such. You cannot compare companies meaningfully if the metric definition shifts beneath you from one ticker to the next. GeminIQ's [Calculated Metrics](/features#calculated-metrics) apply a consistent methodology across every company in the database, drawn directly from as-filed SEC EDGAR data. The definition does not change. That consistency is what makes a screener built on FCF yield actually reliable for cross-company comparison — and why the number you screen on in GeminIQ is the same number that went into the filing. For a deeper look at how aggregator normalization choices distort financial data, see [Third-Party Financial Data: What Gets Lost When the Data Is Processed](/blog/third-party-financial-data-problems).

---

## How to Find High FCF Yield Stocks Using GeminIQ

The [High Free Cash Flow Yield Screener](/screens/stock-screeners/high-fcf-yield) on GeminIQ is built around four filters that, in combination, identify businesses with genuine cash generation relative to their market price — while removing the false signals described above.

The core filter is [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield) **≥ 5%**. This sets the floor: the company must generate at least five cents of free cash for every dollar of market capitalization on a trailing twelve-month basis. The **5%** threshold has long served as a practical reference point for value-oriented investors because it sits meaningfully above typical risk-free alternatives and signals a business not excessively priced relative to its actual cash production.

A ceiling matters as much as a floor. Capping the screen at **50%** removes readings that are arithmetically true but analytically useless — a yield of several hundred percent almost always means the market capitalization in the denominator is wrong or the business is a shell, not that the company is returning multiples of its value in cash each year. Any yield far above the ceiling is a prompt to check the share count and price inputs before treating it as a signal.

The second filter — operating cash flow **≥ $1 million** — ensures the free cash flow is grounded in real operating activity. Without this guard, companies with negative operating cash flow but reduced capital expenditures can appear above the FCF yield threshold on paper. The operating cash floor eliminates that distortion.

The third filter — [Debt To Equity](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) **≤ 2.0** — removes companies where the high FCF yield is real but where debt service claims a significant portion of that cash before it reaches shareholders. A heavily leveraged company generating strong free cash flow is generating it primarily for creditors. The leverage filter narrows the universe to companies where more of the free cash flow is genuinely available to equity holders.

The optional fourth filter — [Net Profit Margin TTM](/metrics/margin-metrics/net-profit-margin) **≥ 5%** — adds a quality layer that most basic screeners omit entirely. Companies with high FCF yield but very low net margins often achieve that yield through heavy depreciation against thin earnings — the signature of a capital-intensive business where accounting depreciation understates true economic asset consumption. When a business combines strong FCF yield with strong net margins simultaneously, the probability that the cash generation is both real and durable increases substantially.

Sort the results by [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield) descending — highest cash yield first — then move from the screener to the filing. Open each candidate in GeminIQ's [Financial Statements](/features#financial-statements) view and pull the operating activities section of the cash flow statement. Verify that operating cash flow consistently exceeds net income across multiple periods. That relationship — when stable over time — is one of the most reliable signals of accounting quality available in fundamental analysis. A one-period spike in FCF yield requires explanation. A multi-year pattern of strong FCF yield from a business with stable or growing revenue and disciplined capex is a different category of evidence entirely, and it is the pattern that the screener is designed to surface.

<center><sup>GeminIQ Stock Screener showing the High Free Cash Flow Yield screen with Free Cash Flow Yield TTM between **5%** and **50%**, trailing-twelve-month Operating Cash Flow ≥ $1M, and Debt To Equity ≤ 2.0 filters applied, sorted descending by Free Cash Flow Yield TTM. The Operating Cash Flow column shows each company's most recent quarter, while the ≥ $1M floor is applied to the trailing-twelve-month figure. Note that a Debt To Equity reading below 2.0 also admits negative values, which indicate negative shareholders' equity rather than low leverage — a reason to open the balance sheet before treating any row as a candidate. All inputs sourced directly from XBRL-tagged SEC cash flow statement data (`Net Cash Provided By Used In Operating Activities` and `Payments To Acquire Property Plant And Equipment`).</sup></center>

---

## Frequently Asked Questions

### Is a high free cash flow yield always a buy signal?

No. It means the market is paying a low price for each dollar of cash the business generates, which is the starting condition for undervaluation but not proof of it. A high yield is only a bargain when the cash generation behind it is durable and repeatable. The same high yield appears when the market is correctly pricing in a decline — at a capex-cycle low, in a business in secular decline, or after a one-time working-capital release. Confirm the cash flow is sustainable before treating the yield as a valuation signal.

### What is a good free cash flow yield?

Above **5%** is broadly attractive and above **8%** is deep-value territory, while below **2%** means paying more than 50x free cash flow. These thresholds are starting points rather than verdicts — the yield always needs to be read against the durability of the cash stream and the prevailing 10-year Treasury rate, since the spread over the risk-free rate is what the market is actually pricing.

### Is free cash flow yield better than the P/E ratio?

For most valuation work, yes. Free cash flow is materially harder to manipulate than reported earnings because it reflects cash that actually moved, net of the capital spending required to keep the business running. Earnings can be shifted by depreciation schedules, accrual timing, and one-time charges that never touch cash. FCF yield sidesteps most of that.

### How do you calculate free cash flow yield?

Free Cash Flow Yield = Free Cash Flow (TTM) ÷ Market Capitalization, where free cash flow is operating cash flow minus capital expenditures. Both inputs come straight from the cash flow statement in a 10-K or 10-Q — `Net Cash Provided By Used In Operating Activities` less `Payments To Acquire Property Plant And Equipment`.

### Why do FCF yield figures differ between platforms?

Two variables account for nearly all of it: how each source defines capital expenditures (some include acquisitions, capitalized software, or leases) and which market cap timestamp it uses. Both choices move the ratio without any change in the underlying filing, which is why an FCF yield quoted on one platform rarely reconciles exactly against another.

### Is a 6% free cash flow yield good?

A 6% free cash flow yield is above the 5% level that is broadly attractive, meaning the company generates about $6 of free cash flow per $100 of market value. Before treating it as cheap, check that the free cash flow is recurring rather than lifted by a one-time cut in capital spending or a working-capital release, and compare it with the company's own history and its peers.

---

### Related Reading

- [Return on Invested Capital (ROIC) Explained](/blog/roic-return-on-invested-capital-explained) — ROIC measures the quality of capital deployment; FCF yield measures the cash price of that deployment. Together they are the two most powerful lenses for identifying genuinely exceptional businesses at reasonable prices.
- [Magic Formula Investing Explained](/blog/magic-formula-investing-explained) — Joel Greenblatt's framework uses earnings yield (EBIT/EV) rather than FCF yield for its valuation component, but the underlying logic — buying quality businesses at cheap prices — is the same. Understanding both approaches clarifies when each is the more appropriate tool.
- [What Investors Miss in SEC Filings](/blog/what-investors-miss-in-sec-filings) — the cash flow adjustments that bridge net income and operating cash flow are hiding in plain sight in every 10-K and 10-Q. Reading them correctly is how you verify whether a high FCF yield is real or manufactured.
- [Third-Party Financial Data: What Gets Lost When the Data Is Processed](/blog/third-party-financial-data-problems) — how aggregator capex definitions and market cap timing produce FCF yield figures that appear comparable but are not.
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary) — full definitions of FCF yield, earnings yield, P/E, ROIC, and every other ratio referenced in this post.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Blog: Interest Coverage Ratio: Formula, Benchmarks, and When It Breaks
source: https://www.geminiq.com/blog/interest-coverage-ratio-explained

### Interest Coverage Ratio: Formula, Benchmarks, and When It Breaks
Interest Coverage Ratio measures how many times a company's EBIT covers its interest expense. This post covers the formula, thresholds by risk zone, industry benchmarks, and the ASC 842 operating lease trap that makes the ratio uncalculable for retailers, airlines, and consumer brands.

The interest coverage ratio is supposed to answer one question: can this company pay its debt? The formula is two numbers — EBIT divided by interest expense — and every financial data platform produces a figure. The problem is that a growing number of public companies carry substantial liabilities on their balance sheets while reporting effectively zero interest expense. Not because the debt is cheap. Because the debt is operating leases, and under ASC 842 — the accounting standard that took effect for most public companies in 2019 — operating lease liabilities are now balance sheet items, but the interest component of those leases does not flow through the income statement line called interest expense. For retailers, restaurant chains, airlines, and consumer brands, the interest coverage ratio as standardly calculated is either uncalculable or produces a number so large it appears to signal financial strength while measuring nothing at all.

This post covers the formula, the thresholds, the industry context, and the structural problem that makes the ratio actively misleading for a wide class of public companies — along with what to pair it with to get a complete picture of leverage risk.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=interest-coverage-ratio-explained)**

---

## Table of Contents

- [What Is the Interest Coverage Ratio?](#what-is-the-interest-coverage-ratio)
- [How to Calculate Interest Coverage Ratio from a Filing](#how-to-calculate-interest-coverage-ratio-from-a-filing)
- [Interest Coverage Ratio Benchmarks: Zones and What They Signal](#interest-coverage-ratio-benchmarks-zones-and-what-they-signal)
- [Why Industry Context Changes the Meaning](#why-industry-context-changes-the-meaning)
- [When the Ratio Breaks: The ASC 842 Operating Lease Trap](#when-the-ratio-breaks-the-asc-842-operating-lease-trap)
- [Interest Coverage Ratio vs. Debt-to-EBITDA](#interest-coverage-ratio-vs-debt-to-ebitda)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is the Interest Coverage Ratio?

### What Does Interest Coverage Ratio Measure?

The interest coverage ratio measures how many times a company's operating earnings — specifically EBIT, earnings before interest and taxes — cover its interest obligations over the trailing twelve months. It is a flow measure: it compares what the business earned from operations during the period to what it owes creditors in interest payments during the same period.

A ratio of **5.0x** means EBIT is five times the interest expense. The company could absorb an **80%** decline in operating earnings and still cover its interest bill entirely from operations. A ratio of **2.0x** means a **50%** earnings decline would leave the company unable to cover interest from operations alone. A ratio below **1.0x** means operating earnings are already insufficient — the company must draw on cash reserves, sell assets, or borrow additional funds to make its interest payments.

The metric matters most in three contexts. In leveraged capital structures — companies that took on significant debt through acquisitions, leveraged buyouts, or capacity expansion — interest is a material annual cash outflow against which operating earnings must be measured. During periods of rising interest rates, companies with floating-rate debt see their interest expense increase independent of anything management does to earnings, compressing coverage without any change in operating performance. And in credit analysis, interest coverage ratios are a standard input to corporate credit ratings and appear frequently as covenant thresholds in bond indentures and loan agreements, where a minimum ratio of **2.5x** or **3.0x** may be a contractual condition of the facility.

What the ratio does not measure is equally important. It does not address the total debt load, the maturity profile, or the company's capacity to repay principal. A company with a strong **6.0x** coverage ratio and **$8 billion** in debt maturing next year has no near-term interest payment problem and a potentially serious refinancing problem — and the coverage ratio gives no indication of the latter. Those questions require [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda), and [Net Debt](/metrics/calculated-values/net-debt) — not in place of the interest coverage ratio, but alongside it in a complete leverage analysis.

---

## How to Calculate Interest Coverage Ratio from a Filing

### What Is the Interest Coverage Ratio Formula?

**Interest Coverage Ratio = EBIT (TTM) ÷ Interest Expense (TTM)**

TTM denotes trailing twelve months — the sum of the four most recently filed quarters, used to smooth seasonality and provide a current picture of operating earnings relative to the ongoing interest burden.

### How to Find EBIT in a 10-K or 10-Q

EBIT does not always appear as a named line item in a company's income statement. When a company reports operating income directly — tagged in SEC EDGAR's XBRL data as `OperatingIncomeLoss` — that figure is frequently used as a proxy for EBIT, though the two are not always equivalent. Operating income excludes non-operating items such as interest income, equity method investment earnings, and gains or losses on asset sales. EBIT technically includes them. For most companies the difference is immaterial; for a company earning **$2 billion** in interest income on its cash balance, it is not.

When EBIT is not reported directly, it is derived:

**EBIT = Net Income + Income Tax Expense + Interest Expense**

The XBRL tags are `NetIncomeLoss` for net income, `IncomeTaxExpenseBenefit` for income tax, and `InterestExpense` or `InterestAndDebtExpense` for interest — the specific tag varies by how the company classifies its obligations. GeminIQ's pre-calculated [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) derives EBIT from the company's own as-filed figures when it is not stated directly. The numerator is not normalized, smoothed, or adjusted before the calculation runs.

### How to Find Interest Expense in a 10-K or 10-Q

Interest expense appears on the income statement, typically labeled "Interest Expense" or "Interest and Debt Expense." Two subtleties matter here. First, some income statements report net interest expense after subtracting interest income — a company with **$200 million** in gross interest expense and **$150 million** in interest income may show a single net line of **$50 million**, which is analytically different from a company that simply owes **$50 million** in annual interest. GeminIQ's [Financial Statements](/features#financial-statements) feature surfaces the as-filed income statement from its XBRL tags, making these components visible rather than presenting a single net figure.

Second, some companies capitalize a portion of their interest expense during construction of long-term assets — rather than expensing it immediately, they add it to the asset's carrying value on the balance sheet and expense it through depreciation over time. The income statement shows only expensed interest; capitalized interest is disclosed in the filing footnotes and in the cash flow statement. For companies actively building out large-scale facilities — semiconductor fabrication plants, energy pipelines, major infrastructure — capitalized interest can be material. An analysis built on the income statement figure alone understates the true cost of carrying that capital — a distinction the filing makes visible and most platforms do not.

---

## Interest Coverage Ratio Benchmarks: Zones and What They Signal

| Coverage zone | Ratio | What it signals |
|---|---|---|
| Strong | **Above 5.0x** | Substantial buffer against earnings deterioration |
| Adequate | **3.0x – 5.0x** | Consistent with investment-grade credit for stable cash flows |
| Watch | **2.0x – 3.0x** | Coverage exists but little room for a downturn |
| Risk | **1.5x – 2.0x** | Thin margin; refinancing risk rises materially |
| Distress | **Below 1.0x** | Operating earnings do not cover interest at all |

Those zones move with the business model. What counts as normal by sector:

| Sector | Typical range | Why |
|---|---|---|
| Software & SaaS | **Undefined or 20x+** | Little or no interest-bearing debt |
| Pharmaceutical | **8x – 15x** | High margins, moderate leverage |
| Consumer staples | **6x – 12x** | Predictable demand supports steady coverage |
| Industrial & manufacturing | **4x – 8x** | Moderate capital intensity |
| Retail | **3x – 6x** | Thin margins; lease obligations distort the figure |
| Telecom | **3x – 5x** | Long-duration debt against long-lived assets |
| Utilities & regulated pipelines | **2.0x – 4.0x** | Regulated returns make low coverage sustainable |
| Airlines | **1.5x – 4.0x** | Extreme capital intensity; mostly ASC 842 lease obligations |

A **2.5x** ratio is a serious warning for a software company and a standard operating condition for a utility. Always read the ratio against its sector before reading it against the zones.

### What Is a Good Interest Coverage Ratio?

Above **5.0x** is generally considered strong. The company generates operating earnings at least five times its interest obligation, providing substantial buffer against earnings deterioration. Most investment-grade technology, pharmaceutical, and consumer staples businesses operate here or above. Companies with no interest-bearing debt at all — those in a net cash position — produce an undefined ratio, since there is no denominator. That is financially the strongest position possible, even though a screener filtering purely on the interest coverage ratio may handle the undefined case inconsistently.

Between **3.0x and 5.0x** is adequate for most stable businesses. Credit rating agencies typically view this range as consistent with investment-grade credit for companies with predictable cash flows. Between **2.0x and 3.0x** is the watch zone — coverage exists, but a **30–50%** decline in operating earnings would threaten it. A company sustaining this level for multiple consecutive years, rather than as a cyclical trough, warrants deeper investigation of the debt maturity schedule and whether the interest rate on existing obligations is fixed or floating. Below **1.5x** is where credit agencies typically begin assigning negative pressure to ratings. Both Moody's and S&P cite approximately **2.5x** as a threshold below which investment-grade status becomes harder to maintain in most sectors. At **1.5x**, a **33%** earnings decline eliminates the coverage margin entirely.

### What Does an Interest Coverage Ratio Below 1.0x Mean?

Below **1.0x**, operating earnings are already insufficient to cover interest expense. The company is not generating enough from operations to service its debt and must rely on cash reserves, asset disposals, or additional borrowing to make interest payments. This is not automatically a distress signal — a cyclical business at an earnings trough, with a strong cash position and a clearly temporary decline, can sustain a sub-**1.0x** reading without defaulting. A company reporting below **1.0x** during a favorable economic environment, or doing so for multiple consecutive periods, is carrying structural debt that its operations cannot service. GeminIQ's pre-calculated [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) — incorporating liquidity, retained earnings, operating efficiency, and market leverage into a single composite score — provides the financial context the coverage ratio cannot: a diagnostic for whether the earnings shortfall is temporary or structural.

---

## Why Industry Context Changes the Meaning

A **2.5x** interest coverage ratio is a serious warning sign for a software company and a standard operating condition for a utility. The difference is not management quality — it is a reflection of how different capital structures fit different business models.

Capital-intensive industries — utilities, telecom, regulated pipelines — routinely operate with interest coverage ratios in the **2.0x to 4.0x** range. The logic is structural: long-duration debt is the appropriate financing tool for assets with 20–40 year useful lives and contracted, predictable cash flows. A regulated electric utility with **2.5x** coverage, fully contracted revenue streams, and a rate base earning a regulated return is a fundamentally different credit risk than a cyclical manufacturer reporting the same number. The ratio is identical; the underlying risk is not.

For capital-light technology and software businesses, the interest coverage ratio is frequently undefined. These companies carry little or no interest-bearing debt, generate substantial operating earnings, and report interest expense near zero. A screener filtering on "interest coverage ratio above **5.0x**" will exclude these companies simply because the calculation returns no valid denominator, while including leveraged businesses whose ratio clears the threshold from a starting point of meaningful debt. The metric was designed for companies with interest-bearing obligations. Applied uniformly across capital structures, it produces results that reflect the screening methodology more than the underlying financial risk.

Airlines sit at the extreme end of capital intensity, with the additional structural wrinkle that the bulk of their obligations in a post-ASC 842 world are operating lease liabilities for aircraft rather than conventional interest-bearing debt. The coverage ratio for a major airline with tens of billions in balance sheet lease obligations can read as healthy or undefined while the actual annual cash outflow for lease payments runs to several billion dollars per year. The ratio and the obligation are measuring fundamentally different things — a structural problem covered fully in the next section.

---

## When the Ratio Breaks: The ASC 842 Operating Lease Trap

A company can carry billions in lease obligations on its balance sheet and report effectively zero in interest expense — and the interest coverage ratio, as conventionally measured, will not catch it. This is not a data error. It is the direct consequence of ASC 842, the accounting standard that moved operating leases onto the balance sheet in 2019 without changing how their costs are classified on the income statement.

Before ASC 842, operating leases — store leases for retailers, aircraft leases for airlines, equipment leases for manufacturers — existed entirely off the balance sheet. They were disclosed in the footnotes as future minimum lease obligations but appeared nowhere as a liability on the face of the balance sheet, and generated no corresponding line in interest expense on the income statement. ASC 842 moved those obligations onto the balance sheet as right-of-use assets and operating lease liabilities. For retail chains, restaurant companies, and airlines, the change was substantial — companies with hundreds of long-term leases suddenly appeared to carry hundreds of millions or billions in balance sheet obligations.

What did not change is the critical point. The interest component of operating leases was not reclassified to interest expense. Under ASC 842, operating lease cost continues to be recognized as a single operating expense, sitting above the operating income line on the income statement. The income statement structure looks the same as it did before 2019. The balance sheet does not.

The result is an analytical gap. For [Lululemon](/stocks/LULU), as analyzed in [Financial Metrics for Value Investors](/blog/financial-metrics-value-investors), total debt of **$2.14 billion** is composed almost entirely of operating lease liabilities, with reported interest expense TTM running effectively at **$0**. Dividing any positive EBIT by an interest expense of zero produces an undefined or astronomically large coverage ratio — a number a standard screener will flag as exceptional. The underlying lease obligation is not exceptional. It is real, substantial, and entirely invisible to the coverage ratio.

The same structural problem appears in airlines, hotel and hospitality chains, and any business with a significant brick-and-mortar footprint built on operating leases. A screener applying "interest coverage ratio above **3.0x**" as a financial safety filter will include companies with zero reported interest expense — appearing to have unlimited coverage — while failing to register that the actual debt burden is simply structured differently than the metric assumes. The companies it misclassifies are not obscure edge cases. They are among the most prominent names in retail, dining, and travel.

GeminIQ's as-filed data makes this visible rather than obscuring it. When the interest expense field reads **$0** or near-zero for a company with billions in balance sheet liabilities, that is not a data anomaly. It is the filing disclosure: the company's obligations are structured as operating leases, and the interest coverage ratio as traditionally calculated does not apply. Knowing the ratio has broken is more analytically useful than receiving a large number that appears meaningful when it is not. But standard financial media doesn't read the footnotes.

The correct tool for operating lease-heavy companies is [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), using a definition of total debt that includes operating lease liabilities — which the as-filed balance sheet now provides directly, and which GeminIQ sources from the company's own XBRL-tagged filings without reclassification.

---

## Interest Coverage Ratio vs. Debt-to-EBITDA

The interest coverage ratio and [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda) answer related but distinct questions, and using both together covers ground that neither covers alone.

Interest coverage is a flow measure. It compares current-period operating earnings to current-period interest expense — asking whether the company's operations can service its debt obligations this year, at this earnings level, at this cost of debt. It is sensitive to near-term earnings changes and to movements in the interest rate on existing obligations. It says nothing about the total size of the debt load, the maturity schedule, or what happens when that debt needs to be refinanced.

Debt-to-EBITDA is a stock measure. It compares total outstanding debt to annual EBITDA, producing a ratio that represents how many years of current earnings the company would theoretically need to devote to debt repayment. A ratio of **3.0x** does not mean the company will default in three years — companies do not devote all EBITDA to repayment — but it provides a standardized measure of total leverage that the coverage ratio cannot.

The most analytically useful cases are where the two diverge. A company with a **6.0x** coverage ratio and **7.0x** Debt-to-EBITDA has no immediate payment problem but carries total debt representing seven years of earnings — when that debt matures, refinancing risk is substantial. Conversely, a company with a **2.0x** coverage ratio and **1.5x** Debt-to-EBITDA has thin current coverage but a total debt load that could be eliminated in less than two years of EBITDA. The coverage ratio flashes yellow; the total leverage picture is manageable. A one-metric read on either company would be wrong in the most important direction.

GeminIQ's pre-calculated [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) refines the picture further by netting cash against the total debt figure. A company carrying **$5 billion** in debt and **$4 billion** in cash has [Net Debt](/metrics/calculated-values/net-debt) of **$1 billion** — a fundamentally different risk profile than a company carrying the same debt against **$500 million** in cash, even though their gross Debt-to-EBITDA ratios are identical. When cash is a meaningful factor, net leverage is the more useful starting point.

For a first-pass distress filter, GeminIQ's [Altman Z-Score Safe screener](/screens/stock-screeners/altman-z-score-safe) integrates liquidity, retained earnings, operating efficiency, market leverage, and asset productivity into a single score calculated from XBRL-tagged filing data. It catches financial deterioration from multiple angles simultaneously. The interest coverage ratio catches only the earnings-to-interest relationship — and only when that relationship is validly calculable in the first place.

The interest coverage ratio tells the story for companies with conventional interest-bearing debt. For every other capital structure, it tells you which tool to reach for next.

---

## Frequently Asked Questions

### Is a 2.5x interest coverage ratio bad?

It depends entirely on the sector, which is why the number alone answers nothing. Above **5.0x** is generally strong and below **1.5x** signals real risk, but the sector matters more than the absolute number. Utilities and regulated pipelines operate sustainably at **2.0x to 4.0x** because regulated returns make long-duration debt appropriate, while a software business at the same level would be a genuine warning sign. Read the ratio against its industry first.

### How do you calculate the interest coverage ratio?

Interest Coverage Ratio = EBIT ÷ Interest Expense, both on a trailing twelve-month basis. EBIT is operating income before interest and taxes, and interest expense is the gross figure from the income statement or the interest note — not interest expense net of interest income, which flatters the ratio for cash-rich companies.

### What does an interest coverage ratio below 1 mean?

It means operating earnings are already insufficient to cover interest expense. The company must fund interest payments from cash reserves, asset sales, or new borrowing. Sustained readings below **1.0x** are among the more reliable quantitative precursors to covenant breach or restructuring.

### Is the interest coverage ratio the same as times interest earned?

Yes. "Times interest earned" is an older name for the same calculation — EBIT divided by interest expense. The two terms are used interchangeably in credit analysis and in most textbooks.

### Why is the interest coverage ratio undefined for some companies?

Because interest expense is zero or near zero, which makes the denominator collapse. This is common for capital-light software and technology businesses that carry no interest-bearing debt. An undefined ratio here means no leverage risk, not missing data — but it also means a screener filtering on the ratio will silently drop these companies unless nulls are handled deliberately.

### Does the interest coverage ratio account for operating leases?

No, and this is its most important blind spot. Under ASC 842 operating lease liabilities sit on the balance sheet, but their cost runs through operating expense rather than interest expense. A retailer or airline can carry billions in lease obligations and still report near-zero interest expense, producing a coverage ratio that looks healthy while the fixed-obligation burden is substantial.

### Is the interest coverage ratio based on EBIT or EBITDA?

The standard interest coverage ratio uses EBIT, operating profit after depreciation and amortization. A variant called EBITDA coverage uses EBITDA instead, which adds those non-cash charges back and produces a higher, more lenient ratio. GeminIQ uses EBIT, so its figures are the more conservative version.

---

### Related Reading

- [Financial Metrics for Value Investors: A Lululemon Case Study](/blog/financial-metrics-value-investors) — a full research workflow applied to a single 10-Q, including the interest coverage breakdown and the ASC 842 operating lease treatment in full.
- [ROIC: Return on Invested Capital Explained](/blog/roic-return-on-invested-capital-explained) — the returns side of the debt equation; how leverage interacts with capital efficiency to determine whether debt is creating or destroying value.
- [EV/EBITDA vs. P/E: Which Valuation Multiple to Use](/blog/ev-ebitda-vs-pe-ratio-explained) — how the EBITDA denominator in leverage ratios connects to valuation multiples, and when each framework applies.
- [Gross Profit Margin: What It Reveals About Business Model Strength](/blog/gross-profit-margin-business-model-analysis) — the income statement layer above EBIT, and how gross margin sets the structural ceiling for the earnings available to cover interest obligations.
- [Altman Z-Score Safe Zone Screener](/screens/stock-screeners/altman-z-score-safe) — applying the composite distress filter to raw SEC filing data as a complement to interest coverage ratio analysis.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=interest-coverage-ratio-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference lululemon athletica inc.'s Q1 FY2026 10-Q (filed June 4, 2026, period ending May 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001397187/000139718726000078/lulu-20260503.htm).

---

## Blog: 10-K vs 10-Q: What's the Difference and Which One Should You Read?
source: https://www.geminiq.com/blog/10-k-vs-10-q-differences-explained

### 10-K vs 10-Q: What's the Difference and Which One Should You Read?
The 10-K is a company's fully audited annual SEC filing; the 10-Q is its unaudited quarterly update. This guide covers what each filing contains, when each is due, the audit status difference, and how to use both together in fundamental research.

**A 10-K is a company's audited annual report to the SEC; a 10-Q is its unaudited quarterly report, filed for each of the first three fiscal quarters.** The 10-K is due 60 to 90 days after fiscal year-end depending on the company's filer status, and the 10-Q 40 to 45 days after quarter-end.

Most investors know the 10-K exists. Fewer read it. Even fewer understand how it relates to the 10-Q — the quarterly filing that updates the annual picture three times a year. This distinction matters more than most financial media lets on. The 10-K is the foundation: comprehensive, audited, filed once a year. The 10-Q is the delta: unaudited, faster, and often the first place a margin inflection, a balance sheet deterioration, or a new risk factor surfaces. Knowing which filing to reach for — and what to look for inside each one — is the starting point for any serious fundamental research. This guide covers both in full.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=10-k-vs-10-q-differences-explained)**

---

## Table of Contents

- [10-K vs 10-Q: The Key Differences at a Glance](#10-k-vs-10-q-the-key-differences-at-a-glance)
- [What Is a 10-K?](#what-is-a-10-k)
- [What Is a 10-Q?](#what-is-a-10-q)
- [Filing Deadlines: When Does Each Document Hit EDGAR?](#filing-deadlines-when-does-each-document-hit-edgar)
- [Audited vs. Unaudited: Why It Matters](#audited-vs-unaudited-why-it-matters)
- [What the 10-K Contains That the 10-Q Does Not](#what-the-10-k-contains-that-the-10-q-does-not)
- [What the 10-Q Reveals That the 10-K Cannot](#what-the-10-q-reveals-that-the-10-k-cannot)
- [How to Use Both Filings Together](#how-to-use-both-filings-together)
- [How GeminIQ Structures Both Filings for You](#how-geminiq-structures-both-filings-for-you)

---

## 10-K vs 10-Q: The Key Differences at a Glance

| | 10-K | 10-Q |
|---|---|---|
| **What it is** | Annual report | Quarterly report |
| **How often** | Once a year | Three times a year (no 10-Q for Q4) |
| **Audited?** | Yes — fully audited by an independent accounting firm | No — reviewed but unaudited |
| **Deadline** | 60–90 days after fiscal year-end, by filer status | 40–45 days after quarter-end, by filer status |
| **Typical length** | 100–200+ pages for large companies | 30–60 pages |
| **Comparative data** | Three years of financial statements | Current quarter vs. prior-year quarter, plus year-to-date |
| **Risk factors** | Full section (Item 1A) | Material changes only |
| **Includes** | Business description, MD&A, audited financials, full notes, controls, exhibits | Condensed financials, MD&A update, material changes |
| **Best for** | The foundation — business model, competitive position, audited baseline | The trajectory — what changed since the annual baseline |

The contrast between the two filings comes down to four dimensions: frequency, audit status, comprehensiveness, and length. The 10-K is filed once a year, fully audited, and runs 100 to 200 pages or more for large companies. The 10-Q is filed three times a year, reviewed but unaudited, and typically runs 30 to 60 pages. The 10-K presents three years of comparative financial data. The 10-Q presents the current quarter against the prior year quarter, and the year-to-date period against the prior year-to-date.

Neither filing is strictly more important than the other — they serve different analytical purposes. The 10-K gives you the foundation. The 10-Q gives you the trajectory. A value investor who only reads 10-Ks is working from data that is already months old before it's published. A value investor who only reads 10-Qs lacks the context and audited baseline that makes the quarterly changes meaningful. The complete picture requires both.

Standard financial media rarely explains this clearly. Most coverage reduces the distinction to "annual vs. quarterly report" and moves on — which is technically accurate but analytically useless. The real distinction lies in what each filing is required to contain, what level of independent verification backs the numbers, and how far ahead of the annual cycle the investors who actually read them can get.

---

## What Is a 10-K?

### What is a 10-K filing?

The 10-K is a company's annual report to the SEC. Every U.S.-listed public company must file one after the close of its fiscal year — no exceptions. It is the single most comprehensive primary source document available to investors: three years of fully audited financial statements, a complete description of the business, a detailed breakdown of risk factors, and management's own discussion of what happened during the year and why.

The key word in that sentence is *audited*. The financial statements inside a 10-K have been reviewed and signed off by an independent accounting firm — the same firms that appear on the cover page of Apple, Amazon, or ExxonMobil's filings. That audit process is what separates a 10-K from every other financial document a company produces. Press releases aren't audited. Earnings call transcripts aren't audited. Investor day presentations aren't audited. The 10-K is.

Every 10-K follows the same structure mandated by the SEC. Part I covers the business: what the company does, who its customers are, what risks it faces. Part II covers the financials: three years of income statements, balance sheets, and cash flow statements, along with management's discussion of the results and extensive footnotes that explain the accounting behind every number. Part III covers governance and compensation. Part IV contains exhibits and signatures. Once you've learned to navigate one 10-K, you can navigate any of them.

For investors focused on U.S. equities, the 10-K is the starting point — the document that establishes the baseline before anything else is read. For a detailed walkthrough of how to navigate one section by section, see [How to Read a 10-K: A Value Investor's Guide](/blog/how-to-read-10-k).

---

## What Is a 10-Q?

### What is a 10-Q filing?

The 10-Q is the quarterly update to the annual 10-K. Companies file one after each of the first three fiscal quarters — the fourth quarter is rolled into the 10-K and does not get its own 10-Q. That means in any given fiscal year, investors receive one 10-K and three 10-Qs: four filings, four opportunities to read the primary source before the financial media interprets it for you.

Where the 10-K is comprehensive, the 10-Q is condensed. It contains unaudited financial statements — reviewed but not fully audited — along with an abbreviated management discussion and analysis, updates on any material changes to risk factors, and disclosures on legal proceedings. What it omits is just as important. A 10-Q does not include the full business description from Item 1, does not repeat the complete risk factors section from Item 1A (only material changes), and does not carry the detailed notes on accounting policies that appear in the annual report.

Think of the 10-Q as the delta between annual reports. The 10-K tells you what the business looked like at year-end. The 10-Q tells you what changed. And because new information — revenue acceleration, margin compression, a new legal risk, a balance sheet shift — shows up in a 10-Q before the next 10-K is ever filed, the investors who read quarterly filings consistently are seeing the story months before everyone else. For a step-by-step guide to reading one efficiently, see [How to Read a 10-Q in Under 30 Minutes](/blog/how-to-read-10-q).

---

## Filing Deadlines: When Does Each Document Hit EDGAR?

### When is the 10-K due?

The SEC sets 10-K deadlines based on a company's filing status — a classification tied to its public float and prior filing history. Large accelerated filers, generally companies with a public float of **$700 million** or more, must file their 10-K within 60 days of fiscal year-end. Accelerated filers must file within 75 days. Non-accelerated filers have 90 days. This means that for a company with a December 31 fiscal year-end, investors can expect the 10-K somewhere between late February and late March, depending on filer status.

The practical implication is that the annual report is already several months old by the time most investors read it. [Apple's](/stocks/AAPL) fiscal year ends in late September; its 10-K typically appears in late October. [Amazon](/stocks/AMZN) and [Google](/stocks/GOOGL) both follow the calendar year and file in early February. [ExxonMobil](/stocks/XOM) does the same. Understanding your target company's fiscal calendar is step one in knowing when to expect its filings.

### When is the 10-Q due?

Deadlines for the 10-Q are tighter. Large accelerated filers must file within 40 days of quarter-end. Accelerated filers and non-accelerated filers have 45 days. In practice, most large-cap companies file well within those windows — often within two to three weeks of quarter-end. That speed is part of what makes the 10-Q valuable: new data arrives quickly, and the investors who access it directly from SEC EDGAR rather than waiting for media coverage have a meaningful head start.

One structural quirk worth knowing: because the fourth quarter is covered by the 10-K, there is no Q4 10-Q. The fiscal year filing sequence for most companies looks like this — Q1 10-Q, Q2 10-Q, Q3 10-Q, then 10-K. Three quarterly updates followed by the annual audit. GeminIQ surfaces all four documents in a unified timeline, so you can track how each metric evolves from the first quarterly filing through the final audited annual.

---

## Audited vs. Unaudited: Why It Matters

This is the distinction most investor guides mention and then immediately underexplain. So here is the full picture.

When a company files its 10-K, an independent public accounting firm — Ernst & Young, Deloitte, KPMG, PwC — has performed a full audit of the financial statements. That means the auditors have examined the company's records, tested its internal controls, verified its accounting judgments, and concluded that the financial statements are presented fairly in accordance with U.S. GAAP. They sign an audit opinion, which appears at the front of Item 8 in the 10-K. A clean (unqualified) opinion is standard. A qualified opinion, an adverse opinion, or a going concern paragraph are all meaningful red flags.

The 10-Q financial statements are reviewed, not audited. The same independent firm performs a review — a significantly less intensive process that involves analytical procedures and inquiries, but not the same level of examination and testing. The financial statements are management's representation, with the auditor providing limited assurance rather than full verification. This does not make 10-Q numbers unreliable — for any established public company, the quarterly figures are almost always accurate. But it does mean that a fraud, a restatement risk, or a material accounting error is more likely to go undetected in a quarterly filing than in an audited annual one.

For a value investor, the practical takeaway is this: treat the 10-K as the verified baseline. Use the 10-Q to track how that baseline evolves. If a figure in a 10-Q strikes you as anomalous — a sudden receivables spike, an unexpected inventory build, a gross margin collapse with no MD&A explanation — that anomaly is worth flagging for closer review when the audited annual arrives. But standard financial media doesn't read the footnotes. The investors who do are the ones who catch restatements before they happen.

---

## What the 10-K Contains That the 10-Q Does Not

The 10-K is structurally required to include several disclosures that the 10-Q omits entirely. Understanding what those are tells you when to reach for the annual filing rather than the quarterly one.

**Item 1 — Full Business Description.** The 10-K requires a complete narrative of the company's business: products and services, operating segments, competitive position, distribution channels, customer concentration, intellectual property, regulatory environment, and human capital. Apple's 10-K business description establishes that the company sells through both direct and indirect channels, that its Services segment spans the App Store, Apple Music, iCloud, and Apple Care, and that no single customer accounts for more than **10%** of net revenue. None of this appears in the 10-Q. If you want to understand the business structure rather than just the quarterly numbers, the 10-K is the document.

**Item 1A — Complete Risk Factors.** The 10-K requires management to disclose every material risk the company faces. The 10-Q only requires disclosure of material *changes* to those risks since the last annual filing. If a 10-Q has no updates to the risk factors section, it means management believes nothing has materially changed — but the baseline risks from the 10-K still apply. Investors who skip the annual risk factors section and only scan the quarterly updates are working from an incomplete picture. It was the 10-K, not any quarterly filing, that first surfaced Apple's detailed tariff exposure across imports from China, India, Japan, South Korea, Taiwan, Vietnam, and the EU — an entirely new set of disclosures with direct margin implications.

**Three Years of Comparative Financials.** The income statement, balance sheet, and cash flow statement in a 10-K present three years of data side by side. The 10-Q presents the current quarter versus the prior year quarter, and the year-to-date period versus the prior year. For long-run trend analysis — revenue compounding rates, margin trajectories over multiple years, capital expenditure cycles — the 10-K's multi-year view is the right starting point. GeminIQ's [Financial Statements](/features#financial-statements) feature extends that view even further, pulling 17+ years of comparable data directly from SEC EDGAR so you can see every filing period in a single unified timeline.

**The Auditor's Opinion and Internal Controls Report.** The 10-K contains the full audit opinion and, for larger filers, management's assessment of internal controls over financial reporting under Sarbanes-Oxley Section 404. These disclosures don't appear in quarterly filings. A company with a material weakness in internal controls will disclose it in the 10-K — not in a 10-Q.

**Executive Compensation and Segment Detail.** Annual reports contain significantly more granular segment reporting and compensation disclosures than quarterly filings. For businesses with multiple operating units, the 10-K's segment data is often more detailed than anything visible at the quarterly level.

> **GeminIQ Tip:** GeminIQ extracts every data point from every 10-K with its [XBRL tag intact](/features#financial-statements) and pre-calculates more than 90 KPIs directly from the tagged filing data — including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield), and the [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score). New filings are processed within one business day of hitting EDGAR.

---

## What the 10-Q Reveals That the 10-K Cannot

Here is the part that most financial media gets wrong by omission: the 10-Q is not just a shorter, less reliable version of the 10-K. It is a fundamentally different analytical tool — one that surfaces specific types of information that the annual filing structurally cannot provide.

**Quarterly Inflection Points.** The 10-K shows full-year averages. A company can have one extraordinary quarter and two mediocre ones and report a clean annual result. The 10-Q breaks that average apart. [Apple's](/stocks/AAPL) Q1 FY2026 gross margin came in at **48.2%** — a 130 basis point expansion over the prior year quarter — but the full-year FY2025 margin was **46.9%**. The quarterly filing told the acceleration story months before the next annual report would confirm it. GeminIQ pre-calculates [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) and [Revenue Growth](/metrics/growth-metrics/revenue-growth) on a trailing twelve-month basis directly from SEC filing data, so those inflection points are visible in the dashboard the moment a new 10-Q hits EDGAR — no spreadsheet required.

**Balance Sheet Changes Between Annual Reports.** The balance sheet in a 10-K is a snapshot of a single day — the fiscal year-end. Everything that happens to the balance sheet between annual filings is only visible in the 10-Qs. In Q1 FY2026, [Apple](/stocks/AAPL) reduced total debt by **$8.1 billion** in a single quarter. That deleveraging signal — meaningful for any investor tracking financial risk — was present in the 10-Q and nowhere in the 10-K. GeminIQ's [Interactive Visualizations](/features#visualizations) let you chart any balance sheet line item quarter by quarter across 17+ years, making those shifts visible immediately.

**New Risk Factor Disclosures.** When a material new risk emerges mid-year, the 10-Q is where it first appears. A 10-Q risk factor update signals that something has changed since the annual filing — and because companies have a legal obligation to disclose material risks, a mid-year addition is almost always worth reading carefully.

**Seasonal and Segment Patterns.** For businesses with strong seasonality — retailers, consumer electronics companies, certain industrials — the quarterly data reveals patterns the annual aggregate obscures. A company that earns the majority of its operating income in a single quarter looks completely different in Q1 than in Q3. Understanding that rhythm requires reading the 10-Qs, not just the 10-K. GeminIQ's [Custom Tables](/features#custom-tables) let you pull any combination of quarterly figures side by side across companies or across time, making seasonal structures explicit rather than buried in year-end totals.

**Accelerated Access to Fresh Data.** Because large accelerated filers must publish 10-Qs within 40 days of quarter-end, the quarterly filing is often the fastest primary source available. Most earnings press releases hit the same day as or before the 10-Q, but the press release is a curated summary. The 10-Q is the complete data. For how to move through one efficiently, see [How to Read a 10-Q in Under 30 Minutes](/blog/how-to-read-10-q).

---

## How to Use Both Filings Together

A useful framework for combining the two: start with the 10-K to build your mental model of the business, then track the 10-Qs as live updates against that model.

The 10-K answers the structural questions. How does this company make money? What are its operating segments and how do they perform? What does management say are the biggest risks? What does five years of margin history look like? What is the debt structure, and when does it mature? These are foundation questions, and the annual filing is the document built to answer them.

The 10-Q answers the trajectory questions. Is margin expanding or compressing relative to last year? Is the balance sheet strengthening or stretching? Did management update the risk factors — and if so, why? Is operating cash flow tracking ahead of or behind last year's pace? These are the questions that tell you whether the business is confirming or contradicting the thesis you built from the annual filing.

The investors who get into trouble are the ones who read only one or the other. Reading only the 10-K leaves you working from data that is already up to nine months old by the time the next quarterly cycle is complete. Reading only the 10-Qs leaves you without the audited baseline and long-run context that makes the quarterly changes meaningful. For a deeper look at the specific items inside each filing that most investors scroll past entirely, see [What Investors Miss in SEC Filings](/blog/what-investors-miss-in-sec-filings).

The SEC makes both filings available for free through EDGAR at sec.gov. The challenge isn't access — it's knowing how to navigate them quickly and extract what matters before the rest of the market has processed it. That is the problem GeminIQ was built to solve.

---

## How GeminIQ Structures Both Filings for You

Most financial research platforms don't show you the 10-K or the 10-Q directly. They show you a processed version — numbers that have been ingested by a third-party aggregator, normalized into a standardized template, and stripped of the XBRL tags that make the original filing data verifiable and traceable. When Apple reports a line item that only Apple reports — like its Vendor Non-Trade Receivables — that item frequently disappears into an aggregator's "Other" bucket. For more on why this matters, see [What Is XBRL and Why Does It Matter for Investors](/blog/what-is-xbrl).

GeminIQ extracts data directly from SEC EDGAR — not from any third-party aggregator. Every number you see in GeminIQ is pulled from the raw 10-K or 10-Q filing, with its original XBRL tag preserved. That means the data on your screen is the data the company filed, in the exact structure the company filed it, traceable to the specific line item in the specific document. When you look at a balance sheet in GeminIQ, you are seeing the balance sheet — not a normalized approximation of it.

GeminIQ's [Financial Statements](/features#financial-statements) tool structures both 10-K and 10-Q data into a unified timeline. GeminIQ's [Calculated Metrics](/features#calculated-metrics) derive more than 90 KPIs from that tagged data — including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow Per Share](/metrics/per-share-metrics/free-cash-flow-per-share), [Diluted EPS](/metrics/per-share-metrics/diluted-earnings-per-share), and the [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) — without substituting processed numbers for the raw filing source. And because GeminIQ processes new filings within one business day of them hitting EDGAR, the quarterly update you need to track a thesis is available before most investors have even seen the headline.

A standard screener shows you last quarter's aggregated summary. By pulling the raw 10-Q directly via GeminIQ, you can see the actual as-filed figures — the ones the company reported, not the ones someone else decided to normalize for you.

## Frequently Asked Questions

### Are both the 10-K and 10-Q audited?

No. The financial statements in a 10-K are audited by an independent accounting firm, which issues an opinion on them. The financial statements in a 10-Q are reviewed, not audited: the auditor performs limited procedures and gives no opinion. See [which SEC filings are audited](/blog/which-sec-filings-are-audited) for the full breakdown.

### What is the difference between a 10-K, 10-Q, and 8-K?

The 10-K is the annual report and the 10-Q the quarterly report, both filed on a fixed schedule. The [8-K](/blog/what-is-8-k) is filed when something material happens between them, such as an acquisition, an executive departure, or an earnings release, and is generally due within four business days of the event.

### Where can I find a company's 10-K and 10-Q?

Every 10-K and 10-Q is free on the SEC's EDGAR system, searchable by company name or ticker, and most companies also post them on their investor relations website. GeminIQ pulls both directly from EDGAR and lays out each filing's financial statements side by side.

### Is a 10-K the same as an annual report?

Not exactly. The 10-K is the annual filing the SEC requires, in a prescribed format. The annual report to shareholders is a separate document, often more promotional, that companies send with their proxy materials. Many companies now use the 10-K itself as the core of their annual report and wrap it with a letter and summary.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=10-k-vs-10-q-differences-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025) and Q1 FY2026 10-Q (filed January 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193).<br>
All financial figures cited in this article reference Amazon.com, Inc.'s Q1 FY2026 10-Q (filed April 30, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1018724/000101872426000014/amzn-20260331.htm).<br>
All financial figures cited in this article reference Alphabet Inc.'s Q1 FY2026 10-Q (filed April 30, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001652044/000165204426000048/goog-20260331.htm).<br>
All financial figures cited in this article reference Exxon Mobil Corporation's Q1 FY2026 10-Q (filed May 4, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0000034088/000003408826000067/xom-20260331.htm).</sup>

---

## Blog: SEC Form 4 Transaction Codes: Full List and What Each Code Means
source: https://www.geminiq.com/blog/form-4-transaction-code-list

### SEC Form 4 Transaction Codes: Full List and What Each Code Means
Form 4 transaction codes are the single-letter identifiers in the Transaction Code column of every SEC Form 4 filing (Column 3 of Table I, Column 4 of Table II) that classify exactly what kind of transaction an insider made, from a voluntary open-market purchase to a routine tax withholding. This reference covers all 20 codes the SEC defines, organized by the same five categories the form itself uses, with a plain-English meaning and signal weight for each one.

**Form 4 transaction codes are the single letters that classify each insider transaction reported to the SEC — P for an open-market purchase, S for an open-market sale, A for a grant or award, F for shares withheld to pay taxes, and M for an option exercise.** The SEC defines 20 codes in five groups; only P and S reflect an insider's own decision to trade on the open market.

Every SEC Form 4 filing carries a single letter in its Transaction Code column — Column 3 of Table I for shares, Column 4 of Table II for options and other derivatives — that determines whether the transaction it reports means anything at all. Financial news headlines rarely mention it. A share count and a name are enough to generate a story — "CEO Sells 200,000 Shares" — regardless of whether that sale was a discretionary market call or an automatic tax withholding triggered by an RSU vesting. The SEC defines exactly twenty of these codes, split across five categories in the form's own instructions. The difference between them is the difference between an insider making an economic decision and an insider going through a scheduled, mechanical process. This is the complete reference: every code, what it actually means, and how much analytical weight it deserves.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=form-4-transaction-code-list)**

---

## Table of Contents

- [Jump to a Code](#jump-to-a-code)
- [Quick Reference: All 20 Codes at a Glance](#quick-reference-all-20-codes-at-a-glance)
- [General Transaction Codes: P, S, V](#general-transaction-codes-p-s-v)
- [Rule 16b-3 Transaction Codes: A, D, F, I, M](#rule-16b-3-transaction-codes-a-d-f-i-m)
- [Derivative Securities Codes: C, E, H, O, X](#derivative-securities-codes-c-e-h-o-x)
- [Other Exempt and Small Acquisition Codes: G, L, W, Z](#other-exempt-and-small-acquisition-codes-g-l-w-z)
- [Other Transaction Codes: J, K, U](#other-transaction-codes-j-k-u)
- [How Codes Combine: Modifiers and Amendment Flags](#how-codes-combine-modifiers-and-amendment-flags)
- [Reading the Code Column for Signal, Not Just Definition](#reading-the-code-column-for-signal-not-just-definition)
- [The GeminIQ Edge: Codes Without the Memorization](#the-geminiq-edge-codes-without-the-memorization)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Jump to a Code

**General:** [P](#code-p) · [S](#code-s) · [V](#code-v)
**Rule 16b-3:** [A](#code-a) · [D](#code-d) · [F](#code-f) · [I](#code-i) · [M](#code-m)
**Derivative:** [C](#code-c) · [E](#code-e) · [H](#code-h) · [O](#code-o) · [X](#code-x)
**Other Exempt:** [G](#code-g) · [L](#code-l) · [W](#code-w) · [Z](#code-z)
**Other:** [J](#code-j) · [K](#code-k) · [U](#code-u)

The three codes that account for most questions: [P](#code-p) is a voluntary open-market purchase, [S](#code-s) is a sale, and [F](#code-f) is shares withheld to cover tax on a vesting event — not a sale decision, despite reducing the insider's share count.

---

## Quick Reference: All 20 Codes at a Glance

The SEC's Form 4 instructions group every transaction code into five categories: General Transaction Codes, Rule 16b-3 Transaction Codes, Derivative Securities Codes, Other Section 16(b)-Exempt and Small Acquisition Codes, and Other Transaction Codes. The table below lists all twenty in that order, with the signal weight each one carries for fundamental and insider-activity research.

| Code | Category | Meaning | Signal Weight |
|---|---|---|---|
| P | General | Open-market or private purchase | High — a voluntary, out-of-pocket capital decision |
| S | General | Open-market or private sale | Conditional — depends on size, footnotes, and 10b5-1 status |
| V | General | Transaction voluntarily reported earlier than required | None — a reporting-timing flag, not a transaction type |
| A | Rule 16b-3 | Grant, award, or other acquisition under a compensation plan | None — compensation delivery, not a market decision |
| D | Rule 16b-3 | Disposition of shares back to the issuer | None — typically forfeiture or a plan-based return |
| F | Rule 16b-3 | Shares withheld to cover exercise price or tax on vesting | None — automatic tax withholding, not a sale decision |
| I | Rule 16b-3 | Discretionary transaction under a Rule 16b-3(f) plan | Low — plan-governed, with limited insider discretion |
| M | Rule 16b-3 | Exercise or conversion of a derivative security | Conditional — check for a same-day disposition |
| C | Derivative | Conversion of a derivative security | None — mechanical exercise of an existing right |
| E | Derivative | Expiration of a short derivative position | None — a written option lapsed unexercised |
| H | Derivative | Expiration or cancellation of a long derivative position with value received | Low — passive settlement, not a market call |
| O | Derivative | Exercise of an out-of-the-money derivative security | Low — often plan-timed or forced by expiration |
| X | Derivative | Exercise of an in-the-money or at-the-money derivative security | Conditional — check whether the shares were retained or sold |
| G | Other Exempt | Bona fide gift | None — no market view expressed |
| L | Other Exempt | Small acquisition exempt under Rule 16a-6 | None — a de minimis acquisition below the reporting threshold |
| W | Other Exempt | Acquisition or disposition by will or the laws of descent and distribution | None — an estate event, not a trading decision |
| Z | Other Exempt | Deposit into or withdrawal from a voting trust | None — a governance structure change, not a market transaction |
| J | Other | Other acquisition or disposition (described in a footnote) | Depends entirely on the footnote |
| K | Other | Equity swap or instrument with similar characteristics | Modifier — appended to another code, not a standalone transaction |
| U | Other | Disposition pursuant to a tender of shares in a change-of-control transaction | None — forced by the acquiring party's tender terms |

---

## General Transaction Codes: P, S, V

These are the only codes that can, on their own, represent a voluntary market decision.

<span id="code-p"></span>

**P — Open-market or private purchase.** The insider spent personal capital to buy shares or a derivative security. No plan required it, no vesting schedule delivered it. Of all twenty codes, P is the one that most directly reflects what an insider believes about the stock right now.

<span id="code-s"></span>

**S — Open-market or private sale.** The insider sold shares or a derivative security at the current price. It is a voluntary act by definition, but S is common enough — executives routinely diversify concentrated equity positions — that the raw code alone says little. Whether an S transaction carries weight depends on context the code itself doesn't supply: size relative to total holdings, a 10b5-1 footnote, and whether the filing breaks an established pattern.

<span id="code-v"></span>

**V — Transaction voluntarily reported earlier than required.** This is not a transaction type; it is a timing flag. Certain small transactions qualify for deferred reporting on Form 5, and a reporting person can choose to disclose one early on a Form 4 instead. When V appears, look at the actual code it accompanies to understand the underlying event.

---

## Rule 16b-3 Transaction Codes: A, D, F, I, M

These five codes cover more Form 4 filings than any other category, because most executive compensation today isn't cash — it's equity. Rule 16b-3 exempts these compensation-related transactions from Section 16(b) short-swing profit liability, and the codes here cover the mechanics: grants, forfeitures, tax withholding, plan-based dispositions, and derivative exercises.

<span id="code-a"></span>

**A — Grant, award, or other acquisition pursuant to Rule 16b-3(d).** An RSU grant, an option award, or any other equity compensation delivered under the company's plan. The compensation committee made this decision, not the insider. A large A transaction is the single most common reason a Form 4 shows a big share count with zero investment signal.

<span id="code-d"></span>

**D — Disposition to the issuer pursuant to Rule 16b-3(e).** Shares surrendered back to the company — most often unvested RSUs forfeited on departure, or shares returned under a specific plan provision. This reduces share count but reflects an employment event, not a market view.

<span id="code-f"></span>

**F — Payment of exercise price or tax liability by delivering or withholding securities.** When equity compensation vests or an option is exercised, the recipient owes tax. Rather than writing a check, the company withholds a portion of the shares automatically. F transactions generate a large share of what financial media casually labels "insider selling" — no cash was ever received in the traditional sense, and no discretionary decision to sell was made.

<span id="code-i"></span>

**I — Discretionary transaction under Rule 16b-3(f).** A transaction inside a tax-conditioned plan — commonly a 401(k) company stock fund — where the insider elects to move money in or out of company stock. It carries limited discretion, but the plan structure and required cooling-off periods between opposite-direction elections constrain how much any single I transaction reveals.

<span id="code-m"></span>

**M — Exercise or conversion of a derivative security exempted under Rule 16b-3.** The mechanical act of exercising options is not itself informative — options get exercised when they're in the money and approaching expiration regardless of the holder's outlook. What matters is what happens next. An M followed immediately by an S on the same or following business day is an exercise-and-sell: cash generated, no equity conviction retained. An M with no corresponding sale means the insider kept the shares — a meaningfully different signal from the same exercise event.

---

## Derivative Securities Codes: C, E, H, O, X

None of the five codes in this category represent a trading decision on their own — they're the mechanical vocabulary for options, warrants, and convertible instruments in Table II, covering transactions the Rule 16b-3 codes above don't reach.

<span id="code-c"></span>

**C — Conversion of a derivative security.** A convertible instrument — often preferred stock or a convertible note — converts into the underlying common equity per its predefined terms. This is contractual mechanics, not a market decision.

<span id="code-e"></span>

**E — Expiration of a short derivative position.** A written (short) option position expires unexercised. The insider who wrote the option collected the premium and the obligation simply lapsed — not itself a directional signal.

<span id="code-h"></span>

**H — Expiration or cancellation of a long derivative position with value received.** A held derivative position expires or is cancelled, and the holder receives some value in the process — commonly cash settlement in a merger or a corporate action affecting outstanding options. It is a passive event driven by a corporate transaction, not a trading decision.

<span id="code-o"></span>

**O — Exercise of an out-of-the-money derivative security.** The insider exercises an option or right at a strike price above the current market value for a call, or below it for a put. This usually happens for structural reasons — a plan requiring exercise before expiration — rather than because the position suddenly became attractive.

<span id="code-x"></span>

**X — Exercise of an in-the-money or at-the-money derivative security.** The more common exercise scenario: the option is profitable to exercise at current prices. As with code M, the exercise itself is close to automatic once an option is deep in the money. The signal lives in whether the resulting shares were sold immediately or retained.

---

## Other Exempt and Small Acquisition Codes: G, L, W, Z

The four codes here have nothing to do with compensation or trading at all — they cover what happens to shares during a gift, a death, a small transfer, or a change in who controls the vote.

<span id="code-g"></span>

**G — Bona fide gift.** Shares transferred to family members, a foundation, or another recipient with no cash changing hands. A G transaction expresses no view on the stock — the insider is not selling and is not signaling anything bearish by giving shares away.

<span id="code-l"></span>

**L — Small acquisition exempt under Rule 16a-6.** The SEC exempts acquisitions that, combined with other acquisitions of the same class over the prior six months, don't exceed **$10,000** in market value — provided the insider doesn't dispose of any of it within that same six-month window. These are minor transactions by design; the dollar threshold itself is the reason they carry no analytical weight.

<span id="code-w"></span>

**W — Acquisition or disposition by will or the laws of descent and distribution.** An inheritance event. Shares change hands because of a death, not a market decision by anyone currently holding them.

<span id="code-z"></span>

**Z — Deposit into or withdrawal from a voting trust.** Shares move into or out of a voting trust structure — a governance arrangement, not a change in the beneficial owner's economic position or market outlook.

---

## Other Transaction Codes: J, K, U

The final three codes are the odd ones out: a catch-all for anything the other categories don't capture, a modifier for equity swaps, and a forced disposition during a change-of-control deal.

<span id="code-j"></span>

**J — Other acquisition or disposition.** The SEC's catch-all. When no other code fits, the filer uses J and is required to describe the actual nature of the transaction in a footnote. A J transaction's meaning is entirely dependent on that footnote — never treat a bare J as informative on its own; always read what it's attached to.

<span id="code-k"></span>

**K — Transaction in an equity swap or instrument with similar characteristics.** K is not a standalone transaction type. The form's own instructions specify it should be appended alongside the code that actually describes the transaction — for example, "S/K" for a sale executed through an equity swap. Seeing K by itself in a summary or a screener output usually means the underlying code was truncated somewhere in the data pipeline.

<span id="code-u"></span>

**U — Disposition pursuant to a tender of shares in a change-of-control transaction.** Shares tendered into an acquirer's tender offer during a merger or acquisition. This is forced by the terms of the deal, not a discretionary decision by the insider — everyone tendering shares under the same offer gets the same code regardless of their personal view of the transaction.

---

## How Codes Combine: Modifiers and Amendment Flags

Two codes function differently from the eighteen that describe standalone transactions. K, as covered above, is a modifier appended to another code rather than a transaction type on its own — it signals that an equity swap or similar derivative structure was involved in executing the reported transaction. V works similarly as a timing flag rather than a transaction description, marking that a transaction eligible for deferred Form 5 reporting was disclosed early on a Form 4 instead.

A separate set of designators — the numbers 3, 4, and 5 — can appear next to a transaction code to flag a correction rather than describe the transaction itself. When a transaction that should have been reported on a prior Form 3 is instead being disclosed now, the filer places a "3" in the code column. A transaction that should have appeared on an earlier Form 4 gets a "4" appended to its code — an open-market purchase reported late shows as "P4." A transaction eligible for Form 5 that's being reported now gets a "5." None of these designators change what the underlying code means; they flag that the disclosure itself is catching up on something that should have appeared earlier.

---

## Reading the Code Column for Signal, Not Just Definition

Twenty codes exist because the SEC needs to categorize every possible way beneficial ownership can change hands. Compensation, estate transfers, governance structures, derivative mechanics, and voluntary market activity all have to fit somewhere. But for an investor trying to extract a signal from insider activity, most of that categorization exists to rule things out. Of the twenty, only P carries unconditional weight. S, M, and X carry conditional weight that depends on context the code itself doesn't provide — size, footnotes, and what transaction happened immediately before or after. The remaining sixteen codes almost never represent a market view: they're compensation delivery, tax mechanics, estate events, gifts, or corporate actions that happen to an insider rather than being chosen by one.

This is why a share count in a headline is close to meaningless without the code attached to it. A **$4 million** insider "sale" reported as code F is a company withholding shares for taxes on a scheduled RSU vesting. The same dollar figure reported as code S with no 10b5-1 footnote is a discretionary decision to convert equity into cash. Same number, same direction, entirely different meaning — and the transaction code is the only field on the form that tells them apart.

---

## The GeminIQ Edge: Codes Without the Memorization

A standard news feed reports the share count and the dollar total. It rarely surfaces the transaction code at all, which means the reader has no way to tell whether a share-count decline reflects a discretionary sale or a mechanical event without pulling the raw Form 4 and checking the Transaction Code column manually. GeminIQ's [Insider Transactions](/features#insider-transactions) feature pulls directly from the raw SEC Form 4 feed and classifies every row as a Purchase or a Sale, so the direction of the transaction is immediately visible without opening the underlying filing.

That classification is the starting point, not the finish line — the table above still matters for deciding how much weight a Purchase or Sale actually deserves once you know which code produced it. For a full field-by-field walkthrough of everything else on the form, including the footnotes and the 10b5-1 disclosure that determine how much an S transaction really tells you, see [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4).

---

## Frequently Asked Questions

### What is the most important Form 4 transaction code?

Code P — an open-market or private purchase — is the only code that unconditionally represents a voluntary, out-of-pocket capital decision by the insider. No compensation plan, tax obligation, or estate event can generate a P transaction; it only appears when someone chooses to spend their own money on the stock.

### What does code F mean on a Form 4?

F is the tax-withholding code, used when a company automatically withholds a portion of newly vested shares to cover the recipient's income tax obligation. It appears as a disposition and reduces share count, but represents no decision by the insider to sell.

### What is the difference between codes M and X?

M is the exercise or conversion of a derivative security exempted under Rule 16b-3 — the standard code for exercising employee stock options. X is the exercise of an in-the-money or at-the-money derivative security outside that specific exemption. Functionally, both describe an option exercise; which one applies depends on which SEC rule governs the specific compensation arrangement. In both cases, the exercise itself carries little signal — what matters is whether the resulting shares were sold or retained.

### Why do most Form 4 filings use code A or F instead of P or S?

Modern executive compensation is heavily weighted toward RSUs and options rather than cash salary, and both generate routine, scheduled Form 4 filings — an A when the equity is granted, an F when a portion is withheld for taxes at vesting. These filings occur automatically as part of the compensation structure, which is why they vastly outnumber discretionary P and S transactions in raw filing volume.

### Can a single Form 4 line have more than one code?

Yes, in one specific case: K is appended alongside another code when the transaction involves an equity swap or similar instrument, producing combinations like "S/K." Outside of that pairing, each line on the form carries one transaction code describing one type of event.

Every one of these questions comes back to the same rule: the code decides whether a transaction means anything — the share count never does.

---

## Related Reading

- [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4) — the full field-by-field breakdown of every section on the form, including the header, both tables, and the footnotes.
- [Insider Trading Tracker: How to Track Insider Buying and Selling](/blog/insider-trading-tracker) — how to build a pattern out of individual Form 4 filings over time, once you know which codes carry weight.
- [Insider Cluster Buying: What It Signals and How to Track It](/blog/insider-cluster-buying-signal-data) — applying the code P signal specifically to multiple insiders buying in a tight window.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — where Form 4 fits alongside the 10-K, 10-Q, 8-K, DEF 14A, and S-1.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=form-4-transaction-code-list)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Section 9e: GeminIQ in Use — Defense Sector
source: https://www.geminiq.com/blog/defense-sector-stock-analysis

### Defense Sector Stock Analysis: Lockheed's Fading Returns
This defense sector stock analysis tracks five years of ROIC, P/E, leverage, and Altman Z-Score trends for Lockheed Martin, Northrop Grumman, and General Dynamics, showing Lockheed's returns eroding as its multiple expands while General Dynamics steadily deleverages.

Defense spending is up across the board, and it shows in the headline numbers. [Lockheed Martin](/stocks/LMT) (LMT), [Northrop Grumman](/stocks/NOC) (NOC), and [General Dynamics](/stocks/GD) (GD) all grew trailing-twelve-month revenue between **4.6% and 9.4%** through their most recent quarterly filings. On revenue growth alone, this looks like a uniformly strong sector.

It isn't. Lockheed Martin's Q1 FY2026 10-Q (filed April 23, 2026, period ending March 29, 2026) shows the highest Price-to-Earnings Ratio of the three primes, **28.80x**, attached to a [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) that has been falling for five straight years. That combination, a rising multiple on a shrinking return, isn't something a single quarter's comps table would flag. It only shows up when you look at the trend.

Using a GeminIQ [Custom Watchlist](/features#custom-watchlists) to pull every quarter of [Calculated Metrics](/features#calculated-metrics) for [Lockheed Martin](/stocks/LMT), [Northrop Grumman](/stocks/NOC), and [General Dynamics](/stocks/GD) back to 2021, the same sector splits into three distinct stories: one prime getting more expensive for less return, one that took a real, filed hit and mostly recovered, and one that has been quietly de-risking every year without anyone pricing it in.

| Company | ROIC (TTM) | P/E Ratio (TTM) | Altman Z-Score |
|---|---|---|---|
| [Lockheed Martin](/stocks/LMT) (LMT) | **23.10%** | **28.80x** | **3.69** |
| [Northrop Grumman](/stocks/NOC) (NOC) | **13.63%** | **21.09x** | **3.46** |
| [General Dynamics](/stocks/GD) (GD) | **14.38%** | **21.17x** | **4.10** |

### Phase 1: The Return-on-Capital Divergence

Read the table above as a single quarter and Lockheed looks like the winner: the highest [Return on Invested Capital](https://www.geminiq.com/metrics/returns-and-profitability/return-on-invested-capital) of the three, by a wide margin. Read it as the end point of a five-year line, and the story flips.

Lockheed's ROIC has fallen in nearly every year since 2021: **41.55%**, then **32.59%**, then **30.42%**, then **24.19%**, a brief tick up to **25.51%** in 2025, and **23.10%** now. That's a decline of nearly half from where it started. General Dynamics moved the other way, holding in the low-teens before climbing every year since 2023: **12.75%**, **12.43%**, **12.16%**, **13.41%**, **14.15%**, and **14.38%** now. Northrop Grumman round-tripped through an actual trough: **19.99%** in 2021, falling to **8.44%** by 2023, before recovering to **13.63%** today.

Lockheed's current ROIC is still the highest of the three in absolute terms. It's also the only one of the three moving in the wrong direction.

<sup>*GeminIQ Calculated Metrics comparison showing Return on Invested Capital, Price-to-Earnings Ratio, and Altman Z-Score for Lockheed Martin, Northrop Grumman, and General Dynamics as of the quarter ended March 2026.*</sup>

### Phase 2: The Multiple That Isn't Falling With It

If Lockheed's return on capital has been shrinking for five years, its valuation multiple should reflect that. It hasn't.

Lockheed's [Price-to-Earnings Ratio](https://www.geminiq.com/metrics/valuation-metrics/price-to-earnings-ratio) has moved from **13.81x** in 2021 to **20.38x**, **15.34x**, **20.83x**, **22.17x**, and **28.80x** now, more than double where it started, over the same five years its ROIC nearly halved. General Dynamics' multiple expanded too, but far more modestly: **16.26x** to **21.17x**. Northrop Grumman's P/E tells a different kind of story entirely: it spiked to **33.09x** in 2023, not because the market bid the stock up, but because earnings that year were depressed by a real, filed charge covered in Phase 4. A P/E built on a temporarily damaged earnings base isn't the same signal as one built on a rising price against a shrinking return, and Lockheed's is the latter.

<sup>*GeminIQ Visualizations chart plotting quarterly Price-to-Earnings Ratio for Lockheed Martin, Northrop Grumman, and General Dynamics from 2021 through Q1 FY2026.*</sup>

### Phase 3: The Balance Sheet Ledger

A shrinking return on capital paired with a rising multiple usually means one of two things: the market expects a turnaround, or the company is borrowing to keep its numbers up. The balance sheet points to the second explanation for Lockheed.

Lockheed's [Debt-to-Equity Ratio](https://www.geminiq.com/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) climbed from **3.64** in 2021 to **4.71**, **6.67**, **7.78**, **7.90**, and **6.91** now, nearly double where it started. Its [Net Debt-to-EBITDA](https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) followed the same path, from **0.88x** to **2.40x**. General Dynamics moved in the opposite direction on both counts: Debt-to-Equity fell from **1.84** to **1.26**, and [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) from **2.09x** to **0.70x**, a genuine, uninterrupted deleveraging run. Northrop Grumman's leverage was choppier but ended lower than it started: Debt-to-Equity from **2.29** to **1.92**, Net Debt-to-EBITDA peaking near **3.09x** in 2023 before settling at **2.17x** now. Of the three, only Lockheed's balance sheet is carrying more risk today than it was five years ago.

<sup>*GeminIQ Visualizations chart plotting quarterly Debt-to-Equity Ratio for Lockheed Martin, Northrop Grumman, and General Dynamics from 2021 through Q1 FY2026.*</sup>

### Phase 4: The Altman Z-Score and the B-21 Scar

None of these three is a distress case. All three have spent most of the last five years in the [Altman Z-Score](https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score)'s "safe zone" above 2.99. But the trend inside that zone tells you who's getting safer and who isn't.

General Dynamics climbed from **3.16** in 2021 to a peak of **4.16** in 2025, now **4.10**, the highest and most consistent improvement of the three. Lockheed drifted down from **3.95** to a 2025 low of **3.31**, recovering slightly to **3.69** now, still comfortably safe but well off its own high. Northrop Grumman actually left the safe zone for two years: its score fell to **2.75** in 2024, into the "gray zone" below the 2.99 threshold. The cause is on the record in its own filings: a **$1.56 Billion** B-21 program charge booked in the fourth quarter of 2023 (labeled "B-21 Charge" on Northrop's cash flow statement) drove the company to a **$535 Million** net loss that single quarter, dragging profitability and retained earnings down with it. Northrop's score has since climbed back to **3.46**, the sharpest single recovery of the three, but it's the only one of the three with an actual excursion below the safe-zone line in this window.

<sup>*GeminIQ Visualizations chart plotting quarterly Altman Z-Score for Lockheed Martin, Northrop Grumman, and General Dynamics from 2021 through Q1 FY2026, showing Northrop's 2023-2024 dip below the 2.99 safe-zone threshold.*</sup>

### Phase 5: What Institutional and Insider Data Confirm

GeminIQ's [Institutional Ownership](/features#institutional-ownership) data shows a gap that lines up with the balance sheet trend, even if it's a modest one: institutions hold **72.92%** of [Lockheed Martin](/stocks/LMT), **78.66%** of [Northrop Grumman](/stocks/NOC), and **82.68%** of [General Dynamics](/stocks/GD), as of the most recent 13F-reported quarter. The GeminIQ [Insider Transactions](/features#insider-transactions) feed shows nothing but Sale filings across all three companies over the past year, a routine post-vesting pattern at this size of company rather than a distinguishing signal on its own. The more useful signal is the one that's held steady all year: the same company with the cleanest balance sheet trend also carries the deepest institutional bench.

### The Analyst's Verdict

Revenue growth is the one number all three primes share right now, and it's the number that makes the sector look uniform from a distance. It isn't. Lockheed Martin's Return on Invested Capital has fallen in nearly every year since 2021 while its Price-to-Earnings Ratio has more than doubled and its leverage has climbed to match, a combination the current-quarter snapshot alone won't show you. General Dynamics has done the opposite on every measure that matters here: steadier returns, a shrinking Debt-to-Equity Ratio, and the highest [Altman Z-Score](/blog/altman-z-score-financial-distress) of the three. Northrop Grumman is the one name with a real, filed scar, the 2023 B-21 charge, and a genuine recovery from it since. Same sector, same demand environment, three different trend lines underneath.

## Frequently Asked Questions

### Why did Northrop Grumman's Altman Z-Score fall below the safe zone in 2023?

A **$1.56 Billion** B-21 program charge, booked in the fourth quarter of 2023, drove Northrop Grumman to a **$535 Million** net loss that quarter, pulling its Altman Z-Score down to **2.75** by 2024, below the model's 2.99 safe-zone threshold. It has since recovered to **3.46**.

### Has Lockheed Martin's Return on Invested Capital improved or worsened since 2021?

It has worsened in nearly every year since 2021, falling from **41.55%** to **23.10%** as of the quarter ended March 29, 2026, even as its Price-to-Earnings Ratio rose from **13.81x** to **28.80x** over the same window.

### Which defense prime carries the lowest leverage by Net Debt-to-EBITDA?

General Dynamics carries the lowest Net Debt-to-EBITDA ratio of the three at **0.70x**, the result of a steady decline from **2.09x** in 2021.

### When did Lockheed Martin, Northrop Grumman, and General Dynamics last file their 10-Q?

Lockheed Martin filed its Q1 FY2026 10-Q on April 23, 2026 (period ending March 29, 2026); Northrop Grumman filed on April 21, 2026 (period ending March 31, 2026); General Dynamics filed on April 29, 2026 (period ending April 5, 2026).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=defense-sector-stock-analysis)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Lockheed Martin Corporation's Q1 FY2026 10-Q (filed April 23, 2026, period ending March 29, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/936468/000162828026026836/lmt-20260329.htm).<br>
All financial figures cited in this article reference Northrop Grumman Corporation's Q1 FY2026 10-Q (filed April 21, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/1133421/000113342126000016/noc-20260331.htm).<br>
All financial figures cited in this article reference General Dynamics Corporation's Q1 FY2026 10-Q (filed April 29, 2026, period ending April 5, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/40533/000004053326000012/gd-20260405.htm).</sup>

---

## Section 9f: GeminIQ in Use — Retail Sector
source: https://www.geminiq.com/blog/retail-sector-stock-analysis

### Retail Sector Stock Analysis: Returns Are Fading
This retail sector stock analysis tracks five years of Return on Invested Capital, Net Debt-to-EBITDA, and Altman Z-Score trends for Home Depot, Lowe's, and Tractor Supply, showing all three names losing capital efficiency and taking on more leverage, even as two of the three no longer have an equity base clean enough to run standard ROE and Debt-to-Equity comparisons.

Home improvement and farm-retail names screen as steady compounders on the surface. [Home Depot](/stocks/HD) (HD), [Lowe's](/stocks/LOW) (LOW), and [Tractor Supply Company](/stocks/TSCO) (TSCO) all grew trailing-twelve-month revenue between **2.2% and 6.2%** through their most recent quarterly filings, and none of the three shows any sign of a demand problem.

Look past revenue and a different, shared trend shows up. Home Depot's Q1 FY2026 10-Q (filed May 27, 2026, period ending May 3, 2026) shows [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) at **24.70%**, down from **58.06%** five years ago. Tractor Supply's fell from **47.56%** to **25.30%** over the same window. Lowe's path was choppier but still sits well below its own 2022 peak. This isn't one company's story. It's the sector's.

The harder question is how to compare the three cleanly, because two of them no longer have an equity base clean enough for half the standard ratio toolkit to mean anything. Using a GeminIQ [Custom Watchlist](/features#custom-watchlists) to pull every quarter of [Calculated Metrics](/features#calculated-metrics) for [Home Depot](/stocks/HD), [Lowe's](/stocks/LOW), and [Tractor Supply](/stocks/TSCO) back to 2021, here's where all three actually stand, and how they got there.

| Company | ROIC (TTM) | Net Debt-to-EBITDA (TTM) | Altman Z-Score |
|---|---|---|---|
| [Home Depot](/stocks/HD) (HD) | **24.70%** | **2.14x** | **5.50** |
| [Lowe's](/stocks/LOW) (LOW) | **31.82%** | **2.96x** | **3.26** |
| [Tractor Supply](/stocks/TSCO) (TSCO) | **25.30%** | **0.92x** | **4.33** |

### Phase 1: The Shared ROIC Erosion

None of the three retailers is compounding capital better than it was five years ago. [Home Depot's](/stocks/HD) [Return on Invested Capital](https://www.geminiq.com/metrics/returns-and-profitability/return-on-invested-capital) has fallen in nearly every year since 2021: **58.06%**, **47.57%**, **43.60%**, **37.68%**, **31.59%**, and **24.70%** now, cut by more than half. [Tractor Supply's](/stocks/TSCO) path is nearly as steep: **47.56%** down to **25.30%**. [Lowe's](/stocks/LOW) peaked at **46.42%** in 2022 before sliding to **31.82%** now, still the highest of the three in absolute terms but well off its own high.

The market hasn't priced this consistently. Home Depot's [Price-to-Earnings Ratio](https://www.geminiq.com/metrics/valuation-metrics/price-to-earnings-ratio) climbed from **20.62x** in 2021 to **23.15x** now, a richer multiple attached to a ROIC less than half what it used to be. Tractor Supply's multiple actually peaked at **26.39x** in 2025 and has pulled back to **21.87x** this year, the one name where the price has started catching up to the trend. Lowe's ended higher too, **18.68x** to **19.98x**, but choppier in between.

<sup>*GeminIQ Calculated Metrics comparison showing Return on Invested Capital, Net Debt-to-EBITDA, and Altman Z-Score for Home Depot, Lowe's, and Tractor Supply as of each company's most recent quarter.*</sup>

### Phase 2: Why Half the Toolkit Doesn't Work Here

A shrinking Return on Invested Capital should show up in Return on Equity and Debt-to-Equity too. For two of these three names, it can't, because the equity in the denominator has stopped behaving like a normal number.

[Home Depot's](/stocks/HD) equity swung negative in 2022 (**-$1.71 Billion**) before recovering to a still-thin **$13.87 Billion** now, against **$107.90 Billion** in total assets. The effect on Return on Equity is exactly what you'd expect from a denominator bouncing near zero: **-1,695%** in 2021, an absurd **84,713%** in 2022 when equity briefly cratered, **-2,487%** the year after, then **128%** now. [Lowe's](/stocks/LOW) equity has been negative every year since 2022 and remains negative today at **-$9.27 Billion**, against **$64.21 Billion** in total liabilities and only **$54.94 Billion** in assets. Lowe's own balance sheet doesn't call this section "equity" anymore. Its cover page labels it "Shareholders' Deficit."

[Tractor Supply](/stocks/TSCO) is the exception. Its equity has stayed solidly positive throughout, growing from **$1.85 Billion** in 2021 to **$2.51 Billion** now, which is why its own [Return on Equity](https://www.geminiq.com/metrics/returns-and-profitability/return-on-equity) and [Debt-to-Equity Ratio](https://www.geminiq.com/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) still behave like normal numbers (currently **45.50%** and **3.64**) instead of swinging wildly or flipping sign. That's the reason this comparison leans on ROIC and [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) throughout: neither one requires a sane, positive equity figure to still mean something.

<sup>*GeminIQ Financial Statements view of the Balance Sheet for Home Depot and Lowe's, showing Total Stockholders Equity of $13.87 Billion and negative $9.27 Billion respectively, against Tractor Supply's positive $2.51 Billion.*</sup>

### Phase 3: The Leverage Creep

Capital efficiency fading is one half of the picture. The other half is that all three are carrying more debt relative to their own cash flow than they were five years ago, not less.

[Home Depot's](/stocks/HD) [Net Debt-to-EBITDA](https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) rose from **1.25x** in 2021 to **2.14x** now. [Lowe's](/stocks/LOW) rose further, from **1.32x** to **2.96x**, the highest reading of the three and the worst point in its own six-year window. [Tractor Supply](/stocks/TSCO) started this period in a net cash position (**-0.12x** in 2021) and has moved to modest net debt, **0.92x** now. Still the lowest of the three by a wide margin, but the direction of travel matches its peers.

<sup>*GeminIQ Visualizations chart plotting quarterly Net Debt-to-EBITDA for Home Depot, Lowe's, and Tractor Supply from 2021 through Q1 FY2026, showing all three trending higher over the window.*</sup>

### Phase 4: The Altman Z-Score Trend

All three retailers remain comfortably in the [Altman Z-Score's](https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score) "safe zone" above 2.99. None of them is a distress case. But none of them is getting safer, either.

[Home Depot's](/stocks/HD) score fell from **6.69** in 2021 to **5.50** now, still the highest of the three but down from a 2024 peak of **6.85**. [Lowe's](/stocks/LOW) declined every single year, from **4.15** to **3.26**, the closest of the three to the gray-zone threshold. [Tractor Supply's](/stocks/TSCO) score held in the low-5s for years before a sharp drop in the most recent twelve months, from **5.07** to **4.33**, the steepest single-year move of the three.

<sup>*GeminIQ Visualizations chart plotting quarterly Altman Z-Score for Home Depot, Lowe's, and Tractor Supply from 2021 through Q1 FY2026.*</sup>

### Phase 5: What Institutional and Insider Data Confirm

GeminIQ's [Institutional Ownership](/features#institutional-ownership) data shows **69.68%** for Home Depot, **68.38%** for Lowe's, and **84.69%** for Tractor Supply, as of the most recent 13F-reported quarter. Tractor Supply's figure is down sharply from roughly 93.7% the quarter before, and Lowe's from roughly 75.9%, both large enough single-quarter moves to note, though 13F data is lagged by design and one quarter isn't a trend on its own. The GeminIQ [Insider Transactions](/features#insider-transactions) feed shows nothing but Sale filings at Home Depot and Tractor Supply over the past year. Lowe's shows mostly Sale filings too, plus a single Director purchase of **$231,060** late last year, a small position against the sale volumes around it and not enough to read as a signal in either direction.

### The Analyst's Verdict

Revenue growth is the number all three retailers share, and it's the number that makes the sector look healthy from a distance. Underneath it, Return on Invested Capital has fallen at all three since 2021, leverage relative to EBITDA has risen at all three over the same window, and none of the three [Altman Z-Score](/blog/altman-z-score-financial-distress)s is moving up. The reason this is easy to miss is that Home Depot's and Lowe's own equity bases have shrunk or gone negative from years of buybacks, breaking Return on Equity and Debt-to-Equity as useful tools for two-thirds of the sector. Tractor Supply's balance sheet is the one clean enough to still read normally, but its own returns are eroding at close to the same pace as its larger peers.

## Frequently Asked Questions

### Why is Lowe's Return on Equity not a useful metric right now?

Lowe's carries negative total equity, **-$9.27 Billion** as of its most recent quarter, so any Return on Equity calculation divides by a negative number and produces a result that doesn't mean what a normal ROE reading means. Lowe's own balance sheet labels this section "Shareholders' Deficit" rather than equity.

### Has Home Depot's Return on Invested Capital improved or worsened since 2021?

It has worsened in nearly every year since 2021, falling from **58.06%** to **24.70%** as of the quarter ended May 3, 2026, even as its Price-to-Earnings Ratio rose from **20.62x** to **23.15x** over the same window.

### Which retailer carries the lowest leverage by Net Debt-to-EBITDA?

Tractor Supply Company carries the lowest Net Debt-to-EBITDA ratio of the three at **0.92x**, though it started the five-year window in a net cash position and has since moved toward modest net debt.

### When did Home Depot, Lowe's, and Tractor Supply last file their 10-Q?

Home Depot filed its Q1 FY2026 10-Q on May 27, 2026 (period ending May 3, 2026); Lowe's filed on May 28, 2026 (period ending May 1, 2026); Tractor Supply filed on May 7, 2026 (period ending March 28, 2026).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=retail-sector-stock-analysis)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference The Home Depot, Inc.'s Q1 FY2026 10-Q (filed May 27, 2026, period ending May 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/354950/000162828026038247/hd-20260503.htm).<br>
All financial figures cited in this article reference Lowe's Companies, Inc.'s Q1 FY2026 10-Q (filed May 28, 2026, period ending May 1, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/60667/000006066726000072/low-20260501.htm).<br>
All financial figures cited in this article reference Tractor Supply Company's Q1 FY2026 10-Q (filed May 7, 2026, period ending March 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/916365/000091636526000024/tsco-20260328.htm).</sup>

---

## Section 9g: GeminIQ in Use — Airlines Sector
source: https://www.geminiq.com/blog/airline-sector-stock-analysis

### Airline Sector Stock Analysis: One Carrier Is Re-Levering
This airline sector stock analysis tracks five years of Net Debt-to-EBITDA, Altman Z-Score, and margin trends for Delta, United, and American Airlines, showing two carriers deleveraging every year while the third reverses course.

Airline stocks have spent the last two years trading on a single narrative: the pandemic-era balance sheet damage is behind the industry, and the "Big Three" U.S. legacy carriers are back to being investable, cash-generating businesses. Revenue supports that story on the surface. [Delta Air Lines](/stocks/DAL) (DAL), [United Airlines Holdings](/stocks/UAL) (UAL), and [American Airlines Group](/stocks/AAL) (AAL) each closed out their Q1 FY2026 10-Qs (filed in April 2026, period ending March 31, 2026) with trailing-twelve-month revenue growth in the **3.3% to 5.2%** range. None of the three is anywhere near the operating losses they were posting three years ago.

But "revenue recovered" and "the balance sheet recovered" are two different claims, and the second one is a trend question, not a snapshot question. A single quarter of [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) or [Altman Z-Score](/blog/altman-z-score-financial-distress) tells you where a company stands today. It says nothing about whether that number has been getting better or worse for the last five years — and in a capital-heavy, debt-financed industry like commercial aviation, the direction of travel matters more than the current altitude.

Using a GeminIQ [Custom Watchlist](/features#custom-watchlists) to pull every quarter of [Calculated Metrics](/features#calculated-metrics) for [Delta](/stocks/DAL), [United](/stocks/UAL), and [American](/stocks/AAL) back to 2021 — not just the latest 10-Q — shows two of the three carriers on a clean, uninterrupted deleveraging path. The third is not.

| Company | Net Debt-to-EBITDA (TTM) | Altman Z-Score | Net Profit Margin (TTM) |
|---|---|---|---|
| [Delta Air Lines](/stocks/DAL) (DAL) | **1.11x** | **1.34** | **6.87%** |
| [United Airlines](/stocks/UAL) (UAL) | **2.00x** | **1.29** | **6.06%** |
| [American Airlines](/stocks/AAL) (AAL) | **7.44x** | **0.60** | **0.36%** |

### Phase 1: The Divergence, By the Numbers

Look at the table above for more than a few seconds and one row stops fitting the pattern. Delta and United sit within a point of each other on every column. American isn't close to either — its leverage ratio is **6.70x** Delta's, its Altman Z-Score is less than half of either peer's, and its margin is a rounding error next to theirs.

None of that is new information by itself; a single current-quarter comps table would show the same gap. What a snapshot can't show is whether that gap is closing or widening — and that's the actual question this piece answers, because the answer isn't the one the "airlines are back" narrative assumes.

<sup>*GeminIQ Calculated Metrics comparison showing Net Debt-to-EBITDA, Altman Z-Score, and Net Profit Margin (TTM) side-by-side for Delta, United, and American as of the quarter ended March 31, 2026.*</sup>

### Phase 2: The Leverage Trajectory Since 2021

A standard screener only shows this quarter's Net Debt-to-EBITDA. Pulling the full quarterly history via GeminIQ's [Visualizations](/features#visualizations) shows the shape of the last five years, and that shape is the real story.

[Delta's](/stocks/DAL) [Net Debt-to-EBITDA](https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) has fallen every single year since 2021, without a single year-over-year reversal: **4.72x** at the end of 2021, **3.39x** in 2022, **2.12x** in 2023, **1.50x** in 2024, **1.16x** in 2025, and **1.11x** as of the latest quarter. [United's](/stocks/UAL) path was choppier in dollar terms — its net debt actually grew from **$15.16 Billion** in 2021 to a peak of **$27.16 Billion** in 2023 as it took on debt to fund fleet growth — but its leverage ratio still came down sharply against a faster-growing EBITDA base: **10.36x**, **4.98x**, **3.95x**, **2.46x**, **2.49x**, and now **2.00x**.

[American's](/stocks/AAL) ratio also fell hard off its distorted 2021 reading of **39.22x**, bottoming at **6.48x** in 2023 and **6.51x** in 2024. Then it reversed. By the end of 2025 it had climbed back to **8.33x** — worse than at any point since 2022 — before ticking down slightly to **7.44x** in the most recent quarter. American's total debt did keep falling in dollar terms, from **$38.06 Billion** in 2021 to **$27.72 Billion** now. But its EBITDA base shrank faster than its debt did, which is precisely what a raw dollar-debt headline won't tell you.

<sup>*GeminIQ Visualizations chart plotting quarterly Net Debt-to-EBITDA for Delta, United, and American from 2021 through Q1 FY2026, showing Delta and United's continuous decline against American's 2025 reversal.*</sup>

### Phase 3: The Valuation Disconnect

If leverage trends this different are hiding behind similar-looking headlines, the market's pricing should tell on it. It does — just not in the direction a screener would suggest.

[Delta](/stocks/DAL) carries a **$43.12 Billion** [market cap](https://www.geminiq.com/metrics/valuation-metrics/market-capitalization) on a [Price-to-Earnings Ratio](https://www.geminiq.com/metrics/valuation-metrics/price-to-earnings-ratio) of **9.63x**; [United](/stocks/UAL), **$29.82 Billion** and **8.14x** earnings. [American](/stocks/AAL) is the outlier: priced at just **$7.10 Billion**, yet carrying the highest P/E ratio of the three at **35.15x**. A novice screener read might flag American as either a deep-value name (smallest market cap) or an expensive one (highest multiple). Both readings would miss the actual explanation: American's trailing net income of **$202 Million** is so thin that the P/E ratio's denominator is doing almost none of the work a healthy earnings base would do. A P/E ratio built on next-to-nothing earnings isn't a valuation signal — it's a symptom of the margin collapse the next section quantifies.

<sup>*GeminIQ Calculated Metrics comparison of Market Capitalization and Price-to-Earnings Ratio (TTM) for Delta ($43.12B, 9.63x), United ($29.82B, 8.14x), and American ($7.10B, 35.15x).*</sup>

### Phase 4: The Margin and ROIC Collapse

American's revenue kept growing through 2025 and into 2026. Its bottom line did not follow.

Trailing-twelve-month net income fell from **$846 Million** at the end of 2024 to **$111 Million** at the end of 2025 to **$202 Million** in the most recent quarter — a decline of more than **70%** over five quarters even as the top line grew. [Net Profit Margin](https://www.geminiq.com/metrics/margin-metrics/net-profit-margin) fell in step, from **1.56%** to **0.36%**, and [Return on Invested Capital](https://www.geminiq.com/metrics/returns-and-profitability/return-on-invested-capital) fell from **7.07%** to **3.90%** over the same window.

Delta and United show no equivalent slide. Delta's [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) sits at **6.87%** and its [ROIC](/blog/roic-return-on-invested-capital-explained) at **15.36%**, both broadly in line with where they've run since 2023. United's margin is **6.06%** and its ROIC **12.25%**, also stable to improving. The revenue-growth headline is common to all three carriers. The profitability trend underneath it is not.

<sup>*GeminIQ Calculated Metrics chart tracking quarterly Net Profit Margin (TTM) for Delta, United, and American, showing American's fall from 1.56% to 0.36% over five quarters against stable readings for its peers.*</sup>

### Phase 5: The Altman Z-Score, and What Smart Money Does With It

A margin gap this wide should also show up in a model built to flag financial distress — and it does. The [Altman Z-Score](https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score) was built to flag bankruptcy risk in manufacturers, and it's a less precise tool for asset-heavy, debt-financed service businesses like airlines — none of these three would be mistaken for a "safe zone" company under the original model. But the same trend logic from Phase 2 applies here too, and it separates the three cleanly.

[Delta's](/stocks/DAL) score climbed from **0.62** in 2021 to **1.44** by the end of 2025, before easing slightly to **1.34** in the latest quarter — still more than double where it started. [United](/stocks/UAL) followed a similar arc, climbing from **0.85** to a plateau in the high-1.2s to high-1.3s for the last three years, now sitting at **1.29**. [American](/stocks/AAL) is the exception: its score rose from **0.28** to a peak of **0.75** in 2024, then fell for two consecutive readings, down to **0.60** now — essentially flat versus where it stood in 2022 despite two more years of runway to improve.

That divergence shows up in who owns the stock. GeminIQ's [Institutional Ownership](/features#institutional-ownership) data shows institutions hold **85.37%** of [Delta](/stocks/DAL) and **84.80%** of [United](/stocks/UAL), but only **64.72%** of [American](/stocks/AAL) — a gap of just over 20 percentage points that has held steady across recent quarters. What are the people actually running American doing with their own money? The GeminIQ [Insider Transactions](/features#insider-transactions) feed shows nothing but Sale filings across all three carriers over the past year, which is a routine post-vesting pattern at this size of company, not a distinguishing signal on its own. The institutional ownership gap is the more telling data point, because it reflects capital that chose where to sit after reading the same filings.

<sup>*GeminIQ Institutional Ownership module for Delta Air Lines, showing 85.37% total institutional ownership as of the most recent 13F-reported quarter.*</sup>

<sup>*GeminIQ Institutional Ownership module for United Airlines, showing 84.80% total institutional ownership as of the most recent 13F-reported quarter.*</sup>

<sup>*GeminIQ Institutional Ownership module for American Airlines, showing 64.72% total institutional ownership as of the most recent 13F-reported quarter.*</sup>

### The Analyst's Verdict

The "airlines recovered" narrative is accurate for two of the three companies in this comparison. [Delta's](/stocks/DAL) and [United's](/stocks/UAL) Net Debt-to-EBITDA and Altman Z-Score have both improved in nearly every year since 2021, and their margins and ROIC have held up alongside that deleveraging. [American's](/stocks/AAL) revenue grew too, but its EBITDA base shrank enough that its own leverage ratio and Altman Z-Score are now moving backward, not forward, and its trailing net income has fallen by more than 70% in five quarters. A discounted market cap and a familiar route network don't offset a trend line that's heading the wrong way — and a trend line is exactly what a single-quarter comps table will never show you.

## Frequently Asked Questions

### How does American Airlines' Net Debt-to-EBITDA compare to Delta and United?

As of the quarter ended March 31, 2026, American Airlines carries a Net Debt-to-EBITDA ratio of 7.44x, versus 1.11x for Delta and 2.00x for United — 6.70x Delta's leverage relative to EBITDA.

### Has American Airlines' Altman Z-Score improved or worsened since 2021?

It improved from 0.28 in 2021 to a peak of 0.75 in 2024, then declined to 0.60 as of the latest quarter — a level essentially flat with where it stood at the end of 2022.

### Which airline carries the lowest leverage risk by Net Debt-to-EBITDA?

Delta Air Lines carries the lowest Net Debt-to-EBITDA ratio of the three at 1.11x, the result of an uninterrupted year-over-year decline since 2021.

### When did Delta, United, and American Airlines last file their 10-Q?

Delta filed its Q1 FY2026 10-Q on April 8, 2026; United filed on April 22, 2026; American filed on April 23, 2026 — all for the quarter ended March 31, 2026.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=airline-sector-stock-analysis)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Delta Air Lines, Inc.'s Q1 FY2026 10-Q (filed April 8, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/27904/000002790426000022/dal-20260331.htm).<br>
All financial figures cited in this article reference United Airlines Holdings, Inc.'s Q1 FY2026 10-Q (filed April 22, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/100517/000010051726000091/ual-20260331.htm).<br>
All financial figures cited in this article reference American Airlines Group Inc.'s Q1 FY2026 10-Q (filed April 23, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/6201/000000620126000032/aal-20260331.htm).</sup>

---

## Section 10a: Company Deep-Dive — Costco (COST)
source: https://www.geminiq.com/blog/costco-stock-analysis-2026

### Costco Stock Analysis (2026): How 3.8% Margin Earns 33% ROIC
Costco just filed its Q3 FY26 10-Q. A pipeline recalculation using the actual filed tax rate puts ROIC at 33.4% — still elite capital efficiency on a wafer-thin margin, just a different number than previously shown.

**[Costco](/stocks/COST) Wholesale Corporation ($COST) just dropped its Q3 FY2026 10-Q (filed June 3, 2026). The surface-level headlines look identical to every other quarter: thin margins, same-store sales chatter, and the usual argument over whether a 50.8x P/E makes sense for a grocer. Every financial commentator frames Costco as a "low-margin retailer" trading at an irrational premium. The raw filing data tells a more interesting story — and this quarter, that includes catching our own platform citing a stale number.**

| Field | Value |
|---|---|
| Ticker | $COST |
| Filing | Q3 FY2026 10-Q |
| Filed | June 3, 2026 |
| Period End | May 10, 2026 |
| ROIC (TTM) | **33.4%** |
| Gross Margin (TTM) | **12.88%** |

## The 12.9% Gross Margin "Trap"

Screen [Costco](/stocks/COST) against any other major retailer and it looks structurally broken. GeminIQ's [Calculated Metrics](/features#calculated-metrics) show [Walmart](/stocks/WMT) running a **24.98%** TTM [gross margin](/metrics/margin-metrics/gross-profit-margin), [Target](/stocks/TGT) at **28.14%**, and even a notoriously thin-margin grocer like [Kroger](/stocks/KR) clearing **23.18%**. Costco posts **12.88% gross margin TTM** — less than half of any of them.

**The Data:** On the Q3 FY2026 10-Q, [Costco](/stocks/COST) posted a TTM operating margin of just **3.82%** on **12.88%** gross margin — a spread that would sink most retailers but funds one of the highest capital-efficiency engines in the S&P 500, covered next.

**The GeminIQ Edge:** A standard screener flags this as a red flag. Pulling the raw Income Statement quarter by quarter via GeminIQ's [Custom Table](/features#custom-tables) shows Costco is *intentionally* running the thinnest possible gross margin. This isn't weakness — it's the moat. Management prices merchandise near breakeven specifically to drive the number that actually matters: membership renewals. The merchandise business is a loss leader for the real product.

<center><sup>GeminIQ Calculated Metrics comparing Gross Profit Margin TTM across Costco (12.88%), Walmart (24.98%), Target (28.14%), and Kroger (23.18%) — structurally thin until you understand the membership engine behind it.</sup></center>

## The ROIC Reality Check

Here's where it gets uncomfortable in a useful way. Our last teardown of this ticker cited a **42.68%** Return on Invested Capital. That number was wrong, and here's exactly why, because burying it would defeat the point of this whole platform.

**The Data:** [ROIC](/blog/roic-return-on-invested-capital-explained) depends on NOPAT, which depends on the effective tax rate. Cross-checking [Costco's](/stocks/COST) filed tax provision against pretax income puts the real trailing effective rate at **24.8%**, not the flat **21%** a quick calculation reaches for. The full chain: TTM EBIT of **$11.23 Billion**, taxed at **24.8%**, produces NOPAT of **$8.44 Billion** against Average [Invested Capital](/metrics/calculated-values/invested-capital) of **$25.24 Billion** — a Return on Invested Capital of **33.4% TTM**, roughly **9 percentage points** below the figure we previously published, and up steadily from **28.8%** in November 2023.

**The GeminIQ Edge:** The gap traced back to a resolver issue: Costco began tagging its pretax income line with an atypical XBRL concept that didn't match our tax-rate lookup, so the calculation fell back to a flat 21% statutory assumption. Worth being precise about how much that actually explains, because it is far less than it looks. Holding EBIT and invested capital fixed, swapping **24.8%** back to **21%** lifts ROIC only to **35.1%** — under two points. The remaining seven points came from the denominator: reproducing **42.68%** requires an invested capital base near **$19.78 Billion**, against the **$25.24 Billion** the filings actually support. The tax rate was the visible error. The capital base was the expensive one. We catch both by cross-referencing [Calculated Metrics](/features#calculated-metrics) against raw filed figures rather than trusting a single derived output — the same discipline we'd expect a reader to apply to any platform's number, including ours. **33.4% ROIC on a 3.82% operating margin** is still an exceptional result. It's just the accurate one.

<center><sup>GeminIQ Calculated Metrics showing Costco's ROIC TTM rising from 28.8% (November 2023) to 33.4% (Q3 FY2026), plotted against an Effective Tax Rate holding near 24.8% — the verified rate, not a flat statutory assumption.</sup></center>

## The $3.2 Billion Float

So where does 30%+ ROIC come from on a near-breakeven merchandise business? The balance sheet answers directly.

Scroll to the liabilities section of the 10-Q and there's a line most retail investors skip past: **Deferred Membership Fees**. This is the annual membership payment members have already paid, in cash, upfront, that Costco hasn't yet recognized as revenue. In accounting terms, it's a liability. In economic terms, it's free capital.

**The Data:** Deferred Membership Fees have grown from **$2.337 Billion** in August 2023 to **$3.157 Billion** in the current filing — up **35%** in under three years. The only interruptions come in the fiscal fourth quarter each year, when the renewal cycle resets — **$2.501 Billion** in August 2024 and **$2.854 Billion** in August 2025 both dipped below the prior quarter before resuming.

**The GeminIQ Edge:** Most financial sites never surface deferred membership fees as a distinct line. Auditing the raw Balance Sheet quarter over quarter via GeminIQ's [Financial Statements](/features#financial-statements) shows the float compounding in real time. It's the same mechanism Buffett describes when he praises insurance float — members are Costco's policyholders, and they keep sending bigger checks.

<center><sup>GeminIQ Financial Statements tracking Deferred Membership Fees from $2.337 Billion (August 2023) to $3.157 Billion (Q3 FY2026) — a compounding, interest-free float funding the operation.</sup></center>

## The Cash Machine

The float doesn't just sit on the balance sheet. It shows up in how completely accounting profit turns into actual cash.

**The Data:** [Costco](/stocks/COST) converts TTM net income of **$8.838 Billion** into **$8.806 Billion** of Free Cash Flow — a **99.6%** conversion rate.

**The GeminIQ Edge:** Retailers typically convert 60-70% of net income to free cash flow, because CapEx and inventory builds eat the difference. Pulling Operating Cash Flow against CapEx via GeminIQ's [Financial Statements](/features#financial-statements) shows Costco clearing a full dollar of cash for every dollar of accounting profit — while still funding warehouse expansion out of the same line. The float and the payables terms cover what CapEx would otherwise take out.

<center><sup>GeminIQ Financial Statements showing Costco's quarterly Net Income Loss, summing across the four most recent quarters to $8.838 Billion, against Free Cash Flow TTM of $8.806 Billion — a 99.6% conversion rate driven by the deferred membership float and payables timing.</sup></center>

## Smart Money Diverging

A good teardown doesn't skip the reality check. What are the people running [Costco](/stocks/COST), and the institutions that own it, actually doing with their money?

**The Data:** GeminIQ's [Insider Transactions](/features#insider-transactions) feed shows an unbroken stream of executive sales, zero open-market purchases since June 2022. Meanwhile [Institutional Ownership](/features#institutional-ownership) data shows a different pattern: institutions recovered from a **57.4%** low in December 2022 to **65.2%** as of the most recent 13F (March 2026), including a step back from a **67.7%** high just three months earlier.

**The GeminIQ Edge:** These aren't contradictory signals, they're two different time horizons. Insiders selling into RSU vesting at a 50.8x multiple is standard behavior for a mature mega-cap, not a distress signal. Institutional 13F data is quarterly and lagged up to 45 days, so the March reading is already old news by the time it's filed, but the multi-year recovery off the 2022 low is the more durable pattern worth tracking. Neither the selling nor the buying settles the valuation debate on its own. Both are visible only because the raw feeds are traceable.

<center><sup>GeminIQ Insider Transactions showing an unbroken stream of Costco executive sales and zero open-market purchases since June 2022.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing Costco institutional ownership recovering from a 57.4% low in December 2022 to 65.2% as of the most recent 13F (March 2026), including a step back from a 67.7% high three months earlier.</sup></center>

## Frequently Asked Questions

### What does GeminIQ's data show about Costco's corrected ROIC?

A verification against Costco's filed tax provision put the real trailing effective rate at 24.8%. Applying it to TTM EBIT of $11.23 Billion gives NOPAT of $8.44 Billion, which over Average Invested Capital of $25.24 Billion produces a Return on Invested Capital of 33.4% — roughly 9 percentage points below a previously cited 42.68% figure. The tax rate accounts for under two points of that gap; the rest sat in the invested-capital base.

### Is 33.4% ROIC unusual for a retailer with a 3.8% margin?

Yes. Most retailers earning a low single-digit operating margin post ROIC in the high single digits to low teens. Costco's membership-funded float and negative working capital structure let it earn a multiple of that on a wafer-thin margin.

### When did Costco last file its 10-Q, and what period does it cover?

Costco's most recent filing is a Form 10-Q filed June 3, 2026, covering the fiscal quarter ended May 10, 2026 (Q3 FY2026).

### Where can I verify Costco's deferred membership fees figure against the original filing?

The figure is drawn directly from Costco's Q3 FY2026 10-Q balance sheet, filed with the SEC on June 3, 2026. The full filing is publicly available on SEC EDGAR (linked in the citation block below).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=costco-stock-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Costco Wholesale Corporation's Q3 FY2026 10-Q (filed June 3, 2026, period ending May 10, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/909832/000090983226000051/cost-20260510.htm).

---

## Section 10b: Company Deep-Dive — NVIDIA (NVDA)
source: https://www.geminiq.com/blog/nvidia-10k-analysis-2026

### NVIDIA 10-K Analysis (2026): Inventory Grew Twice as Fast as Sales
NVIDIA's FY2026 10-K reports revenue up 65.5% to $215.94 Billion, but inventory grew 112.3% and gross margin fell from 74.99% to 71.07%. Receivables grew 66.8%, roughly in line with sales, while the cash conversion cycle extended to 96.9 days. The scale is unprecedented; the working capital is starting to stretch.

**[NVIDIA](/stocks/NVDA) ($NVDA) filed its FY2026 10-K on February 25, 2026, covering the fiscal year ended January 25, 2026. Revenue grew 65.5% to $215.94 Billion, one of the largest single-year dollar increases any company has ever reported. Beneath that number, two things moved faster than sales and one moved the wrong way: inventory grew 112.3%, receivables grew 66.8%, and gross margin fell from 74.99% to 71.07%. None of these is a warning on its own. Together they describe a business whose working capital is starting to stretch under the weight of its own growth.**

| Field | Value |
|---|---|
| Ticker | $NVDA |
| Filing | FY2026 10-K |
| Filed | February 25, 2026 |
| Period End | January 25, 2026 |
| Revenue Growth | **+65.5%** |
| Inventory Growth | **+112.3%** |
| Gross Profit Margin (TTM) | **71.07%** |
| Cash Conversion Cycle | **96.9 Days** |

## Inventory Grew Twice as Fast as Revenue

When a company's inventory outgrows its sales by a wide margin, it is either building for demand it expects or accumulating product it hasn't sold. The filing shows which lines moved.

**The Data:** [NVIDIA's](/stocks/NVDA) Revenues grew **65.5%**, from **$130.50 Billion** to **$215.94 Billion**. Over the same year, Inventory grew **112.3%**, from **$10.08 Billion** to **$21.40 Billion**. That is inventory expanding at roughly **1.7x** the rate of sales. GeminIQ's [Days Inventory Outstanding](/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding) extended to **91.97 days** from **85.9 days**, and [Inventory Turnover](/metrics/efficiency-and-turnover-ratios/inventory-turnover) slowed to **3.97x** from **4.25x**.

Receivables tell a calmer story. Accounts receivable grew **66.8%**, from **$23.06 Billion** to **$38.47 Billion**, almost exactly in line with revenue, though [Days Sales Outstanding](/metrics/efficiency-and-turnover-ratios/days-sales-outstanding) still crept up to **52.0 days** from **46.24 days**.

**The GeminIQ Edge:** Inventory growth outrunning revenue growth by nearly two to one is the kind of divergence a headline revenue figure completely hides. Reading Inventory and Revenues as their own lines from the [Financial Statements](/features#financial-statements), and pulling the turnover metrics alongside, is what turns a **65.5%** growth story into a question about what's sitting in the warehouse.

<center><sup>GeminIQ Financial Statements showing NVIDIA's Inventory Net growing 112.3% to $21.40 Billion against Revenues growth of 65.5% to $215.938 Billion, FY2025 to FY2026. Source: FY2026 10-K filed February 25, 2026.</sup></center>

## The Margin Came Down

The most profitable hardware business at scale in the market gave back nearly four points of gross margin in a single year.

**The Data:** [NVIDIA's](/stocks/NVDA) GeminIQ [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) fell to **71.07%** from **74.99%**, a decline of **3.9 percentage points**. In dollar terms Gross Profit still grew, to **$153.46 Billion** from **$97.86 Billion**, but Cost Of Sales grew faster than revenue: Cost Of Goods Sold rose **91.4%**, from **$32.64 Billion** to **$62.48 Billion**, against the **65.5%** revenue increase. GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) also eased, to **60.38%** from **62.42%**.

The **74.99%** gross margin in FY2025 was an extraordinary figure that reflected acute supply scarcity and pricing power. A move to **71.07%** is still exceptional for hardware, and the decline is worth understanding rather than alarming over: cost of goods grew faster than sales, which is consistent with a richer mix of lower-margin systems and rising input costs as volume scaled.

**The GeminIQ Edge:** A gross margin falling from **74.99%** to **71.07%** while gross profit dollars rose **56.8%** is a genuinely ambiguous signal, and the way to read it is to watch the cost line rather than the margin percentage. Cost Of Goods Sold growing **91.4%** against **65.5%** revenue growth is the specific fact underneath the margin move.

<center><sup>GeminIQ Financial Statements showing NVIDIA's Cost Of Goods Sold growing 91.4% to $62.475 Billion against 65.5% revenue growth, pulling Gross Profit Margin to 71.07% from 74.99%, FY2025 to FY2026. Source: FY2026 10-K filed February 25, 2026.</sup></center>

## The Cash Conversion Cycle Extended

Inventory building faster than sales and receivables creeping up have the same downstream effect: cash gets tied up in working capital for longer.

**The Data:** GeminIQ's [Cash Conversion Cycle](/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle) for [NVIDIA](/stocks/NVDA) extended to **96.9 days**, the combination of **91.97 days** of inventory and **52.0 days** of receivables, offset by payables. That means NVIDIA now waits roughly three months and change between paying for the components in a product and collecting the cash from selling it. The absolute cash generation remains enormous: Net Cash Provided By Operating Activities was **$102.7 Billion** and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) was **$96.68 Billion**, both up roughly **60%**.

Despite the working capital drag, the cash machine kept pace with earnings. Net Income was **$120.07 Billion**, up **64.7%**, and free cash flow grew **58.9%**, so the lengthening cycle slowed the conversion but did not break it.

**The GeminIQ Edge:** A cash conversion cycle near **97 days** at a company generating **$96.68 Billion** of free cash flow is not a liquidity concern. It is a leading indicator. The cycle extends before the cash flow shows strain, which is exactly why reading the working capital metrics matters when the headline cash figure still looks pristine.

<center><sup>GeminIQ Calculated Metrics showing NVIDIA's Cash Conversion Cycle at 96.9 days, built from 91.97 days inventory and 52.0 days receivables, against Free Cash Flow of $96.68 Billion. Source: FY2026 10-K filed February 25, 2026.</sup></center>

## What You Pay for the Growth

The valuation compressed even as the business grew, because earnings grew faster than the price.

**The Data:** [NVIDIA's](/stocks/NVDA) market capitalization reached **$4.65 Trillion** at fiscal year end, and the trailing [Price to Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) actually fell to **38.73** from **40.39** a year earlier, because Net Income growth of **64.7%** outpaced the share price. GeminIQ's [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) held at **2.08%**, essentially flat against **2.07%**.

Capital efficiency remained in a category of its own. GeminIQ's [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) was **91.74%**, down from an extraordinary **110.0%** the prior year but still among the highest of any large company on record. GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) is negative at **-$2.14 Billion**, a net cash position.

**The GeminIQ Edge:** A stock that grew into a lower multiple while compounding earnings at **64.7%** is doing something unusual, and it complicates any simple "expensive" or "cheap" verdict. The working capital signals matter precisely because the valuation and cash metrics give no warning at all.

<center><sup>GeminIQ Calculated Metrics showing NVIDIA's Price to Earnings Ratio at 38.73, down from 40.39, with Return on Invested Capital at 91.74% and a net cash position. Source: FY2026 10-K filed February 25, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **158** sale filings by [NVIDIA](/stocks/NVDA) insiders totaling **$2.79 Billion**, and **zero** purchases. The largest is **885,000** shares by a Director at **$210.07** on June 18, 2026, for **$185.91 Million**, followed by **1,000,000** shares at **$142.80** on June 9, 2025, for **$142.80 Million**.

[Institutional Ownership](/features#institutional-ownership) reached **63.33%** of shares outstanding as of the quarter ending December 31, 2025, easing to **61.45%** as of March 31, 2026. Both come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Heavy insider selling at a stock that has appreciated this much is expected, scheduled, and close to uninformative, which is why the dollar figure matters less than it looks. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) carries more signal here: the stock fell **11.68%** one month after this 10-K was filed, then recovered to gain **3.14%** at two months, **15.22%** at three and **8.01%** at five. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 158 NVIDIA insider sales totaling $2.79 Billion and zero purchases since January 1, 2025.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing NVIDIA institutional ownership at 63.33% of shares outstanding as of the quarter ending December 31, 2025, easing to 61.45% as of March 31, 2026. Both readings come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing NVIDIA's cumulative price path after this 10-K was filed: down 11.68% at one month, recovering to +3.14% at two months, +15.22% at three and +8.01% at five. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### Did NVIDIA's inventory grow faster than its sales in FY2026?

Yes, by a wide margin. Inventory grew **112.3%**, from **$10.08 Billion** to **$21.40 Billion**, while revenue grew **65.5%**. That is inventory expanding at roughly **1.7x** the rate of sales, extending Days Inventory Outstanding to **91.97 days** from **85.9 days**.

### Why did NVIDIA's gross margin fall?

Cost of goods sold grew faster than revenue. Cost Of Goods Sold rose **91.4%** against **65.5%** revenue growth, pulling Gross Profit Margin to **71.07%** from **74.99%**. The prior year's figure reflected acute supply scarcity that has partly normalized.

### What is NVIDIA's cash conversion cycle?

**96.9 days** as of the FY2026 10-K, combining **91.97 days** of inventory and **52.0 days** of receivables, offset by payables. It extended over the year as inventory and receivables grew, though free cash flow still rose more than **58%** to **$96.68 Billion**.

### Is NVIDIA still generating strong free cash flow?

Yes. Free Cash Flow was **$96.68 Billion** in FY2026, up **58.9%**, on operating cash flow of **$102.7 Billion**. The working capital buildup slowed cash conversion but did not stop it.

### How do I check whether a company's growth is straining its working capital?

Compare the growth rates of inventory and receivables against revenue growth for the same period. When inventory grows materially faster than sales, cash is being tied up in unsold or pre-positioned product, and the cash conversion cycle will lengthen before the cash flow statement shows any strain.

---

NVIDIA's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 25, 2026, covering the fiscal year ended January 25, 2026 (FY2026).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=nvidia-10k-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference NVIDIA Corporation's FY2026 10-K (filed February 25, 2026, period ending January 25, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001045810&type=10-K).

---

## Section 10c: Company Deep-Dive — Coca-Cola (KO)
source: https://www.geminiq.com/blog/coca-cola-10k-analysis-2026

### Coca-Cola 10-K Analysis (2026): The Dividend Cash Gap
Coca-Cola's FY2025 10-K reports record operating income of $13.76 Billion and a 28.7% operating margin, but free cash flow of $5.30 Billion did not cover $8.78 Billion in dividends paid — the second consecutive year of that gap. Here's what the cash flow statement shows that the earnings-based payout ratio hides.

**[Coca-Cola](/stocks/KO) Company ($KO) just filed its FY2025 10-K (filed February 20, 2026). By nearly every income statement measure, it was the strongest year the company has posted in over a decade: operating income of $13.76 Billion, an operating margin of 28.7%, and the highest return on invested capital in the seven-year window. The cash flow statement reports something the earnings headlines did not. Free cash flow came in at $5.30 Billion against $8.78 Billion in dividends paid — the second consecutive fiscal year the dividend exceeded the cash the business actually generated.**

| Field | Value |
|---|---|
| Ticker | $KO |
| Filing | FY2025 10-K |
| Filed | February 20, 2026 |
| Period End | December 31, 2025 |
| Operating Margin (TTM) | **28.71%** |
| Free Cash Flow (FY2025) | **$5.30 Billion** |
| Dividends Paid (FY2025) | **$8.78 Billion** |
| FCF Dividend Coverage | **0.60x** |

## Coca-Cola (KO) FY2025 10-K: The Best Income Statement in Over a Decade

Nothing on the face of Coca-Cola's income statement suggests a company under strain.

**The Data:** [Coca-Cola](/stocks/KO) reported Net Operating Revenues of **$47.94 Billion** in FY2025, up from **$47.06 Billion** the prior year. Operating Income climbed to **$13.76 Billion** from **$9.99 Billion**, an increase of **37.7%**. Net Income Attributable To Shareowners Of The Coca-Cola Company reached **$13.11 Billion** against **$10.63 Billion** in FY2024. GeminIQ's pre-calculated [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) puts the TTM figure at **28.71%**, up from **21.23%**, while [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) reached **17.77%** — the highest reading in the seven fiscal years on file — and Return on Equity hit **45.97%**.

Part of that jump is a base effect rather than operating improvement. Other Operating Charges, filed under Other Selling General And Administrative Expense, fell from **$4.16 Billion** in FY2024 to **$1.26 Billion** in FY2025. That single swing accounts for roughly three-quarters of the operating income increase. The underlying business improved. It did not improve by **37.7%**.

**The GeminIQ Edge:** A screener reading the income statement alone records FY2025 as a breakout year and stops there. Pulling the raw [Financial Statements](/features#financial-statements) alongside GeminIQ's [Calculated Metrics](/features#calculated-metrics) exposes the charge line driving most of the comparison — the kind of adjustment that never surfaces in a headline EPS beat.

<center><sup>GeminIQ Financial Statements showing Coca-Cola's FY2025 Income Statement, with Operating Income Loss ($13.762 Billion) up from $9.992 Billion, against Other Selling General And Administrative Expense falling from $4.163 Billion to $1.261 Billion. Source: FY2025 10-K filed February 20, 2026.</sup></center>

## Where the Earnings Stopped Becoming Cash

Record net income only matters if it arrives as cash. In FY2025, most of it did not.

**The Data:** Net Cash Provided By Operating Activities totaled **$7.41 Billion** against net income of **$13.11 Billion** — a conversion rate of **56.5%**. That figure has fallen every year for four years. [Coca-Cola](/stocks/KO) converted **128.8%** of net income into operating cash in FY2021, **115.5%** in FY2022, and **108.3%** in FY2023, before dropping to **64.0%** in FY2024 and **56.5%** in FY2025. A business that reliably produced more cash than accounting profit now produces materially less.

The line responsible sits directly on the cash flow statement. Net Change In Operating Assets And Liabilities, filed as Increase Decrease In Operating Capital, drained **$7.21 Billion** in FY2025 after draining **$6.23 Billion** in FY2024. Two consecutive years of outflows at that scale removed roughly **$13.4 Billion** of cash the income statement had already booked as profit.

**The GeminIQ Edge:** Most platforms display net income and operating cash flow on separate screens, which makes a widening gap between them nearly invisible. Read both statements as filed, in the same view, and a four-year conversion decline stops being a footnote and becomes the headline.

<center><sup>GeminIQ Financial Statements showing Coca-Cola's FY2025 Cash Flow Statement, with Net Cash Provided By Used In Operating Activities ($7.408 Billion) against Net Income Loss ($13.137 Billion), and Increase Decrease In Operating Capital at -$7.208 Billion. Source: FY2025 10-K filed February 20, 2026.</sup></center>

## The Dividend Gap Nobody Prices In

This is where the two statements collide, and where one of the market's most trusted dividend records meets an arithmetic problem.

**The Data:** GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) for FY2025 is **$5.30 Billion** — operating cash flow of **$7.41 Billion** less Purchases Of Property, Plant And Equipment of **$2.11 Billion**. Payments Of Dividends for the same year totaled **$8.78 Billion**. The dividend exceeded free cash flow by **$3.48 Billion**, for coverage of **0.60x**. FY2024 was worse at **0.57x**, a shortfall of **$3.62 Billion**. In each of the five fiscal years before that, coverage ranged between **1.23x** and **1.55x**.

The metric most dividend screeners display for [Coca-Cola](/stocks/KO) tells the opposite story. GeminIQ's [Payout Ratio](/metrics/returns-and-profitability/payout-ratio) reads **66.98%** on a TTM basis, comfortably inside the range investors treat as sustainable — because it measures dividends against accounting earnings, not against cash. The same divergence runs through the yields. [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) sits at **1.78%** while [Dividend Yield](/metrics/valuation-metrics/dividend-yield) sits at **2.96%**. Shareholders are collecting a yield larger than the one the business produced.

**The GeminIQ Edge:** An earnings-based payout ratio of **66.98%** and a cash-based coverage ratio of **0.60x** describe the same dividend, in the same company, in the same year. Only one of them is built from the cash flow statement.

<center><sup>GeminIQ Calculated Metrics showing Coca-Cola's Free Cash Flow ($5.296 Billion) against Payments Of Dividends ($8.779 Billion) for FY2025, a coverage ratio of 0.60x, versus 1.23x–1.55x across FY2020–FY2023. Source: FY2025 10-K filed February 20, 2026.</sup></center>

## What Funded the Difference

A dividend that outruns cash flow for two years has to be paid from somewhere else. The financing and investing sections name the sources.

**The Data:** Proceeds From Issuance Of Debt brought in **$4.98 Billion** during FY2025. Asset sales supplied more: Proceeds From Disposals Of Businesses, Equity Method Investments And Nonmarketable Securities added **$3.57 Billion**, Proceeds From Disposals Of Investments another **$4.67 Billion**, and Proceeds From Minority Shareholders a further **$1.34 Billion**. The buyback absorbed the rest of the pressure. Payments For Repurchase Of Common Stock fell to **$746 Million** from **$1.80 Billion**, a reduction of **58.4%**.

The balance sheet took this without visible stress, which is the part that keeps the story from being a distress story. [Coca-Cola's](/stocks/KO) total debt stands at **$45.49 Billion** and net debt at **$35.22 Billion**, yet GeminIQ's [Net Debt to EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) improved to **2.38x** from **2.99x**, because EBITDA rose faster than borrowings. The [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) strengthened to **8.32x** from **6.03x**, and the [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) sits at **10.45**, deep in the safe zone.

**The GeminIQ Edge:** [Coca-Cola](/stocks/KO) is not a company in financial difficulty, and the leverage metrics say so plainly. What the filing shows is narrower and more specific. The dividend is currently funded by borrowings and asset sales rather than by operations, and a **58.4%** cut to the buyback is the visible price of holding that line.

<center><sup>GeminIQ Financial Statements showing Coca-Cola's FY2025 financing and investing activities, with Proceeds From Issuance Of Debt ($4.980 Billion) and Payments For Repurchase Of Common Stock falling to $746 Million from $1.795 Billion. Source: FY2025 10-K filed February 20, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **36** sale filings by [Coca-Cola](/stocks/KO) insiders totaling **$228.94 Million**, against **2** purchases totaling **$998 Thousand** — a ratio of roughly **229 to 1** by dollar value. Both purchases came from a single Director in October 2025, at **$70.09** and **$69.87** per share. The largest sale on file is **436,296** shares by the Chairman at **$80.13** on June 5, 2026, for **$34.96 Million**, followed by **337,824** shares by the Chairman and CEO at **$77.10** on February 3, 2026, for **$26.05 Million**.

Institutional positioning moved the other way. [Institutional Ownership](/features#institutional-ownership) rose to **71.45%** of shares outstanding as of the quarter ending December 31, 2025, then eased to **70.24%** as of March 31, 2026. Both figures come from quarterly [13F filings](/blog/how-to-read-13f-filing), so they describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Insider selling at a large-cap dividend name is routine and heavily scheduled, which is exactly why the dollar ratio matters more than the raw count. What followed the filing is the more useful record: GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows the stock down **2.47%** one month after this 10-K was filed and down **1.10%** at three months, before turning to **+6.80%** at five months. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 36 Coca-Cola insider sales totaling $228.94 Million against 2 purchases totaling $998 Thousand since January 1, 2025.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing Coca-Cola institutional ownership at 71.45% of shares outstanding as of the quarter ending December 31, 2025, easing to 70.24% as of March 31, 2026. Both readings come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing Coca-Cola's cumulative price path after this 10-K was filed: down 2.47% at one month and down 1.10% at three months, turning to +6.80% at five. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### What does Coca-Cola's FY2025 10-K show?

Coca-Cola's FY2025 annual report shows Net Operating Revenues of **$47.94 Billion**, Operating Income of **$13.76 Billion**, and a **28.7%** operating margin — the strongest income statement the company has posted in over a decade. The cash flow statement tells a different story: free cash flow of **$5.30 Billion** did not cover **$8.78 Billion** in dividends paid.

### What is KO's free cash flow?

Coca-Cola's FY2025 free cash flow was **$5.30 Billion**, down sharply relative to its earnings. Free cash flow is operating cash flow less capital expenditures, both taken directly from the cash flow statement in the 10-K. That figure sits **$3.48 Billion** below the dividends the company paid in the same year.

### Where can I find the KO annual report?

Coca-Cola files its annual report as a Form 10-K with the SEC, available on EDGAR and filed February 20, 2026 for FY2025. Every figure in this analysis is drawn from that filing via its XBRL tags rather than a third-party data feed.

### Did Coca-Cola cover its dividend in FY2025?

Not from free cash flow. The FY2025 10-K shows free cash flow of **$5.30 Billion** against **$8.78 Billion** in Payments Of Dividends, a shortfall of **$3.48 Billion** and coverage of **0.60x**. FY2024 showed a similar gap at **0.57x**. The company covered the difference with debt issuance, asset disposals, and a **58.4%** reduction in [share repurchases](/blog/do-buybacks-reduce-share-count).

### Why does Coca-Cola's payout ratio look healthy?

Because the standard payout ratio measures dividends against accounting earnings rather than cash. GeminIQ's [Payout Ratio](/metrics/returns-and-profitability/payout-ratio) reads **66.98%** TTM, while cash-based coverage reads **0.60x**. The gap between those two numbers is the same gap between net income of **$13.11 Billion** and operating cash flow of **$7.41 Billion**.

### What caused Coca-Cola's cash conversion to fall?

Net Change In Operating Assets And Liabilities, filed as Increase Decrease In Operating Capital, drained **$7.21 Billion** in FY2025 and **$6.23 Billion** in FY2024. Operating cash flow converted **56.5%** of net income in FY2025, down from **108.3%** in FY2023.

### Is Coca-Cola's balance sheet under stress?

The leverage metrics say no. Net Debt to EBITDA improved to **2.38x** from **2.99x**, interest coverage strengthened to **8.32x**, and the Altman Z-Score sits at **10.45**. The FY2025 filing describes a funding-mix question rather than a solvency question.

### How can I check dividend coverage on my own holdings?

Compare GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) against Payments Of Dividends on the cash flow statement for each of the last five fiscal years, then set that ratio beside the reported payout ratio. Where the two disagree, the cash flow statement is the one built from money that actually moved.

---

Coca-Cola's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 20, 2026, covering the fiscal year ended December 31, 2025 (FY2025).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=coca-cola-10k-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference The Coca-Cola Company's FY2025 10-K (filed February 20, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000021344&type=10-K).

---

## Section 10d: Company Deep-Dive — GameStop (GME)
source: https://www.geminiq.com/blog/gamestop-10k-analysis-2026

### GameStop 10-K Analysis (2026): The Profit Isn't From Games
GameStop's FY2025 10-K reports net income of $418.4 Million, its best in a decade, but $271.5 Million of it is interest income on a $6.30 Billion cash pile. The retail operation did turn a $232.1 Million operating profit after an SG&A cut, while a $4.16 Billion convertible note and a 39.1% jump in diluted shares changed the balance sheet entirely.

**[GameStop](/stocks/GME) Corp. ($GME) filed its FY2025 10-K on March 24, 2026, covering the fiscal year ended January 31, 2026. Net income was $418.4 Million, the highest in a decade. The headline reads like a turnaround. The income statement tells a two-part story: the retail business did turn a genuine $232.1 Million operating profit, its first positive operating year since fiscal 2016, but $271.5 Million of the bottom line is interest income earned on a $6.30 Billion cash pile. Take the interest income away and the picture is smaller and more interesting than the net income figure suggests.**

| Field | Value |
|---|---|
| Ticker | $GME |
| Filing | FY2025 10-K |
| Filed | March 24, 2026 |
| Period End | January 31, 2026 |
| Net Income (FY2025) | **$418.4 Million** |
| Operating Income (FY2025) | **$232.1 Million** |
| Interest Income, Net | **$271.5 Million** |
| Cash And Marketable Securities | **$9.01 Billion** |

## Two Income Engines, Only One of Them Retail

The net income figure combines two very different sources of profit, and separating them is the whole analysis.

**The Data:** [GameStop's](/stocks/GME) Operating Income (Loss) was **$232.1 Million** in FY2025, a swing from **-$26.2 Million** the prior year and the first positive operating result since fiscal 2016. Below the operating line, Interest Income, Net contributed **$271.5 Million**, up from **$163.4 Million**. A new item, Loss On Digital Assets And Related Receivables, cost **$131.6 Million**. Income Before Income Taxes came to **$384.0 Million**, and an income tax benefit of **$34.4 Million** lifted Net Income to **$418.4 Million**.

The arithmetic worth holding onto: the retail operation produced **$232.1 Million** of operating profit, while the cash pile produced **$271.5 Million** of interest. More of GameStop's pretax income came from its treasury than from selling anything.

**The GeminIQ Edge:** A single net income figure collapses an operating business and an interest-bearing treasury into one number. Reading Operating Income and Interest Income, Net as separate lines from the [Financial Statements](/features#financial-statements) is what reveals that the larger contributor isn't the stores.

<center><sup>GeminIQ Financial Statements showing GameStop's Operating Income Loss ($232.1 Million) alongside Interest Income Expense Net ($271.5 Million) and Crypto Asset Realized And Unrealized Gain Loss Nonoperating (-$131.6 Million) for FY2025. Source: FY2025 10-K filed March 24, 2026.</sup></center>

## The Operating Turnaround Is Real, and It Came From Cost-Cutting

The operating profit deserves credit on its own terms, but the source of it matters for whether it holds.

**The Data:** [GameStop's](/stocks/GME) Net Sales fell to **$3.63 Billion** from **$3.82 Billion**, a decline of **5.0%** and the continuation of a long revenue slide from **$9.55 Billion** a decade ago. Gross Profit rose to **$1.20 Billion** from **$1.11 Billion**, lifting GeminIQ's [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) to **32.95%** from **29.14%**. The operating swing came from below the gross line: Selling, General, And Administrative Expenses fell to **$910.2 Million** from **$1,130.4 Million**, a reduction of **$220.2 Million** or **19.5%**.

The turnaround, in other words, is a margin-and-cost story rather than a growth story. Revenue is still falling. GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) reached **6.39%**, its best since fiscal 2015, achieved by cutting operating expenses faster than sales declined.

**The GeminIQ Edge:** An operating profit built on a **19.5%** SG&A cut against falling revenue is real but structurally limited. Cost reduction has a floor, and revenue is still contracting. The trend that matters next is whether the top line can stabilize now that the easy cost cuts have been taken.

<center><sup>GeminIQ Financial Statements showing GameStop's Selling General And Administrative Expense falling to $910.2 Million from $1,130.4 Million while Gross Profit rose to $1,196.1 Million, FY2024 to FY2025. Source: FY2025 10-K filed March 24, 2026.</sup></center>

## The Balance Sheet Nobody From 2021 Would Recognize

The cash pile that generated most of the profit did not come from operations, and the financing behind it reshaped the balance sheet.

**The Data:** [GameStop](/stocks/GME) ended FY2025 with **$6.30 Billion** in Cash And Cash Equivalents and a further **$2.71 Billion** in Marketable Securities, for roughly **$9.01 Billion** in cash and equivalents against a total asset base of **$10.39 Billion**. Against that, Long-Term Debt, filed as Long Term Notes Payable, stood at **$4.16 Billion**, up from **$6.6 Million** a year earlier. That debt is the convertible notes the company issued to build the cash position, and it is why GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) reads **-$2.16 Billion**, a net cash position, even with **$4.16 Billion** of gross debt on the books.

The share count moved alongside the debt. Weighted Average Number Of Diluted Shares Outstanding rose to **549.1 Million** from **394.7 Million**, an increase of **39.1%**, reflecting both equity issuance and the dilutive effect of the convertible notes. Basic shares rose to **447.6 Million** from **394.1 Million**. The [Current Ratio](/metrics/liquidity-ratios/current-ratio) sits at **15.3**, a number that reflects a company that is mostly a pile of cash with a retailer attached.

**The GeminIQ Edge:** A net cash position of **-$2.16 Billion** sitting on top of **$4.16 Billion** of gross convertible debt is the kind of structure a summary balance sheet flattens into "net cash, no concern." Reading gross debt and the diluted share count as their own lines shows the cost of assembling that cash: **$4.16 Billion** borrowed and a diluted share base **39.1%** larger than a year ago.

<center><sup>GeminIQ Financial Statements showing GameStop's Long Term Notes Payable rising to $4,164.3 Million from $6.6 Million alongside Cash And Cash Equivalents of $6,304.7 Million and diluted shares of 549.1 Million. Source: FY2025 10-K filed March 24, 2026.</sup></center>

## What the Interest Income Depends On

Because interest income carried more of the bottom line than the retail business did, it is worth asking how durable it is.

**The Data:** The **$271.5 Million** in Interest Income, Net is a function of two things GameStop does not fully control: the size of the cash pile and prevailing short-term rates. On roughly **$9.01 Billion** of cash and marketable securities, that income implies a blended yield in the low-single-digit percent range. GeminIQ's [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) reads **12.94%**, a swing from **-6.54%** a year earlier, though that figure is heavily influenced by the treasury income and the way [invested capital](/metrics/calculated-values/invested-capital) treats the cash and debt.

Against the cash, the market assigns a premium. Market capitalization stands at **$10.69 Billion**, of which the **$9.01 Billion** in cash and securities is roughly **84%**. The [Price to Book](/metrics/valuation-metrics/price-to-book-ratio) ratio is **1.96** against book value of **$5.44 Billion**.

**The GeminIQ Edge:** Interest income is real income, and at current rates it is substantial. It is also the least controllable line on the statement, moving with rates GameStop does not set and a cash balance funded by convertible debt. A valuation that capitalizes **$271.5 Million** of interest income at an operating-business multiple is making an assumption the filing cannot support on its own.

<center><sup>GeminIQ Calculated Metrics showing GameStop's Interest Income Expense Net of $271.5 Million against a $9.01 Billion cash and marketable securities balance, with market capitalization of $10.69 Billion. Source: FY2025 10-K filed March 24, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Unlike most large-cap records, GameStop's insiders have been buying. Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **9** purchase filings totaling **$33.26 Million** against **17** sale filings totaling **$1.76 Million**. The purchases are dominated by the President, CEO and Chairman, who filed three separate buys of **500,000** shares each: at **$21.55** on April 3, 2025, **$21.12** on January 20, 2026, and **$21.60** on January 21, 2026, for roughly **$32.1 Million** combined. The sales are small director dispositions.

[Institutional Ownership](/features#institutional-ownership) has declined steadily, from **38.71%** as of the quarter ending June 30, 2025 to **33.45%** as of March 31, 2026. Both figures come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** A CEO buying **1.5 Million** shares of his own company with his own money is a materially different signal than a scheduled director sale, and it is the rare case where the insider record leans clearly one direction. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows the stock up **7.63%** one month after this 10-K was filed, then down **5.35%** at two months and **4.56%** at three. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 9 GameStop insider purchases totaling $33.26 Million against 17 sales totaling $1.76 Million since January 1, 2025, including three 500,000-share CEO buys.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing GameStop institutional ownership declining from 38.71% as of the quarter ending June 30, 2025 to 33.45% as of March 31, 2026. Both figures come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing GameStop's cumulative price path after this 10-K was filed: up 7.63% at one month, down 5.35% at two months and down 4.56% at three. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### Was GameStop's FY2025 profit from its retail business?

Partly. Operating income was **$232.1 Million**, a genuine retail operating profit and the first since fiscal 2016. But Interest Income, Net contributed **$271.5 Million** on top of that, so more of the pretax income came from the cash pile than from operations. Net income was **$418.4 Million**.

### How did GameStop turn an operating profit if sales fell?

By cutting costs faster than revenue declined. Net Sales fell **5.0%** to **$3.63 Billion**, but Selling, General, And Administrative Expenses fell **19.5%**, from **$1,130.4 Million** to **$910.2 Million**. Gross margin also expanded, to **32.95%** from **29.14%**.

### How much debt does GameStop have now?

**$4.16 Billion** in Long-Term Notes Payable as of January 31, 2026, up from **$6.6 Million** a year earlier. These are convertible notes issued to build the cash position. Because cash and securities total roughly **$9.01 Billion**, Net Debt is still negative at **-$2.16 Billion**.

### How much has GameStop's share count grown?

Weighted average diluted shares rose to **549.1 Million** from **394.7 Million**, an increase of **39.1%**, driven by equity issuance and the dilutive effect of the convertible notes. Basic shares rose to **447.6 Million** from **394.1 Million**.

### How do I separate operating profit from interest income on a filing?

Read the income statement below the operating line. Operating Income (Loss) is the business result; Interest Income, Net and other non-operating lines are separate. When a company holds a large cash balance, the interest line can rival or exceed the operating line, and only reading them separately tells you which engine is actually driving the bottom line.

---

GameStop's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed March 24, 2026, covering the fiscal year ended January 31, 2026 (FY2025).

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference GameStop Corp.'s FY2025 10-K (filed March 24, 2026, period ending January 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001326380&type=10-K).

---

## Section 10e: Company Deep-Dive — Apple (AAPL)
source: https://www.geminiq.com/blog/apple-stock-analysis-2026

### Apple Stock Analysis (2026): Is It Still a Value Play or a Yield Trap?
Apple's retained earnings turned positive for the first time in years — a reversal from the accumulated deficit that made headlines. Here's what changed in the Q2 FY2026 10-Q, and what it means for the capital-efficiency thesis.

**[Apple](/stocks/AAPL) ($AAPL) just dropped its Q2 FY2026 10-Q (filed May 1, 2026). Most of the coverage is still arguing about iPhone units in China and whether a 30x multiple is too rich. The filing tells a different story: for the first time in years, Apple's retained earnings turned positive and its buyback pace visibly throttled back. The capital machine didn't slow down. It recalibrated — and almost nobody read the balance sheet closely enough to notice.**

| Field | Value |
|---|---|
| Ticker | $AAPL |
| Filing | Q2 FY2026 10-Q |
| Filed | May 1, 2026 |
| Period End | March 28, 2026 |
| Retained Earnings (Accumulated Deficit) | **$12.36 Billion** |
| ROIC (TTM) | **81.7%** |

## The Retained Earnings Reversal

The accumulated deficit is gone. For the past several years, [Apple's](/stocks/AAPL) balance sheet carried a negative retained earnings figure — one most retail platforms flag as a red flag, but one that actually reflected a company returning more cash to shareholders than it technically "retained." As of this quarter, that number is positive again.

**The Data:** As of the Q1 FY2026 10-Q (period ending December 27, 2025), GeminIQ's Financial Statements showed Retained Earnings (Accumulated Deficit) at **-$2.18 Billion**. As of this quarter's 10-Q, that same line item reads **$12.36 Billion** — positive, for the first time since the deficit began widening. That is a swing of roughly **$14.5 Billion** in a single fiscal quarter.

**The GeminIQ Edge:** A screener that only flags "negative retained earnings" as a warning sign would have missed both the original bullish read on the deficit and this reversal entirely — it just sees a number cross zero. GeminIQ's [Financial Statements](/features#financial-statements) pulls the actual accumulated deficit or surplus line straight from the filing — not inferred, not smoothed, tagged exactly as reported.

<center><sup>GeminIQ Financial Statements showing Apple's Retained Earnings (Accumulated Deficit) balance sheet line item across the trailing quarters, crossing from -$2.18 Billion (Q1 FY2026) to $12.36 Billion (Q2 FY2026).</sup></center>

## A Buyback Machine That Just Downshifted

The obvious question is whether the reversal means [Apple](/stocks/AAPL) slowed its capital return program. The share count says yes — just not by as much as the headline number implies.

**The Data:** Basic shares outstanding fell by **200.3 million** in the December quarter (Q1 FY2026) as Apple repurchased **$24.7 Billion** of stock in that period alone. In the March quarter (Q2 FY2026), the reduction was **74.9 million shares** — a real deceleration in buyback-driven share retirement. At the same time, quarterly net income grew from **$24.78 Billion** (Q2 FY2025) to **$29.58 Billion** (Q2 FY2026), a **19.4%** year-over-year increase.

**The GeminIQ Edge:** This is the mechanism behind the retained earnings flip: net income accelerated while the pace of capital return eased, and the gap between the two showed up directly on the balance sheet. GeminIQ's [Financial Statements](/features#financial-statements) surfaces the raw quarterly share count and repurchase cash flow as filed, so the deceleration shows up in the actual quarterly numbers instead of disappearing into a trailing-twelve-month average.

<center><sup>GeminIQ Financial Statements showing Apple's basic shares outstanding declining by 200.3 million in Q1 FY2026 versus 74.9 million in Q2 FY2026, against quarterly net income of $29.58 Billion, up 19.4% year-over-year.</sup></center>

## Verifying the Moat: ROIC Still Elite, But Cooling

[Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) is the number that actually tells you whether the capital machine is still working, independent of what's happening with buybacks in any given quarter.

**The Data:** GeminIQ's pre-calculated [ROIC](/blog/roic-return-on-invested-capital-explained) (TTM) for [Apple](/stocks/AAPL) sits at **81.7%** as of this filing, down from **83.1%** last quarter. It is still an extreme figure for a company of this size — Apple is turning roughly $0.82 of after-tax operating profit for every dollar of [invested capital](/metrics/calculated-values/invested-capital) — but the direction matters. This is the first time the trailing figure has ticked down after a run from **65.6%** in the March 2025 quarter to a peak of **83.1%** in December 2025. [Gross margin](/metrics/margin-metrics/gross-profit-margin) (TTM) tells a different part of the story: it has expanded from **46.6%** a year ago to **47.9%** now, a steady mix-shift tailwind that has nothing to do with iPhone unit volumes.

**The GeminIQ Edge:** A single ROIC snapshot tells you the machine is elite. The trend, pulled quarter by quarter from GeminIQ's [Calculated Metrics](/features#calculated-metrics) rather than a static ratio on a screener, tells you whether it's accelerating or normalizing — and right now it's normalizing off a genuine peak, not breaking down.

<center><sup>GeminIQ Calculated Metrics showing Apple's ROIC TTM across the trailing six quarters, from 65.64% (Q2 FY2025) to a peak of 83.11% (Q1 FY2026) and 81.69% (Q2 FY2026).</sup></center>

## The Balance Sheet Behind the Capital Machine

None of the above matters if the balance sheet funding it is deteriorating. It isn't.

**The Data:** [Apple](/stocks/AAPL) carries **$84.7 Billion** in total debt against **$45.6 Billion** in cash, for a Net Debt of **$39.1 Billion** — down from **$45.2 Billion** last quarter. GeminIQ's [Altman Z-Score](/blog/altman-z-score-financial-distress) for the period reads **11.04**, up from **10.60** in the prior quarter, well into the "safe zone" territory the score is designed to flag.

**The GeminIQ Edge:** The total debt figure traces directly to two filed line items — **Commercial Paper** of **$1.997 Billion** and **Term Debt** (current and noncurrent combined) of **$82.7 Billion** — rather than a single aggregated "debt" figure that obscures which instruments make up the total. GeminIQ's [Financial Statements](/features#financial-statements) keeps them separate, exactly as filed.

<center><sup>GeminIQ Financial Statements showing Apple's Commercial Paper ($1.997 Billion), Term Debt Current ($8.31 Billion), and Term Debt Noncurrent ($74.4 Billion), against Net Debt of $39.1 Billion and an Altman Z-Score of 11.04.</sup></center>

## Is $AAPL Still Priced Like a Yield Trap?

A healthy balance sheet doesn't answer the question this post opened with. Forget the debate — here's the actual multiple.

**The Data:** [Apple's](/stocks/AAPL) dividend yield (TTM) is **0.42%** — nowhere near a figure that would attract yield-focused buyers in the first place, which makes the "yield trap" framing largely beside the point. On the value side, P/E (TTM) sits at **30.4x**, down from **34.0x** last quarter and well below the **39.0x** reading from December 2024, even as the stock's market cap held near **$3.72 Trillion**. The multiple has been compressing as earnings caught up, not the other way around.

**The GeminIQ Edge:** [Institutional Ownership](/features#institutional-ownership) data shows institutions holding **59.2%** of shares outstanding as of the most recent 13F reporting period, down modestly from **61.1%** the quarter before — a normal fluctuation, not a distribution pattern. Combined with [Insider Transactions](/features#insider-transactions) data showing zero open-market purchases in the recent filing window — consistent with Apple's pattern of essentially no executive open-market buying in over a decade of filings — there's no smart-money signal here in either direction. It isn't a yield play. It isn't obviously cheap, either. It's a capital-efficiency compounder that got quietly less expensive while everyone argued about iPhone units.

<center><sup>GeminIQ Calculated Metrics showing Apple's P/E (TTM) compressing from 39.0x (Q1 FY2025) to 30.4x (Q2 FY2026) against a dividend yield (TTM) of 0.42% and market capitalization of $3.72 Trillion.</sup></center>

## Frequently Asked Questions

### What does GeminIQ's data show about Apple's retained earnings turning positive?

GeminIQ's Financial Statements show Apple's Retained Earnings (Accumulated Deficit) line item moving from -$2.18 Billion as of the Q1 FY2026 10-Q to $12.36 Billion as of the Q2 FY2026 10-Q, a swing of roughly $14.5 Billion in a single quarter. The shift coincides with a slowdown in buyback-driven share reduction relative to continued net income growth.

### Is Apple's 81.7% ROIC unusual for a company of its size?

Yes. GeminIQ's pre-calculated Return on Invested Capital for Apple has ranged from roughly 65% to 83% over the trailing five quarters, an extreme figure for a company of Apple's market capitalization. Most large-cap companies post ROIC in the 10-20% range; Apple's capital-light model and buyback-compressed equity base produce a structurally higher number.

### When did Apple last file its 10-Q, and what period does it cover?

Apple's most recent filing is a Form 10-Q filed May 1, 2026, covering the fiscal quarter ended March 28, 2026 (Q2 FY2026).

### Where can I verify Apple's retained earnings figure against the original SEC filing?

The figure is drawn directly from Apple's Q2 FY2026 10-Q, filed with the SEC on May 1, 2026. The full filing is publicly available on SEC EDGAR (linked in the citation block below).

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s Q2 FY2026 10-Q (filed May 1, 2026, period ending March 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/320193/000032019326000013/aapl-20260328.htm).

---

## Section 10f: Company Deep-Dive — Amazon (AMZN)
source: https://www.geminiq.com/blog/amazon-10k-analysis-2026

### Amazon 10-K Analysis (2026): ROIC Fell as Margins Rose
Amazon's FY2025 10-K reports record operating income of $79.98 Billion and an 11.16% operating margin, but Return on Invested Capital fell from 25.42% to 19.19% as invested capital grew 49% to $400.9 Billion. Roughly 60% of the pretax income increase came from non-operating items rather than operations.

**[Amazon](/stocks/AMZN) ($AMZN) filed its FY2025 10-K on February 6, 2026, and the headline numbers are the best in company history. Revenue of $716.92 Billion. Operating income of $79.98 Billion. Net income of $77.67 Billion. Every one a record. Underneath them, the number that measures how much profit Amazon earns per dollar of capital went the other way: Return on Invested Capital fell from 25.42% to 19.19% in a single year. Amazon is more profitable per dollar of sales than it has ever been and less profitable per dollar of capital than it was two years ago.**

| Field                            | Value              |
| -------------------------------- | ------------------ |
| Ticker                           | $AMZN              |
| Filing                           | FY2025 10-K        |
| Filed                            | February 6, 2026   |
| Period End                       | December 31, 2025  |
| Operating Margin (TTM)           | **11.16%**         |
| Return on Invested Capital (TTM) | **19.19%**         |
| Invested Capital                 | **$400.9 Billion** |

## The Record That Isn't What It Looks Like

Two measures of profitability moved in opposite directions in FY2025, and only one of them made the headlines.

**The Data:** [Amazon's](/stocks/AMZN) Operating Income reached **$79.98 Billion** on Total Revenues of **$716.92 Billion**, lifting GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) to **11.16%** from **10.75%** a year earlier. That is the highest operating margin in the company's filed history, and roughly double the **5.30%** it posted in FY2021. Over the same year, [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) fell from **25.42%** to **19.19%**, a drop of more than six percentage points.

The arithmetic behind the divergence is not complicated. [Net Operating Profit After Tax](/metrics/returns-and-profitability/net-operating-profit-after-tax) rose from **$59.3 Billion** to **$64.3 Billion**, an increase of about **8.4%**. Average invested capital rose from **$233.4 Billion** to **$335.0 Billion**, an increase of **43.5%**. Profit grew. The capital base grew five times faster.

**The GeminIQ Edge:** Margin and [ROIC](/blog/roic-return-on-invested-capital-explained) answer different questions, and a screener showing only the first will report FY2025 as an unambiguous record. Pulling both from [Calculated Metrics](/features#calculated-metrics) against the same filing puts the two trends side by side, where the divergence is impossible to miss.

<center><sup>GeminIQ Calculated Metrics showing Amazon's Operating Profit Margin rising to 11.16% from 10.75% while Return on Invested Capital fell to 19.19% from 25.42%, FY2024 to FY2025. Source: FY2025 10-K filed February 6, 2026.</sup></center>

## Where the Capital Went

A **43.5%** increase in the capital base in twelve months is not a rounding difference. The balance sheet and the cash flow statement both show where it landed.

**The Data:** GeminIQ's [Invested Capital](/metrics/calculated-values/invested-capital) for [Amazon](/stocks/AMZN) stood at **$400.9 Billion** at the end of FY2025, up from **$269.0 Billion** a year earlier, a **49.0%** increase. Total Assets grew from **$624.9 Billion** to **$818.0 Billion**, a gain of **30.9%**, against revenue growth of **12.4%**. Assets expanded at roughly two and a half times the rate of sales.

The cash flow statement names the spending. Purchases Of Property And Equipment, filed as Payments To Acquire Productive Assets, totaled **$131.82 Billion** in FY2025 against **$83.00 Billion** the prior year. Depreciation And Amortization for the same year was **$65.76 Billion**. Amazon spent **2.00x** its depreciation charge on new assets, the widest ratio in the filed window and up from **1.08x** as recently as FY2023. Operating Cash Flow of **$139.51 Billion** was itself a record, but after that capital spending, [Free Cash Flow](/metrics/calculated-values/free-cash-flow) came to **$7.70 Billion**.

Amazon also went back to the bond market. Proceeds From Issuance Of Long Term Debt were **$15.67 Billion** in FY2025 after **zero** the prior year, though with [Net Debt](/metrics/calculated-values/net-debt) still negative at **-$24.46 Billion**, the company remains in a net cash position.

**The GeminIQ Edge:** Spending twice your depreciation charge is a statement about the future, not a problem in the present. What it does mean is that the asset base carrying today's record margin is far younger than the depreciation running through today's income statement. The gap between **$131.82 Billion** of capital spending and **$65.76 Billion** of depreciation is the part of the story that shows up in later filings, not this one.

<center><sup>GeminIQ Financial Statements showing Amazon's Payments To Acquire Productive Assets ($131.819 Billion) against Depreciation Depletion And Amortization ($65.756 Billion) for FY2025, with Total Assets at $818.0 Billion. Source: FY2025 10-K filed February 6, 2026.</sup></center>

## Sixty Percent of the Earnings Jump Came From Outside Operations

The net income record deserves its own look, because most of the increase did not come from selling anything.

**The Data:** [Amazon's](/stocks/AMZN) Income Before Income Taxes rose from **$68.61 Billion** to **$97.31 Billion**, an increase of **$28.70 Billion**. Operating Income accounted for **$11.38 Billion** of that. Total Non-Operating Income accounted for **$17.32 Billion**, swinging from essentially nothing (**$0.02 Billion** in FY2024) to **$17.34 Billion** in FY2025. That single swing represents roughly **60%** of the entire pretax increase. The line driving it is Other Income (Expense), Net, filed as Other Nonoperating Income Expense, which moved from **-$2.25 Billion** to **$15.23 Billion**.

Net Income landed at **$77.67 Billion** after a tax provision of **$19.09 Billion**, up from **$9.27 Billion**. Share Based Compensation was **$19.47 Billion**, down from **$22.01 Billion**, though basic shares outstanding still rose from **10.473 Billion** to **10.656 Billion**.

**The GeminIQ Edge:** Non-operating income is real income and it belongs on the income statement. It is also the least repeatable line on it. Reading Operating Income and Total Non-Operating Income as separate series rather than collapsing both into a single net income figure is what separates an operating record from an accounting one.

<center><sup>GeminIQ Financial Statements showing Amazon's Nonoperating Income Expense swinging from $0.021 Billion to $17.336 Billion, against Operating Income Loss rising $11.382 Billion, FY2024 to FY2025. Source: FY2025 10-K filed February 6, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **87** sale filings by [Amazon](/stocks/AMZN) insiders totaling **$5.82 Billion**, and **zero** purchases. The four largest are all by the Executive Chair, including **4,273,237** shares at **$227.83** on July 21, 2025, for **$973.57 Million**, and **4,273,237** shares at **$224.98** on July 11, 2025, for **$961.39 Million**.

[Institutional Ownership](/features#institutional-ownership) reached **62.10%** of shares outstanding as of the quarter ending December 31, 2025, then eased to **59.79%** as of March 31, 2026. Both readings come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Executive Chair selling at Amazon runs on long-scheduled plans and reads as noise on its own. The more informative record is what followed the filing. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows the stock roughly flat one month after this 10-K was filed, down **5.22%** at two months, then up **25.52%** at three months and **16.20%** at five. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 87 Amazon insider sales totaling $5.82 Billion and zero purchases since January 1, 2025, led by four Executive Chair sales including 4,273,237 shares at $227.83 on July 21, 2025.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing Amazon institutional ownership at 62.10% of shares outstanding as of the quarter ending December 31, 2025, easing to 59.79% as of March 31, 2026. Both readings come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing Amazon's cumulative price path after this 10-K was filed: roughly flat at one month, down 5.22% at two months, up 25.52% at three months and 16.20% at five. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### Why did Amazon's ROIC fall in FY2025?

Because invested capital grew far faster than profit. NOPAT rose about **8.4%**, from **$59.3 Billion** to **$64.3 Billion**, while average invested capital rose **43.5%**, from **$233.4 Billion** to **$335.0 Billion**. Return on Invested Capital fell from **25.42%** to **19.19%** as a result, even though operating margin hit a record **11.16%**.

### How much did Amazon spend on capital expenditure in FY2025?

Payments To Acquire Productive Assets totaled **$131.82 Billion**, up from **$83.00 Billion** in FY2024. That is **2.00x** the year's Depreciation And Amortization charge of **$65.76 Billion**, the widest ratio in the filed window.

### Was Amazon's record FY2025 net income driven by operations?

Only partly. Pretax income rose **$28.70 Billion**, of which Operating Income contributed **$11.38 Billion** and Total Non-Operating Income contributed **$17.32 Billion**, roughly **60%** of the increase.

### Is Amazon still free cash flow positive?

Yes, at the annual level. FY2025 Free Cash Flow was **$7.70 Billion**, operating cash flow of **$139.51 Billion** less capital expenditure of **$131.82 Billion**. That is down from **$32.88 Billion** in FY2024.

### How do I track capital efficiency on my own holdings?

Set Return on Invested Capital beside operating margin across five or more years for the same company. When margin rises while ROIC falls, the capital base is growing faster than the profit it produces, and the reason will be sitting in capital expenditure or acquisitions on the cash flow statement.

---

Amazon's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 6, 2026, covering the fiscal year ended December 31, 2025 (FY2025).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=amazon-10k-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Amazon.com, Inc.'s FY2025 10-K (filed February 6, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001018724&type=10-K&dateb=&owner=include&count=40).

---

## Section 10g: Company Deep-Dive — Alphabet (GOOGL)
source: https://www.geminiq.com/blog/alphabet-annual-report-analysis-2026

### Alphabet Annual Report (2026): Free Cash Flow Went Flat
Alphabet's FY2025 10-K reports operating cash flow of $164.71 Billion, up 31.5%, against free cash flow of $73.27 Billion, up just 0.7%. Capital expenditure absorbed 98.7% of the incremental operating cash, and the buyback was cut 26.5% in a year when net income rose 32%.

**[Alphabet](/stocks/GOOGL) ($GOOGL) filed its FY2025 10-K on February 5, 2026. Revenue grew 15.1% to $402.84 Billion. Operating cash flow grew 31.5% to $164.71 Billion, an increase of $39.41 Billion in a single year. Free cash flow grew 0.7%. Not 7%. Zero point seven, from $72.76 Billion to $73.27 Billion. Capital expenditure rose $38.91 Billion over the same twelve months, which means 98.7% of every incremental dollar of operating cash Alphabet generated in FY2025 went straight back out the door as capital spending.**

| Field | Value |
|---|---|
| Ticker | $GOOGL |
| Filing | FY2025 10-K |
| Filed | February 5, 2026 |
| Period End | December 31, 2025 |
| Operating Cash Flow (FY2025) | **$164.71 Billion** |
| Capital Expenditure (FY2025) | **$91.45 Billion** |
| Free Cash Flow (FY2025) | **$73.27 Billion** |
| Free Cash Flow Growth | **+0.7%** |

## The Cash Flow That Didn't Move

Three growth rates from the same filing, covering the same twelve months, tell three different stories about the same company.

**The Data:** [Alphabet's](/stocks/GOOGL) Revenues reached **$402.84 Billion**, up **15.1%** from **$350.02 Billion**. Net Cash Provided By Operating Activities climbed to **$164.71 Billion** from **$125.30 Billion**, a gain of **$39.41 Billion** and a growth rate of **31.5%**. Purchases Of Property And Equipment went to **$91.45 Billion** from **$52.54 Billion**, a gain of **$38.91 Billion** and a growth rate of **74.1%**. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) finished at **$73.27 Billion** against **$72.76 Billion** the prior year, an increase of **$504 Million** on a base of roughly **$73 Billion**.

Divide the capital spending increase by the operating cash increase and the year resolves to a single number: **98.7%**. Alphabet generated **$39.41 Billion** more cash from operations than it did in FY2024 and kept about **$500 Million** of it.

**The GeminIQ Edge:** Operating cash flow and free cash flow sit on the same statement, one derived from the other, and a platform showing you the first as a headline growth metric is telling you something true and incomplete. Reading both series from [Financial Statements](/features#financial-statements) across the same years is what turns a **31.5%** cash flow story into a **0.7%** one.

<center><sup>GeminIQ Financial Statements showing Alphabet's Net Cash Provided By Used In Operating Activities ($164.713 Billion) against Payments To Acquire Property Plant And Equipment ($91.447 Billion) for FY2025, with the prior-year figures of $125.299 Billion and $52.535 Billion. Source: FY2025 10-K filed February 5, 2026.</sup></center>

## The Spending Is Larger Than the Cash Number Shows

The **$91.45 Billion** capital expenditure figure understates what Alphabet actually committed during the year, and the filing says so on its own cash flow statement.

**The Data:** A separate line, Purchases Of Property And Equipment Included In Accrued Liabilities And Accounts Payable, filed as Capital Expenditures Incurred But Not Yet Paid, stood at **$15.09 Billion** at the end of FY2025, up from **$10.33 Billion**. That is capital expenditure Alphabet has committed to and recognized but had not yet paid in cash as of the balance sheet date.

The scale relative to the existing asset base is the other measure worth having. Depreciation Of Property And Equipment for FY2025 was **$21.14 Billion**. [Alphabet](/stocks/GOOGL) spent **4.33x** its depreciation charge on new property and equipment, up from **3.43x** in FY2024. GeminIQ's [Invested Capital](/metrics/calculated-values/invested-capital) rose to **$439.2 Billion** from **$319.5 Billion**, a **37.5%** increase, and Total Assets grew **32.2%** to **$595.3 Billion** against that **15.1%** revenue growth. [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) fell to **28.31%** from **31.47%**.

**The GeminIQ Edge:** Accrued capital expenditure is one of the least-read lines on a cash flow statement and it exists precisely because the cash figure and the commitment figure diverge. A company spending **4.33x** depreciation is replacing its asset base several times faster than the accounting is recognizing the cost of it.

<center><sup>GeminIQ Financial Statements showing Alphabet's Capital Expenditures Incurred But Not Yet Paid ($15.090 Billion) alongside Payments To Acquire Property Plant And Equipment ($91.447 Billion) and Depreciation ($21.136 Billion) for FY2025. Source: FY2025 10-K filed February 5, 2026.</sup></center>

## What Got Cut to Pay for It

Flat free cash flow against rising shareholder-return commitments forces a choice, and the financing section shows which one Alphabet made.

**The Data:** Repurchases Of Stock, filed as Payments For Repurchase Of Common Stock, fell to **$45.71 Billion** in FY2025 from **$62.22 Billion**, a reduction of **26.5%**. Alphabet cut its buyback by **$16.51 Billion** in a fiscal year when Net Income rose **32.0%**, from **$100.12 Billion** to **$132.17 Billion**. Dividend Payments moved the other way, rising to **$10.05 Billion** from **$7.36 Billion**.

The balance sheet absorbed the remainder. Proceeds From Issuance Of Debt, Net Of Costs came to **$64.56 Billion** against **$13.59 Billion** the prior year. GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) turned positive at **$15.84 Billion**, the first net debt position in the eleven fiscal years on file. Every prior year in the window shows a net cash position.

**The GeminIQ Edge:** Buyback reductions rarely get their own headline, because a company that keeps buying back stock at all reads as a company returning capital. The comparison that matters is directional: net income up **32.0%**, repurchases down **26.5%**, in the same twelve months.

<center><sup>GeminIQ Financial Statements showing Alphabet's Payments For Repurchase Of Common Stock falling to $45.709 Billion from $62.222 Billion while Payments Of Dividends rose to $10.049 Billion, FY2024 to FY2025. Source: FY2025 10-K filed February 5, 2026.</sup></center>

## What the Market Paid for Flat Cash

Price and free cash flow moved in opposite directions by a wide margin during FY2025.

**The Data:** [Alphabet's](/stocks/GOOGL) market capitalization rose from **$2.320 Trillion** to **$3.787 Trillion** across the fiscal year, an increase of **63.3%**, while free cash flow rose **0.7%**. GeminIQ's [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) fell to **1.93%** from **3.14%** as a direct consequence. The trailing price-to-earnings ratio finished at **28.66**.

Operating margin held steady through all of this. GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) came in at **32.03%** against **32.11%** the prior year, essentially unchanged, so nothing in the income statement signals the cash flow story at all.

**The GeminIQ Edge:** A stable operating margin and a collapsing free cash flow yield in the same year is the clearest possible demonstration that the income statement and the cash flow statement answer different questions. One of them showed nothing unusual in FY2025.

<center><sup>GeminIQ Calculated Metrics showing Alphabet's Free Cash Flow Yield falling to 1.93% from 3.14% while Operating Profit Margin held at 32.03% against 32.11%, FY2024 to FY2025. Source: FY2025 10-K filed February 5, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **92** sale filings by [Alphabet](/stocks/GOOGL) insiders totaling **$256.13 Million**, and **zero** purchases. The largest is **47,574** shares by the President, Global Affairs and Chief Legal Officer at **$301.10** on February 17, 2026, for **$14.32 Million**. The Chief Executive Officer filed three sales of **32,500** shares each, at **$336.84** on February 4, 2026, **$326.20** on January 21, 2026, and **$320.96** on January 7, 2026.

[Institutional Ownership](/features#institutional-ownership) reached **60.51%** of shares outstanding as of the quarter ending December 31, 2025, easing to **58.77%** as of March 31, 2026. Both figures come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Insider selling clustered around a filing date is usually scheduled and reads as noise. The record worth watching is what followed the 10-K itself. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows the stock down **5.88%** one month after filing and down **17.12%** at two months, before recovering to **+4.04%** at three months and **+11.25%** at five. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 92 Alphabet insider sales totaling $256.13 Million and zero purchases since January 1, 2025, alongside Institutional Ownership at 58.77% as of the March 31, 2026 quarter.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing Alphabet's cumulative price path after this 10-K was filed: down 5.88% at one month and down 17.12% at two months, recovering to +4.04% at three months and +11.25% at five. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### Why was Alphabet's free cash flow flat in FY2025?

Capital expenditure grew almost exactly as fast as operating cash flow. Operating cash flow rose **$39.41 Billion** and Purchases Of Property And Equipment rose **$38.91 Billion**, absorbing **98.7%** of the increase. Free cash flow finished at **$73.27 Billion** against **$72.76 Billion**, a gain of **$504 Million**.

### How much did Alphabet spend on capital expenditure in FY2025?

**$91.45 Billion** in cash, up from **$52.54 Billion**. A further **$15.09 Billion** was recognized as Capital Expenditures Incurred But Not Yet Paid at the balance sheet date. Cash capital spending was **4.33x** the year's Depreciation charge of **$21.14 Billion**.

### Did Alphabet reduce its buyback?

Yes. Payments For Repurchase Of Common Stock fell **26.5%**, to **$45.71 Billion** from **$62.22 Billion**, in a year when net income rose **32.0%**. Dividend payments rose to **$10.05 Billion** from **$7.36 Billion**.

### Does Alphabet still have a net cash position?

No. GeminIQ's Net Debt turned positive at **$15.84 Billion** at the end of FY2025, the first net debt position in the eleven fiscal years on file, following **$64.56 Billion** in debt issuance proceeds during the year.

### How do I spot this pattern on my own holdings?

Put operating cash flow and free cash flow side by side across five fiscal years and compare their growth rates rather than their levels. When the two diverge, the gap is capital expenditure, and the cash flow statement will tell you whether it is a one-year step or a new run rate.

---

Alphabet's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 5, 2026, covering the fiscal year ended December 31, 2025 (FY2025).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=alphabet-annual-report-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Alphabet Inc.'s FY2025 10-K (filed February 5, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001652044&type=10-K).

---

## Section 10h: Company Deep-Dive — Palantir (PLTR)
source: https://www.geminiq.com/blog/palantir-10k-analysis-2026

### Palantir 10-K Analysis (2026): The Dilution Story Reversed
Palantir's FY2025 10-K reports revenue up 56.2% to $4.48 Billion and operating margin expanding from 10.8% to 31.6%, while stock-based compensation as a share of revenue fell from 24.1% to 15.3%. The company long criticized for dilution posted its most disciplined SBC year yet, but the valuation carries a price-to-sales ratio above 90.

**[Palantir](/stocks/PLTR) ($PLTR) filed its FY2025 10-K on February 17, 2026. Revenue grew 56.2% to $4.48 Billion and operating margin expanded from 10.8% to 31.6%, one of the sharpest single-year profitability inflections in large-cap software. The stock is reputationally a dilution machine, and for years that was fair. This filing reverses it: stock-based compensation as a share of revenue fell to 15.3% from 24.1%, its lowest ever. The operating leverage is real and improving. The valuation is the part that isn't debatable.**

| Field | Value |
|---|---|
| Ticker | $PLTR |
| Filing | FY2025 10-K |
| Filed | February 17, 2026 |
| Period End | December 31, 2025 |
| Revenue Growth | **+56.2%** |
| Operating Margin (TTM) | **31.59%** |
| Stock Comp to Revenue | **15.28%** |
| Price to Sales (TTM) | **94.11** |

## The Operating Leverage Is Real

Software businesses are supposed to show operating leverage as they scale. Most promise it. Palantir just posted a year where it actually happened at scale.

**The Data:** [Palantir's](/stocks/PLTR) Total Revenues grew **56.2%**, from **$2.87 Billion** to **$4.48 Billion**. Operating Income (Income From Operations) grew far faster, from **$310.4 Million** to **$1.41 Billion**, an increase of **355.5%**. GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) expanded from **10.83%** to **31.59%**, nearly tripling. Net Income reached **$1.63 Billion**, up **251.6%**.

The mechanism is operating expenses growing slower than revenue. Total Operating Expenses rose to **$2.27 Billion** from **$1.99 Billion**, an increase of just **14.2%** against **56.2%** revenue growth. Gross margin also expanded, with GeminIQ's [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) reaching **82.37%**.

**The GeminIQ Edge:** Operating leverage is easy to claim and hard to prove. The proof is in the growth-rate gap: revenue up **56.2%**, operating expenses up **14.2%**. Reading both lines from the [Financial Statements](/features#financial-statements) is what turns a margin percentage into a demonstrated fact.

<center><sup>GeminIQ Financial Statements showing Palantir's Revenues growing 56.2% to $4,475.4 Million while Operating Expenses grew 14.2% to $2,272.3 Million, lifting Operating Income Loss to $1,414.0 Million. Source: FY2025 10-K filed February 17, 2026.</sup></center>

## The Dilution Reputation, Reversed

Palantir's stock-based compensation has been the central bear argument for years. This filing is the first strong evidence against it.

**The Data:** [Palantir's](/stocks/PLTR) Share Based Compensation was **$684 Million** in FY2025, actually down slightly from **$691.6 Million** the prior year, even as revenue grew **56.2%**. GeminIQ's [Stock Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) fell to **15.28%** from **24.14%**, and from **50.47%** as recently as FY2021. Flat SBC dollars against sharply rising revenue is the definition of the dilution problem shrinking.

The share count confirms the improvement without fully clearing it. Weighted Average Number Of Shares Outstanding Basic rose to **2,369.6 Million** from **2,250.2 Million**, an increase of **5.3%**, and diluted shares rose **4.7%**. GeminIQ's [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) sits at **1.08**, meaning diluted shares still exceed basic by roughly **8%**. Dilution has not stopped. It has decelerated hard.

**The GeminIQ Edge:** The bear case on Palantir was always that growth was being bought with shareholder dilution. A **15.28%** SBC-to-revenue ratio, down from **50.47%** four years ago, is the specific number that undercuts it. The stock is still being diluted at roughly **5%** a year, so the argument is weaker, not dead.

<center><sup>GeminIQ Calculated Metrics showing Palantir's Stock Based Compensation to Revenue falling to 15.28% from 24.14%, with Share Based Compensation flat at $684 Million against 56.2% revenue growth. Source: FY2025 10-K filed February 17, 2026.</sup></center>

## Cash Generation Caught Up to the Story

Improving margins mean nothing if they don't convert to cash. Here they did, and by a lot.

**The Data:** [Palantir's](/stocks/PLTR) GeminIQ [Free Cash Flow](/metrics/calculated-values/free-cash-flow) reached **$2.10 Billion** in FY2025, up **84.1%** from **$1.14 Billion**. On revenue of **$4.48 Billion**, that is a free cash flow margin of roughly **47%**. Operating Cash Flow was **$2.13 Billion**. Combined with **56.2%** revenue growth, Palantir's [Rule of 40](/blog/rule-of-40-saas-metric-explained) score, revenue growth plus free cash flow margin, comes to roughly **103**, more than double the **40** threshold the framework treats as the mark of a healthy growth-stage software business.

The balance sheet carries no debt. Cash stood at **$1.45 Billion**, and GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) is **-$1.45 Billion**, a pure net cash position. Deferred Revenue grew to **$409.0 Million** from **$259.6 Million**, a **57.5%** increase roughly in line with revenue.

**The GeminIQ Edge:** A Rule of 40 score above **100** is rare, and Palantir posted it while turning GAAP-profitable and decelerating dilution at the same time. On the operating fundamentals alone, this is close to a best-case software filing.

<center><sup>GeminIQ Calculated Metrics showing Palantir's Free Cash Flow at $2.10 Billion, up 84.1%, for a free cash flow margin near 47% and a Rule of 40 score around 103. Source: FY2025 10-K filed February 17, 2026.</sup></center>

## The Number That Isn't Debatable

Every operating metric argues for Palantir. One metric argues the other way, and it isn't close.

**The Data:** [Palantir's](/stocks/PLTR) market capitalization reached **$421.2 Billion** at fiscal year end. Against **$4.48 Billion** in revenue, that is a GeminIQ [Price to Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) of **94.11**. The trailing [Price to Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) is **259.2**, and GeminIQ's [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) is **0.50%**. For context, the price-to-sales ratio has expanded from **16.57** at the end of FY2023 to **94.11** now, even as revenue grew rapidly, because the share price grew faster.

The stock rose from **$17.17** at the end of FY2023 to **$177.75** at the end of FY2025, a gain of more than **935%** across two years while revenue roughly doubled. The re-rating did the majority of the work.

**The GeminIQ Edge:** A price-to-sales ratio of **94** requires assumptions about future growth that no single filing can validate or refute. The operating improvements documented above are real and would justify a substantial premium. Whether they justify **94x** sales is a question about the next several years of growth, not about this 10-K, and the filing is honest about which parts it can and cannot answer.

<center><sup>GeminIQ Calculated Metrics showing Palantir's Price to Sales Ratio at 94.11, up from 16.57 at the end of FY2023, with a trailing Price to Earnings Ratio of 259.2. Source: FY2025 10-K filed February 17, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records **115** sale filings by [Palantir](/stocks/PLTR) insiders totaling **$1.67 Billion**, against a single purchase of **$1.16 Million**. The largest sale is **2,000,000** shares by a Director at **$144.11** on March 2, 2026, for **$288.22 Million**. Three sales of **1,250,000** shares each, at **$84.77**, **$82.41** and **$81.29** in March 2025, came from a Director and Officer.

[Institutional Ownership](/features#institutional-ownership) reached **53.48%** of shares outstanding as of the quarter ending December 31, 2025, easing to **52.03%** as of March 31, 2026. Both come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Heavy insider selling at a stock up more than **900%** in two years is expected and largely scheduled, and the near-total absence of buying reads as unremarkable in that context rather than as a specific signal. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) shows the stock up **13.48%** one month after this 10-K was filed, then down **3.73%** at two months and up **3.59%** at three. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 115 Palantir insider sales totaling $1.67 Billion against a single $1.16 Million purchase since January 1, 2025.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing Palantir institutional ownership at 53.48% of shares outstanding as of the quarter ending December 31, 2025, easing to 52.03% as of March 31, 2026. Both figures come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing Palantir's cumulative price path after this 10-K was filed: up 13.48% at one month, down 3.73% at two months and up 3.59% at three. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### Is Palantir still diluting shareholders heavily?

Less than before. Stock-based compensation was flat at **$684 Million** while revenue grew **56.2%**, so SBC as a share of revenue fell to **15.28%** from **24.14%**, and from **50.47%** in FY2021. Basic shares still rose **5.3%**, so dilution has decelerated sharply rather than stopped.

### How profitable is Palantir now?

GAAP operating margin reached **31.59%** in FY2025, up from **10.83%**, on revenue of **$4.48 Billion**. Net income was **$1.63 Billion** and free cash flow was **$2.10 Billion**, a free cash flow margin near **47%**.

### What is Palantir's Rule of 40 score?

Roughly **103**, combining **56.2%** revenue growth with a free cash flow margin near **47%**. That is more than double the **40** threshold the framework uses to identify healthy growth-stage software.

### Why is Palantir's valuation controversial?

The price-to-sales ratio is **94.11** and the trailing price-to-earnings ratio is **259.2**. The stock rose more than **935%** in two years while revenue roughly doubled, so the multiple, not the growth, drove most of the gain.

### How do I judge whether stock-based compensation is improving?

Track stock-based compensation as a percentage of revenue over several years rather than the dollar figure alone. Flat or falling SBC dollars against rising revenue means the dilution burden is shrinking, even if the raw compensation number looks large in isolation.

---

Palantir's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 17, 2026, covering the fiscal year ended December 31, 2025 (FY2025).

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Palantir Technologies Inc.'s FY2025 10-K (filed February 17, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001321655&type=10-K).

---

## Section 10i: Company Deep-Dive — Exxon Mobil (XOM)
source: https://www.geminiq.com/blog/exxon-mobil-10k-analysis-2026

### ExxonMobil 10-K Analysis (2026): Earnings Down, Multiple Up
ExxonMobil's FY2025 10-K reports net income of $28.84 Billion, down 48.3% from the 2022 peak of $55.74 Billion, while the share price rose 21% over the same period. Return on Invested Capital fell from 25.56% to 9.81%. The entire share price gain since 2022 came from multiple expansion, not earnings.

**[ExxonMobil](/stocks/XOM) ($XOM) filed its FY2025 10-K on February 18, 2026. Net income came in at $28.84 Billion, the third consecutive annual decline and 48.3% below the $55.74 Billion the company earned in 2022. Over that same three-year stretch the share price rose from $98.16 to $118.70, a gain of 21.0%. Earnings fell by nearly half and the stock went up. The trailing price-to-earnings ratio did the entire job, expanding from 7.41 to 17.72.**

| Field | Value |
|---|---|
| Ticker | $XOM |
| Filing | FY2025 10-K |
| Filed | February 18, 2026 |
| Period End | December 31, 2025 |
| Net Income (FY2025) | **$28.84 Billion** |
| Net Income Change vs 2022 | **-48.3%** |
| Share Price Change vs 2022 | **+21.0%** |
| P/E (TTM) | **17.72** |

## Three Straight Years of Falling Earnings

The 2022 result was an outlier and everyone knew it at the time. What is less discussed is that nothing has stabilized since.

**The Data:** [ExxonMobil's](/stocks/XOM) Net Income (Loss) Attributable To ExxonMobil peaked at **$55.74 Billion** in FY2022. It fell to **$37.35 Billion** in FY2023, **$35.06 Billion** in FY2024, and **$28.84 Billion** in FY2025. That is three consecutive annual declines totaling **48.3%**. Revenues followed the same direction, from **$413.7 Billion** in FY2022 to **$332.24 Billion** in FY2025, a decline of **19.7%**.

Cash generation fell harder than either. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) dropped from **$58.39 Billion** in FY2022 to **$23.61 Billion** in FY2025, a decline of **59.6%**. In the most recent year alone, Net Cash Provided By Operating Activities came to **$51.97 Billion** against **$55.02 Billion** the year before, while capital expenditure rose to **$28.36 Billion** from **$24.31 Billion**.

**The GeminIQ Edge:** A single year against a cyclical peak proves nothing. Three consecutive declines with revenue, earnings and free cash flow all pointing the same way is a different observation, and it only becomes visible when the [Financial Statements](/features#financial-statements) are read as a multi-year series rather than a year-over-year comparison.

<center><sup>GeminIQ Financial Statements showing ExxonMobil's Net Income Loss falling across FY2022 ($55.74 Billion), FY2023 ($37.35 Billion), FY2024 ($35.06 Billion) and FY2025 ($28.84 Billion). Source: FY2025 10-K filed February 18, 2026.</sup></center>

## The Share Price Went the Other Way

If earnings fell **48.3%** and the stock rose **21.0%**, the difference has to come from somewhere. It came from what the market was willing to pay per dollar of those earnings.

**The Data:** [ExxonMobil's](/stocks/XOM) closing price moved from **$98.16** at the end of FY2022 to **$118.70** at the end of FY2025, and market capitalization from **$412.8 Billion** to **$511.2 Billion**, a gain of **23.8%**. Over the same window the trailing [Price to Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) expanded from **7.41** to **17.72**, an increase of **139.3%**. [Price to Book](/metrics/valuation-metrics/price-to-book-ratio) moved from **2.04** to **1.92**, so the re-rating shows up against earnings rather than against assets.

The cash-based valuation moved further. GeminIQ's [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) fell from **14.15%** in FY2022 to **4.62%** in FY2025, a decline of **67.3%**, reflecting both the smaller cash figure and the larger market capitalization.

**The GeminIQ Edge:** Multiple expansion is not a criticism. Investors re-rate businesses for reasons that never appear in a filing, and a **7.41** starting multiple was arguably too low. What the filing does establish is the arithmetic: none of the **21.0%** price gain since 2022 was funded by earnings growth, because there wasn't any.

<center><sup>GeminIQ Calculated Metrics showing ExxonMobil's Price to Earnings Ratio expanding from 7.41 (FY2022) to 17.72 (FY2025) while Free Cash Flow Yield fell from 14.15% to 4.62%. Source: FY2025 10-K filed February 18, 2026.</sup></center>

## Where the Capital Efficiency Went

The profit decline is only half the ratio. The capital base did the other half.

**The Data:** GeminIQ's [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) for [ExxonMobil](/stocks/XOM) fell from **25.56%** in FY2022 to **9.81%** in FY2025, a decline of **61.6%**. [Net Operating Profit After Tax](/metrics/returns-and-profitability/net-operating-profit-after-tax) fell **48.0%**, from **$56.81 Billion** to **$29.54 Billion**, while [Invested Capital](/metrics/calculated-values/invested-capital) rose **37.7%**, from **$222.3 Billion** to **$306.1 Billion**. Return on Equity followed, from **29.48%** to **10.74%**.

The balance sheet carried the expansion. Total Assets grew from **$369.1 Billion** to **$449.0 Billion** across the period, and GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) rose from **$11.53 Billion** at the end of FY2022 to **$32.86 Billion** at the end of FY2025.

**The GeminIQ Edge:** A **9.81%** [return on invested capital](/blog/roic-return-on-invested-capital-explained) is not a distress reading for an integrated major, and the FY2022 figure of **25.56%** was a cycle peak that was never going to hold. The point of putting them side by side is that the multiple moved in the opposite direction to the return on capital, which is the relationship most valuation frameworks assume runs the other way.

<center><sup>GeminIQ Calculated Metrics showing ExxonMobil's Return on Invested Capital falling from 25.56% (FY2022) to 9.81% (FY2025) as Net Operating Profit After Tax fell 48.0% and Invested Capital rose 37.7%. Source: FY2025 10-K filed February 18, 2026.</sup></center>

## Costs Rose While Revenue Fell

The most recent year has a detail worth isolating, because it separates price-driven decline from cost-driven decline.

**The Data:** [ExxonMobil's](/stocks/XOM) Revenues fell **5.0%** in FY2025, from **$349.59 Billion** to **$332.24 Billion**. Crude Oil And Product Purchases fell faster, down **7.6%** from **$199.45 Billion** to **$184.25 Billion**, which is what should happen when input costs track output prices. The controllable cost lines went the other way. Production And Manufacturing Expenses rose **7.1%** to **$42.42 Billion**. Depreciation And Depletion, filed as Depreciation Depletion And Amortization, rose **10.9%** to **$25.99 Billion**. Selling, General And Administrative Expenses rose **11.5%** to **$11.13 Billion**. Exploration Expenses, Including Dry Holes rose **21.9%** to **$1.01 Billion**.

Income Before Income Taxes finished at **$41.27 Billion** against **$48.87 Billion**, and the tax charge fell to **$11.50 Billion** from **$13.81 Billion**.

**The GeminIQ Edge:** Falling revenue at an oil major is usually read as a commodity price story and dismissed as outside management's control. The cost lines are the part that is not. Four separate expense categories grew between **7.1%** and **21.9%** in a year when the top line contracted, and that combination is what turns a price cycle into a margin problem.

<center><sup>GeminIQ Financial Statements showing ExxonMobil's Revenues falling 5.0% to $332.238 Billion while Production And Manufacturing Expenses rose to $42.424 Billion, Depreciation Depletion And Amortization to $25.993 Billion, and Selling General And Administrative Expense to $11.128 Billion. Source: FY2025 10-K filed February 18, 2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money?

**The Data:** Since January 1, 2025, GeminIQ's [Insider Transactions](/features#insider-transactions) records only **9** sale filings by [ExxonMobil](/stocks/XOM) insiders, totaling **$3.10 Million**, and **zero** purchases. The largest is **5,000** shares by the VP of Corporate Strategic Planning at **$139.76** on February 2, 2026, for **$698,800**. The volume here is unusually low for a company of this size, which makes the record closer to uninformative than bearish.

[Institutional Ownership](/features#institutional-ownership) stood at **61.68%** of shares outstanding as of the quarter ending December 31, 2025, easing to **60.86%** as of March 31, 2026. Both come from quarterly [13F filings](/blog/how-to-read-13f-filing) and describe positioning as of those quarter-ends rather than current holdings.

**The GeminIQ Edge:** Nine insider filings across eighteen months is too thin a sample to read anything into, and saying so is more useful than manufacturing a signal from it. GeminIQ's [Earnings Market Reaction Heatmap](/features#price-variance) carries more information here: the stock gained **3.61%** one month after this 10-K was filed and **1.21%** at two months, then fell **4.05%** at three months and **8.40%** at five. The full twelve-month window has not yet elapsed.

<center><sup>GeminIQ Insider Transactions showing 9 ExxonMobil insider sales totaling $3.10 Million and zero purchases since January 1, 2025.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing ExxonMobil institutional ownership at 61.68% of shares outstanding as of the quarter ending December 31, 2025, easing to 60.86% as of March 31, 2026. Both figures come from quarterly 13F filings.</sup></center>

<center><sup>GeminIQ Earnings Market Reaction Heatmap showing ExxonMobil's cumulative price path after this 10-K was filed: up 3.61% at one month and 1.21% at two months, then down 4.05% at three months and 8.40% at five. Figures are cumulative from the filing date.</sup></center>

## Frequently Asked Questions

### How much have ExxonMobil's earnings fallen since 2022?

Net income fell from **$55.74 Billion** in FY2022 to **$28.84 Billion** in FY2025, a decline of **48.3%** across three consecutive down years. Revenue fell **19.7%** and free cash flow fell **59.6%** over the same period.

### Why is ExxonMobil's stock up if earnings are down?

The multiple expanded. The trailing price-to-earnings ratio went from **7.41** at the end of FY2022 to **17.72** at the end of FY2025, an increase of **139.3%**, while the share price rose **21.0%** from **$98.16** to **$118.70**.

### What is ExxonMobil's ROIC?

**9.81%** on a trailing basis as of the FY2025 10-K, down from **25.56%** in FY2022. NOPAT fell **48.0%** while invested capital rose **37.7%**, and both halves of the ratio moved against it.

### Did ExxonMobil's costs increase in FY2025?

Yes, several categories did, while revenue fell **5.0%**. Production And Manufacturing Expenses rose **7.1%**, Depreciation And Depletion rose **10.9%**, Selling, General And Administrative Expenses rose **11.5%**, and Exploration Expenses rose **21.9%**.

### How do I check whether a price gain came from earnings or from the multiple?

Pull net income and the trailing price-to-earnings ratio for the same fiscal year ends and compare their percentage changes across the period. Price change is roughly the earnings change compounded with the multiple change, so when earnings fall and price rises, the multiple accounts for all of it and more.

---

ExxonMobil's most recent annual filing is a [Form 10-K](/blog/how-to-read-10-k) filed February 18, 2026, covering the fiscal year ended December 31, 2025 (FY2025).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=exxon-mobil-10k-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Exxon Mobil Corporation's FY2025 10-K (filed February 18, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000034088&type=10-K).

---

## Blog: 13F Portfolio Concentration: The Only Signal That Matters
source: https://www.geminiq.com/blog/13f-portfolio-concentration-signal

### 13F Portfolio Concentration: The Only Signal That Matters
13F portfolio concentration — not position size, not filing frequency — is the variable that separates genuine conviction signals from index-tracking noise in institutional ownership data. This post explains how to calculate concentration ratios from public filings, what threshold separates signal from clutter, and why the stocks in the most concentrated quality portfolios share measurable fundamental characteristics.

Every quarter, financial media runs the same cycle. A new batch of Form 13F filings hits EDGAR. Analysts pull the largest new positions from the most prominent names. Headlines follow: "Hedge Fund X Added [Ticker]." "Top Institutions Are Buying [Sector]." The implicit message is that 13F data — taken together, across the full population of filers — says something meaningful about where smart money is flowing. It does not. The filing system covers more than **5,000** institutional investment managers, from the most analytically rigorous concentrated long/short funds to bank trust departments mechanically managing **$120 million** in index-matching equity accounts. Their filings look identical on EDGAR. The analysis that treats them as equivalent produces noise, not signal. One variable sorts institutional ownership data into useful and useless: portfolio concentration. A manager with **8 positions** is telling you something. A manager with **400** is telling you nothing.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=13f-portfolio-concentration-signal)**

---

## Table of Contents

- [Why Most 13F Coverage Produces Noise, Not Signal](#why-most-13f-coverage-produces-noise-not-signal)
- [What Portfolio Concentration Is and How to Measure It](#what-portfolio-concentration-is-and-how-to-measure-it)
- [The Closet Indexer Problem](#the-closet-indexer-problem)
- [The Threshold That Separates Signal from Clutter](#the-threshold-that-separates-signal-from-clutter)
- [What Concentrated Portfolios Hold in Common](#what-concentrated-portfolios-hold-in-common)
- [Running the Same Criteria Without the 45-Day Lag](#running-the-same-criteria-without-the-45-day-lag)

---

## Why Most 13F Coverage Produces Noise, Not Signal

The problem with 13F coverage starts before you open a single filing. The Form 13F obligation applies to any institutional investment manager exercising discretion over **$100 million** or more in qualifying U.S. equities — a threshold low enough to mix hedge funds running concentrated conviction portfolios with pension funds tracking liability benchmarks, bank trust departments managing estates, and registered investment advisers running model portfolios for retail clients. The SEC does not distinguish between them. EDGAR does not distinguish between them. And the financial data platforms aggregating 13F filings almost universally do not distinguish between them either.

The result is a signal pool contaminated at the source. When a financial data service reports that institutional ownership of a given stock increased from **47%** to **51%** quarter-over-quarter, it is reporting a mathematical aggregation across all of these filer types simultaneously. The pension fund added to a broad market index. The trust department rebalanced an estate. The hedge fund added to a concentrated bet it has held for seven quarters and increased again because the thesis strengthened. These three events produce identical-looking line items in the aggregate ownership figure. Standard financial media reports the total and calls it the signal. But standard financial media doesn't read the footnotes.

The 13F system is not structurally broken — it produces useful information. But extracting that information requires filtering the filer population before analyzing the holdings data. The variable that performs that filter most efficiently is concentration.

---

## What Portfolio Concentration Is and How to Measure It

Portfolio concentration, in the context of 13F analysis, measures how tightly an institutional manager's disclosed holdings are clustered into a small number of positions. The most direct measurement is the percentage of total disclosed portfolio value held in the manager's top 5, top 10, or top 15 positions.

A manager with **$2 billion** in disclosed equity holdings, with the top five positions representing **$1.6 billion** — **80%** of the disclosed portfolio — is highly concentrated. Every dollar in that fund is working toward a small number of explicit theses. A manager with the same **$2 billion** spread across 350 positions at roughly equal weight is effectively tracking a benchmark. The top five positions represent perhaps **5%** to **7%** of the total. No single holding can materially affect returns. Both portfolios appear in 13F tracking databases under an identical UI. The concentrated manager's filing signals a specific set of investment theses held with enough conviction to allocate meaningful capital against them. The diversified manager's filing reports compliance with a regulatory disclosure obligation.

The calculation is not complicated. For any 13F filing on EDGAR, the [Information Table](/blog/how-to-read-13f-filing) lists every holding with its market value at quarter-end, reported in thousands of dollars. Sum the five largest values, divide by the total aggregate value from the Summary Page, and you have the top-five concentration ratio. A ratio above **50%** for the top five holdings is a meaningful threshold for signal-carrying concentration. Below **20%** for the top ten suggests a portfolio that is, for analytical purposes, indistinguishable from a broad index fund.

For a more granular measure, the effective number of positions — derived by applying the Herfindahl-Hirschman Index to portfolio weights — compresses a portfolio's weight distribution into a single number representing the equivalent of equally-weighted bets. A fund with **$2 billion** across 40 positions but **60%** concentrated in three names has an effective position count closer to 8 than to 40. Both the simple top-N ratio and the effective position count answer the same question — not how many positions this manager holds, but how many actual investment theses.

---

## The Closet Indexer Problem

A portfolio with 300 to 500 positions has a practical constraint that is not analytical — it is arithmetic. A fund managing **$3 billion** across 400 equity positions has an average position size of **$7.5 million**. In a stock with a **$5 billion** market cap, that is a **0.15%** ownership stake. In a stock with a **$50 billion** market cap, it is **0.015%**. Neither position is large enough to represent genuine conviction — it cannot meaningfully move the fund's returns. The manager is not making a bet; they are building a map.

This category of filer is often called a closet indexer: a manager whose disclosed portfolio, despite an active management label, tracks a broad equity benchmark closely enough that its 13F provides zero information about valuation-driven selection. Research on active share — the percentage of a portfolio that differs from the benchmark — consistently finds that managers with high active share outperform those with low active share over long holding periods. The corollary matters for 13F analysis: a manager with low active share, by definition, is not expressing investment conviction in the positions their 13F reports. Their filing tells you what the benchmark holds.

The problem for investors following 13F data without a concentration filter is that closet indexers are overrepresented in the aggregate. There are simply more of them than there are genuinely concentrated managers. Their combined AUM is larger. When their filings shift an aggregate institutional ownership percentage by a few points, financial media covers the move as a collective judgment call. The signal, if there was one, belonged to the concentrated manager who moved first and smaller. The noise came from the closet indexers that followed mechanically.

---

## The Threshold That Separates Signal from Clutter

Two filters applied together reduce that full population to the small group whose holdings actually carry conviction. The exact threshold is not universal — it varies by strategy, market cap of holdings, and AUM relative to position capacity — but in practice, both consistently isolate the signal.

The first is total position count. Institutional managers with fewer than 20 disclosed equity positions are making explicit choices about each name. Adding a 17th position to a 20-name portfolio is a deliberate act — it displaces capital, requires a valuation rationale, and increases the fund's tracking error against any benchmark. These constraints do not exist for a 350-position manager. Below 20 positions, almost every holding is a thesis. Between 20 and 50, most holdings are theses. Above 100, the signal drops quickly. Above 200, the filing carries little more analytical content than an index fund's quarterly disclosure.

The second filter is top-five concentration ratio. A ratio above **50%** of disclosed portfolio value confirms that the small position count represents genuine weight allocation rather than a manager in transition or holding legacy positions at minimal weight. Applied together — fewer than 20 total positions and top-five ratio above **50%** — these two filters leave a short list of managers actually expressing investment theses through their disclosed holdings.

Finding these managers through EDGAR directly requires sorting by position count and comparing aggregate values across thousands of quarterly filings — labor-intensive without purpose-built tools. GeminIQ's [Institutional Ownership](/features#institutional-ownership) feature surfaces 13F holder data by stock, tied directly to SEC EDGAR source data. Applying both filters simultaneously is the difference between reading a filing and reading a conviction.

---

## What Concentrated Portfolios Hold in Common

Apply the concentration filters to a cross-section of 13F filings from genuinely concentrated managers — fewer than 20 total positions, top-five ratio above **50%** — and a pattern appears in what they own. It is not a pattern by sector or market cap. It is a pattern by fundamental characteristic.

The stocks that appear most frequently across concentrated institutional portfolios tend to share four measurable qualities. [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) is consistently high — above **15%** on a trailing twelve-month basis, and stable across multiple years rather than a function of a single exceptional quarter. [Return on Equity (ROE)](/metrics/returns-and-profitability/return-on-equity) is similarly elevated, reflecting businesses compounding shareholder capital at attractive rates. Balance sheets are conservative: [Debt-to-Equity](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) ratios run below **0.5**, which limits the risk that a capital structure disruption forces a position exit at the worst time. And [Net Income Growth](/metrics/growth-metrics/net-income-growth) is positive and durable over multi-year periods, not the spike-and-revert profile of a cyclical recovery.

These characteristics are not coincidental. A concentrated manager committing **15%** to **20%** of a fund to a single position requires a business model strong enough to withstand a multi-year hold through earnings volatility, competitive pressure, and market cycles. High ROIC combined with low leverage and consistent earnings growth is the quantitative profile of a business that compounds through difficulty rather than breaking under it. Concentrated managers have a practical incentive to find these businesses — the cost of being wrong is **15%** of the fund, not **0.25%**.

The convergence of concentrated quality managers on the same fundamental profile is why GeminIQ's [Buffett-Style Screener](/screens/stock-screeners/buffett-style) surfaces candidates that appear disproportionately in concentrated institutional portfolios. The screener applies the same criteria — ROIC above **15%**, ROE above **15%**, Debt-to-Equity below **0.5**, net income growth above **8%** over three years — that concentrated quality managers evaluate before allocating meaningful capital. For a full breakdown of how each criterion works and what the screen produces, the [Buffett stock criteria](/blog/buffett-stock-criteria-quality-business) post covers the framework in depth. The core finding is consistent: the businesses clearing all four thresholds are the same ones appearing quarter after quarter in the portfolios of managers whose conviction is measured in position count, not basis points.

---

## Running the Same Criteria Without the 45-Day Lag

The mechanics of the 13F system create a timing problem for acting on that insight. The filing is due within **45 calendar days** after each quarter ends. A manager who built a position through February and March reports it by mid-May, describing holdings as of March 31. By the time that filing is public, the market has had up to **45 days** to price in whatever information prompted the position. The entry point is gone. The [institutional ownership guide](/blog/institutional-ownership-13f-filing-explained) in this series covers the lag mechanics in full — but the practical consequence for concentration analysis is clear: even the most signal-carrying concentrated filing describes a thesis formed last quarter.

The response is not to abandon 13F concentration analysis but to understand what it is actually useful for. Following concentrated manager filings over multiple quarters reveals which businesses meet a consistent quality threshold — companies that appear repeatedly because their fundamental characteristics make them appropriate long-duration holds. That is a more durable signal than a real-time buy prompt, and it points toward a more actionable question: if you know what criteria concentrated quality managers are applying, why wait for their lag-delayed filing to tell you what they already own?

GeminIQ's [Stock Screener](/features#screener) applies ROIC, ROE, Debt-to-Equity, net income growth, and valuation filters directly to data extracted from SEC EDGAR filings, without third-party normalization between the source and your screen. The [Buffett-Style Screener](/screens/stock-screeners/buffett-style) runs those criteria out of the box, on current data. The [High ROIC, Low Debt Screener](/screens/stock-screeners/high-roic-low-debt) isolates the balance sheet and return characteristics that concentrated managers weight most heavily. The [Quality Compounder Screener](/screens/stock-screeners/quality-compounder) surfaces businesses combining all three — high ROIC, consistent earnings, and conservative debt — into a single filtered list updated from the most recently filed SEC data. The 13F tells you what concentrated managers already own. The screener tells you what they are most likely to buy next.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=13f-portfolio-concentration-signal)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: 8-K Item Codes: The Complete Reference List
source: https://www.geminiq.com/blog/8-k-item-codes-reference-list

### 8-K Item Codes: The Complete Reference List
Every SEC Form 8-K carries one or more numbered item codes — from 1.01 to 9.01 — that classify exactly what kind of material event triggered the filing, and financial media almost never reports which item number a story actually falls under. This is the complete reference: all 33 item codes the SEC defines across the form's nine sections, what each one means, when it's due, and how much weight it typically carries for investors.

Every SEC Form 8-K carries a number in its heading before a single word of the disclosure is read, and that number determines whether the filing is worth stopping for. Financial media rarely reports it. A headline says "Company Announces CEO Departure" or "Company Discloses Cybersecurity Incident," and the item code that actually classifies the event — 5.02, 1.05, whichever applies — almost never makes it into the coverage. That's true even though the SEC's own instructions organize the entire form around exactly that number. The code tells you the deadline, the disclosure requirements, and often the legal liability standard attached to the filing, before you read a word of the text itself.

The SEC defines 33 of these item codes across nine numbered sections, from Section 1 (Registrant's Business and Operations) to Section 9 (Financial Statements and Exhibits). This is the complete reference: every item, its official title, its filing deadline, and how much weight it typically carries for investors.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=8-k-item-codes-reference-list)**

---

## Table of Contents

- [Quick Reference: All 33 Item Codes at a Glance](#quick-reference-all-33-item-codes-at-a-glance)
- [Section 1 — Registrant's Business and Operations](#section-1-registrants-business-and-operations)
- [Section 2 — Financial Information](#section-2-financial-information)
- [Section 3 — Securities and Trading Markets](#section-3-securities-and-trading-markets)
- [Section 4 — Matters Related to Accountants and Financial Statements](#section-4-matters-related-to-accountants-and-financial-statements)
- [Section 5 — Corporate Governance and Management](#section-5-corporate-governance-and-management)
- [Sections 6 Through 9 — ABS, Regulation FD, Other Events, and Exhibits](#sections-6-through-9-abs-regulation-fd-other-events-and-exhibits)
- [Filed vs. Furnished: What the Item Number Doesn't Tell You](#filed-vs-furnished-what-the-item-number-doesnt-tell-you)
- [Verifying an Item Code Against the Filed Numbers](#verifying-an-item-code-against-the-filed-numbers)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Quick Reference: All 33 Item Codes at a Glance

The table below lists every item the SEC defines on Form 8-K, grouped by the form's own nine sections, with each item's standard filing deadline and its typical weight as an investor signal. The deadlines here are the 8-K's own; the periodic-report deadlines that vary by filer size are covered separately in our guide to [SEC filing deadlines by filer status](/blog/sec-filing-deadlines-by-filer-status).

| Item | Title | Deadline | Investor Relevance |
|---|---|---|---|
| 1.01 | Entry into a Material Definitive Agreement | 4 business days | High |
| 1.02 | Termination of a Material Definitive Agreement | 4 business days | Moderate |
| 1.03 | Bankruptcy or Receivership | 4 business days | High |
| 1.04 | Mine Safety — Reporting of Shutdowns and Patterns of Violations | 4 business days | Rare — mining issuers only |
| 1.05 | Material Cybersecurity Incidents | 4 business days after materiality determination | High |
| 2.01 | Completion of Acquisition or Disposition of Assets | 4 business days | High |
| 2.02 | Results of Operations and Financial Condition | 4 business days | High |
| 2.03 | Creation of a Direct Financial Obligation or an Off-Balance Sheet Obligation | 4 business days | Moderate |
| 2.04 | Triggering Events That Accelerate or Increase a Financial Obligation | 4 business days | Moderate |
| 2.05 | Costs Associated with Exit or Disposal Activities | 4 business days | Moderate |
| 2.06 | Material Impairments | 4 business days | High |
| 3.01 | Notice of Delisting or Failure to Satisfy a Continued Listing Rule | 4 business days | High |
| 3.02 | Unregistered Sales of Equity Securities | 4 business days | Moderate |
| 3.03 | Material Modification to Rights of Security Holders | 4 business days | Moderate |
| 4.01 | Changes in Registrant's Certifying Accountant | 4 business days | High |
| 4.02 | Non-Reliance on Previously Issued Financial Statements | 4 business days | High |
| 5.01 | Changes in Control of Registrant | 4 business days | High |
| 5.02 | Departure of Directors or Officers; Election of Directors; Appointment of Officers | 4 business days | High |
| 5.03 | Amendments to Articles of Incorporation or Bylaws; Change in Fiscal Year | 4 business days | Routine |
| 5.04 | Temporary Suspension of Trading Under Employee Benefit Plans | 4 business days | Rare |
| 5.05 | Amendments to Code of Ethics, or Waiver of a Provision | 4 business days | Routine |
| 5.06 | Change in Shell Company Status | 4 business days | Moderate |
| 5.07 | Submission of Matters to a Vote of Security Holders | 4 business days | Routine |
| 5.08 | Shareholder Director Nominations | 4 business days after meeting date is set | Rare |
| 6.01 | ABS Informational and Computational Material | 4 business days | ABS issuers only |
| 6.02 | Change of Servicer or Trustee | 4 business days | ABS issuers only |
| 6.03 | Change in Credit Enhancement or Other External Support | 4 business days | ABS issuers only |
| 6.04 | Failure to Make a Required Distribution | 4 business days | ABS issuers only |
| 6.05 | Securities Act Updating Disclosure | 4 business days | ABS issuers only |
| 6.06 | Static Pool | Tied to registration effectiveness | ABS issuers only |
| 7.01 | Regulation FD Disclosure | Per Regulation FD timing | Moderate |
| 8.01 | Other Events | Voluntary — no fixed deadline | Catch-all — depends entirely on content |
| 9.01 | Financial Statements and Exhibits | 4 business days (71-day extension for acquired-business financials) | Routine, but critical for M&A |

---

## Section 1 — Registrant's Business and Operations

**Item 1.01 — Entry into a Material Definitive Agreement.** A material contract not made in the ordinary course of business — a credit facility, an acquisition agreement, a major licensing deal — with a brief description of the terms attached as an exhibit. This is the single most commonly filed item on the form.

**Item 1.02 — Termination of a Material Definitive Agreement.** The counterpart to 1.01: a material agreement ends other than by its own scheduled expiration, along with any early termination penalties incurred.

**Item 1.03 — Bankruptcy or Receivership.** A receiver, fiscal agent, or similar officer has been appointed over substantially all of the registrant's assets, or a reorganization plan has been confirmed by a court. As direct a signal as exists on the form.

**Item 1.04 — Mine Safety.** A narrow, industry-specific item requiring disclosure of imminent-danger orders or patterns-of-violations notices from the Mine Safety and Health Administration. Relevant only to registrants that operate coal or other mines.

**Item 1.05 — Material Cybersecurity Incidents.** Added in 2023, this requires disclosure of the nature, scope, and timing of a cybersecurity incident the registrant has determined to be material, along with its likely impact on financial condition and operations. A narrow national-security delay provision exists, but the default clock starts at the materiality determination, not the incident itself.

---

## Section 2 — Financial Information

**Item 2.01 — Completion of Acquisition or Disposition of Assets.** Confirms that a previously announced deal has actually closed — the significant-assets threshold is generally **10%** of total consolidated assets, or an acquired business meeting the SEC's separate significance tests.

**Item 2.02 — Results of Operations and Financial Condition.** The earnings-release item. A public announcement of material non-public information about a completed quarter or fiscal year, with the release itself attached as an exhibit — almost always furnished, not filed (more on that distinction below).

**Item 2.03 — Creation of a Direct Financial Obligation or an Off-Balance Sheet Obligation.** A new material debt obligation, finance or operating lease obligation, or off-balance-sheet arrangement such as a guarantee.

**Item 2.04 — Triggering Events That Accelerate or Increase a Financial Obligation.** A default, covenant breach, or similar triggering event that accelerates or increases an existing obligation disclosed under 2.03.

**Item 2.05 — Costs Associated with Exit or Disposal Activities.** A board- or officer-level commitment to a restructuring plan — layoffs, facility closures — with an estimate of the material charges involved. If the estimate isn't determinable at filing time, an amendment is required once it is.

**Item 2.06 — Material Impairments.** A conclusion that a material impairment charge is required under GAAP — most often a goodwill write-down, an admission that a prior acquisition is worth less than what was paid for it.

---

## Section 3 — Securities and Trading Markets

**Item 3.01 — Notice of Delisting or Failure to Satisfy a Continued Listing Rule.** The exchange has notified the registrant that it no longer meets a listing standard, or has moved to delist or transfer the listing. Applies even during a grace period the exchange grants to cure the deficiency.

**Item 3.02 — Unregistered Sales of Equity Securities.** A sale of equity securities not registered under the Securities Act — generally exempt from disclosure if the shares sold are below **1%** of shares outstanding (**5%** for smaller reporting companies) since the last such report.

**Item 3.03 — Material Modification to Rights of Security Holders.** The rights attached to a registered class of securities — including dividend or voting rights — have been materially modified or limited, including through the issuance of a new class of securities.

---

## Section 4 — Matters Related to Accountants and Financial Statements

**Item 4.01 — Changes in Registrant's Certifying Accountant.** The registrant's independent auditor resigns, is dismissed, declines to stand for reappointment, or a new one is engaged. Whether the change was voluntary and whether any disagreements existed with the departing auditor are required disclosures.

**Item 4.02 — Non-Reliance on Previously Issued Financial Statements.** The board or an authorized officer concludes that previously issued financial statements contain a material error and can no longer be relied upon. This is the formal restatement-trigger item — what to do with one once you find it is covered in [how to find restatements in filings](/blog/how-to-find-restatements-in-filings) — and it is one of exactly two items — alongside 4.01 — that cannot be deferred into the next periodic report even if the four-day window falls close to a 10-K or 10-Q deadline.

---

## Section 5 — Corporate Governance and Management

**Item 5.01 — Changes in Control of Registrant.** A change in control has occurred, with the identity of the new controlling party, the basis and percentage of control, and the consideration used.

**Item 5.02 — Departure of Directors or Officers; Election of Directors; Appointment of Officers.** The broadest and most frequently filed governance item: departures, appointments, and elections of directors and principal officers, plus material compensatory arrangements tied to those events. A departure tied to a disagreement with the registrant carries additional disclosure requirements beyond a routine retirement.

**Item 5.03 — Amendments to Articles of Incorporation or Bylaws; Change in Fiscal Year.** A charter or bylaw amendment not previously disclosed in a [proxy statement](/blog/what-is-def-14a), or a change in fiscal year outside a shareholder vote.

**Item 5.04 — Temporary Suspension of Trading Under Employee Benefit Plans.** A blackout period suspending trading in company stock within an employee benefit plan — tied to ERISA notice requirements and Regulation BTR.

**Item 5.05 — Amendments to Code of Ethics, or Waiver of a Provision.** A change to, or a waiver granted from, the code of ethics covering the principal executive, financial, or accounting officer. Can be satisfied via the company website instead of a filing, under specific conditions.

**Item 5.06 — Change in Shell Company Status.** A registrant that was a shell company completes a transaction causing it to cease being one — the disclosure event that typically follows a reverse merger or de-SPAC transaction.

**Item 5.07 — Submission of Matters to a Vote of Security Holders.** The results of an annual or special shareholder meeting — director elections, say-on-pay, shareholder proposals — including the vote tally. Preliminary results can be filed first, with final results following by amendment.

**Item 5.08 — Shareholder Director Nominations.** Discloses the deadline by which a shareholder must submit a director nomination, where the registrant is required to include shareholder nominees in its own proxy materials.

---

## Sections 6 Through 9 — ABS, Regulation FD, Other Events, and Exhibits

Section 6 applies exclusively to asset-backed securities issuers and covers six narrow items: ABS informational material (6.01), a change of servicer or trustee (6.02), a change in credit enhancement (6.03), a failed distribution (6.04), updating disclosure on the actual asset pool versus the prospectus (6.05), and static pool information (6.06). None of these apply to an operating company, and they rarely surface outside structured-finance filers.

Section 7 holds a single item: **7.01, Regulation FD Disclosure** — used when a registrant discloses material non-public information under Regulation FD, most often an investor-day presentation or analyst briefing delivered outside a formal earnings release. Like Item 2.02, it is furnished rather than filed by default.

Section 8 holds the form's catch-all: **8.01, Other Events** — any event the registrant deems important enough to disclose but that isn't captured by another item. It carries no fixed deadline unless it's being used to satisfy a Regulation FD obligation, which gives companies real discretion over both content and timing.

Section 9 holds **9.01, Financial Statements and Exhibits** — the item that lists every exhibit attached to the filing. It also carries the financial statements and pro forma financial information required after a completed acquisition under Item 2.01. Those acquisition-related financials can be filed with the initial report or added by amendment within **71 calendar days**, which is why a completed deal and its full financial picture on EDGAR often arrive weeks apart.

---

## Filed vs. Furnished: What the Item Number Doesn't Tell You

The item number alone doesn't tell you the legal liability standard attached to the disclosure, and that distinction matters more than most investors realize. Content furnished under Item 2.02 or Item 7.01 is explicitly not subject to Section 18 liability under the Exchange Act unless the registrant states otherwise — a lower standard than a filed item like 1.01 or 5.02 carries. That's part of why earnings-release exhibits under 2.02 can present non-GAAP figures more favorably than the audited numbers that follow weeks later in the 10-Q. For the full mechanics of that distinction and which items it applies to, see [How to Read an 8-K](/blog/what-is-8-k).

---

## Verifying an Item Code Against the Filed Numbers

An 8-K item code is a disclosure trigger, not a financial data source — most items, outside the cover page's Inline XBRL, carry no tagged financial data at all. An Item 2.02 earnings release previews figures; an Item 4.02 restatement announces that prior numbers can't be trusted; an Item 2.06 impairment states a charge is coming. None of it becomes auditable, XBRL-tagged financial statement data until the next 10-Q or 10-K is filed, which is what GeminIQ's [Financial Statements](/features#financial-statements) feature extracts and structures.

That gap is exactly where the item code earns its keep as a research signal rather than a headline. An Item 2.02 release that previews adjusted earnings can be checked against the GAAP figures in the subsequent 10-Q. An Item 4.02 non-reliance disclosure is the first sign that a [10-K/A or 10-Q/A](/blog/amended-sec-filings-10-k-a-explained) is coming, with the corrected numbers to follow. Knowing the item code tells you which filing to watch for next — the 8-K starts the clock; the periodic filing that follows is where the number gets confirmed. Filing-browser tools index 8-Ks by item code, which makes the first half of that workflow fast; our [comparison with BamSEC](/competitor-comparison/bamsec) covers where browsing filings stops and structured financial data has to take over.

---

## Frequently Asked Questions

### What is the most important 8-K item code for investors?

There isn't a single one, but Item 2.02 (earnings), Item 5.02 (executive departures), and Item 4.02 (non-reliance on prior financials) are the three that most consistently move stock prices, because each discloses information the market didn't previously have.

### Which 8-K items don't have the standard 4-business-day deadline?

Item 8.01 has no fixed deadline since it's a voluntary catch-all. Item 7.01 follows Regulation FD's own timing rather than the standard rule. Item 5.08's clock starts when the meeting date is determined, not when a triggering event occurs. Item 9.01's acquisition-related financial statements carry a 71-calendar-day extension beyond the initial report.

### How many item codes does Form 8-K have in total?

33, across nine numbered sections. Section 5 (Corporate Governance and Management) has the most, with eight items; Section 6 (Asset-Backed Securities), Section 7 (Regulation FD), Section 8 (Other Events), and Section 9 (Financial Statements and Exhibits) apply to narrower or single-item categories.

### Is every 8-K item legally required to be filed?

No. Item 8.01 (Other Events) is entirely voluntary — a company chooses to disclose under it because it deems the event important, not because a rule requires it. Every other item is mandatory once its specific triggering event occurs.

### Which 8-K item codes apply only to certain types of issuers?

Section 6's six items (6.01 through 6.06) apply exclusively to asset-backed securities issuers and never surface on an operating company's filings. Item 1.04 (Mine Safety) is similarly narrow, applying only to registrants that operate coal or other mines.

### Which 8-K items can't be deferred into the next periodic report?

Item 4.01 (change in certifying accountant) and Item 4.02 (non-reliance on previously issued financial statements) — exactly two of the 33. Both must be reported on their own 8-K even when the four-business-day window falls close to a 10-K or 10-Q deadline.

Every one of these codes exists to answer the same question before you read a word of the disclosure text: is this a routine administrative update, or a material event the market didn't already know about?

---

## Related Reading

- [How to Read an 8-K: Material Events That Actually Move Stocks](/blog/what-is-8-k) — the full explainer, including the filed-vs-furnished distinction and which items historically move stock prices most.
- [Amended SEC Filings: What a 10-K/A Actually Means](/blog/amended-sec-filings-10-k-a-explained) — where an Item 4.02 non-reliance disclosure leads next.
- [How to Find Restatements in SEC Filings](/blog/how-to-find-restatements-in-filings) — the restatement event itself, from the Item 4.02 announcement through the corrected numbers.
- [SEC Filing Deadlines by Filer Status](/blog/sec-filing-deadlines-by-filer-status) — why the 8-K's four-business-day clock is fixed while the 10-K's is not.
- [10-K vs. 10-Q: Key Differences for Investors](/blog/10-k-vs-10-q-differences-explained) — the periodic filings that turn an 8-K's preview into audited, XBRL-tagged data.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — where the 8-K fits alongside the 10-K, 10-Q, DEF 14A, and S-1.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=8-k-item-codes-reference-list)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: AI Financial Research Data Quality: The Full Stack Explained
source: https://www.geminiq.com/blog/ai-financial-research-data-quality

### AI Financial Research Data Quality: The Full Stack Explained
AI financial research tools run on four-layer data pipelines that introduce invisible reclassifications before the AI ever processes a number. This post maps each layer from SEC EDGAR to AI-generated answer and documents exactly where data quality breaks down.

AI financial research tools have exploded in popularity. The promise is straightforward: ask a question in plain language, get a data-backed answer in seconds. No Bloomberg terminal. No spreadsheet models. No manual extraction from 100-page PDFs. Just type, ask, and invest.

The problem is not the AI. The problem is what the AI is working with.

Every AI financial research tool is built on top of a data pipeline. That pipeline starts at the SEC's EDGAR system — where every public company files its 10-K and 10-Q — and ends at the screen where the AI generates its answer. Between those two points, the data passes through multiple layers of processing, each of which introduces decisions the user never sees. Line items get reclassified. Distinct financial instruments get merged. Company-specific labels get replaced with generic ones. The XBRL tags that link every number to its source filing get stripped and replaced with proprietary identifiers. By the time the AI sees the data, it is already a processed version of what the company actually reported.

An AI that answers confidently from processed data is not the same as an AI that answers from the source. And the difference between those two things is not an edge case — it is the entire foundation of data-driven investing.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=ai-financial-research-data-quality)**

---

## Table of Contents

- [Why the Data Layer Is the AI's Blind Spot](#why-the-data-layer-is-the-ais-blind-spot)
- [The Full Stack: From SEC Filing to AI Answer](#the-full-stack-from-sec-filing-to-ai-answer)
- [Layer 1: The SEC Filing — The Source of Truth](#layer-1-the-sec-filing--the-source-of-truth)
- [Layer 2: The Aggregator — Where Most Information Is Lost](#layer-2-the-aggregator--where-most-information-is-lost)
- [Layer 3: The Platform — Where the Gaps Become Invisible](#layer-3-the-platform--where-the-gaps-become-invisible)
- [Layer 4: The AI — Where Errors Become Confident Answers](#layer-4-the-ai--where-errors-become-confident-answers)
- [Why "Linking Back to the Source" Does Not Fix the Problem](#why-linking-back-to-the-source-does-not-fix-the-problem)
- [The Compounding Effect: How Data Errors Multiply Through Metrics](#the-compounding-effect-how-data-errors-multiply-through-metrics)
- [What a Clean Data Stack Looks Like](#what-a-clean-data-stack-looks-like)
- [Who This Matters For](#who-this-matters-for)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## Why the Data Layer Is the AI's Blind Spot

When investors evaluate an AI research tool, they examine what the user can see: the interface, the speed of the response, the naturalness of the conversation, the breadth of company coverage. These are the things that show up in reviews and comparison articles. They are also the least important layer of the stack.

The most important layer is the one no one examines: the data the AI ingests before it generates any answer.

An AI model does not have independent knowledge of a company's financials. It does not read the 10-K the way a human analyst does. It receives structured data — numbers, labels, categories — from the platform's data source, and it reasons over that data to produce an answer. The quality of the answer is bounded by the quality of the input. Not partially bounded. Entirely bounded. An AI cannot surface a data point it was never given. It cannot correct a reclassification it does not know happened. It cannot flag a merged line item as a merger if the merger occurred before the data reached it.

This is not a critique of any particular AI model. It is a structural property of how AI financial research tools are built. The model is downstream of the data. Always.

---

## The Full Stack: From SEC Filing to AI Answer

Most investors imagine a direct line between an SEC filing and the answer their AI research tool produces. The actual path has four distinct layers, and each one introduces changes that accumulate silently.

---

## Layer 1: The SEC Filing — The Source of Truth

A public company prepares its 10-K or 10-Q, has it audited or reviewed, and files it with the SEC through the EDGAR system. Since 2018, all major filers submit in Inline XBRL format — meaning every financial data point carries an embedded machine-readable tag that identifies exactly what that number represents and links it to the source filing.

At this layer, the data is as clean as it will ever be. Apple's FY2025 10-K, filed October 31, 2025, contains "Vendor Non-Trade Receivables" as its own line item at **$33.2 billion** — separate from trade receivables, with its own XBRL tag (`NontradereceivablesCurrent`) — because Apple's business model creates a specific type of receivable that trade receivables do not describe. Apple reports three distinct debt instruments because they carry different maturities, rates, and risk profiles. Apple separates "Repurchases of common stock" (**$90.7 billion**) from "Payments for taxes related to net share settlement of equity awards" (**$6.0 billion**) on its cash flow statement because these are economically different cash outflows.

Every one of those distinctions matters for analysis. And every one of them is at risk the moment the data leaves EDGAR.

---

## Layer 2: The Aggregator — Where Most Information Is Lost

Within hours of a filing hitting EDGAR, third-party data providers ingest it. Their job is to take thousands of filings from thousands of companies — each with its own reporting structure, its own labels, and its own line items — and map them all into a single standardized template that allows cross-company comparison.

This is where the most consequential processing happens.

The aggregator's template has a fixed number of line items. Apple reports items that don't fit. The aggregator must make decisions: fold the unfamiliar line into the nearest available category, merge two instruments into one, reclassify a cash outflow, or in some cases simply drop the item. These decisions are made at scale, across thousands of companies, in an automated pipeline. They are not documented in any output the user ever sees.

The documented consequences of this process — verified against Apple's FY2025 10-K — are precise. One widely-used platform combined Apple's **$90.7 billion** stock repurchase line with its **$6.0 billion** equity tax payment and displayed the sum as a single "Repurchase of Common Stock" at **$96.7 billion**. The same platform displayed Apple's "Other Non-Current Liabilities" as **$29.9 billion** — subtracting **$11.6 billion** in capital leases from the line while keeping the identical label used in the filing, which shows **$41.5 billion**. The filing shows $41.5 billion. The aggregator shows $29.9 billion. Same label. No indication that anything changed.

These are not rounding errors. They are reclassifications embedded invisibly in the data before any AI model, any screener, or any investor ever touches a number.

---

## Layer 3: The Platform — Where the Gaps Become Invisible

Retail financial research platforms — the tools investors actually use — typically do not build their own data ingestion pipelines from EDGAR. Building and maintaining a direct pipeline that preserves XBRL fidelity requires parsing thousands of filings with different structures, handling XBRL extension tags, managing historical data across taxonomy changes, and correcting known tagging errors without reclassifying what the company reported. It is technically complex and expensive. Most platforms choose to license pre-processed data from an aggregator instead.

At this layer, the platform makes its own display decisions: which line items to show, how to label columns, how to round numbers, which items to surface in the summary view versus hide in a detail panel. The platform also calculates its own metrics — [ROIC](/blog/roic-return-on-invested-capital-explained), free cash flow, [debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained) — on top of the aggregator's already-processed data. Every calculation inherits the normalization decisions made at Layer 2. A ROIC figure calculated on a balance sheet where Apple's three debt instruments have been merged into two categories is not the same ROIC as one calculated from the as-filed data. The formula may be identical. The inputs are not.

The platform does not typically disclose which aggregator supplied the underlying data. The aggregator's specific normalization decisions are not documented. The user has no mechanism to determine whether any given number was reclassified, merged, or relabeled on its way through the pipeline.

---

## Layer 4: The AI — Where Errors Become Confident Answers

This is where the data layer problem becomes most dangerous for investors.

An AI research tool's job is to synthesize structured data into a coherent, conversational answer. It does this well. The problem is that "well" means coherent and fluent — not necessarily accurate relative to the source filing. The AI does not know what reclassifications happened at Layer 2. It does not know that the **$96.7 billion** buyback figure it was given is actually two separate line items merged by an aggregator. It does not know that the "Other Non-Current Liabilities" figure it is reasoning from carries an **$11.6 billion** gap versus the filing. It answers from the data it received, with the same confidence it would have if the data were clean.

A confident, fluent answer from a large language model reads as authoritative. That is the design. The problem is that the authority of the answer is entirely disconnected from the accuracy of its inputs. If the AI was given processed data, the AI produces processed conclusions — and it does so without any indication that the underlying numbers were touched.

This is not a failure of AI. It is a consequence of where the AI sits in the stack. The model is Layer 4. The data quality problem is at Layer 2. No model improvement at Layer 4 can fix a reclassification that happened at Layer 2.

---

## Why "Linking Back to the Source" Does Not Fix the Problem

Several AI financial research platforms offer a "link back to the source filing" feature — the ability to click a number and see a PDF page or filing excerpt. This is presented as a data quality guarantee. It is not.

Linking to the source filing is a navigation feature, not a data integrity feature. The link shows you where to find the original number. It does not tell you whether the number displayed on the platform matches the number in the filing. If an aggregator reclassified Apple's "Other Non-Current Liabilities" from **$41.5 billion** to **$29.9 billion** and kept the same label, the link will take you to the correct balance sheet page — which will show you **$41.5 billion**. You now know there is a discrepancy, but only because you clicked through and manually compared. The platform never told you to do that. The AI never flagged it. The link only reveals the problem if you already suspect there is one.

True data fidelity means the number on the platform matches the filing before you click anything. The link is a verification tool. It is not a substitute for having the right number in the first place.

---

## The Compounding Effect: How Data Errors Multiply Through Metrics

Single line-item discrepancies are consequential. But the more significant problem is what happens when those discrepancies propagate through derived metrics.

Consider [Invested Capital](/metrics/calculated-values/invested-capital) — the denominator in Return on Invested Capital (ROIC), one of the most important metrics in fundamental analysis. Invested Capital is calculated from balance sheet inputs: total assets, operating liabilities, cash, and sometimes specific adjustments for debt and lease obligations. If the balance sheet the AI was given has Apple's three debt instruments merged into two categories, has **$11.6 billion** stripped from "Other Non-Current Liabilities," and has company-specific assets folded into generic buckets, then the Invested Capital figure is calculated on a different balance sheet than the one Apple filed.

The ROIC that results is not Apple's ROIC. It is the ROIC of Apple as reinterpreted by the aggregator's template. The difference may be small for some companies. For companies with complex or company-specific reporting structures, the difference can be material — and it compounds across every ratio, every screen, and every AI-generated comparison that uses it.

GeminIQ's [Calculated Metrics](/features#calculated-metrics) are derived directly from XBRL-tagged as-filed data. Every metric shows its formula and its source inputs — the exact XBRL tags from the exact filing period that went into the calculation. There is no black box. If the metric output surprises you, you can trace it to its inputs and verify those inputs against the original filing in under 30 seconds. That traceability is only possible because the data was never normalized away from the source.

---

## What a Clean Data Stack Looks Like

The alternative to the aggregator pipeline is a direct connection between EDGAR and the analytical layer — XBRL tags preserved, company-specific line items kept as filed, no normalization template applied to standardize across companies.

GeminIQ extracts data directly from SEC EDGAR with every XBRL tag intact. Apple's "Vendor Non-Trade Receivables" remains "Vendor Non-Trade Receivables" at **$33.2 billion** — not folded into "Other Current Assets." Apple's three debt instruments remain three instruments with three tags. Apple's buyback and equity tax payment remain two separate line items. Apple's "Other Non-Current Liabilities" remains **$41.5 billion** as filed.

When an AI or an analyst reasons over that data, the inputs match the filing. The metrics calculated from those inputs are calculated from as-filed numbers. The answer the AI produces is grounded in the data the company actually reported — not a processed approximation of it.

GeminIQ's [Financial Statements](/features#financial-statements) display every line item with its XBRL tag visible. Any number can be verified against the original EDGAR filing in under 30 seconds. This is what verifiable financial data looks like — and it is the only standard that makes AI-assisted analysis trustworthy.

---

## Who This Matters For

For investors running broad screens across thousands of companies to surface initial ideas, normalized data is often adequate. The approximations are close enough, and the standardization makes comparison fast. This is what the aggregator pipeline was designed for, and it does it reasonably well.

The pipeline gap becomes critical as soon as you move from screening to analyzing:

When you are building a financial model, your inputs need to match the filing, or every downstream calculation inherits the discrepancy. When you are auditing an existing position, you need to verify that the numbers you are looking at are the numbers that were reported. When you are running a quantitative strategy and backtesting on historical data, you need the historical data to reflect what was actually filed — because if an aggregator retroactively reclassifies a line item when updating its template, your backtest changes without any underlying economic event. And when you are evaluating a company with complex, company-specific reporting — the kinds of companies where information advantage is highest — the aggregator pipeline strips out precisely the information that creates that advantage.

The GeminIQ [Stock Screener](/features#screener) lets you run broad scans across 100+ metrics to find companies worth deeper analysis. The XBRL-tagged [Financial Statements](/features#financial-statements) let you analyze those companies with data that traces to the source. The [Custom Tables](/features#custom-tables) let you build reusable analytical frameworks that preserve company-specific line items that normalized platforms discard. The entire workflow runs on data that has not been touched between EDGAR and your screen — and that distinction is the only thing that makes AI-assisted financial research trustworthy.

---

## Frequently Asked Questions

### What is XBRL and why does it matter for AI financial research?

XBRL (eXtensible Business Reporting Language) is the data standard the SEC requires every public company to use when filing financial statements. Each number in a 10-K or 10-Q carries a specific XBRL tag that identifies exactly what that number represents and creates a verifiable link back to the source filing. When a platform preserves XBRL tags, every number can be traced to the exact line item in the exact filing. When a platform discards them — replacing them with proprietary identifiers during normalization — the audit trail is severed. An AI reasoning over data without XBRL traceability is reasoning over numbers it cannot independently verify. For a full explanation, see [What Is XBRL and Why It Matters for Investors](/blog/what-is-xbrl).

### Does it matter which data source an AI financial tool uses?

It is the only thing that matters more than the AI model itself. Two AI tools using the same underlying language model but different data sources will produce different answers — and one of those answers will be closer to what the company actually reported. The model determines fluency. The data source determines accuracy. Most investors evaluate AI tools by the former and ignore the latter entirely.

### How do I tell if my financial research platform normalizes data?

Compare any company-specific line item on the platform to the same line in the original 10-K or 10-Q on SEC EDGAR. Start with a line item that the company reports using a specific, unusual label — something that would not survive normalization into a generic template. Apple's **$33.2 billion** Vendor Non-Trade Receivables is the clearest test case: if your platform shows it as its own line item, the data may be sourced directly. If it has been folded into "Other Current Assets" or any generic bucket, the platform is using normalized data. For a step-by-step walkthrough of documented discrepancies, see [Third-Party Financial Data Problems](/blog/third-party-financial-data-problems).

### Does normalization affect all companies equally?

No. Companies with straightforward reporting structures — standard line items, simple balance sheets, conventional debt structures — lose relatively little in normalization because their data fits most aggregator templates without major adjustment. Companies with complex, company-specific reporting structures — multi-instrument debt, proprietary asset categories, non-standard working capital items — lose the most. The irony is that the companies where normalization strips the most information are often the companies where that information matters most for analysis. The information edge in public markets lives in the details that generic templates discard.

### Can AI hallucinations be caused by bad data, not the AI model?

Yes. The distinction matters because "hallucination" in the AI research context is typically attributed to the model producing plausible-sounding but fabricated information. But an AI research tool can produce an answer that is internally consistent, draws directly from its data source, and is still materially wrong relative to the source filing — not because the model invented anything, but because the data it was given had already been reclassified. The model reports what the data says. If the data was processed before it arrived, the error is upstream of the model. Fixing the model does not fix the pipeline.

---

### Related Reading

- [See how the four-stage pipeline is documented step by step with Apple's FY2025 data](/blog/how-financial-data-reaches-investors)
- [See the specific discrepancies third-party normalization creates in Apple's as-filed numbers](/blog/third-party-financial-data-problems)
- [See what XBRL is and why the SEC built it to prevent exactly this problem](/blog/what-is-xbrl)
- [See what else investors miss when they stop at the headline financials](/blog/what-investors-miss-in-sec-filings)

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=ai-financial-research-data-quality)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Blog: Alphabet Q1 2026 10-Q: The Debt-Funded AI Buildout
source: https://www.geminiq.com/blog/alphabet-10q-analysis-q1-2026

### Alphabet Q1 2026 10-Q: The Debt-Funded AI Buildout
Alphabet's Q1 FY2026 10-Q shows long-term debt has grown roughly sevenfold in a year, from $10.9 Billion to $77.5 Billion, funding a $175-185 Billion capital expenditure program aimed at AI infrastructure. The debt increase includes a rare 100-year bond, the first issued by a tech company since Motorola in 1997.

**[Alphabet](/stocks/GOOGL) ($GOOGL) just filed its Q1 FY2026 10-Q (filed April 30, 2026). The balance sheet has changed more in the past twelve months than in the prior decade combined: Long-Term Debt has grown from roughly $10.9 Billion to $77.5 Billion, a roughly sevenfold increase, funding a capital expenditure program guided at $175-185 Billion for 2026 alone. This isn't a company quietly compounding retained earnings anymore. It's a company that has gone to the bond market repeatedly, including a rare 100-year note, to fund the largest infrastructure buildout in its history.**

| Field          | Value              |
| -------------- | ------------------ |
| Ticker         | $GOOGL             |
| Filing         | Q1 FY2026 10-Q     |
| Filed          | April 30, 2026     |
| Period End     | March 31, 2026     |
| Long-Term Debt | **$77.5 Billion**  |
| TTM CapEx      | **$109.9 Billion** |

## The Debt Load Has Transformed

This is the single largest year-over-year change on the balance sheet, and it's worth being precise about the scale.

**The Data:** [Alphabet's](/stocks/GOOGL) Long-Term Debt stood at approximately **$10.9 Billion** in Q1 FY2025. By Q4 FY2025 it had grown to **$46.5 Billion**, and by this filing it reached **$77.5 Billion** — a roughly sevenfold increase in a single year. The jump between the two most recent quarters alone reflects a series of bond offerings completed in February 2026, including a landmark note maturing in **2126**, a full century out, the first bond of that maturity issued by a technology company since 1997.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) balance sheet data quarter by quarter, rather than trusting a single annual snapshot, makes a change of this magnitude impossible to miss. A debt load transforming this dramatically in twelve months is exactly the kind of structural shift that a year-over-year 10-K comparison alone can smooth over.

<center><sup>GeminIQ Financial Statements showing Alphabet's Long-Term Debt growing from approximately $10.9 Billion (Q1 FY2025) to $46.5 Billion (Q4 FY2025) to $77.5 Billion (Q1 FY2026).</sup></center>

## The CapEx Program Behind It

The debt didn't appear on its own. It's directly tied to a capital expenditure program of a scale this company hasn't previously attempted.

**The Data:** TTM CapEx is **$109.9 Billion**, against TTM Operating Cash Flow of **$174.4 Billion** and TTM Free Cash Flow of **$64.4 Billion**. Free cash flow remains solidly positive, but it has compressed materially as capital spending has scaled toward the company's guided **$175-185 Billion** for full-year 2026.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) cash flow data alongside the debt trend above shows the two moving together: rather than fund this buildout entirely from operating cash flow, which would have compressed free cash flow further, [Alphabet](/stocks/GOOGL) has chosen to finance a meaningful portion of it externally.

<center><sup>GeminIQ Financial Statements showing Alphabet's quarterly Payments To Acquire Property Plant And Equipment and Net Cash Provided By Used In Operating Activities, which sum across the four most recent quarters to $109.9 Billion and $174.4 Billion respectively, against a Free Cash Flow TTM of $64.43 Billion.</sup></center>

## The Core Business Is Still Very Profitable

None of the above changes the fact that [Alphabet's](/stocks/GOOGL) underlying business generating the cash to service this debt remains highly profitable.

**The Data:** TTM Revenue is **$422.5 Billion**, with TTM Net Income of **$160.2 Billion**. TTM [Gross Margin](/metrics/margin-metrics/gross-profit-margin) is **60.4%**, and TTM Operating Margin is **32.7%**, both stable to slightly improving over the past two years even as the capex program scaled up.

**The GeminIQ Edge:** Pulling [Calculated Metrics](/features#calculated-metrics) margin trends alongside the debt and capex trends above shows the core advertising and cloud business hasn't weakened to fund this buildout — margins have held. The new debt is financing growth investment, not offsetting a deteriorating core business.

<center><sup>GeminIQ Calculated Metrics showing Alphabet's TTM Gross Margin of 60.4% and TTM Operating Margin of 32.7%, both stable over the trailing two years.</sup></center>

## Smart Money and the Insider Record

Two different signals around [Alphabet](/stocks/GOOGL) worth checking on their own terms.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has held in a fairly narrow band, at **60.5%** in December 2025 and **58.8%** as of the most recent 13F (March 2026, filed with the standard lag) — a modest decline, not a dramatic shift. [Insider Transactions](/features#insider-transactions) show an overwhelmingly sale-weighted record: 838 sales against 3 purchases in the available history.

**The GeminIQ Edge:** Neither figure is dramatic in isolation, and that's the honest read. A stable institutional base and a heavily sale-weighted insider pattern are standard for a mature mega-cap with substantial employee equity compensation, not a signal worth over-reading in either direction.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership holding a stable 58.8%-60.5% band over the trailing year.</sup></center>

## Frequently Asked Questions

### How much has Alphabet's debt grown?

Alphabet's Long-Term Debt has grown from approximately $10.9 Billion in Q1 FY2025 to $77.5 Billion as of the Q1 FY2026 10-Q, a roughly sevenfold increase, driven by bond offerings completed to fund AI infrastructure capital expenditure.

### What is Alphabet's 2026 capital expenditure guidance?

Alphabet has guided to $175-185 Billion in capital expenditure for full-year 2026, more than double the prior year's spending, funding data center and AI infrastructure buildout.

### Is Alphabet's core business still profitable?

Yes. TTM Net Income is $160.2 Billion on TTM Revenue of $422.5 Billion, with TTM Gross Margin of 60.4% and TTM Operating Margin of 32.7%, both stable over the trailing two years.

### When did Alphabet last file its 10-Q, and what period does it cover?

Alphabet's most recent filing is a Form 10-Q filed April 30, 2026, covering the fiscal quarter ended March 31, 2026 (Q1 FY2026).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=alphabet-10q-analysis-q1-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Alphabet Inc.'s Q1 FY2026 10-Q (filed April 30, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001652044/000165204426000048/goog-20260331.htm).

---

## Blog: Alphabet Q2 2026 10-Q: The $99 Billion Line Item
source: https://www.geminiq.com/blog/alphabet-10q-analysis-q2-2026

### Alphabet Q2 2026 10-Q: The $99 Billion Line Item
Alphabet's Q2 FY2026 10-Q reports Net Income of $112.193 Billion and Diluted EPS of $9.11, but $98.999 Billion of that quarter's pretax income came from a single non-cash line item, a mark-to-market gain on debt and equity securities, not from operating performance.

**[Alphabet](/stocks/GOOGL) ($GOOGL) just filed its Q2 FY2026 10-Q (filed July 23, 2026). The headline numbers look almost unbelievable: Net Income of $112.193 Billion for the quarter and Diluted EPS of $9.11, against $62.578 Billion and $5.11 just one quarter earlier. Trailing-twelve-month revenue grew 20.1%. Trailing-twelve-month net income grew 111.3%. Those two growth rates should never diverge this violently on the same income statement, and the raw filing shows exactly why: $98.999 Billion of this quarter's pretax income came from a single tagged line item, a non-cash mark-to-market gain on debt and equity securities, not from selling more ads or renting more cloud compute.**

| Field | Value |
|---|---|
| Ticker | $GOOGL |
| Filing | Q2 FY2026 10-Q |
| Filed | July 23, 2026 |
| Period End | June 30, 2026 |
| Net Income (Q2 FY2026) | **$112.193 Billion** |
| Operating Income (Q2 FY2026) | **$40.77 Billion** |

## The $99 Billion Line Item

Every quarter's cash flow statement carries a reconciliation section that backs non-cash items out of net income to arrive at actual cash generated. Most quarters, that section is a rounding exercise. This quarter, one line in it swamped everything else the company reported.

**The Data:** The raw filing tags this line item **Debt And Equity Securities Gain Loss**. It carried a value of **$98.999 Billion** this quarter — a gain, since the tag records losses as positive and gains as negative. That figure didn't appear from nowhere: the same line was **$36.804 Billion** in Q1 FY2026 and just **$1.451 Billion** in the same quarter a year ago. On the balance sheet, the line GeminIQ tags **Other Long Term Investments** — the category holding [Alphabet's](/stocks/GOOGL) non-marketable and private-company equity stakes — grew from **$106.946 Billion** to **$131.461 Billion** in a single quarter, and from just **$36.177 Billion** in September 2024. That portfolio has more than tripled in under two years, and the mark-to-market swings in its value now move Alphabet's reported earnings more than the operating business does.

**The GeminIQ Edge:** Standard financial media strips this kind of item out to publish an "[adjusted EPS](/metrics/per-share-metrics/adjusted-eps)" figure, but rarely shows you the line doing the stripping. Pulling [Financial Statements](/features#financial-statements) directly from the as-filed 10-Q shows the exact tagged value causing the divergence, sourced to the same XBRL tag every quarter, so the reader can verify the number instead of trusting someone else's adjustment.

<center><sup>GeminIQ Financial Statements showing Alphabet's Debt And Equity Securities Gain Loss growing from $1.451 Billion (Q2 FY2025) to $36.804 Billion (Q1 FY2026) to $98.999 Billion (Q2 FY2026), alongside Other Long Term Investments of $131.461 Billion.</sup></center>

## What the Core Business Actually Earned

None of this means the underlying advertising and cloud business is inventing numbers. It means the two lines on the income statement that matter for valuing a business — operating income and net income — just told two completely different stories in the same quarter.

**The Data:** [Alphabet's](/stocks/GOOGL) Operating Income was **$40.77 Billion**, up **2.7%** from **$39.696 Billion** the prior quarter and up **30.4%** from **$31.271 Billion** a year earlier — real, healthy growth, just nothing like the net income headline. Income Before Income Taxes was **$138.753 Billion**. Subtract the **$98.999 Billion** Debt And Equity Securities Gain Loss from that figure directly — a calculation GeminIQ derives from the two filed lines rather than displaying as a platform metric. Pretax income falls to **$39.754 Billion**, within a rounding error of the **$40.77 Billion** of operating income alone. Virtually the entire gap between operating income and the reported pretax figure this quarter came from one non-operating item.

The margin data confirms it. GeminIQ's pre-calculated [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) (TTM) jumped to **54.8%** from **37.9%** the prior quarter, a swing of nearly **17 percentage points** in a single quarter. Over the same stretch, [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) (TTM) moved from **32.7%** to **33.1%** — a **0.4 percentage point** shift. One margin exploded. The other barely moved.

**The GeminIQ Edge:** A screener that only surfaces net margin would show Alphabet's profitability doubling in a quarter. Pulling [Calculated Metrics](/features#calculated-metrics) for both margins side by side shows the operating business is compounding steadily, not doubling — the explosion lives entirely in the non-operating line above.

<center><sup>GeminIQ Calculated Metrics showing Alphabet's Net Profit Margin (TTM) jumping to 54.8% from 37.9% while Operating Profit Margin (TTM) held nearly flat at 33.1% versus 32.7%, Q1 to Q2 FY2026.</sup></center>

## Free Cash Flow Just Turned Negative

Net income is an accounting figure. Cash is not, and the cash story this quarter runs in the opposite direction of the headline.

**The Data:** Net Cash Provided By Operating Activities for the quarter was **$39.069 Billion**. Payments To Acquire Property Plant And Equipment was **$44.924 Billion**. Subtracting the two — a calculation GeminIQ derives from the filed cash flow lines rather than a displayed metric — puts quarterly free cash flow at **negative $5.855 Billion**. That's the first negative quarter visible in this filing history, against a positive **$10.116 Billion** the prior quarter. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) (TTM) is still positive at **$53.273 Billion**, but it's down from **$64.429 Billion** a quarter earlier as the trailing figure absorbs this one negative quarter. [Alphabet's](/stocks/GOOGL) Long Term Debt Noncurrent grew to **$98.165 Billion** from **$77.501 Billion**, a **26.7%** jump, and the balance sheet's Common Stocks Including Additional Paid In Capital line grew from **$96.902 Billion** to **$131.371 Billion**, an increase of **$34.469 Billion** in a single quarter — consistent with fresh capital being raised alongside the debt.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) cash flow data quarter by quarter shows the capex ramp has now outrun operating cash generation entirely, something the still-positive TTM Free Cash Flow figure alone would mask for another two quarters.

<center><sup>GeminIQ Financial Statements showing Alphabet's Net Cash Provided By Operating Activities of $39.069 Billion against Payments To Acquire Property Plant And Equipment of $44.924 Billion, a negative $5.855 Billion quarterly free cash flow.</sup></center>

## Why GeminIQ's ROIC Fell While Net Income Tripled

The debt and equity growth above didn't stop at the balance sheet — it flows straight into the one metric investors actually use to judge capital efficiency, and it explains a number a headline P/E ratio hides entirely. [Alphabet's](/stocks/GOOGL) trailing Price-to-Earnings Ratio (P/E) actually *fell* this quarter, from **21.70** to **17.78**, purely because trailing net income grew faster than the stock price did. A falling P/E usually reads as a stock getting cheaper. Here it's an artifact of the same non-cash gain inflating the denominator.

**The Data:** GeminIQ's pre-calculated [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) (TTM) fell to **22.6%** from **26.3%** the prior quarter — a **3.6 percentage point** decline in the same quarter net income more than doubled. The reason lives in the formula's two halves. GeminIQ's NOPAT (TTM), built from operating income rather than net income, grew a modest **5.9%**, from **$113.806 Billion** to **$120.465 Billion**. But GeminIQ's pre-calculated [Invested Capital](/metrics/calculated-values/invested-capital) jumped **31.3%**, from **$526.634 Billion** to **$691.651 Billion**, as Total Equity grew **$161.734 Billion** in a single quarter — largely the same paper gain flowing through net income into retained earnings, then into the capital base ROIC is measured against.

**The GeminIQ Edge:** Because ROIC's numerator is built from operating income and excludes the securities gain, while its denominator absorbs that same gain the moment it lands in equity, the metric captures a real compression in returns on capital that a net-income-based screen would completely miss. [Net Debt](/metrics/calculated-values/net-debt) also grew to **$42.254 Billion** from **$39.438 Billion**, a second, smaller drag on the same ratio.

<center><sup>GeminIQ Calculated Metrics showing Alphabet's Return on Invested Capital (ROIC) falling to 22.6% from 26.3% as Invested Capital grew 31.3% to $691.651 Billion, Q1 to Q2 FY2026.</sup></center>

## Smart Money and the Insider Record

What are the people actually running the company doing with their own money, and who is still holding the stock at the institutional level?

**The Data:** [Institutional Ownership](/features#institutional-ownership) stood at **58.77%** as of the most recent 13F (quarter ending March 31, 2026, filed with the standard lag), down modestly from **60.51%** the prior quarter — not a dramatic shift either direction. [Insider Transactions](/features#insider-transactions) show a heavily sale-weighted record across the available filing history: **838** sales against just **3** purchases. The most recent activity is small and routine — a handful of sub-$500,000 sales by the VP, Chief Accounting Officer and other filers, consistent with scheduled equity compensation vesting rather than any reaction to this quarter's results.

**The GeminIQ Edge:** Neither figure is dramatic in isolation, and neither one is the number that actually moved this quarter. The operating business grew at a real, single-digit-to-low-thirties clip across every core line. The $99 billion that made headlines came from somewhere else entirely, and only the raw filing data shows you where.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership easing to 58.77% from 60.51%, quarter over quarter into Q1 FY2026.</sup></center>

## Frequently Asked Questions

### What caused Alphabet's Q2 2026 net income to jump so sharply?

A single non-operating, non-cash line item the filing tags as Debt And Equity Securities Gain Loss, valued at $98.999 Billion this quarter, a mark-to-market gain tied to Alphabet's growing portfolio of non-marketable and equity securities. It is not related to advertising or cloud revenue.

### Is Alphabet's core operating business still growing?

Yes. Operating Income was $40.77 Billion, up 30.4% year-over-year, and revenue grew 24.2% year-over-year to $119.796 Billion. Both figures exclude the securities gain entirely.

### Why did GeminIQ's ROIC for Alphabet fall this quarter if net income tripled?

Because ROIC's numerator (NOPAT) is built from operating income, which grew only 5.9%, while its denominator (Invested Capital) absorbed the same securities gain once it flowed into retained earnings, growing Invested Capital 31.3% in a single quarter.

### When did Alphabet file its Q2 FY2026 10-Q, and what period does it cover?

Alphabet's most recent filing is a Form 10-Q filed July 23, 2026, covering the fiscal quarter ended June 30, 2026 (Q2 FY2026).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=alphabet-10q-analysis-q2-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Alphabet Inc.'s Q2 FY2026 10-Q (filed July 23, 2026, period ending June 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001652044/000165204426000071/goog-20260630.htm).

---

## Blog: AlphaSense Alternative for Filing Financial Data
source: https://www.geminiq.com/blog/alphasense-alternative-sec-data

### AlphaSense Alternative for Filing Financial Data
An AlphaSense alternative for structured filing data. AlphaSense searches 500 million documents and returns cited passages; this post explains why retrieving a sentence and computing across a time series are different problems.

AlphaSense built the best document search in finance, and the scale is the point. More than 500 million premium documents — SEC filings, broker and independent research, earnings transcripts, news, trade journals — plus an expert call transcript library that expanded substantially after the Tegus acquisition in 2024. Generative Search returns cited answers with sentence-level attribution, and Deep Research will run dozens of searches and cite well past a hundred sources before producing a synthesis. Pricing is quote-only and commonly lands in the five figures per seat.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=alphasense-alternative-sec-data)**

For the question "what is being said about this, across everything that has been written," nothing else comes close.

That framing contains the boundary. Search is a retrieval problem, and fundamental analysis is a computation problem. They look adjacent because both involve filings, and they require entirely different data structures.

## Table of Contents

- [Retrieval and Computation Are Different Problems](#retrieval-and-computation-are-different-problems)
- [The Unit of a Search Result Is a Passage](#the-unit-of-a-search-result-is-a-passage)
- [Questions Search Cannot Reach](#questions-search-cannot-reach)
- [The Add-On Proves the Gap](#the-add-on-proves-the-gap)
- [Structured Filing Data as the Other Half](#structured-filing-data-as-the-other-half)
- [Sequencing the Two](#sequencing-the-two)
- [Frequently Asked Questions](#frequently-asked-questions)

## Retrieval and Computation Are Different Problems

A search index is built to find text. It tokenizes documents, ranks passages by relevance to a query, and returns the ones most likely to answer it. Every engineering decision behind AlphaSense serves that goal, and the results are excellent.

A financial dataset is built to compute. It stores facts keyed by company, period, and concept, so that a value can be compared to the same company's prior periods and to other companies in the same period without anyone reading anything.

Those are not two implementations of the same thing. Text retrieval can surface a sentence containing a number. It cannot rank fifteen thousand filers by that number, because ranking requires the value to exist as a typed fact rather than as characters inside a paragraph.

That is why an AI layer, however capable, does not close the gap. Generative synthesis over retrieved passages produces a well-cited answer to a question about what was said. It does not turn an unstructured corpus into a queryable time series.

## The Unit of a Search Result Is a Passage

The consequence shows up immediately in what comes back.

Ask for a company's operating income and search returns passages mentioning operating income — from the filing, from a broker note discussing it, from a transcript where management characterized it, from a news article summarizing all three. Each is cited and each may be accurate. Reconciling them into one number for one period is work the reader does.

Ask for the same figure across forty quarters and the problem multiplies. Now there are forty periods, several document types per period, restatements that changed prior figures, and presentation changes that renamed captions. Retrieval returns more passages. It does not return a series.

This is not a shortcoming of AlphaSense's implementation — it is what a corpus is. Documents are the native format of qualitative research and the wrong format for quantitative analysis, and no amount of search quality converts one into the other.

The tell is the shape of the output. Search gives you evidence. Analysis needs measurements.

## Questions Search Cannot Reach

The boundary is easiest to see in the questions that never get asked of a search product, because users learn quickly that they do not work.

Which filers reduced share count in each of the last eight quarters. Which companies carry a specific leverage profile alongside a specific return profile. What the distribution of a margin looks like across an industry, and where a given company sits inside it. How a metric behaved in the four quarters before a known outcome, across every company that experienced it.

Every one of those is a computation over a structured universe. Each requires values keyed by company and period, sorted and filtered — the operations a database does and an index does not.

They are also, not coincidentally, where original work comes from. A conclusion assembled from what everyone has already written is a summary of consensus. A conclusion derived from computing across filed data is something nobody has published, which is the only kind worth the effort.

## The Add-On Proves the Gap

There is a strong piece of evidence for this argument, and it comes from AlphaSense's own product line.

Financial models are sold as a separate content add-on. If document search alone were sufficient for quantitative work, a structured modeling product would be redundant inside a platform that already indexes every filing. It exists because the corpus cannot produce what a model needs, and the company knows it.

The same logic explains why AlphaSense describes offering quantitative financial data alongside its search capability rather than as an output of it. Two distinct layers, sold together, because they solve two distinct problems.

Read that as confirmation rather than criticism. The people who built the best search in the industry did not try to make search do this job.

## Structured Filing Data as the Other Half

GeminIQ is the database side of that split, scoped narrowly. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value — which is what makes a figure a fact rather than a string.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years as a series rather than as documents to read. [Custom Tables](/features#custom-tables) assemble specific reported items across periods. [Visualizations](/features#visualizations) chart the reported structure over time. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield), and [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) are computed from as-filed inputs across the universe rather than derived from a passage. [Stock Screeners](/features#screener) run the filtering operations that retrieval cannot perform at all.

The corpus is small by comparison. US public company filings, and nothing else — no broker research, no expert transcripts, no news, no private company intelligence. What it offers instead is that every number in it can be sorted, filtered, and compared.

## Sequencing the Two

The workflows are complements and the order matters.

Search is where a question gets shaped. Reading what analysts, competitors, customers, and management have said about an industry is how you learn which variable matters, and expert transcripts in particular surface things no document discloses. That phase is qualitative and AlphaSense is built for exactly it.

Computation is where the question gets answered. Once you know which metric decides the thesis, the work becomes measuring it — across periods, across peers, against a base rate — and that requires structured data.

For the transcript half of the same corpus, the [Quartr alternatives](/blog/quartr-alternative-sec-filing-data) post covers what first-party IR material can and cannot settle.

Search tells you what the market believes. Only the filed data tells you whether the numbers agree, and the second half is where the answer stops depending on who wrote the loudest note.

## Frequently Asked Questions

### What are the best AlphaSense alternatives?

It depends on which capability you need. For AI-powered search across broker research, expert transcripts, news, and filings, the substitutes are other document intelligence platforms. For structured, computable financial data, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability — a database rather than an index.

### How much does AlphaSense cost?

AlphaSense does not publish pricing. Access is quote-only on annual subscriptions scaled to team size, content packages, and add-ons such as expert calls and financial models. Third-party reports commonly place full-featured seats in the five-figure annual range, with pricing opacity a frequent complaint in reviews.

### Can AlphaSense screen stocks on financial metrics?

Document search is built to retrieve relevant passages, not to rank a universe by a computed value. Screening requires values stored as typed facts keyed by company and period, which is a database operation rather than a retrieval one. AlphaSense sells structured financial data and models as separate content, which is the practical acknowledgment of that split.

### What did AlphaSense acquire Tegus for?

AlphaSense acquired Tegus in 2024, adding a large expert call transcript library and private company intelligence to a platform previously centered on filings, broker research, and news. The combination pairs primary expert research with secondary document search in one content set.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=alphasense-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- AlphaSense content library scale, product packages, Generative Search and Deep Research descriptions, add-on structure including expert calls and financial models, and the Tegus acquisition reviewed August 2, 2026 from AlphaSense's own site and help center plus third-party platform reviews.
- Seat pricing figures are third-party estimates; AlphaSense does not publish pricing.

---

## Blog: Altman Z-Score: Formula, Zones, and Limitations Explained
source: https://www.geminiq.com/blog/altman-z-score-financial-distress

### Altman Z-Score: Formula, Zones, and Limitations Explained
The Altman Z-Score predicts corporate bankruptcy risk using five financial ratios combined into a single weighted score. Here is how the formula works, what the three zones mean, and where the model breaks down.

The Altman Z-Score is one of the most widely cited quantitative tools in financial analysis — and one of the most widely misunderstood. Most financial platforms display a Z-Score. Most do not tell you which inputs they used to compute it. That gap matters more than the number itself. The same company can show a **3.4** on one platform and a **2.1** on another for the identical filing period, the difference driven entirely by how each platform sourced its working capital, EBIT, and market capitalization figures. Edward Altman developed the Z-Score at New York University in 1968 to predict corporate bankruptcy, producing a model with documented **72%** accuracy two years ahead of filing. It does one thing: estimates the probability that a company will enter financial distress within the next two years. It does not measure quality, competitive position, or growth trajectory. Used correctly, the Z-Score is among the most reliable first-pass risk filters in fundamental analysis. Used carelessly — run on normalized data and misread as an investment signal — it provides false precision about a company's financial health.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=altman-z-score-financial-distress)**

## Table of Contents

- [What Is the Altman Z-Score?](#what-is-the-altman-z-score)
- [The Altman Z-Score Formula](#the-altman-z-score-formula)
- [The Five Components Explained](#the-five-components-explained)
- [The Three Zones: Safe, Grey, and Distress](#the-three-zones-safe-grey-and-distress)
- [Where the Altman Z-Score Breaks Down](#where-the-altman-z-score-breaks-down)
- [Why Two Platforms Show Different Z-Scores](#why-two-platforms-show-different-z-scores)
- [How to Use the Altman Z-Score in Practice](#how-to-use-the-altman-z-score-in-practice)
- [Altman Z-Score vs. Piotroski F-Score](#altman-z-score-vs-piotroski-f-score)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is the Altman Z-Score?

In 1968, Edward Altman published "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy" — a paper that became one of the most referenced works in quantitative finance. The study applied discriminant analysis to 66 manufacturing companies, half of which had filed for bankruptcy, to identify which financial ratios could most reliably predict financial distress before it became visible to the market. Altman identified five ratios spanning liquidity, cumulative profitability, operating efficiency, market confidence, and asset productivity. Combined into a single weighted score, they produced a model that correctly classified bankrupt companies with **72%** accuracy two years before their filing.

What makes the Z-Score durable is also what limits it: it is a structured, systematic assessment of whether a company's financial profile resembles those of companies that went bankrupt. It does not incorporate management quality, competitive dynamics, market conditions, or any qualitative factor. It reads the numbers and outputs a distress probability signal. For equity investors, that makes the Z-Score most valuable as a negative screener — a mechanism for eliminating companies with measurable bankruptcy risk before spending further analytical time on their valuation or business quality. A company in the distress zone is not necessarily uninvestable, but it carries an existential risk dimension that changes the return profile in a specific way. Bankruptcy produces total loss. A **40%** drawdown does not.

## The Altman Z-Score Formula

The full formula is:

**Z = 1.2(A) + 1.4(B) + 3.3(C) + 0.6(D) + 1.0(E)**

Where each variable represents a specific financial ratio drawn from the balance sheet and income statement:

**A = Working Capital ÷ Total Assets**
**B = Retained Earnings ÷ Total Assets**
**C = EBIT ÷ Total Assets**
**D = Market Value of Equity ÷ Total Liabilities**
**E = Revenue ÷ Total Assets**

The weights are not arbitrary. Altman derived them through statistical analysis of which ratios were most discriminating between the bankrupt and non-bankrupt cohorts in his original sample. Component C (EBIT/Total Assets) carries the highest weight at **3.3** because operating profitability relative to assets proved to be the single most predictive signal of impending bankruptcy. A company that cannot generate operating earnings from its asset base is consuming rather than producing value, and that structural problem compounds faster than any balance sheet adjustment can offset.

GeminIQ calculates the [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) and all five individual component inputs directly from XBRL-tagged SEC filing data. Each component — labeled `Altman A` through `Altman E` on the platform — is available as a separately viewable and filterable field, which means you can see not just the composite score but exactly which dimension of the business is driving it.

<center><sup>GeminIQ Calculated Metrics view showing the Altman Z-Score composite and its five individual component inputs — `Altman A` (Working Capital / Total Assets), `Altman B` (Retained Earnings / Total Assets), `Altman C` (EBIT / Total Assets), `Altman D` (Market Cap / Total Liabilities), and `Altman E` (Revenue / Total Assets) — sourced directly from XBRL-tagged SEC filing data.</sup></center>

## The Five Components Explained

### Component A: Working Capital ÷ Total Assets (Liquidity)

[Working Capital](/metrics/liquidity-ratios/working-capital) is current assets minus current liabilities. Dividing by total assets normalizes the liquidity position to the scale of the business. A company with strong working capital relative to its asset base has a cushion to meet near-term obligations without liquidating long-term assets. A negative or rapidly shrinking Component A is an early warning: the company may be able to service long-term debt but is already struggling to fund day-to-day operations.

The weight of **1.2** reflects that liquidity is necessary but not singularly predictive. A business can run negative working capital and survive for years if it generates strong operating cash flow — retailers and subscription businesses routinely do. Component A reads the balance sheet snapshot; the rest of the formula contextualizes what that snapshot means.

### Component B: Retained Earnings ÷ Total Assets (Accumulated Profitability)

Retained earnings represent the cumulative profit a company has kept inside the business across its entire operating history. Dividing by total assets produces a ratio that captures how much of the company's asset base has been self-funded through earnings rather than debt or equity issuances. A high Component B score means the business has a long track record of profitable operations. A low or negative B score means the company has either sustained historical losses, paid out most of its earnings, or is simply young.

This component receives a weight of **1.4** and embeds a structural bias against younger companies. A recently public business — even one that is currently profitable — will carry minimal retained earnings relative to assets because it has not had time to accumulate them. Altman was explicit that the model was designed for established public manufacturing companies. Component B is the place where the model most clearly shows its age when applied to modern businesses.

### Component C: EBIT ÷ Total Assets (Operating Efficiency)

EBIT divided by total assets measures how productively the company converts its asset base into operating earnings. The weight of **3.3** reflects Altman's finding that this was the most discriminating ratio between bankrupt and non-bankrupt companies in his sample. A business that structurally cannot earn operating income from the assets it deploys is on a path toward distress regardless of how its balance sheet is temporarily arranged.

For investors familiar with [Return on Assets](/metrics/returns-and-profitability/return-on-assets), Component C is a close conceptual relative — both measure how much operating return a company generates per dollar of assets. The practical difference is that EBIT excludes taxes, making it comparable across tax regimes, and Component C feeds into the formula at the heaviest weight because Altman's data identified it as the single most discriminating signal of all five.

### Component D: Market Value of Equity ÷ Total Liabilities (Market Confidence)

This is the Z-Score's market-facing input. It measures how much investor confidence exists in the company's equity value relative to what it owes — a high ratio signals that the market believes the business can service and ultimately retire its obligations. As the ratio falls toward 1.0 or below, the market is expressing doubt about whether the equity buffer is sufficient against the liability stack.

Component D receives a weight of **0.6** — the lowest in the formula — partly because market prices introduce short-term noise and partly because this ratio was less consistently predictive in Altman's original research than the pure accounting ratios. It is also the input most vulnerable to cross-platform differences: the same company will show materially different Component D values depending on whether the platform uses market cap at the filing period end date, at some arbitrary subsequent date, or averaged across a period.

### Component E: Revenue ÷ Total Assets (Asset Productivity)

The final component measures how efficiently the company generates revenue from its asset base — essentially a version of [Asset Turnover](/metrics/efficiency-and-turnover-ratios/asset-turnover). High revenue relative to assets indicates a productive balance sheet. Low asset turnover may reflect overcapitalization, operational drag, or a business model that requires significant capital to operate. The weight is **1.0**.

Component E can mislead in both directions for businesses that differ structurally from 1960s manufacturers. A capital-light software company may show very high Revenue/Total Assets — not because of operational excellence, but simply because it carries minimal physical assets on its balance sheet. A capital-intensive utility may show low Component E even with completely stable, predictable revenue. Neither reading reflects financial distress. Both reflect a structural mismatch with the formula's original context.

## The Three Zones: Safe, Grey, and Distress

The Z-Score produces a continuous number, but Altman identified three interpretive zones from the distribution of scores in his bankrupt and non-bankrupt cohorts.

A score above **3.0** places a company in the safe zone. Historically, companies at this level showed a very low probability of bankruptcy within two years. The safe zone is not a quality signal. It does not mean the business is a good investment, that it is growing, or that its stock is cheap. It means the composite of its liquidity, profitability, leverage, and efficiency does not resemble the companies in Altman's bankrupt cohort.

A score between **1.8 and 3.0** is the grey zone — statistically uncertain territory where the Z-Score alone cannot reliably classify a company as healthy or distressed. Further investigation is required. A score of **2.8** trending downward over consecutive quarters is a very different situation from a **1.9** that has been stable or improving. The grey zone is where trend analysis becomes as important as the level.

A score below **1.8** is the distress zone, where the empirical frequency of bankruptcy within two years is meaningfully elevated. This does not guarantee bankruptcy — companies in the distress zone can and do recover, restructure, or access capital. But the historical probability is high enough that equity investors should treat a sub-**1.8** score as a flag requiring explicit explanation before committing capital.

The practical severity becomes concrete when applied to real companies. In GeminIQ's [airline sector analysis](/blog/airline-sector-stock-analysis), [American Airlines](/stocks/AAL) posted an Altman Z-Score of **0.60** — more than a full point below the distress threshold of **1.8** and deep into territory where the empirical probability of financial distress is elevated — while [Delta Air Lines](/stocks/DAL) showed **1.34** and [United Airlines](/stocks/UAL) showed **1.29**, both also in the distress zone — below the **1.8** threshold, if not as deeply as American — despite broadly similar capital structures. The divergence traced primarily to negative retained earnings — accumulated historical losses that drove Component B deep into negative territory. Same industry. Similar asset footprints. A Z-Score of **0.60** versus **1.34** and **1.29**, explained almost entirely by one component's accumulated history.

## Where the Altman Z-Score Breaks Down

The Z-Score's limitations are structural. Altman himself acknowledged that the model was calibrated on a specific dataset — **66 publicly traded manufacturing companies** in the 1960s — and that its predictive accuracy degrades outside that context.

Financial institutions are explicitly excluded from the model's scope. Banks, insurance companies, and investment firms have capital structures that make the five ratio inputs either meaningless or inverted. A bank's liabilities include customer deposits, not just creditor obligations. Its assets are primarily financial instruments rather than productive business assets. Running the Z-Score on a financial institution produces a number that carries no valid interpretive meaning.

Capital-light technology companies present a different problem. A profitable software business with strong recurring revenue may carry minimal retained earnings because it is young, minimal total assets because its intellectual property is not capitalized at cost, and high revenue relative to assets. The composite score can look distressed even when the business generates strong free cash flow. The model reads a company with thin asset coverage and a short earnings history and flags distress. The reality is that its capital-light structure simply does not conform to the 1960s manufacturing template.

Utilities and infrastructure businesses encounter the opposite distortion. Heavy asset bases suppress Components C and E, while stable regulated revenues produce consistent but modest operating margins. Many utilities maintain grey-zone Z-Scores through periods that bear no resemblance to financial distress, their scores driven by a business model rather than by any balance sheet deterioration.

Early-stage and recently public companies run into the retained earnings problem directly: any company that invested at a loss during its growth phase — even one that has been profitable for years — enters every Z-Score calculation with Component B handicapped by accumulated historical losses. That is a record of past investment, not present failure, but the formula makes no distinction.

## Why Two Platforms Show Different Z-Scores

The Z-Score is more input-sensitive than most composite metrics. All five components feed into a single weighted sum, so a discrepancy in any one of them shifts the final number — sometimes enough to move a company across a zone boundary.

The most common sources of divergence are working capital treatment, EBIT definition, and market cap timing. Under ASC 842, adopted by most public companies between 2019 and 2021, operating lease obligations appear as current liabilities on the balance sheet. A company with significant lease commitments — a retailer, restaurant chain, or airline — shows higher current liabilities and therefore lower working capital on an as-filed basis than it would have under the prior standard. A platform applying a pre-ASC 842 normalized balance sheet template inflates working capital for these companies, producing a more favorable Component A — and a higher composite Z-Score — than the raw filing supports.

EBIT is also not standardized across platforms. Some use operating income as a direct proxy for Component C, which is usually correct but diverges when there are non-operating items classified above the operating income line. Others apply normalization adjustments for restructuring charges or acquired intangible amortization, changing the EBIT figure without changing the underlying filing data. The as-filed `OperatingIncomeLoss` XBRL tag from the income statement is the most consistent input for Component C, but not every platform uses it without modification.

Component D's market cap input is the most timing-sensitive of the five. A company that reports on a March 31 period end but whose market cap is pulled at any subsequent date will show a Component D that does not correspond to the balance sheet being analyzed. GeminIQ computes market capitalization for Component D as the closing price on the filing period end date multiplied by basic shares outstanding from that same period — keeping the market confidence ratio internally consistent with the balance sheet inputs it is being compared against.

Standard screeners display a Z-Score and rarely disclose which of these choices were made in computing it. GeminIQ's [Calculated Metrics](/features#calculated-metrics) exposes each input separately — `Altman A` through `Altman E` — so the specific component driving an anomalous composite is immediately visible rather than buried in an opaque final number. For a deeper look at how data sourcing choices affect calculated financial metrics more broadly, the [financial data verification guide](/blog/verify-financial-data-against-sec-filing) covers the mechanics in detail. A platform that shows a single Z-Score without exposing its five inputs is not showing you the Altman Z-Score. It is showing you its own version of it.

## How to Use the Altman Z-Score in Practice

The most reliable application of the Altman Z-Score is as a negative filter. It eliminates companies with elevated bankruptcy risk before investing analytical energy in their valuation, competitive position, or management quality. A value screen run without a distress filter will consistently surface companies trading at low multiples for exactly one reason: the market has priced in the possibility of permanent impairment. Filtering out sub-**1.8** scores before examining those names removes the most dangerous category of value trap in a systematic way, without requiring any judgment about individual companies.

GeminIQ's [Altman Z-Score Safe screener](/screens/stock-screeners/altman-z-score-safe) applies a single filter — [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) ≥ **3.0** — to restrict results to the safe zone. The screener can be combined with additional overlays: [Return on Assets](/metrics/returns-and-profitability/return-on-assets) to add a profitability gate, [Debt Ratio](/metrics/leverage-and-debt-ratios/debt-ratio) for a leverage check, or [Current Ratio](/metrics/liquidity-ratios/current-ratio) for a liquidity confirmation. Because GeminIQ exposes `Altman A` through `Altman E` as separate filterable fields, it is also possible to filter on individual components — for example, targeting companies with strong Component C (EBIT/Total Assets) even if their composite score falls in the grey zone, which may identify operationally sound businesses temporarily penalized by low retained earnings or market confidence.

The trend of the Z-Score across quarters is often as informative as its level at any single point. A company sitting at **2.6** is in the grey zone regardless of direction. A company that was at **3.2** twelve months ago and has declined to **2.6** is on a trajectory the static number alone does not capture.

<center><sup>GeminIQ Stock Screener showing the Altman Z-Score Safe screen — Altman Z-Score ≥ 3.0 applied — surfacing companies in the safe zone. All five individual component inputs (`Altman A` through `Altman E`) are available as separate filterable fields. All data sourced from XBRL-tagged SEC 10-K and 10-Q filings.</sup></center>

GeminIQ's historical view makes period-over-period comparisons direct — the full filing history visible in a single view. A distress reading on accurate, as-filed data is a signal. The same reading on normalized inputs is noise with a number attached.

## Altman Z-Score vs. Piotroski F-Score

The Altman Z-Score and the Piotroski F-Score are complementary tools that answer fundamentally different questions. Treating them as alternatives misses the specific value each provides.

The Z-Score asks: does this company's financial profile resemble those of companies that went bankrupt? It is a static snapshot measured against an external historical benchmark. A score of **1.4** means the company's ratios, at this moment, place it in territory where bankruptcy probabilities have historically been elevated.

The Piotroski F-Score asks: is this company's financial situation improving or deteriorating? It scores nine binary signals across profitability, financial strength, and efficiency — each reflecting whether that dimension has improved or declined year-over-year. The output is a directional reading, not a distress probability.

A company can carry a safe Z-Score above **3.0** and a low F-Score of **0–2**, which means it is not currently at near-term distress risk but its fundamentals are trending in the wrong direction. A company can also carry a grey-zone Z-Score with a high F-Score of **8–9**, signaling uncertain distress probability but consistent fundamental improvement. The [Piotroski F-Score analysis](/blog/piotroski-f-score-value-trap) covers these dynamics in depth. Used together, the Z-Score screens out existential risk and the F-Score screens out slow fundamental deterioration — the two most common failure modes in value investing, addressed simultaneously.

They also complement each other on a data dimension. The Z-Score embeds a historical accumulation signal through Component B (retained earnings) that the F-Score does not measure. The F-Score captures near-term trend reversals through its year-over-year comparisons that a static Z-Score snapshot will miss. Together, they address the two most reliable ways a cheap stock destroys capital — by going bankrupt, or by continuing to deteriorate until the valuation is no longer a bargain.

## Frequently Asked Questions

### What is a good Altman Z-Score?

Above **3.0** is the safe zone — the company's financial profile does not resemble Altman's bankrupt cohort. Between **1.8 and 3.0** is the grey zone, where the outcome is statistically uncertain and further investigation is required. Below **1.8** is the distress zone, where the empirical frequency of bankruptcy within two years is meaningfully elevated. These thresholds come directly from Altman's original research and have been validated across subsequent studies, though they are probability thresholds derived from a historical sample, not hard physical limits. A score just above **3.0** is not categorically safer than a score of **2.98**.

### Does the Altman Z-Score work for technology companies?

With significant reservations. The model was built on manufacturing companies with substantial physical assets, long operating histories, and straightforward capital structures. Capital-light software businesses often show suppressed Component B scores because they are young or invested at a loss during early growth, and their Revenue/Total Assets ratios differ structurally from manufacturers. A low Z-Score on a profitable, cash-generating software company is frequently a model mismatch rather than a genuine distress signal. The Z-Score is most reliable for established, asset-heavy companies in traditional industries — manufacturing, retail, transportation, energy. For technology companies, it functions best as one signal among several rather than a standalone risk filter.

### How often should I update the Z-Score?

Quarterly, aligned with 10-Q filing cadence. Each new filing updates the balance sheet and income statement inputs that drive all five components. A company scoring **2.3** in Q1 may score **2.8** or **1.9** by Q3 depending on how its working capital, retained earnings, and EBIT have moved. The trend of the score across consecutive quarters is often as informative as its level at any point. GeminIQ updates the [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) and all five component inputs with each new filing automatically.

### Why does my platform show a different Z-Score than GeminIQ?

The composite score depends entirely on five inputs, and any difference in how those inputs are sourced, normalized, or timed propagates into the final number. The three most common sources of divergence are working capital treatment under ASC 842 (operating lease current liabilities affect Component A), EBIT definition (adjusted vs. as-filed operating income affects Component C), and market cap timing (which date is used for the share price in Component D). GeminIQ sources all inputs from XBRL-tagged SEC filings, uses period-end market cap for Component D, and preserves the as-filed balance sheet structure rather than applying normalized templates. Because the five individual component values are visible separately on the platform, when a composite score looks anomalous, the specific input driving the discrepancy can be identified and traced directly to the filing.

### Can a distress-zone company still be a good investment?

Financially distressed companies do sometimes offer recovery opportunities — but the Z-Score distress zone is specifically territory where bankruptcy risk is not negligible. The asymmetry matters: a correct recovery thesis produces strong returns; an incorrect one produces permanent capital loss, because common equity holders are last in the liquidation priority queue. A value investor buying into a distress-zone company is making a specific claim about recovery probability that must be priced explicitly into the analysis — the cheap valuation alone is not a margin of safety against an existential outcome. Using the [Altman Z-Score Safe screener](/screens/stock-screeners/altman-z-score-safe) as a first-pass filter removes this risk category entirely for investors who choose not to take it on.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=altman-z-score-financial-distress)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Amazon Q1 2026 10-Q: Free Cash Flow Just Went Negative
source: https://www.geminiq.com/blog/amazon-10q-analysis-q1-2026

### Amazon Q1 2026 10-Q: Free Cash Flow Just Went Negative
Amazon's Q1 FY2026 10-Q shows trailing twelve-month free cash flow turned negative for the first time in years — not because the business weakened, but because CapEx has tripled in two years funding the AI infrastructure buildout.

**[Amazon](/stocks/AMZN) ($AMZN) just dropped its Q1 FY2026 10-Q (filed April 30, 2026). Most coverage is still fixated on whether AWS growth justifies the multiple. The raw cash flow statement shows something more dramatic happening beneath that debate: trailing twelve-month free cash flow just went negative, for a company famous for generating enormous cash. It isn't a warning sign. It's the clearest evidence yet of how much Amazon is spending to build AI infrastructure.**

| Field                | Value              |
| -------------------- | ------------------ |
| Ticker               | $AMZN              |
| Filing               | Q1 FY2026 10-Q     |
| Filed                | April 30, 2026     |
| Period End           | March 31, 2026     |
| Free Cash Flow (TTM) | **-$2.47 Billion** |
| CapEx (TTM)          | **$151.0 Billion** |

## The CapEx Supercycle

Free cash flow going negative sounds like distress. For [Amazon](/stocks/AMZN) right now, it's the opposite — it's the cost of building capacity fast enough to meet AI and cloud demand.

**The Data:** [Amazon's](/stocks/AMZN) TTM Operating Cash Flow is a robust **$148.5 Billion**. Against that, TTM CapEx (Purchases of Property and Equipment) hit **$151.0 Billion** — enough to flip Free Cash Flow to **-$2.47 Billion**. Quarterly CapEx has nearly tripled in two years, from **$14.9 Billion** in Q1 2024 to **$44.2 Billion** this quarter.

**The GeminIQ Edge:** A headline "operating cash flow" figure from a standard aggregator would still show a healthy $148.5 Billion and stop there. Pulling the raw [Financial Statements](/features#financial-statements) and netting CapEx against it shows the actual free cash flow story — and confirms the number wasn't manufactured by a one-time write-off or a working-capital swing. It's a straight, multi-quarter capital spending ramp.

<center><sup>GeminIQ Financial Statements showing Amazon's quarterly Net Cash Provided By Used In Operating Activities summing to $148.5 Billion TTM, against Free Cash Flow TTM of -$2.47 Billion — the gap between the two is the capital expenditure line.</sup></center>

## The Stock-Based Compensation Reality

The dilution story here isn't new, but it still holds up under a fresh look.

**The Data:** [Amazon's](/stocks/AMZN) TTM Stock-Based Compensation is **$19.81 Billion**, roughly **13%** of TTM Operating Cash Flow. Basic shares outstanding have grown to **10.74 Billion**, continuing a steady climb.

**The GeminIQ Edge:** GeminIQ's [Financial Statements](/features#financial-statements) isolates the SBC line directly from the Cash Flow Statement rather than blending it into a single "adjusted" earnings figure, so the actual scale of equity-funded compensation stays visible rather than buried in a non-GAAP add-back.

<center><sup>GeminIQ Financial Statements showing Amazon's TTM Stock-Based Compensation of $19.81 Billion against Operating Cash Flow of $148.5 Billion, alongside basic shares outstanding of 10.74 Billion.</sup></center>

## Verifying the Moat Underneath the Spending

None of the capex or SBC story matters if [Amazon's](/stocks/AMZN) core business is deteriorating to fund it. It isn't.

**The Data:** GeminIQ's pre-calculated [Gross Margin](/metrics/margin-metrics/gross-profit-margin) (TTM) sits at **50.6%**, up from **47.6%** two years ago. Operating Margin (TTM) is **11.5%**, and [ROIC](/blog/roic-return-on-invested-capital-explained) (TTM) is **17.5%**.

**The GeminIQ Edge:** Margin expansion during the heaviest capex ramp in the company's history is the detail a pure cash flow headline misses. Pulling [Calculated Metrics](/features#calculated-metrics) alongside the raw cash flow data shows the spending is layered on top of a business getting more profitable, not one straining to stay afloat.

<center><sup>GeminIQ Calculated Metrics showing Amazon's Gross Profit Margin TTM expanding from 48.85% to 50.60% across the six quarters shown, alongside Operating Profit Margin TTM of 11.50% and ROIC TTM of 17.48%.</sup></center>

## Insiders Selling, Institutions Steady

Two different signals around [Amazon](/stocks/AMZN) worth separating rather than blending into one "smart money" narrative.

**The Data:** GeminIQ's [Insider Transactions](/features#insider-transactions) feed shows executive sales dominate the record — CEO Andy Jassy and other senior executives have filed dozens of open-market sales in recent months, consistent with scheduled diversification of large SBC-funded equity stakes rather than a new signal. [Institutional Ownership](/features#institutional-ownership), by contrast, has stayed in a **57.8%-62.1%** band over the past year, currently **59.8%** — stable, not a story either direction.

**The GeminIQ Edge:** Treating routine executive share sales as a bearish "smart money" signal overstates what's actually a predictable pattern for any large company compensating employees heavily in stock. Selling shares to diversify a large equity stake isn't a smart-money tell. It's just what happens when a company pays people well in stock.

<center><sup>GeminIQ Insider Transactions tracker showing routine executive sales dominating Amazon's insider record.</sup></center>

<center><sup>GeminIQ Institutional Ownership showing Amazon's institutional ownership since 2014, holding a stable 57.8%-62.1% band over the trailing year and currently at 59.8%. Figures come from quarterly 13F filings.</sup></center>

## Frequently Asked Questions

### What does GeminIQ's data show about Amazon's free cash flow?

Amazon's TTM Operating Cash Flow of $148.5 Billion is now smaller than its TTM CapEx of $151.0 Billion, producing negative Free Cash Flow of roughly -$2.47 Billion. Quarterly CapEx has nearly tripled over the past two years, from $14.9 Billion to $44.2 Billion.

### Is Amazon's negative free cash flow a warning sign?

Based on the filing data, it doesn't appear to be. Gross margin and operating margin have both expanded over the same period the capex ramp occurred, and the negative figure traces entirely to a documented, multi-quarter capital spending increase rather than a one-time charge or declining core profitability.

### When did Amazon last file its 10-Q, and what period does it cover?

Amazon's most recent filing is a Form 10-Q filed April 30, 2026, covering the fiscal quarter ended March 31, 2026 (Q1 FY2026).

### Where can I verify Amazon's CapEx figures against the original filing?

The figures are drawn directly from Amazon's Q1 FY2026 10-Q cash flow statement, filed with the SEC on April 30, 2026. The full filing is publicly available on SEC EDGAR (linked in the citation block below).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=amazon-10q-analysis-q1-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Amazon.com, Inc.'s Q1 FY2026 10-Q (filed April 30, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1018724/000101872426000014/amzn-20260331.htm).

---

## Blog: Amended SEC Filings: What a 10-K/A Actually Means
source: https://www.geminiq.com/blog/amended-sec-filings-10-k-a-explained

### Amended SEC Filings: What a 10-K/A Actually Means
An amended SEC filing — most often a 10-K/A or 10-Q/A — corrects or supplements information a company already reported to the SEC, and unlike the original filing it carries no fixed deadline at all. This guide covers what triggers each type of amendment, how to read the Explanatory Note that tells you which kind you're looking at, and how to check any company's amendment history directly on EDGAR.

A company files a 10-K/A, and almost nothing happens. No press release lands in most investors' inboxes. No financial media segment breaks it down. The filing on EDGAR looks almost identical to the original, one character longer, and most retail research platforms either bury it in a generic filing-history list or drop it from the feed entirely. But the "/A" suffix is not a formality. It means the company is telling the SEC — and by extension every investor reading the record — that something in a document it already certified as accurate needs to be corrected, restated, or supplemented. Sometimes that something is a missing exhibit. Sometimes it is the entire set of financial statements the company reported for the year.

An amended SEC filing is any resubmission of a previously filed form, marked with an "/A" and a sequential amendment number, that corrects, restates, or adds to what the company already told the SEC. The two an investor is most likely to encounter are the 10-K/A, which amends the annual report, and the 10-Q/A, which amends a quarterly report. The first thing to understand about both is that neither one carries a filing deadline. An original 10-K is due on a fixed, tiered schedule tied to filer status; its amendment is due whenever the company gets it ready, which is why a name can go quiet for months after promising a correction. Reading an amendment correctly means separating routine housekeeping from something that touches the numbers — and most investors never learn the difference, because standard financial media treats every "/A" filing the same way it treats a typo correction: as nothing worth a headline. This guide covers what triggers a 10-K/A or 10-Q/A, how to read the explanatory note that tells you which kind you are looking at, and how to check any company's amendment history directly on EDGAR before it shows up anywhere else.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=amended-sec-filings-10-k-a-explained)**

## Table of Contents

- [What Is a 10-K/A?](#what-is-a-10-k-a)
- [What Is a 10-Q/A?](#what-is-a-10-q-a)
- [Why Companies File Amended Filings](#why-companies-file-amended-filings)
- [How to Read the Explanatory Note on an Amendment](#how-to-read-the-explanatory-note-on-an-amendment)
- [Step 1: Open the Company's EDGAR Filing History](#step-1-open-the-companys-edgar-filing-history)
- [Step 2: Filter for 10-K/A and 10-Q/A Filings](#step-2-filter-for-10-k-a-and-10-q-a-filings)
- [Step 3: Read the Explanatory Note First](#step-3-read-the-explanatory-note-first)
- [Step 4: Cross-Check the Company's 8-K History](#step-4-cross-check-the-companys-8-k-history)
- [What Amendments Mean for the Data You're Actually Using](#what-amendments-mean-for-the-data-youre-actually-using)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is a 10-K/A?

A **10-K/A** is an amendment to a company's previously filed annual report. It is not a new 10-K — it is a correction, restatement, or supplement layered on top of a document the company already certified and filed with the SEC. Every 10-K/A carries a sequential amendment number on its cover page — Amendment No. 1, Amendment No. 2, and so on — because a single annual report can be amended more than once if new issues surface after the first correction goes out.

Unlike the original 10-K, which follows the tiered [60-, 75-, or 90-day filing deadline](/blog/sec-filing-deadlines-by-filer-status) tied to a company's filer status, a 10-K/A carries no fixed regulatory deadline at all. The SEC does not require an amendment within a set number of days of discovering an error. What creates the practical clock is exchange listing compliance. A company that becomes a delinquent filer under Nasdaq Listing Rule 5250(c)(1) or the equivalent NYSE rule typically gets an initial 60-day window to submit a compliance plan, with a total grace period capped at **180 calendar days** before the exchange begins delisting proceedings. NYSE will not keep a stock listed past **12 months** of continued delinquency, regardless of the compliance plan filed. A company under SEC investigation for a restatement can spend far longer than that gathering facts before the amendment is ready. That is why a name goes quiet for months after announcing a restatement — the exchange clock, not an SEC deadline, is what eventually forces the filing.

A 10-K/A can amend the entire original document or a single part of it. The SEC's own instructions to Form 10-K allow a company to incorporate Part III information — executive compensation, related-party transactions, and beneficial ownership — by reference to its upcoming [proxy statement](/blog/what-is-def-14a), provided that proxy is filed within 120 days of fiscal year-end. When the proxy runs late, the company must instead file a 10-K/A adding Part III directly. That version touches nothing in the financial statements. It exists purely to satisfy a disclosure requirement the original 10-K deferred. Reading only the cover page's Explanatory Note tells you immediately whether you are looking at that kind of housekeeping amendment or something that touches the actual numbers.

---

## What Is a 10-Q/A?

A **10-Q/A** works the same way for the quarterly report: an amendment to a previously filed 10-Q, numbered sequentially, correcting or restating what the company reported for that quarter. The financial statements inside the original 10-Q were only [reviewed, not audited](/blog/which-sec-filings-are-audited) — a lighter process than the annual audit — which means an error has a real chance of surviving three months of investor scrutiny before anyone catches it. Some 10-Q/A filings correct that kind of error directly: a misclassified balance sheet line, a mis-tagged XBRL fact, a cash flow statement that doesn't reconcile. Others exist because a problem uncovered while preparing the next annual audit forces the company to look backward and restate one or more of the quarters that led into it. That is why 10-Q/A filings often arrive in clusters — several quarters restated together — rather than as an isolated correction to a single period.

The same absence of a fixed deadline applies here — the exchange-compliance pressure that governs the 10-K/A applies just as directly to a delinquent 10-Q/A.

---

## Why Companies File Amended Filings

Every amendment falls into one of a small number of categories, and the category is usually stated in the first paragraph of the filing's Explanatory Note.

### Missing or Corrected Exhibits

The least consequential reason a company files a 10-K/A or 10-Q/A is to attach an exhibit that was accidentally omitted from the original submission — a material contract, a subsidiary list, a consent letter from the auditor. These amendments touch nothing in the financial statements and rarely draw attention because none is warranted. The Explanatory Note on the cover page will typically say exactly that: it amends the filing "solely to" add or correct a named exhibit.

### Deferred Part III Disclosure

As covered above, a company that misses the 120-day window for its annual proxy must file a 10-K/A to add the governance and compensation disclosures the original 10-K deferred. This is routine and predictable — it happens every year to companies with later annual meeting dates — and, again, touches nothing in Part II's financial statements.

### When an Amendment Carries Restated Numbers

The consequential category is a genuine restatement: the company has concluded that previously issued financial statements can no longer be relied upon and must be corrected. This is the scenario tied to Item 4.02 of [Form 8-K](/blog/what-is-8-k) — the event itself, including how to spot one, is covered in [how to find restatements in filings](/blog/how-to-find-restatements-in-filings) — where the company first announces the non-reliance determination in a current report, then follows with the restated numbers themselves in a 10-K/A or 10-Q/A. The 8-K is the announcement. The amendment is where the corrected financial statements actually live, inside a new footnote — typically titled something close to "Restatement of Previously Issued Financial Statements" — that walks through exactly which line items changed and by how much.

Restatements are not always the result of fraud or a control failure serious enough to make headlines. The clearest example in recent history was almost entirely mechanical: on April 12, 2021, the SEC's Division of Corporation Finance issued a staff statement on how special purpose acquisition companies were required to classify the warrants they issued to investors. The guidance concluded that a common warrant structure, previously booked as equity, should instead be classified as a liability remeasured every period. According to Audit Analytics, more than **340 SPACs** restated their financial statements in the following months because of that single piece of guidance. The wave was large enough that at least one target, [Virgin Galactic Holdings](/stocks/SPCE), drew a securities class action alleging deficient internal controls tied to its warrant restatement. None of it involved a bad actor. It was an accounting classification the SEC decided the market had been getting wrong at scale, and hundreds of 10-K/A and 10-Q/A filings followed as the correction worked its way through the SPAC universe.

---

## How to Read the Explanatory Note on an Amendment

Every 10-K/A and 10-Q/A opens with an Explanatory Note before the amended content begins, and that note is the single highest-value paragraph in the filing. It states, in the company's own words, exactly what is being amended and why — and the specific verb the company chooses is the tell.

"Restate" is the word that matters most: a filing that says it is restating previously issued financial statements is telling you the original numbers contained a material error and can no longer be relied upon, while "revise" or "reclassify" typically signal a smaller presentation change that did not rise to the level of a formal restatement. The accounting line between those two outcomes is covered in [how to find restatements in filings](/blog/how-to-find-restatements-in-filings) — for reading the amendment itself, the verb is the fastest signal available before a single line item.

The second thing worth checking is scope. Does the amendment touch Part II — the actual financial statements — or only Part I or Part III? An amendment that leaves the numbers untouched and exists solely to add an exhibit or defer compensation disclosure is not comparable to one that restates the balance sheet. Skimming the table of contents inside the amendment tells you in seconds which kind you are looking at.

The third signal is pattern. A single 10-K/A, filed once, for a stated administrative reason, is unremarkable — it happens to well-run companies for reasons that have nothing to do with the quality of their accounting. A company that files 10-Q/A amendments across multiple consecutive quarters, or that follows an Item 4.02 8-K with a 10-K/A months later after an extended delinquency, is telling a different story: the original controls that were supposed to catch the error before it reached the market did not. That pattern is worth more scrutiny than the number in the restated line item itself.

Read together, the three signals sort almost every amendment into one of two piles:

| Signal | Routine amendment | Red-flag amendment |
|---|---|---|
| Verb in the Explanatory Note | "Revise" or "reclassify" — a presentation change, sometimes made voluntarily | "Restate" — the original numbers can no longer be relied upon |
| Scope | Touches Part I or Part III only, leaving the financial statements untouched | Touches Part II — the financial statements themselves |
| Pattern | Filed once, for a stated administrative reason | Consecutive quarterly amendments, or a 10-K/A months after an Item 4.02 8-K |
| Typical trigger | An omitted exhibit, or a proxy that missed the 120-day Part III window | A non-reliance determination on previously issued financial statements |
| New audit opinion | Not required | Required for the corrected figures |

---

Checking a company's amendment history takes under a minute and requires nothing beyond EDGAR itself.

## Step 1: Open the Company's EDGAR Filing History

Navigate to SEC EDGAR's company search and pull up the filer's complete filing history rather than just its most recent 10-K or 10-Q. Every filing a company has ever submitted under its CIK appears here in reverse chronological order, amendments included.

## Step 2: Filter for 10-K/A and 10-Q/A Filings

Use the form-type filter to isolate only 10-K/A and 10-Q/A filings. A company with a clean amendment history will show none. A company that has restated multiple periods will show every amendment stacked together, which is itself useful context. A cluster of amendments filed within weeks of each other across multiple fiscal years is a different situation than one 10-K/A filed a decade ago for a housekeeping reason.

## Step 3: Read the Explanatory Note First

Open the amendment and go straight to the Explanatory Note before reading anything else. It is almost always the first substantive paragraph, and it states the reason for the amendment in the company's own words — the "restate" versus "revise" distinction covered above lives here.

## Step 4: Cross-Check the Company's 8-K History

Cross-reference the date of the amendment against the company's 8-K history for the same window. An Item 4.02 8-K filed shortly before the amendment confirms this is a formal restatement rather than a minor correction, and reading the two together — the announcement and the restated numbers — gives a materially more complete picture than either filing alone.

---

## What Amendments Mean for the Data You're Actually Using

An amendment does not just change what a company disclosed. It changes which number is correct for every downstream platform that already ingested the original filing — and how a given platform handles that change says a great deal about how much you can trust the number on your screen in the first place.

[Financial data normalization](/blog/financial-data-normalization-explained) already introduces a layer of interpretation between the as-filed line item and what a third-party aggregator displays. A restatement compounds that problem. Many aggregators overwrite the prior period's figure with the corrected one silently, with no flag indicating that the number changed or which filing — the original or the amendment — the displayed figure now reflects. A user pulling a five-year trend on a platform like that has no way of knowing whether a given year's number reflects what the company originally reported or what it later corrected, unless the platform explicitly preserves both. Whether a given platform does is worth checking before you rely on it — our [comparison of how GeminIQ and Fiscal.ai source their data](/competitor-comparison/fiscal-ai) is one place to start.

GeminIQ pulls every fact directly from the XBRL exhibit of the specific filing it was tagged in. A restated figure in a 10-K/A carries the same [as-filed traceability](/features#financial-statements) as the original — the figure is tied to the filing that produced it, not silently merged into a single "current" number with the history erased. Verifying a figure against the underlying SEC filing is the standard GeminIQ applies to every number on the platform. An amendment is exactly the situation where that standard matters most: the moment a company's own reported numbers changed, and the only reliable way to know it is to trace the figure back to the specific document that produced it.

---

## Frequently Asked Questions

### Does a 10-K/A always mean a restatement?

No. Most 10-K/A filings exist for administrative reasons — adding a missing exhibit, or supplying Part III disclosures that were deferred pending a late proxy statement. Only an amendment whose Explanatory Note describes restating the financial statements, typically alongside an Item 4.02 8-K, involves a change to previously reported numbers.

### Is there a deadline to file a 10-K/A or 10-Q/A?

The SEC does not set a fixed number of days to file an amendment. The practical pressure comes from stock exchange listing rules: Nasdaq Listing Rule 5250(c)(1) allows an initial 60-day compliance window with a total grace period capped around **180 calendar days**, and NYSE will not continue trading a stock past roughly **12 months** of continued filing delinquency.

### Do amended filings get audited again?

A 10-K/A that restates the financial statements requires the company's independent auditor to re-issue an opinion covering the corrected figures, since the original opinion no longer applies to numbers the company itself says can't be relied on. A 10-K/A filed only to add exhibits or Part III disclosure does not require a new audit opinion, because it never touches the audited financial statements in the first place.

### How common are 10-K/A filings?

There is no fixed base rate — amendment frequency swings with the accounting issue of the moment. The clearest recent example is the SPAC warrant reclassification wave that followed the SEC's April 2021 staff statement, which alone drove restatements at more than **340 companies** within a few months.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Balance Sheet Red Flags: A Filing-Based Checklist
source: https://www.geminiq.com/blog/balance-sheet-red-flags-checklist

### Balance Sheet Red Flags: A Filing-Based Checklist
A balance sheet red flag rarely shows up as a single alarming number — it shows up as one line item growing faster than the business around it, quarter after quarter, until the pattern is unmistakable. This checklist covers seven filing-based checks — receivables outpacing revenue, inventory outpacing sales, working capital eroding, goodwill concentration, debt outpacing earnings, shrinking liquidity, and the composite Altman Z-Score — with what each one actually means and where nuance matters, since several of these signal real strength in the right business model.

A company rarely collapses because of one bad number on the balance sheet. It collapses because several ordinary-looking numbers were quietly moving in the wrong direction, relative to each other, for multiple quarters before anyone treated the pattern as a pattern. Receivables growing a little faster than revenue looks like nothing in isolation. Inventory building a little faster than sales looks like nothing in isolation. Read four or five of these signals together, across the same set of quarters, and isolation stops being the right way to read them.

This checklist covers seven filing-based checks that, together, catch most of what a balance sheet quietly reveals before an income statement admits anything is wrong. One caveat belongs in front of every one of them: several of these signals mean something different depending on the business model, and none of them is a sell signal on its own.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=balance-sheet-red-flags-checklist)**

---

## Table of Contents

- [Why a Balance Sheet Red Flag Is Rarely a Single Number](#why-a-balance-sheet-red-flag-is-rarely-a-single-number)
- [Step 1: Check Whether Receivables Are Growing Faster Than Revenue](#step-1-check-whether-receivables-are-growing-faster-than-revenue)
- [Step 2: Inventory vs. Sales, Covered in Full Elsewhere](#step-2-inventory-vs-sales-covered-in-full-elsewhere)
- [Step 3: Check the Working Capital Trend](#step-3-check-the-working-capital-trend)
- [Step 4: Check Goodwill and Intangibles as a Share of Total Assets](#step-4-check-goodwill-and-intangibles-as-a-share-of-total-assets)
- [Step 5: Check Whether Debt Is Growing Faster Than Earnings](#step-5-check-whether-debt-is-growing-faster-than-earnings)
- [Step 6: Check the Liquidity Cushion](#step-6-check-the-liquidity-cushion)
- [Step 7: Run the Composite Check — Altman Z-Score](#step-7-run-the-composite-check-altman-z-score)
- [Reading the Checklist as a Whole, Not Item by Item](#reading-the-checklist-as-a-whole-not-item-by-item)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Why a Balance Sheet Red Flag Is Rarely a Single Number

Every check on this list looks at a relationship between two figures, not a figure in isolation — receivables versus revenue, debt versus earnings, current assets versus current liabilities. That's deliberate. A dollar amount alone rarely tells you whether something is wrong; the same dollar amount can be perfectly healthy at one company and a genuine warning sign at another, depending entirely on what it's growing relative to.

Here is the whole checklist in one place, with where each check gets its full treatment:

| # | Check | What to compare | What warrants a closer look | Covered in full |
| --- | --- | --- | --- | --- |
| 1 | Receivables vs. revenue | Receivables growth against revenue growth over the same trailing period, or DSO directly | A steady, multi-quarter climb in DSO with no stated explanation | [Cash Conversion Cycle Formula Explained](/blog/cash-conversion-cycle-formula-explained) |
| 2 | Inventory vs. sales | Inventory growth against revenue growth over the same window | A sustained, widening gap, unexplained in the MD&A | [Inventory Growing Faster Than Sales](/blog/inventory-growing-faster-than-sales) |
| 3 | Working capital trend | Current assets against current liabilities, across quarters | A slide toward zero driven by draining cash and rising short-term debt rather than by payables funding growth | [Liquidity Ratios and Working Capital Explained](/blog/liquidity-ratios-working-capital-explained) |
| 4 | Goodwill concentration | Goodwill and intangibles as a share of total assets | A rising share, with no acquisition ever written down despite some visibly underperforming | — |
| 5 | Debt vs. earnings | Debt against the earnings available to service it | A leverage ratio climbing alongside decelerating earnings growth, or approaching a covenant limit | [Gross Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained) |
| 6 | Liquidity cushion | Current Ratio and Quick Ratio, quarter over quarter | A steady decline across several consecutive quarters, alongside other signals on this list | [Liquidity Ratios and Working Capital Explained](/blog/liquidity-ratios-working-capital-explained) |
| 7 | Composite cross-check | All of the above, resolved into one score | A reading that corroborates what the individual checks already found | [Altman Z-Score: Reading Financial Distress](/blog/altman-z-score-financial-distress) |

Each row below gets the short version of why it matters. Where a check has its own full guide, this list routes you there rather than repeating it.

---

## Step 1: Check Whether Receivables Are Growing Faster Than Revenue

Revenue growing on its own reads as unambiguous good news, and often it is. That reading holds only when the cash keeps pace: accounts receivable growing faster than revenue, quarter over quarter, means the company is collecting cash more slowly relative to what it's selling. That can happen because credit terms loosened to pull in sales, because a concentrated customer is paying late, or because revenue was recognized before cash actually changed hands. The clean way to check this: compare receivables growth to revenue growth over the same trailing period, or track [Days Sales Outstanding](/blog/cash-conversion-cycle-formula-explained) directly, which the cash conversion cycle guide defines and places alongside inventory days and payables days as a single working-capital loop.

A modest, temporary widening tied to a specific new contract or customer isn't automatically concerning. A steady, multi-quarter climb in DSO with no stated explanation is the pattern worth investigating in the filing's own notes before assuming it away.

---

## Step 2: Inventory vs. Sales, Covered in Full Elsewhere

It's tempting to assume a demand problem will show up on the income statement first, in a softer [gross margin](/metrics/margin-metrics/gross-profit-margin). Inventory shows it earlier: building faster than sales shows up on the balance sheet well before the income statement admits anything, because a company overproducing relative to demand has to either discount its way through the backlog or write it down, and both hit gross margin only once they land. This one has its own full treatment — mechanics, the multi-quarter lead time, and a real case where the divergence preceded the stock's reaction — in [Inventory Growing Faster Than Sales](/blog/inventory-growing-faster-than-sales).

---

## Step 3: Check the Working Capital Trend

A working capital trend sliding toward zero is the textbook liquidity warning, and it's also where nuance matters most on this whole checklist — some business models run structurally negative working capital by design rather than by distress. [Liquidity Ratios and Working Capital Explained](/blog/liquidity-ratios-working-capital-explained) covers the full construction and which business models legitimately invert it.

For checklist purposes, one question separates the two cases: is the decline driven by growing payables funding growth, or by draining cash and rising short-term debt? The balance sheet's own line items answer that directly.

---

## Step 4: Check Goodwill and Intangibles as a Share of Total Assets

Goodwill is the premium a company paid in an acquisition over the fair value of what it actually acquired, and it sits on the balance sheet as an asset that generates no cash flow of its own and cannot be sold. A rising goodwill-to-total-assets ratio doesn't mean fraud or mismanagement — plenty of legitimate roll-up strategies carry heavy goodwill by design — but it does mean a growing share of the company's reported book value is an accounting artifact of past deals rather than tangible, productive capacity.

The follow-up question this ratio should prompt: has any of that goodwill ever been impaired? A company that has made acquisition after acquisition without ever writing one down, despite some of those businesses visibly underperforming, is worth a closer look at how rigorously impairment testing is actually being applied.

---

## Step 5: Check Whether Debt Is Growing Faster Than Earnings

Debt levels alone say very little — a growing, profitable company can carry more debt than a shrinking one and be in a stronger position. What matters is the trend in debt relative to the earnings available to service it, which is the ground covered in [Gross Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained) and, for the cash-adjusted version, [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda).

For this checklist, the flag is the direction rather than the level: a leverage ratio climbing steadily alongside decelerating earnings growth means the company is adding obligation faster than its capacity to carry it. That becomes binding where debt agreements specify a maximum leverage ratio the borrower must stay under.

---

## Step 6: Check the Liquidity Cushion

The [Current Ratio and Quick Ratio](/blog/liquidity-ratios-working-capital-explained) both measure the same underlying question from slightly different angles: can the company cover what it owes in the next twelve months using what it can convert to cash in that window? The [Quick Ratio](/metrics/liquidity-ratios/quick-ratio) is the stricter of the two, excluding inventory.

A single low reading, in isolation, doesn't mean much — plenty of well-run companies operate with structurally lean liquidity ratios as a matter of capital efficiency. A ratio that's been declining steadily over several consecutive quarters, especially alongside any of the other signals on this list, is the version worth taking seriously.

---

## Step 7: Run the Composite Check — Altman Z-Score

A single composite score looks like the shortcut that makes the other six checks optional — run the one formula, skip the line-by-line work. That's not how it functions here. Every check above looks at one line item or one relationship in isolation. The Altman Z-Score is the closest thing to a single composite answer, and [our full breakdown of its mechanics, its published thresholds, and its real limitations](/blog/altman-z-score-financial-distress) covers where it tends to mislead.

Its role on this checklist is positional rather than analytical: run it last, after the individual signals have already been checked, as a cross-check on whether the pattern you found adds up to something a formula built specifically to detect distress would also flag.

---

## Reading the Checklist as a Whole, Not Item by Item

None of these seven checks, on its own, is disqualifying. Every one of them has a legitimate business reason to occur in isolation, in the right company, in the right industry. What the checklist is actually built to catch is convergence: two or three of these trends moving in the same direction, in the same company, over the same stretch of quarters, with no stated explanation in the filing's own notes that accounts for it.

Several of these checks also roll up into a single aggregate figure. Receivables outrunning revenue, inventory building ahead of sales, and estimates drifting optimistic are all components of the gap between reported net income and operating cash flow — which is to say, of accruals. [Earnings Quality: Reading Accruals From Filings](/blog/earnings-quality-accruals-analysis) covers that aggregate directly, and [Reading the Cash Flow Statement for Fraud Signals](/blog/cash-flow-statement-fraud-signals) covers the cases where the aggregate itself has been managed.

That convergence only becomes visible if the underlying figures are actually comparable quarter over quarter — the same tag, tracked the same way, across every filing. That's a higher bar than it sounds: a platform that has normalized each quarter's line items into its own template has already made comparability decisions on your behalf, and a red flag built from a relationship between two lines is exactly the kind of signal that survives or dies on whether those two lines were left as the company filed them. Our comparison against [TIKR](/competitor-comparison/tikr) works through that difference in detail. GeminIQ's [Financial Statements](/features#financial-statements) view and [Custom Tables](/features#custom-tables) builder are built specifically to make that kind of side-by-side, multi-quarter comparison possible directly from as-filed data, rather than requiring a fresh manual pull from EDGAR every time a new filing lands.

---

## Frequently Asked Questions

### Is negative working capital always a red flag?

No. Businesses with strong supplier leverage — large retailers, subscription and membership companies — can run structurally negative working capital by design, effectively financed by vendors rather than debt. For most other companies, a working capital trend sliding toward zero alongside declining cash is the more genuine warning sign.

### Is rising deferred revenue a red flag?

Generally the opposite. Deferred revenue is cash a company already collected for a product or service it hasn't delivered yet — it's filed as a liability, but growing deferred revenue is often a sign of strong demand, not weakness. The distinction that matters is what kind: subscription-based deferred revenue is typically low-risk, while project-based deferred revenue tied to a specific deliverable carries more real performance risk if the project fails.

### How many of these red flags need to show up before it's actually concerning?

There's no fixed threshold, but convergence matters more than any single signal. One metric trending unfavorably for a quarter or two, with a clear explanation in the filing, is usually not concerning on its own. Multiple signals moving the same direction over multiple consecutive quarters, without an explanation the filing itself provides, is the pattern worth taking seriously.

### Does a high Altman Z-Score guarantee a company is safe?

No. It's a statistical model built from historical bankruptcy patterns, not a guarantee, and it has known blind spots for certain industries and company structures. It's best used as a composite cross-check alongside the individual signals on this list, not as a standalone verdict.

A balance sheet doesn't announce a problem. It leaves a trail — and the trail is only visible to someone tracking the same line items, the same way, across every quarter the company has filed.

---

## Related Reading

- [Inventory Growing Faster Than Sales: What It Signals](/blog/inventory-growing-faster-than-sales) — the full mechanics behind Step 2.
- [Altman Z-Score: Reading Financial Distress](/blog/altman-z-score-financial-distress) — the full mechanics behind Step 7, and where the model tends to mislead.
- [Cash Conversion Cycle Formula Explained](/blog/cash-conversion-cycle-formula-explained) — how receivables, inventory, and payables interact as a single working-capital cycle.
- [Earnings Quality: Reading Accruals From Filings](/blog/earnings-quality-accruals-analysis) — the single aggregate figure several of these individual signals roll up into.
- [Liquidity Ratios and Working Capital Explained](/blog/liquidity-ratios-working-capital-explained) — the full construction behind Steps 3 and 6.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=balance-sheet-red-flags-checklist)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: BamSEC Alternative: Document Layer vs. Data Layer
source: https://www.geminiq.com/blog/bamsec-alternative-sec-data

### BamSEC Alternative: Document Layer vs. Data Layer
BamSEC is a document workflow layer over EDGAR — filing search, table extraction, redlines, and transcripts. GeminIQ is a data layer that parses XBRL into structured time series and pre-calculated metrics across the filing universe. This comparison covers what each one is built to do, where they overlap, and which job each is the wrong tool for.

Searching for a BamSEC alternative usually means one of two things, and they point at completely different products. Either the cost stopped making sense for the amount of use it was getting, or the tool turned out to be built for a job adjacent to the one that actually needed doing. The first is a budget question with a lot of answers. The second is a category question with very few, because most of what gets recommended as an alternative is another document reader — a faster way to do the same thing BamSEC already does well.

## What BamSEC Is Actually Built For

BamSEC is a workflow layer that sits on top of EDGAR. That is not a criticism; it is the design, and the design is good.

The core of it is document retrieval and manipulation. Filing search runs across millions of documents with phrase, boolean, and proximity operators, filtered by form type, industry, market cap, and watchlist. Tables download to clean Excel files, with the option to pull matching historical tables and merge them across periods. Redline comparison highlights what changed between two versions of a filing. Earnings call transcripts sit alongside the filings. Insider transactions from Forms 3, 4, and 5 and institutional holdings from [13F filings](/blog/how-to-read-13f-filing) are both surfaced with their own filters. Alerts fire on new filings for watched companies or on all-company searches across the EDGAR universe.

For an analyst whose day involves finding a specific credit agreement, checking what language changed in a risk factor, or pulling the segment table out of a 10-K without retyping it, that feature set is the right one. The reason it works is that it never pretends the filing is anything other than a document — it makes the document easier to find, read, compare, and extract from, and it leaves the document intact.

## The Bottleneck Isn't Finding the Filing

Here is the assumption almost every tool in this category is built on: the hard part of fundamental research is locating the right document fast enough.

For a banker checking a covenant or a lawyer diffing a proxy, that assumption holds. For an investor building a view on a business, it does not. The 10-K was never hard to find — it is free, it is public, and it has been on EDGAR since the day it was filed. What takes the hours is what happens after the document is open: pulling the same line out of twelve consecutive filings, aligning it across fiscal calendars that don't match, computing the ratios the company never reports, and doing all of it again for every other company under consideration.

A table extracted to Excel is a snapshot of one period as one company chose to present it. Turning forty of those snapshots into a comparable series is manual work that document tools are not built to eliminate, because eliminating it requires reading the filing as structured data rather than as a document.

## What the Data Layer Does Differently

GeminIQ starts where the extraction ends. Every 10-K and 10-Q is parsed from its XBRL tags into a structured time series — the same numbers the company filed, already aligned across periods, already carrying the tag that identifies what each figure is.

That structural difference produces three things a document layer cannot. Pre-calculated metrics come first: [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda), [Invested Capital](/metrics/calculated-values/invested-capital), and the rest of the metric library are computed from as-filed inputs across every company, using one convention applied identically. No company reports ROIC. Extracting a table cannot produce it. Building the time series can.

Screening comes second. Filtering the entire filing universe on a computed ratio — every company above a ROIC threshold, every company under a leverage ceiling — requires the metric to already exist for every company. A search that returns documents, however precisely filtered, returns documents.

Traceability comes third and matters most. GeminIQ's [Financial Statements](/features#financial-statements) view carries the XBRL tag alongside every figure, which means a number traces back to the specific tag in the specific filing that produced it. That is the property the platform is built around: not that the data is processed well, but that nothing was reclassified on the way in.

## Where BamSEC Wins Outright

Three capabilities have no GeminIQ equivalent, and pretending otherwise would be dishonest.

Full-text search across filing bodies is the first. GeminIQ reads the financial data in a filing. It does not index the narrative sections, which means a question like "which companies named a specific supplier in their risk factors" has no answer here and a good one there.

Earnings call transcripts are the second. They are not SEC filings, they are not XBRL-tagged, and they sit outside what a filing-data platform covers. An analyst who works from management commentary needs a source that carries it.

Redline comparison is the third. Diffing two versions of a filing to see what language management changed is a document operation on document text, and it earns its place — a quietly rewritten risk factor or a modified covenant definition is a real signal that structured financial data will not surface.

## The Cost Question Is a Layer Question

BamSEC is a paid subscription, and whether the number on the invoice is reasonable has almost nothing to do with the number itself.

An analyst pulling twenty filings a week and extracting tables from most of them recovers a document tool's cost in time almost immediately. An investor who wanted a leverage screen across the universe, or a ten-year ROIC series on eight companies, bought a document tool and still has the spreadsheet work ahead — at any price. The spend was not too high. It was aimed at the wrong layer.

The useful question is not which platform costs less. It is which layer the work actually lives at, because a tool that solves a bottleneck you don't have is expensive at any figure, and a tool that solves the one you do is cheap at most of them.

## The Honest Recommendation

Neither tool replaces the other, and the strongest setup for a professional research workflow is frequently both. But the choice is clear at the edges.

Choose BamSEC when the work is document-shaped: searching filing text, comparing versions, extracting a specific table from a specific filing, or reading transcripts alongside the disclosures. That is what it was designed for and it does it better than a filing-data platform ever will.

Choose GeminIQ when the work is data-shaped: multi-year time series, computed metrics that no company reports, screening the universe on those metrics, and tracing any figure back to the XBRL tag that produced it.

The real BamSEC alternative for most investors is not another document reader. It is a layer down — the filings as data rather than the filings as documents, which is a different tool for a different bottleneck.

## Frequently Asked Questions

### What is the best BamSEC alternative?

That depends on which BamSEC feature is doing the work. For filing text search, transcripts, and redline comparison, the alternatives are other document platforms. For multi-year financial data, computed metrics, and universe screening, the alternative is a filing-data platform rather than a document one — a different category, not a cheaper version of the same thing.

### Do I need both BamSEC and a filing-data platform?

Many professional workflows use both, because they solve different problems. BamSEC handles document work — searching filing text, comparing versions, extracting a specific table, reading transcripts. A filing-data platform handles structured work — multi-year series, computed metrics, and universe screening. The overlap between them is small enough that neither displaces the other for someone doing both kinds of work.

### Does BamSEC provide financial data or just documents?

Documents, with tools for extracting data out of them. Table download converts a filing table to Excel and can pull matching historical tables, but the output is the table as the company presented it rather than a normalized or computed series. Metrics like ROIC or net debt-to-EBITDA are not reported by companies and are therefore not extractable from a filing table.

### Is BamSEC better than EDGAR?

For document work, substantially — EDGAR has no full-text search across filings with proximity operators, no table extraction, no redlines, and no alerting. Both draw from the same source. BamSEC makes that source faster to navigate.

### Does BamSEC have an API?

No public API is offered, which matters for anyone intending to pull filing data into their own models or systems programmatically rather than working inside the platform interface.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=bamsec-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Bed Bath & Beyond: The Buybacks That Funded a Bankruptcy
source: https://www.geminiq.com/blog/bed-bath-beyond-buyback-bankruptcy

### Bed Bath & Beyond: The Buybacks That Funded a Bankruptcy
GeminIQ's as-filed data traces Bed Bath & Beyond's thirteen-year buyback history against its deteriorating fundamentals, quantifying how roughly $9.55 Billion in share repurchases continued even after Total Shareholders' Equity turned negative, months before the company's April 2023 Chapter 11 bankruptcy filing.

<center><sup>GeminIQ data study: annual Payments For Repurchase Of Common Stock against Total Shareholders' Equity, fiscal 2010 through fiscal 2023. Built from as-filed 10-K data via GeminIQ. n = 13 fiscal years.</sup></center>

Bed Bath & Beyond filed for Chapter 11 bankruptcy in April 2023, wiping out its remaining shareholders. In the thirteen fiscal years before that filing, the company spent roughly **$9.55 Billion** buying back its own stock. Was the collapse visible in the numbers the whole time, or did it arrive suddenly? For most of the 2010s, the market treated Bed Bath & Beyond as a mature, disciplined retailer — the kind of company confident enough in its own cash flow to keep returning capital to shareholders. The filings tell a more specific story: the buybacks didn't stop when the fundamentals started breaking. They kept going for years afterward, funded increasingly by debt, and in the final stretch, spent directly out of a balance sheet that had already gone negative.

Every figure below is drawn from Bed Bath & Beyond Inc.'s own 10-K and 10-Q filings between fiscal 2010 and fiscal 2023, read in the order they were filed.

| Field | Detail |
|---|---|
| Ticker (historical) | BBBY — delisted 2023; the ticker is now used by an unrelated company |
| Filing window | FY2010–FY2023, 56 filings (14 10-Ks, 42 10-Qs) |
| Filing types covered | 10-K, 10-Q |
| Outcome metric | Total Shareholders' Equity: **$3.65 Billion** (FY2010) → **-$2.80 Billion** (FY2023, final filing) |

## The Full Timeline: Buybacks, Equity, Margins and Altman Z by Fiscal Year

| Fiscal Year | Buyback Spend | Total Shareholders' Equity | Gross Margin | Operating Margin (TTM) | Altman Z-Score |
|---|---|---|---|---|---|
| FY2010 | $95 Million | $3.65 Billion | 40.8% | — | Above 5.0 |
| FY2011 | — | — | — | — | Above 5.0 |
| FY2012 | — | — | — | — | Above 5.0 |
| FY2013 | — | — | — | — | Above 5.0 |
| FY2014 | — | — | — | — | Above 5.0 |
| FY2015 | $2.25 Billion | — | 38.9% | — | Above 5.0 |
| FY2016 | $1.10 Billion | — | 38.2% | — | — |
| FY2017 | $547 Million | — | — | — | — |
| FY2018 | $252 Million | — | — | — | — |
| FY2019 | $148 Million | — | 34.1% | **-0.7%** | — |
| FY2020 | No annual figure tagged | — | — | — | — |
| FY2021 | $332.5 Million | $1.28 Billion | — | **-3.6%** | — |
| FY2022 | $589.4 Million | $174 Million | — | **-5.2%** | — |
| FY2023 | $46 Million | **-$2.80 Billion** | — | **-9.1%** (May 2022) | **-2.66** (final quarter) |

Blank cells are fiscal years for which this study does not report a filed figure, not zeros. Two readings inside fiscal 2023 are worth pulling out of the annual row: shareholders' equity first went negative at **-$220 Million** in the quarter ended May 2022, the same quarter the company spent **$43.0 Million** on buybacks, and the [Altman Z-Score](/blog/altman-z-score-financial-distress) had already fallen to **3.44** by August 2022 before reaching **-2.66** in the final reported quarter. FY2010–FY2015 buyback spend totals **$6.54 Billion**; cumulative spend through the FY2019 operating-margin crossover was **$8.58 Billion**.

## The Buyback Machine, FY2010–FY2015

In the early 2010s, Bed Bath & Beyond was a genuinely strong business — gross margins in the low-to-mid 40s, operating margins in the mid-teens, and an Altman Z-Score well above **5.0**, deep in the "safe" zone. Buybacks in this era reflected real cash generation, not desperation.

**The Filing Data:** Annual buyback spend climbed from **$95 Million** in FY2010 to a peak of **$2.25 Billion** in FY2015 alone. Across these six fiscal years, the company spent **$6.54 Billion** total on repurchases. Long Term Debt first appears on the balance sheet in the quarter ended August 2014, at **$1.5 Billion** — the first time the company had borrowed money — arriving in the same fiscal year the company spent a record **$2.25 Billion** on buybacks.

**The Signal:** [Gross margin](/blog/gross-profit-margin-business-model-analysis) was already sliding roughly a point a year through this stretch (from **40.8%** in early FY2010 to **38.9%** by FY2015) even as buyback spending accelerated to its all-time high. The debt didn't fund expansion — it showed up the same year the buyback pace reached its peak, needing more cash than the operating business alone was generating.

## FY2016–FY2019: Operating Margin Went Negative, Buybacks Didn't Stop

Revenue was still growing on paper through fiscal 2018, which masked how much profitability was already eroding underneath it.

**The Filing Data:** Gross margin kept falling, from **38.2%** to **34.1%** (TTM). Operating margin (TTM) crossed from positive to negative for the first time in the quarter ended February 2019, at **-0.7%**. Buybacks slowed but never stopped: **$1.10 Billion** (FY2016), **$547 Million** (FY2017), **$252 Million** (FY2018), **$148 Million** (FY2019).

**The Signal:** By the time operating margin turned negative, the company had already spent a cumulative **$8.58 Billion** on buybacks since FY2010. Long Term Debt held flat near **$1.49 Billion** throughout this stretch rather than being paid down — the borrowing from the prior era was never unwound, even as the business it had helped fund kept weakening.

## $43.0 Million of Buybacks the Same Quarter Equity Went Negative

Revenue turned into an outright, sustained decline. Net margin was now solidly negative every quarter, and the balance sheet was running out of room to absorb it.

**The Filing Data:** Total Shareholders' Equity fell from **$1.28 Billion** (February 2021, FY2021 year-end) to **$174 Million** (February 2022, FY2022 year-end) — even as the company spent **$332.5 Million** (FY2021) and **$589.4 Million** (FY2022) on buybacks across those same two fiscal years. Equity crossed into negative territory the very next quarter, at **-$220 Million** (May 2022, the first quarter of fiscal 2023) — and the company still spent **$43.0 Million** on buybacks that same quarter, per the filed cash flow data. Operating margin (TTM) was already negative through this stretch: **-3.6%** (February 2021), **-5.2%** (February 2022), **-9.1%** by May 2022. The Altman Z-Score, which had sat above **5.0** for most of the company's history, fell to **3.44** by August 2022.

**The Signal:** This is the clearest single data point in the whole filing history: a company with negative shareholders' equity, negative and worsening margins, and a deteriorating credit profile still wrote a **$43 million** check to buy back its own stock. Announced repurchase capacity and actual spend are two different things, in both directions — the [gap between a buyback authorization and what gets filed](/blog/do-buybacks-reduce-share-count) is the only place this kind of decision is visible.

## FY2023: Buybacks Reverse Into Share Issuance, Altman Z at -2.66

By early 2023, the buyback era was effectively over — but not because the company chose to stop.

**The Filing Data:** Buyback spend collapsed to **$46 Million** for the full fiscal year, then to essentially nothing (**$219,000**) in the final quarter. Basic shares outstanding, which had fallen from **257.8 Million** to **79.6 Million** over that span — a **69%** reduction funded almost entirely by buybacks — increased for the first time in years, to **90.7 Million** (November 2022) and **97.1 Million** (February 2023), as the company turned to issuing new shares to raise cash. The Altman Z-Score was **-2.66** in the final reported quarter. Total Shareholders' Equity: **-$2.80 Billion**.

**The Signal:** The exact mechanism reversed. A stretch spent retiring shares to return capital to shareholders ended with the company diluting those same shareholders just to survive a few more months — the same move, made under duress, that shows up across GeminIQ's ranking of [companies that dilute shareholders](/blog/companies-that-dilute-shareholders).

## Three Warning Signs Converged Eleven Months Before Chapter 11

By the quarter ended May 31, 2022, at least three separate warning signs had already converged in Bed Bath & Beyond's own filings: shareholders' equity had turned negative, operating margin was solidly negative and worsening, and the company was still buying back stock rather than conserving cash. None of this required special access — it was sitting in the same [10-Q](/blog/10-k-vs-10-q-differences-explained) anyone could have pulled. GeminIQ's post-filing price-reaction data isn't available for this period, since the company delisted before a resolvable ongoing trading history could be captured. But the public record isn't in dispute: the company filed for Chapter 11 bankruptcy eleven months later, in April 2023, and common shareholders were wiped out.

A delisted 2023 bankruptcy is also exactly the kind of entity that normalized-data providers drop from coverage or never carried in the first place — once a company stops trading, the ticker stops being worth maintaining, and the history behind it tends to go with it. GeminIQ still holds all **56** of Bed Bath & Beyond's filings from this window — **14** 10-Ks and **42** 10-Qs — exactly as they were filed, which is the coverage difference our comparison with [BamSEC](/competitor-comparison/bamsec) is about.

## Check Your Holdings

This same check works on any company you hold, whether or not it's anywhere near trouble. Pull up Payments For Repurchase Of Common Stock alongside Total Shareholders' Equity and operating margin in GeminIQ's [Financial Statements](/features#financial-statements) and [Calculated Metrics](/features#calculated-metrics) views. A company still buying back stock while equity is shrinking toward zero, or while margins are compressing quarter after quarter, is showing the exact pattern that sat in Bed Bath & Beyond's own filings more than a year before its bankruptcy. That's worth checking before the next buyback announcement gets read as a vote of confidence.

## Frequently Asked Questions

### How much did Bed Bath & Beyond spend on buybacks before filing for bankruptcy?

Roughly **$9.55 Billion** across fiscal 2010 through fiscal 2023, based on GeminIQ's as-filed data for the `Payments For Repurchase Of Common Stock` line. No annual repurchase figure was tagged for fiscal 2020, likely reflecting a pause during that year.

### Did Bed Bath & Beyond keep buying back stock after its equity went negative?

Yes. The quarter ended May 31, 2022 shows **$43.0 Million** in buybacks the same three months Total Shareholders' Equity first went negative, per GeminIQ's filed data.

### When did Bed Bath & Beyond file for bankruptcy?

April 2023, according to public record — about eleven months after its own filings first showed negative shareholders' equity.

### What happened to Bed Bath & Beyond?

The company filed for Chapter 11 bankruptcy in April 2023 and its common shareholders were wiped out. Its filings show the deterioration running for more than a decade first: gross margin fell from **40.8%** in early FY2010 to **34.1%** by FY2019, operating margin turned negative in the quarter ended February 2019, Total Shareholders' Equity went from **$3.65 Billion** to **-$2.80 Billion**, and the Altman Z-Score fell from above **5.0** to **-2.66**. Across that same stretch the company spent roughly **$9.55 Billion** repurchasing its own stock.

### Did buybacks cause Bed Bath & Beyond's bankruptcy?

This study doesn't make that claim, and the filings alone can't establish it. What they do show is sequencing: **$9.55 Billion** left the company as repurchases while margins compressed, debt first appeared on the balance sheet in the same fiscal year buyback spend peaked at **$2.25 Billion**, and **$43.0 Million** was still being spent in the quarter equity turned negative. That is cash unavailable to absorb what came next, whatever else contributed.

### Is buying back stock always a warning sign?

No. Buybacks funded by genuine, sustained cash generation are an ordinary capital allocation choice — the [companies that genuinely shrank their share count](/blog/companies-reducing-share-count) over the last decade did it out of real cash flow. The pattern in this post — buybacks continuing while margins deteriorate and the balance sheet weakens — is the specific combination worth watching for, not buybacks in isolation.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=bed-bath-beyond-buyback-bankruptcy)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures in this article are drawn from Bed Bath & Beyond Inc.'s (CIK0000886158) 10-K and 10-Q filings, filed 2009–2023 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000886158&type=10-K). This entity is no longer publicly traded. The Bed Bath & Beyond brand and ticker were subsequently acquired out of bankruptcy by a separate company and are not the subject of this analysis.</sup>

---

## Blog: Bloomberg Terminal Alternative for Fundamental Research
source: https://www.geminiq.com/blog/bloomberg-terminal-alternative-sec-data

### Bloomberg Terminal Alternative for Fundamental Research
A Bloomberg Terminal alternative for filing-based fundamental research. The terminal is built for the trading desk; reading as-filed 10-K and 10-Q data is a different job, and this post separates the two.

Most Bloomberg Terminal alternative comparisons make the same mistake: they line up feature grids and argue that a cheaper product does eighty percent of what the terminal does. That argument loses on contact with anyone who actually uses a terminal, because the twenty percent it concedes is the part they pay for.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=bloomberg-terminal-alternative-sec-data)**

The terminal is not a research library with a high price tag. It is a trading desk — a real-time feed across hundreds of global exchanges, a messaging network that functions as the industry's addressable directory, dealer quoting for instruments that do not trade on a screen, and execution wired into all of it. Bloomberg does not publish pricing, but the figures circulate consistently: roughly **$31,980** per seat per year for a single terminal in 2026, near **$28,320** per seat for firms running two or more, typically on a two-year minimum. That number holds steady across independent sources precisely because the product is uniform. Everyone gets the same bundle.

Nothing in that bundle is designed to answer the question a fundamental investor actually asks: what did this company report, and does the number tie back to the filing?

## Table of Contents

- [The Terminal Is a Trading Desk](#the-terminal-is-a-trading-desk)
- [Filing Research Is a Different Job](#filing-research-is-a-different-job)
- [Why Breadth Is the Wrong Argument](#why-breadth-is-the-wrong-argument)
- [What Filing-First Actually Buys](#what-filing-first-actually-buys)
- [The Seat Nobody Talks About](#the-seat-nobody-talks-about)
- [When a Terminal Is the Only Answer](#when-a-terminal-is-the-only-answer)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Terminal Is a Trading Desk

Every expensive component of a Bloomberg subscription exists to compress time.

Real-time pricing across equities, fixed income, currencies, commodities, and derivatives matters because a stale quote is a losing quote. The messaging network matters because a bond desk needs a counterparty in seconds, not after an email thread. Dealer quoting matters because large parts of the fixed income market have no public order book, so price discovery happens through relationships the terminal indexes. News delivery matters because the trade is in the first minute.

That is a coherent product with a defensible moat, and the price reflects a genuine monopoly on the network rather than a markup on data. It is also why the terminal's cost is so stubborn. You are not paying for numbers. You are paying for the fact that everyone else is on it too.

None of those clocks are running when you open a 10-K.

## Filing Research Is a Different Job

Fundamental filing analysis has almost the opposite shape.

It is asynchronous — the 10-K was filed weeks ago and will not change. It is historical, because the interesting question is usually how a line item behaved across twelve quarters rather than what it printed this morning. It is verification-driven, which means the value is not in receiving the number quickly but in being able to prove where it came from. And it is narrow by design: one company, one filing, one caption, traced to the footnote that explains it.

Speed is irrelevant to that work. Traceability is everything.

This is why the price argument misfires in both directions. A terminal is not overpriced for a trader; it is mispurchased by a fundamental analyst who needed a filing archive and bought a market-data feed. The waste is not in the dollars. It is in the mismatch.

## Why Breadth Is the Wrong Argument

Do not position against the terminal on coverage, because that argument cannot be won and does not need to be.

Bloomberg's breadth is real, and any product claiming to match it across asset classes, geographies, and instrument types is overselling. The relevant question is narrower and more useful: within the slice of work that is US public company fundamental analysis, does the platform preserve what the company filed, or does it show you a standardized version of it?

That question has nothing to do with breadth. It is a question about chain of custody.

Any platform that presents thousands of companies in one comparable template has to map each company's reported line items into that template. Two distinct cash outflows can become one row. One filed liability caption can be split into two rows so a component can be tracked separately. A label can survive while its contents change, which is the version that costs an analyst the most, because the screen gives no signal that anything was decided.

Those are reasonable engineering choices for a comparison product. They are a problem for a verification workflow, and no amount of additional coverage fixes them.

## What Filing-First Actually Buys

GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR and keeps the company's own reported structure intact, including the [XBRL tag](/blog/what-is-xbrl) behind each value. There is no mapping layer between the filing and the display, so there is no mapping decision to reverse-engineer when a figure looks wrong.

That premise shapes the rest of the product rather than the other way around. [Financial Statements](/features#financial-statements) show a company's own line items across quarters and years. [Custom Tables](/features#custom-tables) build a view from specific reported items instead of template rows. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow](/metrics/calculated-values/free-cash-flow), and [Invested Capital](/metrics/calculated-values/invested-capital) are computed from those as-filed inputs, which means the metric can be checked against the numbers that produced it rather than trusted on reputation. [Visualizations](/features#visualizations) chart the reported structure over time, and [Stock Screeners](/features#screener) run on the same layer.

One documented case shows what survives the trip and what does not. [Home Depot's](/stocks/HD) FY2025 10-K reports net proceeds from commercial paper as a single net line at **+$4,148M**. A widely used retail aggregator dissolves that figure into separate gross debt-issued and debt-repaid buckets, leaving no single net commercial paper line at all.

Reconstructing gross flows from a net figure is a reasonable modeling convenience. It also carries a specific failure: in a year when a company is a net repayer, the reconstruction can invert the economic direction entirely, turning a paydown into what looks like new borrowing. The filing said one thing and the template said another, and neither the label nor the value announces the reconstruction.

That case is documented against a retail platform rather than the terminal, and the logic is generic to any product that maps filings into a comparison template. The [documented normalization cases](/blog/third-party-financial-data-problems) post covers it in full.

The scope is narrow on purpose. US public company fundamentals, sourced from EDGAR, is the entire universe. Covering less is what makes the traceability possible.

## The Seat Nobody Talks About

There is a structural consequence of terminal pricing that rarely appears in comparisons: most of the people doing serious fundamental work do not have one.

A two-year commitment at roughly **$31,980** a seat prices out the independent analyst, the family office, the emerging manager, the corporate development team that needs filings twice a month, and effectively every serious individual investor. Those are not people doing lesser work. They are people whose work happens to have no real-time component, priced out of a product whose real-time component is the whole cost structure.

The terminal's economics assume a desk with a P&L. Filing analysis does not require one.

## When a Terminal Is the Only Answer

Some jobs have no substitute, and it is worth being direct about them.

If you trade fixed income, need dealer runs, work across derivatives or FX, require real-time execution, depend on the messaging network to reach counterparties, or hold a role where being off Bloomberg means being unreachable, the terminal is not an expensive option. It is the job. No filing archive changes that, and a comparison that pretends otherwise is not worth reading.

The useful decision is not terminal versus alternative. It is recognizing that a subscription bought for market access is answering a different question than the one your analysis actually turns on. If the work is reading what a company reported and proving the number ties to the document, the source filing is the product — and it does not require a trading desk to reach it.

For a feature-level breakdown, see the [GeminIQ vs. Bloomberg Terminal comparison](/competitor-comparison/bloomberg-terminal). The same job-to-be-done test applies to the other institutional standard, covered in the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) post. For what happens to a filing between EDGAR and a screen, [how financial data reaches investors](/blog/how-financial-data-reaches-investors) walks the full chain.

## Frequently Asked Questions

### Are there free Bloomberg Terminal alternatives?

For fundamental research, the underlying source material is free: every 10-K and 10-Q is public on SEC EDGAR the moment it is filed, complete with the XBRL data behind each reported figure. GeminIQ's own Free plan closes part of the extraction gap at no cost too, with 3 years of history and 24 calculated metrics built on the same XBRL traceability as the paid product. The full 17-plus years of history, 90-plus metrics, Stock Screener, and Custom Watchlists are reserved for the paid Annual or Monthly plan.

### What is the best Bloomberg Terminal alternative for fundamental analysis?

For US public company fundamental work, the alternative worth evaluating is a platform that extracts directly from SEC EDGAR and preserves as-filed 10-K and 10-Q line items with XBRL tag traceability. That answers the verification question the terminal was never built to answer. It does not replace real-time market data, messaging, or execution, and no product at a fraction of terminal pricing does.

### How much does a Bloomberg Terminal cost in 2026?

Bloomberg does not publish pricing, but widely reported figures put a single terminal near **$31,980** per seat per year in 2026, dropping to roughly **$28,320** per seat for firms with two or more terminals, typically on a two-year minimum commitment. Those figures are consistent across independent sources because the terminal is a uniform bundle rather than a per-customer configuration.

### Can I do fundamental research without a Bloomberg Terminal?

Yes, and the terminal contributes relatively little to it. Filing-based analysis depends on as-filed statement history, footnote detail, and traceability back to the source document — none of which requires a real-time feed, a messaging network, or execution capability. Every 10-K and 10-Q is public on SEC EDGAR the moment it is filed.

### Why is the Bloomberg Terminal so expensive?

The cost reflects the network more than the data. Real-time coverage across hundreds of global exchanges, dealer quoting in markets without public order books, and a messaging network that functions as the industry's directory are all things that get more valuable as more people subscribe. That dynamic supports pricing that a pure data product could not.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=bloomberg-terminal-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Bloomberg Terminal per-seat cost figures are widely reported third-party estimates compiled from procurement trackers and subscriber reports; Bloomberg does not publish pricing.
- Bloomberg Terminal capability descriptions reflect the platform's publicly documented functions across market data, messaging, and execution.
- GeminIQ Bloomberg Terminal comparison page: /competitor-comparison/bloomberg-terminal

---

## Blog: Buffett Stock Criteria: Quality Business at a Fair Price
source: https://www.geminiq.com/blog/buffett-stock-criteria-quality-business

### Buffett Stock Criteria: Quality Business at a Fair Price
Warren Buffett's stock criteria in plain English — five filters that separate quality businesses from the noise, and how to run them on clean SEC filing data.

Warren Buffett is the most studied investor alive, and his framework is also one of the most misapplied. The popular version focuses almost entirely on finding cheap stocks — low P/E, low price-to-book, something that looks undervalued by a simple ratio. That is the Benjamin Graham framework, and Buffett spent his early career using it. The shift came in 1972, when Berkshire Hathaway acquired See's Candies for **$25 million** — roughly **3x book value**, far above what the early Buffett would have paid for anything. That price looked wrong by Graham's logic. It turned out to be the most important trade of Buffett's career, not because it was cheap, but because See's was a wonderful business. This post breaks down the five criteria that define Buffett's quality-at-fair-price framework, explains what aggregator data gets wrong on each one, and shows exactly how to run the screen on data sourced directly from SEC filings.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=buffett-stock-criteria-quality-business)**

---

## Table of Contents

- [What Are Warren Buffett's Stock Criteria?](#what-are-warren-buffetts-stock-criteria)
- [Criterion One: Return on Invested Capital (ROIC ≥ 15%)](#criterion-one-return-on-invested-capital-roic--15)
- [Criterion Two: Return on Equity (ROE ≥ 15%)](#criterion-two-return-on-equity-roe--15)
- [Criterion Three: A Conservative Balance Sheet (Debt-to-Equity ≤ 0.5)](#criterion-three-a-conservative-balance-sheet-debt-to-equity--05)
- [Criterion Four: Consistent Earnings Growth (≥ 8% Over Three Years)](#criterion-four-consistent-earnings-growth--8-over-three-years)
- [Criterion Five: A Price You Won't Regret (P/E Between 1x and 30x)](#criterion-five-a-price-you-wont-regret-pe-between-1x-and-30x)
- [What Financial Aggregators Get Wrong on Each Criterion](#what-financial-aggregators-get-wrong-on-each-criterion)
- [How to Run the Buffett Screen in GeminIQ](#how-to-run-the-buffett-screen-in-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Are Warren Buffett's Stock Criteria?

Warren Buffett's stock criteria come down to five filters applied together: a return on invested capital above **15%**, a return on equity above **15%**, a conservative balance sheet (debt-to-equity at or below **0.5**), consistent earnings growth of at least **8%** over three years, and a price-to-earnings ratio that is not catastrophically high. Each is covered in turn below, with the SEC-filing inputs behind it.

The insight Buffett credits to Charlie Munger is simple to state and difficult to internalize: it is better to own a wonderful business at a fair price than a fair business at a wonderful price. A cigar-butt stock — one cheap enough to squeeze a few more puffs out of before it goes cold — requires you to be right about the exit. A wonderful business, compounding capital at **20% or 25% ROIC** for a decade, makes you money whether or not you time anything correctly. The stock price is almost irrelevant if the underlying business keeps earning exceptional returns on every dollar it retains.

The framework that operationalizes this preference has five components: high returns on invested capital, high returns on equity, a conservative balance sheet, consistent earnings growth, and a price that is not catastrophically high relative to current earnings. None of these filters in isolation is sufficient. A business with **40% ROIC** and **6x debt-to-equity** is not a Buffett-style investment — leverage that high eliminates the margin of safety that quality businesses are supposed to provide. A business with **0.1 Debt-to-Equity** and **5% ROIC** fails the quality test entirely. All five criteria must be satisfied simultaneously, which is why the screen produces a short list rather than a long one.

The screen has a hard limit, and Buffett himself would name it first. His actual selection process is heavily qualitative: he is looking for durable competitive moats — brands with genuine pricing power, network effects that compound over time, switching costs that make customers reluctant to leave — and management teams with the capital allocation discipline to reinvest earnings at high rates of return for years. A screen can narrow a universe of thousands down to a manageable list of candidates worth investigating. It cannot perform the qualitative analysis that determines whether a candidate belongs in a long-term portfolio. That step requires reading the filing. But standard financial media doesn't read the footnotes.

---

## Criterion One: Return on Invested Capital (ROIC ≥ 15%)

GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) is the primary quality filter in this framework for a foundational reason: it answers the most important question in investing. For every dollar of capital deployed in this business — by both debt holders and equity investors — how many cents of after-tax operating profit does it generate? A business with a ROIC consistently above its cost of capital is creating economic value. A business earning less than its cost of capital is destroying value, even when it appears profitable on the net income line.

The threshold in this screen is ROIC at or above **15%** on a trailing twelve-month basis. This clears the estimated cost of capital for most US companies — typically in the **7% to 12%** range — with a meaningful buffer. A ROIC above **25%** on a sustained basis is exceptional and almost always signals a genuine, defensible competitive advantage. The kind of business that earns **30% ROIC** year after year tends to have structural protection — a brand, a network, a cost structure, a switching cost — that competition has not been able to erode. That is precisely the business Buffett is looking for, and ROIC is the metric that finds it.

[Apple](/stocks/AAPL) illustrates what the high end of this distribution looks like. Apple's trailing twelve-month ROIC registered at **81.7%** as of its Q2 FY2026 10-Q (period ended March 28, 2026) — an extreme case reflecting a capital-light, high-margin business running at full compounding power, with an equity base compressed by aggressive buybacks. For most Buffett-style candidates, the threshold is far more modest than that. But the principle is identical: the business must earn more on deployed capital than that capital costs to obtain.

Buffett himself focuses on return on tangible equity, which strips goodwill and acquired intangibles from the [invested capital](/metrics/calculated-values/invested-capital) base. For acquisitive companies that have accumulated large goodwill balances, this distinction matters significantly. GeminIQ reports invested capital as-filed, with goodwill visible as a separate balance sheet line, so you can evaluate the return on both total and tangible capital independently. For a complete treatment of the formula, benchmarks, and where the metric breaks, the [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) pillar post covers the full methodology.

---

## Criterion Two: Return on Equity (ROE ≥ 15%)

Return on equity measures profit generated per dollar of shareholder equity. Where ROIC evaluates the return on all capital deployed by both debt and equity investors, GeminIQ's pre-calculated [Return on Equity](/metrics/returns-and-profitability/return-on-equity) measures specifically what equity holders are earning on the book value of their stake. Buffett has used ROE as a quality signal because, for a business that grows primarily through retained earnings rather than debt issuance, a high ROE means the company is compounding the equity base efficiently. A **20% ROE** sustained over a decade means the equity base doubles approximately every **3.6 years** — and if earnings multiple stays constant, so does the investor's wealth.

The threshold in this screen is ROE at or above **15%**. Paired with a Debt-to-Equity ceiling of **0.5**, this filter is designed to isolate businesses where the high ROE reflects genuine operational excellence rather than financial engineering. A company that borrows aggressively to fund buybacks shrinks its equity base, which inflates ROE even if the underlying business is not more profitable. That is why both criteria must be evaluated together. A **25% ROE** with a **Debt-to-Equity of 3.0** is a leverage play. A **20% ROE** with a **Debt-to-Equity of 0.2** is a quality business.

One structural limitation is worth flagging directly. Companies with very aggressive share buyback programs sometimes operate with negative book equity, at which point ROE becomes mathematically unreliable — the denominator shrinks toward zero or turns negative, producing extreme or undefined ratios. In those cases, ROIC becomes the primary quality signal, and the screen's earnings growth and P/E filters carry more of the evaluative burden. The screen's design accommodates this by requiring all five criteria to hold, not any single one in isolation.

---

## Criterion Three: A Conservative Balance Sheet (Debt-to-Equity ≤ 0.5)

Buffett has described financial leverage with characteristic clarity over decades of shareholder letters: borrowed money eliminates the margin of safety that rational investing requires. A wonderful business drowning in debt can face forced selling at exactly the wrong moment. A merely adequate business with no debt can survive almost anything. The Buffett framework therefore imposes a strict balance sheet test: total liabilities cannot exceed **50%** of total shareholders' equity, expressed as GeminIQ's pre-calculated [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) at or below **0.5**.

This threshold is deliberately conservative by broad market standards. Many respectable companies carry Debt-to-Equity ratios between **1.0 and 2.0** without operational stress. The screen is not trying to find the average public company — it is trying to find the subset whose competitive advantages are so durable that they do not need debt to generate attractive returns. A business with **20% ROIC** and zero debt is compounding capital for its owners without transferring any of that return to creditors through interest expense. That structural advantage compounds quietly over time.

The filter also serves as a structural exclusion for capital-intensive sectors where high leverage is a business model feature rather than a risk signal. Banks, utilities, and REITs routinely operate with Debt-to-Equity ratios above **2.0** by design — their business model is, in effect, to borrow at low rates and deploy at higher rates. The **0.5** ceiling appropriately filters them out, since the quality metrics — ROIC and ROE — are not comparably useful for evaluating financial institutions anyway.

---

## Criterion Four: Consistent Earnings Growth (≥ 8% Over Three Years)

A quality business earns high returns on capital. But high returns on a stagnant earnings base are less valuable than high returns on a growing one. Criterion four filters for businesses where net income is genuinely expanding — not in a single exceptional year, but on a sustained three-year basis. The screen requires GeminIQ's pre-calculated [Net Income Growth](/metrics/growth-metrics/net-income-growth) at or above **8%** over three years.

The three-year window is intentional. One-year net income can be distorted by a single item: a tax benefit from stock-based compensation, a one-time gain on asset sales, a reversal of a legal reserve. Three years of sustained growth filters out these one-off effects and requires the underlying business to be expanding its earnings power over time. Buffett has consistently stated that he prefers a business earning **15% ROIC** with reliable consistency over one that earns **35%** in peak years and **5%** in troughs. The three-year requirement operationalizes that preference. Consistency is the filter that separates businesses with moats from businesses that had a good run.

The threshold of **8%** is not aggressive — it is a floor, not a target. A quality business compounding earnings at **15% or 20% annually** over three years clears this criterion easily. The **8%** minimum is designed to exclude businesses in structural decline: those whose earnings have grown, in aggregate, less than inflation over three years are not compounding capital for shareholders in any meaningful sense, regardless of what the ROIC number says about a single trailing period.

---

## Criterion Five: A Price You Won't Regret (P/E Between 1x and 30x)

The fifth criterion is the least Buffett-specific of the five, and it requires careful interpretation. A P/E ceiling of **30x** is not a Graham "margin of safety" threshold. Graham was looking for stocks at deep discounts — P/E ratios of **8x or 10x**, stocks selling below working capital. Buffett's evolved framework tolerates a much higher price for a much better business. Coca-Cola was accumulated in Berkshire's portfolio at more than **15x earnings**. Buffett paid a quality premium, not a distress discount. The point of the **30x** ceiling is not to find cheap stocks — it is to avoid paying a catastrophically high multiple for even a wonderful business, where the mathematics of compounding cannot catch up with the entry price within a reasonable investment horizon.

The floor at GeminIQ's pre-calculated [Price-to-Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) of **1x** serves a different purpose: it removes companies with negative or near-zero earnings that would otherwise produce mathematically valid but economically meaningless low multiples. A company reporting minimal net income on a multi-billion dollar market cap clears a P/E ceiling of **30x** by generating a calculated ratio in the thousands — which is a screener artifact, not a valuation signal. The **1x floor** eliminates this class of result entirely.

Two limitations of P/E as a valuation criterion are worth stating plainly. First, P/E is sensitive to one-time items: a large impairment charge or restructuring cost suppresses net income, inflating trailing P/E even if the underlying business is unchanged. Second, P/E does not account for growth. A business growing earnings at **25% annually** can justify a **30x P/E** far more easily than a business growing at **3%**. The P/E criterion in this screen functions as a basic reasonableness check, not a primary quality signal. The first four criteria do that work.

---

## What Financial Aggregators Get Wrong on Each Criterion

Running this screen on aggregated, normalized financial data produces a different set of results than running it on SEC filing data. Each criterion is affected by a specific category of normalization error, and the distortions are not random — they are systematic, introduced by methodological choices that aggregators apply across their entire database.

On ROIC, the most common distortions are the effective tax rate assumption and goodwill treatment. Most aggregators apply a flat **21% federal statutory rate** to calculate NOPAT. Companies with significant foreign income, R&D credits, or deferred tax assets routinely report effective rates of **12% to 17%**. Applying **21%** to those companies overstates tax expense, understates NOPAT, and suppresses ROIC — meaning businesses with genuine international tax efficiency may fail the screen on aggregated data despite passing on as-filed figures. The gap between a **21% assumed rate** and a **14% actual rate** on a large EBIT base can move the calculated ROIC by **5 percentage points or more** for the same company in the same period. GeminIQ uses the actual effective rate derived from the `IncomeTaxExpenseBenefit` and pretax income XBRL tags filed with the SEC.

On ROE, the primary aggregator issue is the definition of shareholders' equity. Some platforms include minority interests in equity; others exclude them. Some classify preferred equity inside equity; others reclassify it as a liability or mezzanine instrument. These choices change the denominator of the ratio and produce different ROE values for identical underlying businesses. GeminIQ uses Total Shareholders' Equity as reported in the filing — the figure the company itself calculated and submitted to the SEC, with no reclassification.

On stock-based compensation, technology companies in particular carry significant SBC expense that some aggregators add back when calculating adjusted earnings, making ROE and earnings growth appear better than the as-filed numbers. GeminIQ surfaces as-filed net income, and the pre-calculated [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric shows exactly what share of revenue is being distributed as equity compensation. For any quality screen that surfaces high-ROIC technology companies, this metric provides essential context: a business reporting **20% net income growth** while paying **15% of revenue** in stock compensation is sharing a meaningful portion of that growth with employees rather than compounding it for existing shareholders.

On Debt-to-Equity, aggregators make different choices about where to classify hybrid instruments, operating lease obligations, and pension liabilities. Each reclassification moves a balance from one side of the ledger to another, directly changing the ratio. GeminIQ preserves the company's as-filed balance sheet classification, sourced from the XBRL tags `Liabilities` and `StockholdersEquity` in the SEC filing.

On net income growth, the aggregator issue is the definition of net income itself. A company that sold a major business division reports the divested segment as a discontinued operation, typically excluded from continuing earnings. Some aggregators strip discontinued operations from both periods to show "cleaner" comparable growth — which, depending on the size of the discontinued segment, produces a materially different three-year growth rate than total as-filed net income. GeminIQ uses total Net Income as reported: not adjusted, not normalized, not stripped of the items a company would prefer analysts to ignore.

---

## How to Run the Buffett Screen in GeminIQ

The GeminIQ [Stock Screener](/features#screener) lets you apply all five criteria simultaneously, running on data extracted directly from XBRL-tagged SEC filings. The Buffett-Style screen is available pre-configured at [geminiq.com/screens/stock-screeners/buffett-style](/screens/stock-screeners/buffett-style), or you can build it manually with the following filters:

| Filter | Operator | Value |
|---|---|---|
| ROIC TTM | ≥ | 15 |
| ROE TTM | ≥ | 15 |
| Debt-to-Equity | ≤ | 0.5 |
| Net Income TTM Growth 3Y | ≥ | 8 |
| P/E TTM | ≤ | 30 |
| P/E TTM | ≥ | 1 |

Set Sort By to ROIC TTM, direction Descending, so the highest-quality businesses by return on capital appear first. For each result that clears the quantitative filters, pull the company's [Financial Statements](/features#financial-statements) in GeminIQ and examine whether ROIC has been stable or improving across at least eight quarters. A company posting a high trailing ROIC that has declined for three consecutive quarters is a materially different situation from one with a consistent or rising trend. The [Calculated Metrics](/features#calculated-metrics) trend view surfaces ROIC, ROE, and Debt-to-Equity trended across multiple periods so you can assess whether the numbers that cleared the screen today reflect a durable business pattern or a single strong filing period.

Buffett-style quality is defined by consistency. A business that earns **20% ROIC** reliably across a full market cycle is more valuable than one that earns **35%** in one year and **8%** the next. That is the filter that cannot be faked — and it is the one that requires clean, unprocessed data to run correctly.

<center><sup>GeminIQ Stock Screener — Buffett-Style filter set returning 53 results sorted by ROIC TTM descending. Top result: PPTA at **116.08% ROIC TTM**. Filters applied: ROIC TTM ≥ 15%, ROE TTM ≥ 15%, Debt-to-Equity ≤ 0.5, Net Income TTM Growth 3Y ≥ 8%, P/E TTM between 1x and 30x. All data sourced directly from XBRL-tagged SEC filings as of Q1 2026.</sup></center>

---

## Frequently Asked Questions

### What ROIC does Buffett look for in a stock?

This framework uses a floor of **15%** return on invested capital on a trailing twelve-month basis, which clears the estimated cost of capital for most US companies — typically **7% to 12%** — with a meaningful buffer. Sustained ROIC above **25%** is exceptional and almost always indicates a durable competitive advantage rather than a good year. One nuance: Buffett himself focuses on return on *tangible* equity, which strips goodwill and acquired intangibles out of the capital base. For serially acquisitive companies carrying large goodwill balances, that distinction moves the number materially.

### Why does a Buffett-style screen exclude banks, utilities, and REITs?

The Debt-to-Equity ceiling of **0.5** does it structurally rather than by name. Banks, utilities, and REITs routinely operate above **2.0** by design — borrowing is the business model, not a risk signal — so a conservative leverage filter removes them automatically. That is intended. The screen is not trying to find the average public company; it is isolating businesses whose competitive advantages are strong enough that they do not need leverage to produce attractive returns.

### Does Buffett only buy stocks with a low P/E ratio?

No, and this is the criterion most often misread. The **30x** ceiling here is not a Graham-style margin-of-safety threshold — Graham looked for **8x** or **10x** multiples and stocks trading below working capital. Buffett's evolution, under Munger's influence, was toward paying a fair price for a wonderful business rather than a wonderful price for a fair one. The **1x** floor serves a separate purpose entirely: it removes companies with negative or near-zero earnings that would otherwise produce mathematically valid but economically meaningless low multiples.

### Why does the earnings growth threshold use three years instead of one?

Because one year of net income can be distorted by a single item — a tax benefit from stock-based compensation, a one-time gain on an asset sale, the reversal of a legal reserve. Requiring **8%** growth sustained across three years filters those one-off effects out. The **8%** figure is a floor rather than a target: a business compounding earnings at **15%** or **20%** clears it easily, and the threshold exists mainly to exclude companies in structural decline.

### Can a stock screen actually replicate how Buffett picks stocks?

Not fully, and it is worth being direct about the limit. Buffett's actual selection process is heavily qualitative — durable moats, brands with real pricing power, network effects, switching costs, and management teams with the capital allocation discipline to reinvest at high rates of return. None of that is screenable. What these five filters do is narrow a universe of thousands of companies down to the subset whose *financial* profile is consistent with a quality business, which is where the qualitative work starts rather than ends.

---

### Related Reading

- [Return on Invested Capital (ROIC): Formula, Benchmarks, and How to Use It](/blog/roic-return-on-invested-capital-explained) — the full methodology behind the primary quality criterion in this screen, including the NOPAT formula, benchmarks, and where the metric breaks.
- [Magic Formula Investing Explained](/blog/magic-formula-investing-explained) — a related quality-and-value screen using ROIC and EV/EBIT combined ranking, and how data normalization distorts which companies appear.
- [Piotroski F-Score: The Value Trap Filter](/blog/piotroski-f-score-value-trap) — a nine-point financial health checklist that pairs well with any quality screen to eliminate deteriorating businesses that pass on surface metrics.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — why FCF yield complements the P/E criterion for evaluating whether a quality business is trading at a genuinely fair price.
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary) — plain-English definitions of every metric and concept referenced in this post.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s Q2 FY2026 10-Q (filed May 1, 2026, period ending March 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/320193/000032019326000013/aapl-20260328.htm).

---

## Blog: Negative Equity From Buybacks: 31 Companies
source: https://www.geminiq.com/blog/buybacks-into-negative-equity

### Negative Equity From Buybacks: 31 Companies
Negative stockholders' equity is usually read as a distress signal, but as-filed data shows a specific group of companies with negative equity driven entirely by share buybacks rather than accumulated losses.

**[Booking Holdings](/stocks/BKNG)** reports **-$10.8 billion** in total stockholders' equity. Read the balance sheet in isolation and that number looks like a company drowning in accumulated losses. Read the filing itself and a different picture emerges: Booking Holdings has **$43.0 billion** in retained earnings — a profitable, cash-generative history — and **$62.1 billion** parked in treasury stock. The company did not lose its way into negative equity. It bought its way there, on purpose, one repurchase at a time.

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period. It isolates companies with **negative total stockholders' equity and positive retained earnings** — the specific combination that identifies a deficit built by buybacks rather than by losses. **31 companies** in GeminIQ's current filing snapshot meet that description. Separately, across the full population of **1,239 companies** currently showing negative equity for any reason, **52** have treasury stock alone — before retained earnings even enters the calculation — large enough to fully explain the deficit on its own.

## The Pattern

Negative stockholders' equity gets treated as a single warning signal in most screeners, and it collapses two entirely different stories into one number. A company can post negative equity because it has burned through capital on losses, which is a real solvency concern. Or it can post negative equity because it has spent decades generating profit and returning nearly all of it to shareholders through buybacks large enough to exceed the retained earnings that funded them. That is closer to a capital-allocation choice than a warning sign. The retained-earnings-positive filter below separates the second group from the first, and the twenty largest names in it are some of the most recognizable, cash-generative businesses in the market.

<center><sup>GeminIQ Financial Statements for McDonald's (MCD): Stockholders' Equity of -$1.0B sits below zero only because Treasury Stock of $80.5B exceeds Retained Earnings of $72.0B — a buyback-driven deficit, not a loss-driven one.</sup></center>

## The Data

| Rank | Company | Ticker | Total Equity | Treasury Stock | Retained Earnings |
|---|---|---|---|---|---|
| 1 | Booking Holdings Inc. | BKNG | **-$10.8B** | $62.1B | $43.0B |
| 2 | Philip Morris International | PM | **-$6.7B** | $35.5B | $36.1B |
| 3 | Marriott International Inc. | MAR | **-$4.5B** | $29.7B | $19.5B |
| 4 | McKesson Corp | MCK | **-$4.2B** | $34.9B | $22.8B |
| 5 | Fair Isaac Corp | FICO | **-$4.1B** | $10.3B | $5.2B |
| 6 | Avis Budget Group, Inc. | CAR | **-$3.4B** | $10.7B | $0.9B |
| 7 | Cardinal Health Inc. | CAH | **-$2.7B** | $7.6B | $2.0B |
| 8 | MSCI Inc. | MSCI | **-$2.7B** | $10.4B | $5.9B |
| 9 | Altria Group, Inc. | MO | **-$2.6B** | $43.5B | $36.4B |
| 10 | Dell Technologies Inc. | DELL | **-$1.4B** | $16.1B | $6.3B |
| 11 | Verisk Analytics, Inc. | VRSK | **-$1.2B** | $12.1B | $8.0B |
| 12 | McDonald's Corp | MCD | **-$1.0B** | $80.5B | $72.0B |
| 13 | Travel & Leisure Co. | TNL | **-$1.0B** | $7.9B | $2.5B |
| 14 | Jack in the Box Inc. | JACK | **-$0.9B** | $3.2B | $1.8B |
| 15 | Pitney Bowes Inc. | PBI | **-$0.9B** | $3.0B | $2.7B |
| 16 | Equitable Holdings, Inc. | EQH | **-$0.8B** | $5.6B | $8.2B |
| 17 | United Parks & Resorts Inc. | PRKS | **-$0.6B** | $2.2B | $0.8B |
| 18 | DaVita Inc. | DVA | **-$0.5B** | $0.8B | $0.1B |
| 19 | BellRing Brands, Inc. | BRBR | **-$0.5B** | $0.9B | $0.4B |
| 20 | Papa John's International Inc. | PZZA | **-$0.4B** | $1.1B | $0.2B |

<center><sup>GeminIQ's Treasury Stock To Equity metric for Booking Holdings (BKNG), quarterly, 2016–2026 — the ratio form of the same buyback-vs-equity relationship ranked across companies in this post. The ratio turns negative once total equity falls below zero.</sup></center>

## McDonald's: The Cleanest Case in the Data

**[McDonald's](/stocks/MCD)** is the sharpest illustration in this list. The company's **$72.0 billion** in retained earnings is larger than the total stockholders' equity of most companies on the S&P 500, and its **$80.5 billion** treasury stock balance exceeds it — the arithmetic difference is the entire **-$1.0 billion** equity figure on the balance sheet. This is not a company that lost money; it is a company that has returned more capital to shareholders over its history than the accounting value of the business it built to generate that capital in the first place.

**[Philip Morris International](/stocks/PM)** and **[McKesson](/stocks/MCK)** tell the same story at different scale — both carry retained earnings that would put total equity solidly positive if treasury stock were excluded from the calculation entirely, and both are large, liquid, dividend-paying businesses that a "negative equity" screen alone would flag as distressed.

## The ASC 842 Distinction Worth Knowing

A separate and unrelated reason a balance sheet can look more levered than it is: operating lease liabilities recognized under ASC 842. Third-party aggregators routinely count these liabilities as debt, even though they are not notes payable and do not carry the same default risk. That distinction does not explain the negative-equity pattern in this study — treasury stock and retained earnings are the entire story here. But it is worth separating from buyback-driven negative equity when reading any balance sheet screen that flags "high leverage" without showing the underlying line items.

## The Method

Total stockholders' equity, treasury stock, and retained earnings are as-filed figures for each company's most recent filing period within the last fifteen months, read directly from GeminIQ's Financial Statements data. The ranking is restricted to companies with negative total equity and positive retained earnings — isolating deficits attributable to repurchases rather than to accumulated losses — and sorted by the magnitude of the equity deficit. GeminIQ's [Treasury Stock To Equity](https://www.geminiq.com/metrics/remaining-metrics/treasury-stock-to-equity) metric expresses the same relationship as a ratio for any individual company on the platform. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position showing negative stockholders' equity on GeminIQ and check retained earnings before assuming distress. A negative-equity company with a large positive retained-earnings balance and a treasury stock line to match is telling a capital-return story, not a solvency one; a negative-equity company with negative retained earnings is a fundamentally different situation. Every reader can run that same check directly against GeminIQ's as-filed data.

## Frequently Asked Questions

### What does negative stockholders' equity mean?

It means a company's total liabilities exceed its total assets on the balance sheet. That can reflect accumulated losses, or — as this study isolates — a company that has simply returned more capital to shareholders through buybacks than the retained earnings that funded them, which is a very different situation.

### Is negative equity from buybacks a warning sign?

Not in the way negative equity from accumulated losses is. In GeminIQ's data, Booking Holdings shows **-$10.8 billion** in equity alongside **$43.0 billion** in retained earnings — a profitable history, with **$62.1 billion** parked in treasury stock. The deficit reflects a capital-allocation choice, not a solvency problem.

### How can you tell if negative equity comes from losses or buybacks?

Check retained earnings alongside total equity. A negative-equity company with positive retained earnings and a treasury stock balance large enough to explain the gap is a buyback-driven case; a negative-equity company with negative retained earnings reflects accumulated losses instead.

### How many companies does this study cover?

**31** companies in GeminIQ's current filing snapshot show negative total stockholders' equity alongside positive retained earnings — the specific combination that identifies a deficit built by buybacks rather than losses.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=buybacks-into-negative-equity)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Rankings are computed from GeminIQ's Financial Statements data across the described universe and snapshot window.

---

## Blog: Capex Intensity by Sector: What Filings Show
source: https://www.geminiq.com/blog/capex-intensity-by-sector-filings

### Capex Intensity by Sector: What Filings Show
Capex intensity by sector, measured against depreciation rather than revenue, shows a majority of companies currently spending less on capex than they are depreciating their existing asset base.

**[Oracle Corp](/stocks/ORCL)** is currently spending capex at **7.3x** its own depreciation and amortization. **[Alphabet Inc.](/stocks/GOOGL)** is running **5.2x**. Both numbers are visible proof of the AI infrastructure buildout everyone already knows is happening — but the more useful comparison sits on the other side of the ledger, where the majority of the filing universe is running the opposite pattern: spending less on capex than it is depreciating the assets already on the books.

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period for non-financial companies with usable capex and depreciation data — **3,191 companies** at the most recent snapshot. A persistence check runs separately across **6,676 companies** with at least three of the last four quarterly trailing-twelve-month readings available. Every figure is drawn directly from as-filed capex and depreciation-and-amortization line items via GeminIQ's Financial Statements data, with the top and bottom **1%** of each sector's distribution trimmed.

## The Pattern

Capex as a share of revenue is the number most benchmark tables lead with, and it varies enormously by sector — from roughly **1%** of revenue in Wholesale Trade to nearly **10%** in Transportation, Communications & Utilities. But the ratio that actually says something about a business's trajectory is capex against its own depreciation, not against revenue. A company spending less on capex than it is depreciating is, asset by asset, not fully replacing what it uses up. The universe median currently sits at **0.68x** — the typical company is running capex at barely two-thirds of its depreciation charge. **55.0%** of companies with sufficient recent history have run below that 1x line in every one of their last four quarterly trailing-twelve-month readings, not just the latest one.

## The Data

| Sector | N | Capex / Revenue (median) | Capex / D&A (median) |
|---|---|---|---|
| Transportation, Communications & Utilities | 291 | **9.8%** | **0.99x** |
| Mining | 142 | **6.7%** | **0.69x** |
| Agriculture, Forestry & Fishing | 29 | **3.3%** | **0.37x** |
| Retail Trade | 204 | **2.7%** | **0.97x** |
| Manufacturing | 1,557 | **2.5%** | **0.70x** |
| Services | 812 | **1.3%** | **0.43x** |
| Wholesale Trade | 96 | **1.0%** | **0.68x** |
| Construction | 60 | **0.9%** | **1.04x** |
| **Universe (ex-financials)** | **3,191** | **2.3%** | **0.68x** |

Construction and Wholesale Trade sit under the 200-company floor GeminIQ applies to Filing Data Study buckets and should be read as directional. Every other sector's median capex-to-D&A ratio sits at or below 1.0x (Construction, at 1.04x, is the one exception, and it is one of the two thin buckets) — including Transportation, Communications & Utilities, the most capital-intensive sector on a revenue basis, which still runs a median of just **0.99x**. The revenue-based ratio makes some sectors look capital-hungry and others look capital-light; the depreciation-based ratio shows that almost none of them, at the median, are spending enough to fully replace what they're using up.

<center><sup>GeminIQ data study: capex as a percentage of revenue and as a multiple of depreciation & amortization, by SIC sector, across 3,191 non-financial companies, as-filed. Built from as-filed 10-K/10-Q data via GeminIQ. n = 3,191 companies, trailing-twelve-months as of the most recent filing within the last 15 months.</sup></center>

## The Extremes

**[Oracle Corp](/stocks/ORCL)** and **[Alphabet Inc.](/stocks/GOOGL)**, at **7.3x** and **5.2x** capex-to-D&A respectively, sit far above every sector median in this study — the filed evidence of a buildout cycle large enough to be reshaping the Services sector's own aggregate numbers. **[McDonald's Corp](/stocks/MCD)**, at **7.7x**, is the less obvious name on this list: a mature, franchise-heavy restaurant chain running capex intensity in the same range as the AI infrastructure builders, reflecting a multi-year push into company-operated restaurant reinvestment and technology upgrades that doesn't show up in the "McDonald's is a slow-growth compounder" framing most investors default to.

At the other end, **[Baxter International](/stocks/BAX)** is running capex at just **0.3x** its own depreciation charge, and **[Twilio Inc.](/stocks/TWLO)** at **0.9x** — both companies effectively harvesting their existing asset base rather than reinvesting in it. Neither figure alone proves decline; a low-capex-intensity software or services business can be a genuine feature of the model rather than a warning sign. The distinction is whether the pattern holds for multiple consecutive periods or reflects one light quarter, which is exactly what the persistence check above is built to separate.

## The Method

Capex-to-revenue and capex-to-D&A are both computed from as-filed trailing-twelve-month figures via GeminIQ's Financial Statements data, for each company's most recent filing period within the last fifteen months. The persistence figure — companies running capex below D&A in every one of their last four quarterly TTM readings — was computed separately across the fuller history in GeminIQ's lake, requiring at least three of the last four quarterly snapshots to be present. Sectors are grouped by SIC division from each company's own filed SIC code. This is a historical distribution measured across the current filing snapshot and recent history, not a forecast. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's Financial Statements on GeminIQ, divide its trailing capex by its trailing depreciation and amortization, and check whether that ratio has been below 1.0x for more than one recent period — a single light quarter is normal, but a sustained run below 1x, especially outside a capital-light sector like Services, is the kind of signal a headline revenue number won't show. Every reader can rebuild this check for their own holdings directly from GeminIQ's as-filed data.

## Frequently Asked Questions

### What is a good capex-to-depreciation ratio?

There's no fixed threshold, but a ratio persistently below 1.0x means a company is spending less on capex than it's depreciating its existing asset base. In GeminIQ's data, the universe median currently sits at **0.68x**, and **55.0%** of companies with sufficient history have run below 1x in every one of their last four quarterly readings.

### What does it mean when a company's capex is below its depreciation?

Asset by asset, the company is not fully replacing what it uses up in a given period. It isn't automatically a warning sign — a low-capex-intensity software or services business can be a genuine feature of the model — but a sustained run below 1x outside a capital-light sector is worth a closer look.

### Which sectors have the highest capex intensity?

By capex-to-revenue, Transportation, Communications & Utilities leads at **9.8%** of revenue in GeminIQ's data. But even that sector's capex-to-D&A ratio sits at just 0.99x — nearly every sector's median capex-to-depreciation ratio sits at or below 1.0x, regardless of how capital-intensive it looks on a revenue basis.

### How many companies does this study cover?

**3,191** non-financial companies with usable capex and depreciation data at the most recent snapshot, plus a persistence check across 6,676 companies with sufficient recent quarterly history.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capex-intensity-by-sector-filings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Sector medians, quartiles, and the multi-quarter persistence figure are computed from GeminIQ's Financial Statements data across the described universe and snapshot window.

---

## Blog: A Capital Allocation Scorecard Built From Filings
source: https://www.geminiq.com/blog/capital-allocation-scorecard-filings

### A Capital Allocation Scorecard Built From Filings
Every dollar of free cash flow a company generates gets deployed to one of five places — reinvestment, acquisitions, debt paydown, dividends, or buybacks — and management picks the mix. This guide scores all five levers using only what a 10-K and 10-Q disclose: how to tell maintenance capex from growth capex, whether a buyback was actually executed or just authorized, whether debt paydown is real deleveraging or just refinancing, and why M&A is the hardest of the five to verify from filings alone.

Every dollar of free cash flow a company generates gets deployed somewhere — reinvested in the business, spent acquiring another one, used to pay down debt, returned as a dividend, or used to buy back stock. Management picks the mix. Reading a company's own filings over several years shows exactly which mix it actually chose, at what pace, and whether the choice created value or just moved cash around. Most investor attention goes to the two most visible levers — dividends and buybacks — while the other three go largely unscored, even though a bad decision on any one of them can offset good decisions on the rest.

This guide covers all five uses of capital as a single scorecard, built entirely from what a 10-K and 10-Q actually disclose: what each lever looks like when it's working, what it looks like when it isn't, and where the deeper mechanics of the levers already covered in depth elsewhere on this site are worth reading further.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-allocation-scorecard-filings)**

---

## Table of Contents

- [The Five Uses of Capital](#the-five-uses-of-capital)
- [Lever 1: Reinvestment — Is Capex Building the Business or Just Maintaining It?](#lever-1-reinvestment-is-capex-building-the-business-or-just-maintaining-it)
- [Lever 2: Debt Paydown — Deleveraging vs. Treading Water](#lever-2-debt-paydown-deleveraging-vs-treading-water)
- [Lever 3: Dividends — The Floor, Not the Whole Story](#lever-3-dividends-the-floor-not-the-whole-story)
- [Lever 4: Buybacks — Execution, Not Announcement](#lever-4-buybacks-execution-not-announcement)
- [Lever 5: M&A — The Lever With the Weakest Filed Evidence](#lever-5-ma-the-lever-with-the-weakest-filed-evidence)
- [Scoring the Whole Picture](#scoring-the-whole-picture)
- [Running the Scorecard on GeminIQ](#running-the-scorecard-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## The Five Uses of Capital

It's tempting to treat cash sitting on the balance sheet, unassigned to any of the five levers, as a neutral non-choice — capital that just hasn't been decided yet. That's rarely accurate: every dollar of free cash flow a business generates has exactly five active destinations — reinvestment in the existing business (capex and R&D), acquiring another business, paying down debt, dividends, and share repurchases — and cash that isn't deployed to one of them doesn't wait in limbo. It accumulates on the balance sheet, which is itself a sixth, passive choice worth noticing when it persists for multiple years without explanation.

Scoring a company's capital allocation means asking the same question of all five: given the returns available elsewhere, was this the highest-value use of that dollar? Filings can't answer the counterfactual directly, but they can show the pattern of choices clearly enough to judge the discipline behind them.

---

## Lever 1: Reinvestment — Is Capex Building the Business or Just Maintaining It?

On its own, capex running well above depreciation looks like clean evidence of growth investment. That reading only holds once the spending is shown to be earning a return — something the capex line by itself can't demonstrate. Capital expenditures split into two categories that matter enormously for how to read them, even though most filings don't separate them explicitly: maintenance capex, spent just to keep existing assets functioning, and growth capex, spent to expand capacity or capability. A company whose capex roughly tracks depreciation, quarter after quarter, is likely running close to maintenance-only spending — a mature, harvest-mode profile. A company whose capex runs well above depreciation, especially alongside genuine revenue growth, is reinvesting for expansion.

Comparing revenue growth against the cumulative capex that preceded it, over a multi-year window, is the closest a filing-based check gets to answering the return question directly — a business whose capex has scaled up without a corresponding acceleration in revenue or margin is a business spending more to generate the same result.

---

## Lever 2: Debt Paydown — Deleveraging vs. Treading Water

On its own, a shrinking debt balance reads as deleveraging. That reading only holds when the decline is funded by scheduled principal repayment from operating cash flow — not by simply refinancing debt into new debt at maturity, which can leave the headline balance looking just as stable. Debt paydown is the least glamorous of the five levers, but it's also the easiest to score cleanly, because the entire question is visible on the balance sheet. A company rolling debt forward at maturity isn't deleveraging even if the headline balance looks stable, and a company truly paying down principal ahead of schedule is making a real capital allocation choice rather than a routine one.

[Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained) trending down over several consecutive periods, alongside declining absolute debt levels rather than just a growing EBITDA denominator, is the cleanest filed signal that this lever is being used deliberately rather than by default.

---

## Lever 3: Dividends — The Floor, Not the Whole Story

On its own, dividend yield reads as the full measure of how much cash a company returns to shareholders. That reading is incomplete for any company that also runs a buyback program: a dividend is the most visible and most conservatively read capital return signal, precisely because a cut carries such a heavy market penalty that management treats it as a floor rather than a variable — and that same conservatism is exactly why the yield alone leaves out part of the picture. [our full breakdown of shareholder yield](/blog/shareholder-yield-dividends-buybacks-explained) covers why the combined dividend-and-buyback figure is the more complete measure, and what specifically breaks when a screener relies on dividend yield alone.

For scoring purposes, the dividend lever comes down to sustainability: does free cash flow comfortably cover the dividend with room to spare, or is the payout ratio creeping toward or past what the business actually generates in cash?

---

## Lever 4: Buybacks — Execution, Not Announcement

It's tempting to read a buyback announcement as capital already returned to shareholders. It doesn't, necessarily — an authorized repurchase program and an executed one are two entirely different things, and only one of them shows up as an actual cash outflow in the filing, which is exactly why buybacks are the lever most vulnerable to being scored on the wrong number. The specific tags behind this — `Payments For Repurchase Of Common Stock` for the actual repurchase, and the separate tag covering tax withholding on vested equity awards, which many platforms incorrectly merge into the same figure — are covered in detail in [our XBRL tags guide](/blog/xbrl-tags-fundamental-investors-guide).

For scoring purposes, this lever reduces to one question — did the share count actually fall — and that question has its own dedicated coverage rather than a summary here. [Do Buybacks Reduce Share Count?](/blog/do-buybacks-reduce-share-count) works through the arithmetic, [Companies Reducing Share Count](/blog/companies-reducing-share-count) and [Companies That Dilute Shareholders](/blog/companies-that-dilute-shareholders) show both outcomes at company level, and [Stock Buybacks vs. Stock Compensation](/blog/stock-buybacks-vs-stock-compensation) covers the offset that decides which of the two a company lands in. Whether a repurchase was funded from operating cash or from borrowing is its own separate question, worked through in [Bed Bath & Beyond's buyback and bankruptcy](/blog/bed-bath-beyond-buyback-bankruptcy).

---

## Lever 5: M&A — The Lever With the Weakest Filed Evidence

Acquisitions are the hardest of the five levers to score from filings alone, and that difficulty is itself informative. A completed acquisition shows up clearly enough — the cash paid, the assets and goodwill added to the balance sheet — but the question that actually matters, whether the acquisition earned back its cost, plays out over years and rarely gets a clean, isolated answer in any single subsequent filing.

The best filed proxy available is tracking return on invested capital before and after a material acquisition closes. A company whose consolidated ROIC declines and stays lower for several years following a large deal is showing, in aggregate, that the acquired business is diluting returns rather than adding to them — even when management's own commentary continues to frame the deal as a success. Goodwill impairments, when they eventually arrive, are the filing's own admission that this was the outcome; the ROIC trend is the earlier, unofficial version of the same signal.

---

## Scoring the Whole Picture

The five levers, side by side, with the filed evidence each one is scored from:

| Lever | Filed evidence to pull | What a good score looks like | What to flag | Score threshold |
| --- | --- | --- | --- | --- |
| 1. Reinvestment | Capital expenditures against depreciation, across multiple years, alongside revenue and margin | Capex above depreciation with genuine revenue growth behind it, or capex tracking depreciation in a deliberate harvest-mode business | Cumulative capex scaling up without a corresponding acceleration in revenue or margin | Capex &divide; D&A above ~**1.2&times;** reads as growth; near **1.0&times;** is maintenance; below **1.0&times;** sustained is underinvestment |
| 2. Debt paydown | Total debt on the balance sheet, principal activity on the cash flow statement | Absolute debt declining from operating cash flow, with leverage falling alongside it | Debt rolled forward at maturity while the headline balance looks stable | Total debt falling year over year while cash is flat or rising is real deleveraging; debt flat with maturities pushed out is refinancing |
| 3. Dividends | Dividends paid, against free cash flow | Free cash flow covering the dividend with room to spare | A payout ratio creeping toward or past what the business generates in cash | Free cash flow &divide; dividends paid above ~**2&times;** is comfortable coverage; below **1&times;** means the payout is funded from somewhere other than operations |
| 4. Buybacks | `Payments For Repurchase Of Common Stock`, and the filed diluted share count history | Share count actually declining over the period | An authorization announced but not executed; repurchases merged with tax withholding on vested equity awards | Diluted share count down year over year is execution; flat or rising while repurchases are reported means compensation is absorbing them |
| 5. M&A | Cash paid for acquisitions, goodwill added, ROIC before and after the deal closes | ROIC holding or improving in the years after a material acquisition | ROIC declining and staying lower for several years; goodwill impairments arriving later | ROIC in the two years after close against the two years before &mdash; flat or lower means the deal has not yet earned its cost |

No company scores well on all five levers simultaneously, because the right mix depends on the business's stage rather than a fixed ideal. A business in heavy growth-capex mode should show relatively little in dividends or buybacks — that allocation is correct for a company still funding expansion internally. A mature, slow-growth business running large buybacks and minimal capex is making the correct call for its own stage, returning cash once the growth opportunities to reinvest it in have narrowed. The scorecard works as a consistency check: whether what a company says its capital allocation priorities are matches what the filed cash flow statements actually show it did.

The pattern worth real scrutiny is a mismatch: a management team narrating disciplined, returns-focused capital allocation while the filed evidence shows debt-financed buybacks, acquisitions that never earned their cost back, and reinvestment that isn't translating into growth. None of those three, alone, is disqualifying. All three together, over multiple years, is a management team whose actions and its own narrative have quietly diverged.

---

## Running the Scorecard on GeminIQ

Every input this scorecard needs is a line item on the cash flow statement or the balance sheet, tracked across multiple periods: capital expenditures, cash paid for acquisitions, debt principal activity, dividends paid, and net share repurchases. GeminIQ's [Financial Statements](/features#financial-statements) view carries every one of these as-filed, and the [Custom Tables](/features#custom-tables) builder puts them side by side across as many quarters as needed to see the trend rather than a single snapshot.

The as-filed part is doing real work in that sentence. A scorecard built from an aggregator's processed figures inherits whatever bucketing that aggregator chose — repurchases merged with equity-award withholding, acquisition cash folded into a general investing total — and those are precisely the distinctions three of these five levers are scored on. Getting to the underlying document is the alternative, which is the workflow our comparison against [BamSEC](/competitor-comparison/bamsec) covers.

The two calculated metrics that tie the whole scorecard together are [Free Cash Flow](/metrics/calculated-values/free-cash-flow) — the total pool being allocated across all five levers in the first place — and [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), the metric that ultimately reveals whether the sum of all five decisions actually created value or just moved cash from one place to another.

---

## Frequently Asked Questions

### What are the five uses of capital?

Reinvestment in the business (capex and R&D), acquiring other companies, paying down debt, paying dividends, and repurchasing shares. Every dollar of free cash flow a company generates goes to one of these five, or accumulates on the balance sheet as a passive sixth option.

### Which capital allocation lever is easiest to verify from filings?

Debt paydown and buybacks are both directly traceable to specific cash flow statement line items. Dividends are similarly clean. M&A is the hardest to score, because whether an acquisition actually earned back its cost only becomes visible over several years, if it becomes visible at all.

### Is it bad if a company doesn't pay a dividend or run buybacks?

Not on its own. A company reinvesting heavily in genuine growth capex, or paying down debt aggressively, may correctly have little left over for dividends or buybacks — the right allocation depends entirely on the returns available to the business at its current stage, not on matching a generic capital-return profile.

Five levers, one pool of cash, and a filing history that shows exactly how each dollar actually got used — reading it as a whole tells you more about a management team than any single ratio on its own ever could.

---

## Related Reading

- [Shareholder Yield: Dividends and Buybacks Explained](/blog/shareholder-yield-dividends-buybacks-explained) — the full mechanics behind Levers 3 and 4.
- [XBRL Tags: A Fundamental Investor's Guide](/blog/xbrl-tags-fundamental-investors-guide) — the exact tags behind buybacks, dividends, and equity compensation.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — the pool of capital this whole scorecard is allocating.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-allocation-scorecard-filings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Capital IQ Alternative: As-Filed SEC Filing Data
source: https://www.geminiq.com/blog/capital-iq-alternative-sec-data

### Capital IQ Alternative: As-Filed SEC Filing Data
A Capital IQ alternative built on as-filed SEC data. This post compares the two on the normalization axis rather than the price axis, and explains what standardization changes about a financial statement line item before an analyst ever sees it.

S&P Capital IQ Pro is the institutional standard for financial data, and it earns that position. Anyone searching for Capital IQ alternatives is not searching because the product is bad. When S&P Global Market Intelligence launched the Pro platform in September 2021, it described coverage spanning sixty-two thousand public companies and eighteen million private companies, credit risk indicators from S&P Global Ratings, Dow Jones Newswires coverage, an AI-assisted Document Viewer, and Office Tools that push hundreds of prebuilt models into Excel and PowerPoint. Nothing on this page argues that a smaller product replaces that.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-iq-alternative-sec-data)**

The argument is narrower, and it is the one almost every "Capital IQ alternative" comparison skips. Most of those comparisons are written on the price axis: Capital IQ is expensive, this other thing is cheap, therefore consider the other thing. That framing loses, because a firm that needs global private company coverage and credit analytics does not switch to save money. It also misses what actually changes when a fundamental investor moves from one platform to another.

The axis that matters is normalization.

## Table of Contents

- [What Capital IQ Actually Sells](#what-capital-iq-actually-sells)
- [How Capital IQ Competitors Are Usually Compared](#how-capital-iq-competitors-are-usually-compared)
- [The Normalization Axis, Not the Price Axis](#the-normalization-axis-not-the-price-axis)
- [Where a Standardized Figure and a Filed Figure Part Ways](#where-a-standardized-figure-and-a-filed-figure-part-ways)
- [What As-Filed Means in Practice](#what-as-filed-means-in-practice)
- [Who Should Stay on Capital IQ](#who-should-stay-on-capital-iq)
- [When a Capital IQ Alternative Actually Fits](#when-a-capital-iq-alternative-actually-fits)
- [Frequently Asked Questions](#frequently-asked-questions)

## What Capital IQ Actually Sells

Capital IQ sells comparability across a universe that does not naturally compare.

Public companies in dozens of countries, reporting under different accounting standards, using thousands of different line item labels, filing on different calendars, have to be forced into one schema before anyone can screen across them. That work is enormous, and it is the product. An analyst who opens Capital IQ and pulls revenue for a Japanese industrial, a German bank, and a US software company gets three numbers that sit in the same row of the same template.

That is not a side effect of the platform. That is the platform.

The same logic explains why Capital IQ data shows up underneath products that are not Capital IQ. Broad retail and prosumer platforms license standardized fundamentals rather than building an extraction pipeline, which means a chain of tools that look independent are often reading from the same normalized layer. An investor comparing four platforms may be comparing four interfaces to one dataset.

None of that is a criticism. It is a description of what standardization buys and what it costs.

## How Capital IQ Competitors Are Usually Compared

Search "Capital IQ competitors" and the results sort into two piles.

The first pile is peer terminals — Bloomberg, FactSet, LSEG Workspace, and the other institutional platforms that compete with CapIQ on the same ground: global coverage, private company data, credit analytics, estimates consensus. Those are genuine substitutes, and a firm evaluating them is running a procurement exercise where coverage and price are the variables.

The second pile is everything cheaper. Those comparisons almost always run on cost, because cost is the easiest axis to chart. They are also the least useful, because a firm that needs private company coverage does not abandon it to save money, and a fundamental investor who never touches private companies was never paying for the right thing to begin with.

Neither pile asks the question that changes what appears on your screen.

## The Normalization Axis, Not the Price Axis

Every standardized financial dataset has to answer the same question thousands of times: what does this company's line item mean, and which bucket does it belong in?

That question has no mechanical answer. A company reports a liability under a label of its own choosing, describes its composition in a footnote, and moves on. A data provider building a comparable template has to decide whether that liability belongs with the items other companies report under a similar name, whether it should be split apart so a component can be tracked separately, and whether the resulting bucket should keep the company's original label or the template's.

Each of those decisions is defensible. Each of them is also invisible on the screen.

That is the cost of standardization, and it is not a bug to be fixed. A template that preserved every company's idiosyncratic structure would not be a template. The moment you make ten thousand companies comparable, you have accepted that the number on screen answers "what is the standardized value?" rather than "what did this company file?"

For most institutional work, that trade is correct. Screening a global universe, running a comp set, or benchmarking margins across an industry all require the standardized answer. The filed answer would be unusable at that scale.

The trade stops being obviously correct at the moment the workflow narrows to one company and one filing.

## Where a Standardized Figure and a Filed Figure Part Ways

The divergence is rarely a mistake. It is almost always a methodology choice that reconciles cleanly once you can see both sides.

The pattern repeats in three recognizable shapes. A company reports two distinct cash outflows on separate lines and a standardized template shows their sum, because the template has one row where the filing has two. A company reports one liability total and a standardized template shows two rows, because the template tracks a component the filing folded into a broader caption. Or the label survives while the contents change, which is the most dangerous version, because nothing on screen signals that the row means something different than it did in the 10-K.

The first two are recoverable. An analyst who notices a variance can usually reconcile it from the footnote detail. The third one is not, because there is nothing to notice.

The consequence is not that a model built on standardized inputs is wrong. It is that the model inherits a methodology the modeler never chose and cannot inspect. Leverage ratios move when a lease obligation is pulled out of a liability caption. [Invested capital](/metrics/calculated-values/invested-capital) moves with it. Anything downstream of those inputs moves too.

A documented case makes the shape concrete. [Apple's](/stocks/AAPL) FY2025 10-K, filed October 31, 2025, reports Repurchases of common stock at **$90,711M** and Payments for taxes related to net share settlement of equity awards at **$5,960M** — two cash outflows, reported on two lines, carrying two XBRL tags. A widely used retail aggregator displays one Repurchase of Common Stock line at **$96,671M**, which is the sum of the two.

The reconciliation is exact, and the merge is defensible for a template with one buyback row. It is also the difference between a [share repurchase](/blog/do-buybacks-reduce-share-count) program and a payroll tax obligation on equity compensation. An analyst measuring capital allocation from the merged figure overstates the buyback by **$5,960M** and has no way to detect it, because the label reads the way a buyback line should read.

That discrepancy is documented against a different platform than the one this post discusses, and the mechanism belongs to standardization rather than to any vendor. The full set of documented cases is in [third-party financial data problems](/blog/third-party-financial-data-problems).

## What As-Filed Means in Practice

"As-filed" is a claim about chain of custody, not about accuracy.

Both approaches read the same source document. The difference is what survives the trip. GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR and preserves the company's reported structure, including the [XBRL tag](/blog/what-is-xbrl) behind each value, so a line item on the screen can be matched to the specific fact in the specific filing that produced it. There is no mapping layer between the filing and the display, which means there is no mapping decision to reverse-engineer.

That changes what an analyst can do when a number looks wrong. On a normalized platform, an unexpected value sends you looking for the methodology. On a filing-first platform, it sends you to the filing.

The rest of the product follows from that premise rather than the other way around. [Financial Statements](/features#financial-statements) show the company's own line item structure across quarters and years. [Custom Tables](/features#custom-tables) let an analyst build a view from specific reported items rather than template rows. [Calculated Metrics](/features#calculated-metrics) such as [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from those same as-filed inputs, so a metric can be checked against the numbers that produced it. [Stock Screeners](/features#screener) run on the same layer.

The scope is deliberately narrower: US public company fundamentals, sourced from EDGAR. That is the whole universe the product covers, and covering less is what makes the traceability possible.

## Who Should Stay on Capital IQ

Anyone whose job requires the things standardization exists to deliver.

Private company coverage has no filing-based substitute, because private companies do not file. Credit analytics, ratings research, global comp sets across accounting regimes, sell-side estimate consensus, deal and transaction screening, and industry-specific operational metrics for banking, insurance, real estate, or energy are all real institutional needs that a US-filings product does not attempt to serve. An investment banking analyst building a cross-border comp table is doing the exact job Capital IQ was designed for.

Switching platforms to save money in that situation is not a cost decision. It is a coverage decision with a cost story attached, and it usually ends badly.

The honest version of the alternative question is not "what is cheaper than Capital IQ." It is "which part of my workflow does Capital IQ answer, and which part does it answer at one remove from the filing?"

## When a Capital IQ Alternative Actually Fits

The break point arrives when the analysis stops being comparative and starts being forensic.

Building a model on a single US company, auditing a balance sheet caption against its footnote, checking whether a metric's inputs are the inputs you think they are, tracking a line item's behavior across a decade of filings, or verifying a figure before it goes into a memo you have to defend — these all depend on the number matching the filing exactly. Standardization is not a help in that work. It is a layer to be undone.

That is the workflow GeminIQ is built for, and it is why the comparison is not really a competition. Capital IQ answers "how does this company compare to everything else?" A filing-first platform answers "what did this company actually report?" Most serious research needs both answers, and the mistake is assuming one tool has to give you both.

For a feature-by-feature breakdown against the platform itself, see the [GeminIQ vs. S&P Capital IQ comparison](/competitor-comparison/sp-capital-iq). The same normalization question applies to the [Bloomberg Terminal alternative](/blog/bloomberg-terminal-alternative-sec-data) decision and to [Fiscal.ai](/blog/fiscal-ai-alternative-sec-data), which licenses the same S&P Global Market Intelligence fundamentals underneath its AI layer. For the mechanics of what happens to a filing between EDGAR and a screen, [how financial data reaches investors](/blog/how-financial-data-reaches-investors) walks the whole chain.

The best Capital IQ alternative is not a cheaper terminal. It is the source document, made usable.

## Frequently Asked Questions

### What is the best Capital IQ alternative for SEC filing data?

For US public company fundamentals, the alternative worth evaluating is a platform that extracts directly from SEC EDGAR and preserves as-filed line items with XBRL tag traceability, rather than one that licenses standardized data from another aggregator. Many platforms marketed as Capital IQ alternatives license S&P Global Market Intelligence data underneath, which means the normalization layer is identical even though the interface is not.

### What are the main Capital IQ competitors?

At the institutional tier, the direct competitors are Bloomberg Terminal, FactSet, and LSEG Workspace — platforms competing on the same ground of global coverage, private company data, credit analytics, and estimates consensus. Below that tier sit prosumer platforms, many of which license standardized fundamentals rather than extracting from primary filings, which makes them interface competitors more than data competitors. A filing-first platform competes on a different axis entirely.

### What is the difference between as-filed and standardized financial data?

As-filed data preserves the line items, labels, and structure the company used in its own 10-K or 10-Q. Standardized data maps those line items into a common template so companies can be compared against each other. Both read the same filing. Standardized data answers "what is the comparable value across companies," and as-filed data answers "what did this company report."

### How much does S&P Capital IQ cost?

S&P Global does not publish pricing for Capital IQ Pro. The platform is quote-only, and the login page routes prospective users to a demo request rather than a price. Publicly circulating third-party estimates disagree with each other by more than an order of magnitude, which is covered in detail in the post on [Capital IQ pricing and cost](/blog/capital-iq-pricing-cost-explained).

### Is SEC EDGAR data free?

The filings themselves are free and public on SEC EDGAR, including the XBRL data behind them. Turning that into usable, comparable statement history is engineering work, and GeminIQ's own Free plan gives away part of that work at no cost: 3 years of history and 24 calculated metrics, with the same XBRL traceability as the paid product. The full 17-plus years of history, 90-plus metrics, and the Stock Screener are what the paid Annual or Monthly plan charges for.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-iq-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- S&P Global Market Intelligence press release, "S&P Global Market Intelligence launches S&P Capital IQ Pro," September 7, 2021, for platform coverage and feature claims.
- S&P Capital IQ login and demo-request flow, reviewed August 2, 2026, for the absence of published pricing.
- GeminIQ S&P Capital IQ comparison page: /competitor-comparison/sp-capital-iq

---

## Blog: S&P Capital IQ Pricing: What It Costs and Alternatives
source: https://www.geminiq.com/blog/capital-iq-pricing-cost-explained

### S&P Capital IQ Pricing: What It Costs and Alternatives
S&P Capital IQ pricing is not published. This post covers what is actually known about the cost, why the third-party estimates disagree by more than an order of magnitude, and what the underlying filing data costs when sourced directly from SEC EDGAR.

S&P Global does not publish a price for Capital IQ Pro. There is no pricing page, no plan comparison, and no per-seat rate anywhere on the product's own properties. The login screen offers a demo request. That is the entire public answer, and it is the reason this query gets searched so often: the people typing it have usually already looked.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-iq-pricing-cost-explained)**

What fills the vacuum is a layer of third-party procurement sites, review aggregators, and forum posts, each reporting a number with confidence. Read four of them and you will find four different answers. Published estimates for annual cost per user run from roughly **$12,000** at the low end to figures above **$300,000** at the high end, and at least one procurement site contradicts itself inside a single page — quoting a contract range with a median near **$53,000** in one place and a median of **$327,500** in another.

That spread is not sloppiness. It is the actual finding, and understanding why it exists tells you more about what you would be buying than any single number would.

## Table of Contents

- [S&P Capital IQ Cost: What Is Publicly Known](#sp-capital-iq-cost-what-is-publicly-known)
- [Why the Estimates Disagree by 25x](#why-the-estimates-disagree-by-25x)
- [Why Bloomberg's Number Is Known and This One Is Not](#why-bloombergs-number-is-known-and-this-one-is-not)
- [The Costs That Do Not Appear in the Quote](#the-costs-that-do-not-appear-in-the-quote)
- [What the Underlying Filing Data Costs](#what-the-underlying-filing-data-costs)
- [Deciding Without a Number](#deciding-without-a-number)
- [Frequently Asked Questions](#frequently-asked-questions)

## S&P Capital IQ Cost: What Is Publicly Known

Three things are verifiable without a sales call.

Capital IQ Pro — CapIQ, in the shorthand most of its users type — is sold by quote, on an annual subscription, through a demo-request flow rather than a checkout. S&P Global Market Intelligence describes the platform as its most comprehensive desktop solution, covering — as of the September 2021 Pro launch announcement — sixty-two thousand public companies and eighteen million private companies, with credit risk indicators from S&P Global Ratings, Dow Jones Newswires, an AI-assisted document viewer, and Excel and PowerPoint integration. And the configuration is modular, spanning private company data, credit analytics, industry-specific datasets, real-time market data, and data feed delivery.

Everything past that is inference from other people's contracts.

The direct version of the answer is that there is no list price to report, because the product does not have one. That is not evasion on S&P's part. It is a consequence of how the thing is sold.

## Why the Estimates Disagree by 25x

A quote-only enterprise data contract is priced on variables that have nothing to do with each other.

Firm type and size come first — a two-person advisory shop and a global asset manager are not being sold the same product under the same terms even when the interface is identical. Seat count matters, and so does whether those seats need real-time exchange data, which carries exchange fees that pass straight through. Module selection matters enormously: private company coverage, credit analytics, industry-specific operational datasets, and Preqin or Visible Alpha content are separable, and a base seat with none of them is a different purchase than a fully loaded one. Delivery method matters — desktop access and an API or bulk data feed are priced on entirely different logic. Contract length and region move the number again.

Multiply those out and there is no single number to publish, because there is no single product being sold. A **$12,000** seat and a **$300,000** contract can both be accurate reports of what a real customer paid.

This is why aggregator estimates are not just imprecise but structurally unreliable. A site reporting a median from four buyer submissions is reporting the median configuration of four unnamed firms, not a price. Treat any specific figure you find for Capital IQ as a data point about someone else's contract.

## Why Bloomberg's Number Is Known and This One Is Not

The contrast makes the mechanism obvious.

Bloomberg also declines to publish pricing, and yet the number circulates freely and consistently: widely reported figures put a single Bloomberg Terminal seat near **$31,980** per year in 2026, dropping to roughly **$28,320** per seat for firms running two or more, typically on a two-year minimum commitment. Independent trackers converge on those figures because the underlying product is uniform. A terminal is a terminal. There is one bundle, everyone gets the same thing, and price increases are announced across the base — which is why a reported **6.5%** increase applied to renewals from January 2025 shows up in multiple sources with the same arithmetic.

Capital IQ has no equivalent because it has no equivalent bundle. That difference is worth more than the price itself: it tells you the sales process will be a scoping exercise, and that what you end up paying depends heavily on how well you can define which modules you actually need before someone else defines it for you.

## The Costs That Do Not Appear in the Quote

The subscription line is not the total.

Implementation and onboarding are commonly reported as separate charges on enterprise data contracts. Training is often billed. Add-on modules and additional datasets extend the base. Real-time market data carries exchange fees. API and feed delivery are separately licensed. Contracts typically auto-renew with an annual minimum commitment, which converts a one-year evaluation mistake into a multi-year expense.

There is a quieter cost that never appears on any invoice, and for a fundamental analyst it is the expensive one: the time spent reconciling a standardized figure back to the filing it came from. Every hour spent working out why a liability caption on screen does not match the caption in the 10-K is an hour the data was supposed to save.

## What the Underlying Filing Data Costs

For US public company fundamentals, the source material is free.

Every 10-K and 10-Q is public on SEC EDGAR the moment it is filed, complete with the XBRL data behind each reported figure. No subscription gates it. Anyone can download Apple's filing history this afternoon at zero cost.

What is not free is making it usable. Parsing every filing, resolving tag changes as the US GAAP taxonomy is revised year over year, handling restatements and amended filings, reconciling fiscal calendars that do not line up with quarters, and assembling seventeen years of filings into comparable statement history is a sustained engineering problem. That extraction work — not the data — is what a filing-first platform charges for, and it is why [what XBRL is](/blog/what-is-xbrl) and [how financial data reaches investors](/blog/how-financial-data-reaches-investors) are worth understanding before evaluating any platform's price.

The pricing question then splits cleanly. An institutional data contract buys breadth: global coverage, private companies, credit analytics, estimates, and the standardization that makes them comparable. A filing-first product buys depth on a narrower universe: as-filed 10-K and 10-Q line items with [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) traceability, [Financial Statements](/features#financial-statements), [Calculated Metrics](/features#calculated-metrics), and [Stock Screeners](/features#screener) built from the same source records.

GeminIQ publishes its pricing on the [pricing page](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-iq-pricing-cost-explained). That is a deliberate difference in kind, not just in degree — a product with one configuration can print a number, and a product configured per customer cannot.

## Deciding Without a Number

If you are researching Capital IQ pricing because you are deciding whether to start a sales conversation, the useful preparation is not finding a better estimate. It is scoping the requirement first.

Write down which datasets the work actually depends on. If private company coverage, credit analytics, sell-side consensus, or global cross-border comparability appear on that list, no filing-based product substitutes for them and the conversation is worth having. If the list is US public company fundamentals traced back to the filing, the expensive contract is buying capability the workflow will never touch.

The question that saves the most money is not "what does Capital IQ cost." It is "which of the things Capital IQ standardizes does my analysis actually require standardized." Most fundamental investors who work through that list find it shorter than they assumed — and the shorter it gets, the more the unpublished price stops being the relevant unknown.

For a feature-level breakdown, see the [GeminIQ vs. S&P Capital IQ comparison](/competitor-comparison/sp-capital-iq), and for the data-fidelity side of the same decision, the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) post covers what standardization changes before a number reaches your screen. The [Bloomberg Terminal alternative](/blog/bloomberg-terminal-alternative-sec-data) post runs the same cost-versus-job analysis for the other institutional standard.

## Frequently Asked Questions

### How much does S&P Capital IQ cost per year?

S&P Global does not publish pricing. Capital IQ Pro is quote-only, sold on an annual subscription arranged through a demo request. Third-party estimates of annual cost per user circulate widely but disagree by more than an order of magnitude — from roughly **$12,000** to above **$300,000** — because the platform is configured per customer rather than sold as a fixed bundle.

### Why does S&P Capital IQ not publish pricing?

Because there is no single product to price. Cost varies with firm type and size, seat count, which modules and datasets are licensed, whether real-time exchange data is included, whether delivery is desktop or API and feed, contract length, and region. A published number would be wrong for nearly every buyer.

### Is Capital IQ more expensive than a Bloomberg Terminal?

It can be either. A Bloomberg Terminal seat is widely reported near **$31,980** per year in 2026, with multi-seat pricing around **$28,320**, and those figures are consistent across sources because the terminal is a uniform bundle. Capital IQ contracts are reported both well below and well above that range depending on configuration.

### What is the Capital IQ subscription cost for a small firm?

There is no published small-firm rate. Capital IQ subscription cost scales with seat count, module selection, delivery method, and contract length, so a small firm licensing a base desktop seat with no private company data, credit analytics, or real-time feed is buying a materially different product than a fully configured institutional contract. The only way to establish the number is to scope the requirement first and then request a quote.

### Can I get the same SEC filing data for free?

The filings themselves are free on SEC EDGAR, including the XBRL data behind each figure. Free access to a filing is not automatically usable statement history, though — the extraction, tag resolution across taxonomy years, restatement handling, and period alignment are the actual work. GeminIQ's own Free plan does that work at no cost for 3 years of history and 24 calculated metrics; the full 17-plus years and 90-plus metrics are what the paid Annual or Monthly plan charges for.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=capital-iq-pricing-cost-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- S&P Capital IQ login and demo-request flow, reviewed August 2, 2026, confirming no published pricing.
- S&P Global Market Intelligence press release, "S&P Global Market Intelligence launches S&P Capital IQ Pro," September 7, 2021, for coverage and feature claims.
- Cost figures attributed to Capital IQ are third-party procurement and pricing-aggregator estimates, not official vendor pricing, and are cited only to show the range and its inconsistency.
- Bloomberg Terminal per-seat figures are widely reported third-party estimates; Bloomberg does not publish pricing either.
- GeminIQ S&P Capital IQ comparison page: /competitor-comparison/sp-capital-iq

---

## Blog: Carvana Stock Crash and Recovery: What the Filings Showed
source: https://www.geminiq.com/blog/carvana-stock-crash-recovery

### Carvana Stock Crash and Recovery: What the Filings Showed
Carvana's stock fell 98.4% into its 2022 collapse and then climbed more than 6,500% off the bottom — this forensic study reads Carvana's full 10-K and 10-Q history to find out whether both the crash and the recovery were visible in the company's own filings before the market caught up.

**[Carvana](/stocks/CVNA) ($CVNA) closed out 2022 at **$0.95** a share — down **98.4%** from the **$60.36** it traded at eighteen months earlier. The company had just burned through more than a billion dollars in a single quarter and posted negative shareholders' equity for the first time in its public history. By the quarter ended March 31, 2026, that same share closed at **$62.88**, having touched as high as **$84.40** along the way — a recovery of more than **6,500%** off the bottom. The story everyone tells is that Carvana nearly collapsed under a reckless, debt-funded expansion and then staged one of the great comeback rallies in recent market history, more on momentum than on anything visible in the numbers. But standard financial media doesn't read the footnotes twice — once for the fall, and again for the turn. Read Carvana's own 10-Ks and 10-Qs in the order they were filed, and both moves are sitting in the filed record. A debt and inventory buildup stacked three warning signs deep while the stock still traded in the twenties. An operating turnaround showed up in the income statement a full quarter before the balance-sheet fix that grabbed the headlines — and the company's own founders bought heavily on the way down, still missing the actual bottom by seven months and another 95% decline.**

Every figure below is drawn from Carvana Co.'s own 10-K and 10-Q filings, filed between June 2017 and April 2026 — 37 consecutive quarterly filings (9 10-Ks and 28 10-Qs) spanning Carvana's first quarter as a public company through the quarter ended March 31, 2026 — read in the order they were filed and joined to how the stock actually traded in the one to three months after each 10-Q hit SEC EDGAR, and the twelve months after each 10-K.

## The Bet on Bigger

Heading into 2022, the market's read on Carvana was simple: the fastest-growing online used-car retailer in the country was scaling into a durable logistics advantage, and every dollar of new debt was buying market share nobody else could touch.

**The Filing Data:** [Carvana's](/stocks/CVNA) [Total Debt](https://www.geminiq.com/metrics/calculated-values/total-debt) climbed from **$3.66 Billion** in the September 2021 quarter to **$5.41 Billion** by December 2021 — a **47.8%** jump in a single quarter. It kept climbing, to **$6.25 Billion** by March 2022 and **$7.94 Billion** by June 2022, more than doubling in three quarters. [Net Debt](https://www.geminiq.com/metrics/calculated-values/net-debt) moved in lockstep, from **$3.26 Billion** to **$6.74 Billion** over the same stretch. `Vehicle Inventory` grew even faster in percentage terms, from **$1.44 Billion** in the March 2021 quarter to **$3.30 Billion** by March 2022 — up **129.6%** year-over-year. The FY2022 10-K separately shows **$2.20 Billion** under `Payment For Acquisitions, Net Of Cash Acquired`, the cash portion of a major physical-infrastructure purchase completed that year and layered on top of the new debt. Trailing-twelve-month `Interest Expense` rose from **$176 Million** in December 2021 to **$486 Million** by December 2022 — a **176%** increase — and the [Interest Coverage Ratio](https://www.geminiq.com/metrics/leverage-and-debt-ratios/interest-coverage-ratio) had already gone negative well before that climb finished, reading **-0.63x** in December 2021 and **-2.60x** by March 2022.

**The Signal:** A company whose operating earnings can't cover its interest expense before that expense has even finished climbing isn't scaling into an advantage — it's financing a bet that requires the growth rate to hold. Carvana's growth rate wouldn't hold.

<center><sup>GeminIQ Calculated Metrics showing Carvana's Total Debt and Net Debt climbing from $3.66 Billion and $3.26 Billion in Q3 2021 to $7.94 Billion and $6.74 Billion by Q2 2022.</sup></center>

## The Inventory Nobody Could Move

By mid-2022, used-car pricing across the industry was cooling from its pandemic peak, and the sell-side narrative shifted to "sector-wide normalization" rather than company-specific distress. That framing gave Carvana's own numbers less scrutiny than they deserved.

**The Filing Data:** [Gross Profit Margin](https://www.geminiq.com/metrics/margin-metrics/gross-profit-margin) fell from **15.1%** trailing-twelve-months in December 2021 to **13.4%** in March 2022, **11.9%** in June, **10.8%** in September, and **9.2%** by December 2022 — the low point in this entire record. `Net Income (Loss) Attributable To Carvana Co.` on a trailing basis worsened from **-$757 Million** in March 2022 to **-$1.59 Billion** by December 2022, while [Free Cash Flow](https://www.geminiq.com/metrics/calculated-values/free-cash-flow) bottomed at **-$3.35 Billion** trailing-twelve-months in the March 2022 quarter. By December 2022, `Retained Earnings (Accumulated Deficit)` had reached **-$2.08 Billion**, and Total Shareholders' Equity turned negative for the first time in Carvana's public history, at **-$1.05 Billion**. The [Altman Z-Score](https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score) fell from **1.86** in March 2022 to **1.42** in June, **1.30** in September, and **1.09** by December — deep in the distress zone below the 1.81 threshold for five straight quarters. [Carvana's](/stocks/CVNA) stock closed those same four quarters at **$23.86**, **$4.52**, **$4.06**, and finally **$0.95**.

The market's own reaction lagged the filings by a step. The FY2021 10-K, filed February 24, 2022, was followed by a cumulative one-month return of **+13.0%** — the stock didn't even react immediately — before reversing into a cumulative three-month return of **-69.6%** and a twelve-month return of **-94.9%**. The September 2022 10-Q, filed November 3, 2022, was followed by a cumulative three-month return of **-54.8%**, after dipping as low as **-71.8%** two months in.

**The Signal:** Five consecutive quarters in Altman's distress zone, a first-ever negative equity print, and a [gross margin](/metrics/margin-metrics/gross-profit-margin) cut nearly in half — none of that is a sector-wide repricing story. It's a single company's balance sheet buckling in plain sight, a full quarter before the worst of the stock's decline had even happened.

<center><sup>GeminIQ Calculated Metrics showing Carvana's Gross Profit Margin falling from 15.1% (Q4 2021) to 9.2% (Q4 2022), alongside the Altman Z-Score dropping from 2.37 to 1.09 over the same four quarters.</sup></center>

## The Founders Bought In — Just Not at the Bottom

While the balance sheet cracked in full view, the people running the company were buying more of it. A common assumption among investors is that insider buying, especially from a company's own founders, is close to a reliable timing signal — when the people who know the business best start spending their own money, the bottom can't be far off. [Carvana's](/stocks/CVNA) own Form 4 record tests that assumption directly.

**The Filing Data:** On April 26, 2022, Chairman Ernest C. Garcia II (through Verde Investments) and CEO Ernest C. Garcia III together purchased 3,662,500 shares at **$80.00** apiece — a combined **$293.0 Million**. Over the following seven weeks, Garcia II added two more blocks: 793,790 shares at **$21.95** on June 10, and 1,191,468 shares at **$20.74** on June 13, bringing the family's total committed capital across these three dates to **$335.1 Million**. No further purchase from either Garcia appears anywhere in the record after June 13, 2022. The stock kept falling — from that **$20.74** final buy price down to **$0.95** by the close of the December 2022 quarter, a further **95.4%** decline after the family's last recorded purchase. A separate, smaller round of buying showed up that November from other officers and directors: Michael Maroone, Ira Platt, Thomas Taira, Gregory Sullivan, and Daniel Gill together purchased shares at prices between **$6.86** and **$11.13**, a combined **$2.68 Million** — closer to the eventual low than the Garcias' buys, but still **7 to 12 times** the **$0.95** close the stock actually ended the quarter at. No insider purchases appear anywhere in the record for the entire 2023 recovery year; the next one on file is a March 2024 purchase at **$76.68**–**$77.00**, by which point the stock had already recovered roughly **eighteenfold** off its low.

Institutional and insider positioning data in GeminIQ reflects each entity's quarterly SEC filing cadence, not live holdings. On that basis, GeminIQ's Institutional Ownership data shows institutional holders trimming their position from **125.8 Million** shares in September 2022 to **102.9 Million** by September 2023 — reducing, not adding, through the trough and into the early rebound.

**The Signal:** The largest-dollar insider conviction in Carvana's history arrived six to eight months before the actual bottom and still absorbed another **95%** decline. The buying closest to the real low came in smaller size, from directors rather than the founders, and even that missed by a wide margin. Cluster buying here reads as a signal of long-term conviction — not a timing tool, and not a call on the bottom.

<center><sup>GeminIQ data study: Carvana's quarterly closing price, 2021–2023, marked at each Garcia family and director Form 4 purchase date and price. Built from as-filed 10-K/10-Q closing-price data and SEC Form 4 filings via GeminIQ. n = 12 quarterly closes, 2021–2023, with 4 marked purchase events.</sup></center>

## The Quarter the Balance Sheet Reset

By early 2023, commentary on the stock's early rebound largely treated it as speculative froth sitting atop a company still burning cash — a bet on survival, not a read on the fundamentals actually turning.

**The Filing Data:** `Operating Income (Loss)` read **-$132 Million** in the March 2023 quarter — the first quarter it appears as its own filed line item in Carvana's income statement. By June 2023, it turned positive for the first time on record, at **$42 Million**, and held positive again in September at **$48 Million**. `Net Income (Loss) Attributable To Carvana Co.` for that September quarter spiked to **$741 Million** — but that figure is not organic. The same 10-Q recorded a **$878 Million** `Loss (Gain) On Debt Extinguishment`, and `Long-Term Debt, Excluding Current Portion` fell from **$6.54 Billion** in June 2023 to **$5.31 Billion** in September — a **$1.24 Billion** reduction in a single quarter. Total Debt, GeminIQ's full calculated aggregate, fell from **$7.90 Billion** to **$5.93 Billion** over the same stretch.

The market didn't wait for the debt deal to start moving, and it didn't move cleanly, either. The FY2022 10-K, filed February 23, 2023, was followed by a cumulative return of **-24.1%** one month out and **-11.0%** two months out, before reversing to **+4.2%** by month three and accelerating to **+89.2%** by month four and **+404.5%** by month seven — the re-rating was already underway well before the September 2023 debt exchange closed. Yet the June 2023 10-Q — the filing that reported that first positive `Operating Income (Loss)` — was itself followed by a cumulative three-month return of **-32.5%**. [Carvana's](/stocks/CVNA) stock closed that June 2023 quarter at **$5.18**.

**The Signal:** The operating business turned a full quarter before the balance sheet got its dramatic, headline-grabbing fix — and the market punished the stock for three more months even after that operating turn was sitting in the filing. The fix that got the attention wasn't the one that mattered first.

<center><sup>GeminIQ Financial Statements showing Carvana's `Long-Term Debt, Excluding Current Portion` falling from $6.54 Billion to $5.31 Billion in a single quarter, alongside the $878 Million `Loss (Gain) On Debt Extinguishment` recorded in the September 2023 10-Q.</sup></center>

## The Efficiency Turn

A one-quarter debt exchange doesn't sustain [Carvana's](/stocks/CVNA) **89-fold** recovery off a **$0.95** low on its own. What follows in the filings is eleven consecutive quarters of the same signals moving the same direction, together.

**The Filing Data:** `Selling, General And Administrative Expenses` fell from a peak of **$727 Million** in the March 2022 quarter to **$433 Million** by September 2023 — a **40.4%** reduction — even as the business kept operating. [Days Inventory Outstanding](https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding) fell from **76.5 days** in March 2023 to **61.0 days** by December 2023, **52.2 days** by March 2024, and **41.8 days** by March 2025. Gross Profit Margin climbed from that **9.2%** trough to **16.0%** by December 2023 and **21.0%** by December 2024 — more than double the crisis-era low and above every pre-crisis reading in this record. The [Altman Z-Score](/blog/altman-z-score-financial-distress) climbed from its **1.06** trough in March 2023 to **1.88** by March 2024, **2.68** by December 2024, and **3.42** by June 2025 — the first quarter to clear the 2.99 safe-zone threshold — before reaching **3.79** by September 2025. `Retained Earnings (Accumulated Deficit)`, which bottomed at **-$2.29 Billion** in June 2023, turned positive for the first time in the company's history by March 2026, at **$241 Million**.

**The Signal:** Every metric in this section moved the same direction, in the same order, quarter after quarter. A cost structure, an inventory cycle, and a solvency score improving together over eleven straight quarters is not a lucky earnings beat. It's a business that was rebuilt from the balance sheet up.

<center><sup>GeminIQ Calculated Metrics showing Carvana's Days Inventory Outstanding falling from 76.5 days (Q1 2023) to 42.3 days (Q1 2026), alongside Gross Profit Margin climbing from 10.1% to 20.1% over the same stretch.</sup></center>

## What the Filings Said Before the Market Knew

Stack the danger signals against the calendar, and the March 31, 2022 10-Q — filed May 10, 2022 — is the point where three of them sat in the same filing at once: Total Debt at **$6.25 Billion**, more than double its year-earlier level; an [Interest Coverage Ratio](/blog/interest-coverage-ratio-explained) of **-2.60x**; and `Vehicle Inventory` at a then-record **$3.30 Billion** against a Gross Profit Margin that had already fallen to **13.4%** trailing-twelve-months from **15.2%** two quarters earlier. [Carvana's](/stocks/CVNA) stock closed that quarter at **$23.86** — down from its highs, but with another **96%** of decline still ahead of it, a fall the market would take eight more months to finish pricing in.

The turn signals stacked on a different calendar, and the market was even slower to believe them. The June 30, 2023 10-Q — filed July 19, 2023 — was the first filing to show `Operating Income (Loss)` positive, at **$42 Million**, alongside a Days Inventory Outstanding already falling and a Gross Profit Margin that had climbed in three straight quarters. That is the exact quarter this record's operating turnaround becomes visible. The stock closed that quarter at **$5.18** — and over the following three months, as that filing sat in front of anyone reading it, the stock fell another cumulative **32.5%**. The balance-sheet fix that would draw the headlines — the **$878 Million** debt-extinguishment gain — was still three months away. The filings had the turn a full quarter before the market started believing it, and the market spent three more months disbelieving it after that.

## Check Your Holdings

Neither half of this pattern requires Carvana specifically — both are checks anyone can run against their own portfolio inside GeminIQ. Pull up [Calculated Metrics](/features#calculated-metrics) for any company you hold and track the Interest Coverage Ratio and Altman Z-Score across four or five consecutive quarters rather than as a single snapshot; a coverage ratio that's gone negative while debt is still climbing, or a Z-Score that's fallen below the 1.81 distress threshold, is the same combination that sat in Carvana's filings months before the worst of its decline. Then open [Financial Statements](/features#financial-statements) and watch `Operating Income (Loss)` specifically, separate from `Net Income (Loss)` — a swing from negative to positive on the operating line is a cleaner signal of an actual business turn than a net income number that a one-time gain or charge can distort in either direction, exactly as the debt-extinguishment gain did here. Finally, check [Insider Transactions](/features#insider-transactions) for cluster buying, but treat the price paid as a data point, not a floor. Carvana's own founders bought in size and still weren't done watching the stock fall for another seven months.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=carvana-stock-crash-recovery)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures in this article are drawn from Carvana Co.'s 10-K and 10-Q filings, filed 2017–2026 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001690820&type=10-K).

---

## Blog: Cash Flow Statement Explained: How to Read the Three Sections
source: https://www.geminiq.com/blog/cash-flow-statement-explained

### Cash Flow Statement Explained: How to Read the Three Sections
A cash flow statement reconciles accounting profit to actual cash by sorting every movement into three buckets — operating, investing, and financing. Understanding what belongs in each, and why net income and operating cash flow can diverge, is what turns a reported earnings number into a read on real cash generation.

Net income is an opinion; cash is a fact. That old accounting line exists because the income statement is built on rules about *when* to record revenue and expenses — rules that deliberately ignore when the cash actually moves. A company can book a sale it hasn't been paid for, depreciate an asset it bought years ago, and record a tax bill it will pay next year, all of which shift reported profit away from the cash in the bank. The cash flow statement is the correction. It takes the accounting profit and walks it back to what actually happened to cash.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=cash-flow-statement-explained)**

That's why experienced investors read it first. A company can report rising net income for years while its cash position quietly bleeds — and the only statement that exposes the gap is this one. The structure is simple once you see it: every cash movement in the business gets sorted into one of three buckets, and the story is usually in how those three relate to each other.

This guide walks through the cash flow statement section by section, using **[Apple's](/stocks/AAPL) Q3 FY2026 10-Q** (filed July 31, 2026, for the period ending June 28, 2026) as the example, and shows how [GeminIQ](/) extracts each line directly from the SEC filing with its XBRL tag preserved — so the cash flow you analyze matches the cash flow the company reported.

---

## Apple's Cash Flow at a Glance (Trailing Twelve Months)

| Line item | Value | Section |
|---|---|---|
| Net income | $128.93 Billion | (income statement starting point) |
| Operating cash flow | **$146.72 Billion** | Operating |
| Capital expenditures | $10.04 Billion | Investing |
| Free cash flow | **$136.68 Billion** | Operating − Capex |
| Financing cash flow | −$122.05 Billion | Financing |
| Free cash flow yield | 3.23% | (FCF ÷ market cap) |

<sup>*Trailing-twelve-month figures as of Apple's Q3 FY2026 10-Q, period ending June 28, 2026.*</sup>

---

## Table of Contents

- [What Is a Cash Flow Statement?](#what-is-a-cash-flow-statement)
- [Step 1: Start With Cash From Operating Activities](#step-1-start-with-cash-from-operating-activities)
- [Step 2: Read Cash From Investing Activities](#step-2-read-cash-from-investing-activities)
- [Step 3: Read Cash From Financing Activities](#step-3-read-cash-from-financing-activities)
- [Step 4: Calculate Free Cash Flow](#step-4-calculate-free-cash-flow)
- [Why Net Income and Operating Cash Flow Diverge](#why-net-income-and-operating-cash-flow-diverge)
- [Reading the Three Sections Together](#reading-the-three-sections-together)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is a Cash Flow Statement?

A cash flow statement tracks the actual movement of cash into and out of a business over a period — the same quarter or year the income statement covers, but measured in cash rather than accounting profit. It exists because most large companies use accrual accounting, which records revenue when it's earned and expenses when they're incurred, regardless of when money changes hands. That's the right way to measure economic performance, but it means the profit figure and the cash figure can drift far apart.

The statement resolves the drift by sorting every cash movement into three categories: **operating** (cash from running the business), **investing** (cash spent on or received from long-term assets), and **financing** (cash exchanged with lenders and shareholders). Add the three together and you get the net change in cash for the period, which reconciles to the cash line at the top of the [balance sheet](/blog/how-to-read-a-balance-sheet). Every public company reports this statement in each 10-K and 10-Q, and in the 10-K it's audited.

The reason this statement is harder to manipulate than the income statement is structural: revenue recognition involves judgment, but cash either arrived or it didn't. That's what makes it the value investor's favorite.

---

## Step 1: Start With Cash From Operating Activities

The operating section is the one that matters most, because it measures the cash the core business generated — before any decisions about investing or financing. It almost always starts from net income and then adds back or subtracts a series of adjustments to convert accrual profit into cash. This is called the indirect method, and it's what nearly every large company uses.

The adjustments fall into two groups. First, **non-cash expenses** get added back: depreciation and amortization reduced net income but no cash left the building, so they're added back in. Stock-based compensation works the same way — it's a real expense that lowers reported profit, but it's paid in shares, not cash, so it's added back here. Second, **changes in working capital** are netted in: if accounts receivable grew during the period, the company booked sales it hasn't collected yet, so cash is *lower* than profit and the increase is subtracted. If accounts payable grew, the company is holding onto cash it owes suppliers, so cash is *higher* than profit and the increase is added.

For [Apple's](/stocks/AAPL) trailing twelve months, operating cash flow of **$146.72 Billion** comfortably exceeds net income of $128.93 billion, which is the healthy pattern — the add-back of non-cash charges like depreciation ($13.10 billion) and stock-based compensation ($13.71 billion) more than offsets any working-capital drag. When you see the opposite, operating cash flow persistently *below* net income, that's the flag worth chasing: it usually means receivables or inventory are swelling faster than the business is collecting, and the reported profit isn't turning into money.

> **GeminIQ Tip:** GeminIQ presents the operating section [exactly as filed](/features#financial-statements), with every add-back and working-capital line preserved — including [stock-based compensation](/metrics/calculated-values/stock-based-compensation), which many dashboards bury. Because SBC is added back to operating cash flow, a company with heavy stock compensation can show strong operating cash flow while quietly diluting shareholders — a gap you can only see when the line is left intact.

---

## Step 2: Read Cash From Investing Activities

The investing section captures cash spent acquiring long-term assets and cash received from selling them. For most operating companies, the dominant line here is **capital expenditures** (capex) — money spent on property, equipment, and infrastructure. Capex is almost always negative, because the company is spending, and that's normal: a business that never invests in itself is a business slowly winding down.

The other lines in this section include purchases and sales of marketable securities (large for cash-rich companies like Apple, which parks excess cash in short- and long-term investments), and acquisitions of other businesses. Apple's total investing cash flow ran to −$21.40 billion over the trailing twelve months, with capital expenditures of just $10.04 billion — strikingly light for a company its size, a direct consequence of its outsourced, asset-light manufacturing model. A big negative number from an acquisition, by contrast, tells you the company grew by buying rather than building — and it's worth connecting back to the goodwill line on the [balance sheet](/blog/how-to-read-a-balance-sheet), which is where the premium paid for that acquisition lands.

The read on the investing section is directional. Heavy capex isn't inherently good or bad — it depends on whether those investments earn a return above the company's cost of capital. But the *trend* matters: capex that suddenly spikes as a share of revenue signals a company entering a heavy-investment phase (building factories, data centers, capacity), which will pressure free cash flow in the near term whether or not it pays off later. That's a setup you want to notice before it shows up in the free cash flow number, not after.

---

## Step 3: Read Cash From Financing Activities

The financing section records cash exchanged with the people who fund the company — lenders and shareholders. It answers a single question: over this period, did the company raise capital, or return it?

The main lines are **debt issuance and repayment** (borrowing brings cash in, paying down debt sends it out), **share buybacks** (cash out, repurchasing stock), and **dividends** (cash out, paid to shareholders). The sign of the total tells you which kind of company you're looking at. A young, growing company usually shows positive financing cash flow — it's raising money by issuing stock or taking on debt to fund expansion. A mature, cash-generating company usually shows deeply negative financing cash flow, because it's returning capital: buying back shares and paying dividends faster than it borrows.

Apple is the textbook mature case — its financing section runs sharply negative, at −$122.05 billion over the trailing twelve months, dominated by buybacks and $15.64 billion in dividends. That negative number isn't weakness; it's the signature of a business generating more cash than it can reinvest and handing the surplus back. The line to watch is whether those returns are funded by operating cash flow or by new debt. Apple's $146.72 billion in operating cash flow more than covers the $122.05 billion it returned — the buybacks are funded by genuine surplus. A company borrowing to buy back stock while its operating cash flow stagnates is manufacturing a shrinking share count on credit — a very different situation, and the financing section read against the operating section is what tells them apart.

---

## Step 4: Calculate Free Cash Flow

The single most useful number you can build from the cash flow statement isn't printed on it: free cash flow. It's the cash left over after the business has paid to maintain and grow itself — the cash actually available to return to shareholders, pay down debt, or stockpile.

**Free Cash Flow = Operating Cash Flow − Capital Expenditures**

You pull operating cash flow from the top of the statement and capex from the investing section, and subtract. For Apple's trailing twelve months, that's **$146.72 Billion** in operating cash flow minus **$10.04 Billion** in capex, leaving **$136.68 Billion** in free cash flow — nearly all of the operating cash flow converts to free cash flow, precisely because Apple's capex is so light. The reason free cash flow beats net income as a measure of what a business produces is that it captures the real cash cost of staying in business — the capex that the income statement only recognizes slowly, through depreciation. A company can report healthy net income while free cash flow is thin or negative because it's pouring cash into capex; the income statement smooths that spending out over years, but free cash flow shows it hitting all at once.

GeminIQ computes [free cash flow](/metrics/calculated-values/free-cash-flow) directly from the as-filed operating cash flow and capex, and expresses it per share as [free cash flow per share](/metrics/per-share-metrics/free-cash-flow-per-share) ($9.33 for Apple) and against market value as [free cash flow yield](/metrics/valuation-metrics/free-cash-flow-yield) (3.23%) — the valuation figure that answers "how much cash am I buying per dollar of stock?" A high free cash flow yield is one of the cleaner signals that a stock may be undervalued, precisely because free cash flow is so much harder to manufacture than accounting profit.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=cash-flow-statement-explained)**

---

## Why Net Income and Operating Cash Flow Diverge

If you internalize one thing from this statement, make it this: net income and operating cash flow should track each other loosely over time, and when they persistently diverge, the cash flow statement is almost always telling the truer story.

They diverge for legitimate reasons constantly. A capital-heavy company records large depreciation, which depresses net income but not cash — so its operating cash flow sits well above net income, year after year, with nothing wrong. A fast-growing company ties up cash in receivables and inventory to support the growth, so its operating cash flow can lag net income even as the business thrives. Neither of these is a problem; both are patterns you'd misread if you only watched the income statement.

The divergence that *is* a problem is the one that widens without a benign explanation: net income climbing while operating cash flow flattens or falls, driven by receivables and inventory ballooning quarter after quarter. That pattern — profit going up, cash not following — is the classic signature that reported earnings are running ahead of economic reality. It's the reason forensic-minded investors reconcile the two statements every quarter rather than trusting the headline EPS. The gap is the tell.

---

## Reading the Three Sections Together

The three sections are most powerful read as a single shape, because the *combination* of signs describes the company's life stage more precisely than any one number.

The healthiest mature profile is **positive operating, negative investing, negative financing**: the business generates cash, reinvests some of it, and returns the rest to shareholders. That's Apple, and most quality compounders. A young growth company often shows **positive operating (or slightly negative), heavily negative investing, positive financing**: it's spending on expansion and raising outside capital to fund it — fine if the growth is real, dangerous if the operating cash never turns positive. The profile to be wary of is **weak or negative operating, with positive financing propping up the cash balance**: a company covering an operating shortfall by continually raising debt or equity is running on borrowed time, and the cash flow statement shows it before the income statement or a valuation multiple ever will.

This is also where the cash flow statement closes the loop with the other two. Its top line — net income — comes straight from the [income statement](/blog/how-to-read-an-income-statement). Its bottom line — the net change in cash — flows into the cash balance atop the [balance sheet](/blog/how-to-read-a-balance-sheet). Read all three together and each one checks the others; read the income statement alone and you're trusting an opinion when a fact was available. GeminIQ presents all three [as the company filed them](/features#financial-statements), across every period side by side, so the reconciliation the pros do by hand is already laid out in front of you.

---

## Frequently Asked Questions

### What are the three sections of a cash flow statement?

Operating activities (cash generated by running the core business), investing activities (cash spent on or received from long-term assets like equipment and acquisitions), and financing activities (cash exchanged with lenders and shareholders through debt, buybacks, and dividends). The three sum to the net change in cash for the period.

### Why is net income different from cash flow?

Because accrual accounting records revenue and expenses when they're earned or incurred, not when cash moves. Non-cash expenses like depreciation and stock-based compensation reduce net income without reducing cash, and changes in working capital (receivables, inventory, payables) shift cash away from profit. The operating section of the cash flow statement reconciles the two by adjusting net income for exactly these items.

### How do you find free cash flow on a cash flow statement?

Free cash flow isn't a printed line — you calculate it. Take operating cash flow from the top section and subtract capital expenditures from the investing section: Free Cash Flow = Operating Cash Flow − Capex. It represents the cash left after the business has paid to maintain and grow itself, available to return to shareholders or pay down debt.

### Which section of the cash flow statement matters most?

Operating activities, because it measures whether the core business actually generates cash before any investing or financing decisions. A company that can't produce positive operating cash flow is dependent on raising outside capital to survive. The investing and financing sections then tell you what the company does with — or how it supplements — that operating cash.

---

## Wall Street's data. Main Street's price.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. We built GeminIQ because we believe you deserve a better fundamental analysis tool—one that goes beyond basic price charts and processed numbers. We extract our data directly from SEC 10-K and 10-Q filings to ensure that when you look at a balance sheet or a cash flow statement, you are seeing the numbers exactly how the company reported them. Our goal is to give you the tools to verify the narrative for yourself using clean, traceable data. Start researching now at [GeminIQ.com](/).

---

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All financial figures cited in this article reference Apple Inc.'s Q3 FY2026 10-Q (filed July 31, 2026, for the fiscal period ending June 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-Q).

---

## Blog: Reading the Cash Flow Statement for Fraud Signals
source: https://www.geminiq.com/blog/cash-flow-statement-fraud-signals

### Reading the Cash Flow Statement for Fraud Signals
The cash flow statement has a reputation as the hardest financial statement to manipulate, because cash either moved or it didn't. That reputation is only partly earned: a cash flow statement has three sections, and which section a real cash outflow gets classified into is itself a judgment call — one that, in one of the largest accounting frauds in U.S. history, was the entire mechanism. This guide covers the standard net-income-versus-cash-flow fraud check, the real, court-documented case where that exact check failed to catch $3.8 billion in misclassified expenses, and what would have actually caught it.

An income statement runs on judgment calls — how to recognize revenue, how much to reserve for bad debts, when an asset is impaired. A cash flow statement is supposed to be the check on all of that: cash either moved or it didn't, and no accounting estimate changes that fact. That reputation is largely deserved, and it's also incomplete. The cash flow statement doesn't just record whether cash moved — it also has to record where in the statement that movement gets classified. The classification itself is a judgment call, and in at least one of the largest corporate frauds in U.S. history, that judgment call was the entire mechanism.

This guide covers the classic cash-flow fraud signal every finance course teaches, a real, court-documented case where that exact signal failed to catch $3.8 billion in misclassified expenses, and what actually would have caught it — because the lesson from that case is more useful than the simple version most red-flag checklists teach.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=cash-flow-statement-fraud-signals)**

---

## Table of Contents

- [Why the Cash Flow Statement Is Considered Harder to Fake](#why-the-cash-flow-statement-is-considered-harder-to-fake)
- [The Classic Signal, and Why It Isn't Enough](#the-classic-signal-and-why-it-isnt-enough)
- [WorldCom: How $3.8 Billion in Ordinary Expenses Became "Investments"](#worldcom-how-38-billion-in-ordinary-expenses-became-investments)
- [Why the Classic Signal Missed It](#why-the-classic-signal-missed-it)
- [What Actually Would Have Caught It](#what-actually-would-have-caught-it)
- [Other Cash Flow Statement Red Flags Worth Knowing](#other-cash-flow-statement-red-flags-worth-knowing)
- [Reading the Signals on GeminIQ](#reading-the-signals-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Why the Cash Flow Statement Is Considered Harder to Fake

The reasoning behind the cash flow statement's reputation is sound as far as it goes. Revenue recognition, expense timing, and asset valuation all involve estimates a company controls directly. Cash either arrived in the bank or it didn't, and no accounting policy changes that underlying fact. For decades, the standard advice to a skeptical investor was some version of: if you don't trust the income statement, check whether cash flow confirms it.

What that advice leaves out is that a cash flow statement has three sections — operating, investing, and financing. Which section a given cash movement lands in is itself a classification decision, made by the company, following rules that leave real room for judgment at the margins. Moving a real, undisputed cash outflow from one section to another doesn't fabricate a transaction. It just misrepresents what kind of transaction it was — and that reclassification can be every bit as consequential as fabricating a number outright.

---

## The Classic Signal, and Why It Isn't Enough

The standard check taught in nearly every fundamental analysis course is simple: compare net income's growth rate to operating cash flow's growth rate over the same periods. When they move together, reported earnings and actual cash generation are telling a consistent story. When net income grows while operating cash flow stagnates or declines, the gap is exactly the kind of divergence [covered in depth in our earnings quality guide](/blog/earnings-quality-accruals-analysis) — a signal that reported profit is increasingly built from accounting estimates rather than cash actually collected.

It's a useful check, and it catches a meaningful share of earnings-quality problems. It is not, however, foolproof — and the case that best demonstrates its limits is also one of the largest corporate accounting frauds ever prosecuted in the United States.

---

## WorldCom: How $3.8 Billion in Ordinary Expenses Became "Investments"

WorldCom's fraud is often grouped with Enron's in the same breath, as though the two companies used the same technique. Enron built an elaborate structure of off-balance-sheet entities to hide losses entirely outside its financial statements. WorldCom's scheme worked inside the cash flow statement's own three-section structure, moving a real, undisputed cash outflow from one section to another.

In June 2002, WorldCom announced it would restate its financial statements after its own internal audit team — led by vice president Cynthia Cooper — discovered that the company had improperly transferred **$3.055 billion** in 2001 and **$797 million** in the first quarter of 2002 from operating expenses into capital expenditures — together, the **$3.8 billion** in misclassified costs this fraud is now remembered by. The specific costs involved were "line costs" — the fees WorldCom paid other telecommunications carriers to access their networks, a routine, recurring operating cost with no plausible argument for treatment as a long-term capital investment. The reclassification inflated WorldCom's reported earnings by an estimated **$11 billion** between 1999 and 2002 — an overstatement large enough that when it unwound, WorldCom's Chapter 11 filing became the largest corporate bankruptcy in U.S. history at the time — and both CEO Bernard Ebbers and CFO Scott Sullivan were later convicted of fraud in connection with the scheme.

The mechanics matter for understanding why the standard divergence check missed it. Reclassifying an operating expense as a capital expenditure does two things simultaneously. It removes the cost from the income statement immediately, replacing it with a much smaller depreciation charge spread across future years, which inflates net income. And because the cash outflow itself moves from the operating section of the cash flow statement to the investing section, it inflates operating cash flow by the exact same amount, in the exact same period, that net income was inflated. Net income and operating cash flow didn't diverge in WorldCom's fraudulent filings — they moved up together, because the same reclassification boosted both at once.

---

## Why the Classic Signal Missed It

This is the part worth sitting with. The single most commonly taught fraud-detection check — does operating cash flow confirm net income — is specifically defeated by a technique that boosts both figures through the same mechanism. Bernard Ebbers told the market "we are free cash flow positive" during the exact period the fraud was active, and the statement was technically true given the fraudulent classification, because free cash flow is calculated from the same manipulated operating cash flow figure.

A single ratio check, applied mechanically, is only as reliable as the assumption that the numbers feeding it were classified correctly in the first place. WorldCom's case is the clearest evidence that assumption can fail at the largest possible scale, for years, before anyone catches it.

Worth separating two different exercises here, because they get conflated constantly. Finding a restatement that has already been filed is a mechanical search problem with a known answer — the company has admitted the numbers were wrong, and [how to find restatements in filings](/blog/how-to-find-restatements-in-filings) covers exactly where that admission appears. Detecting the pattern before the restatement exists is the harder problem, and it's the only one this guide is about.

---

## What Actually Would Have Caught It

The signal that did eventually catch a version of this pattern, before WorldCom's own internal audit found it, came from a financial journalist comparing line-cost expenses as a percentage of revenue across WorldCom's own business segments and against its direct competitors. The consolidated, company-wide numbers looked smooth and plausible. The segment-level numbers didn't: at WorldCom's MCI consumer division, line costs as a percentage of revenue actually rose from **44% to 51%** during the same stretch the company's blended results were improving — the opposite of what a single capitalization policy, applied evenly across the business, should have produced.

The lesson generalizes past this one case. A capitalization or classification policy that's actually legitimate should apply consistently across a company's own segments and hold up against how peer companies in the same industry treat the same category of cost. A blended, company-wide ratio that looks smoother than the same ratio does at the segment or peer level is itself a signal worth chasing down — precisely because averaging together inconsistent treatment is one of the easiest ways to make a real divergence disappear into a headline number.

---

## Other Cash Flow Statement Red Flags Worth Knowing

A reader who just absorbed WorldCom's scale might assume this kind of manipulation only shows up in frauds large enough to draw a federal indictment. The same underlying move — classifying a cash outflow in a way that flatters operating cash flow at the expense of accuracy — shows up in ordinary financial statements too, at a fraction of that scale. WorldCom's mechanism, capitalizing a recurring operating cost, is one version of that broader category. A company factoring or securitizing receivables converts a future operating cash inflow into a current one, temporarily boosting operating cash flow while borrowing against collections that haven't actually happened yet. A company stretching payables unusually far right before a period ends — paying vendors meaningfully slower than its own historical pattern or its industry peers — inflates operating cash flow for that specific period at the cost of an equally unusual catch-up the following period.

The four signals this guide covers, and what each one does to the number most investors read first:

| Signal | Effect on reported operating cash flow | What to compare it against | Does the classic net-income-vs-cash-flow check catch it? |
| --- | --- | --- | --- |
| Capitalizing a recurring operating cost (WorldCom's line costs) | Inflates it — the same real outflow is moved into the investing section | The expense line as a percentage of revenue, segment by segment and against direct peers | No. Net income and operating cash flow rise together by the same amount, in the same period |
| Factoring or securitizing receivables | Inflates it — a future operating inflow is converted into a current one | The company's own collection pattern in prior periods | No. Operating cash flow rises while net income is untouched, so the gap the check looks for narrows rather than widens |
| Stretching payables before a period ends | Inflates it for that period, at the cost of a catch-up the next | The company's own historical payment pattern and its industry peers | No, and it inverts the signal for one period — cash flow outruns net income, which reads as strength |
| A blended, company-wide ratio smoother than the segment-level version | No direct effect; it conceals the effect of the others | Segment-level ratios against the consolidated figure | No. This is the check that catches what the classic one misses |

None of these require anything as dramatic as WorldCom's scale to be worth checking. The common thread across all of them is the same one WorldCom's case demonstrates most clearly: a single period's headline operating cash flow figure is a summary of classification choices as much as it is a summary of cash that moved, and the choices are only visible by reading the components, not the total.

---

## Reading the Signals on GeminIQ

Catching a divergence like WorldCom's requires the individual line items a fraud reclassifies to still be visible, separately, rather than merged into a single blended total that makes the reclassification invisible by construction. GeminIQ's [Financial Statements](/features#financial-statements) view preserves operating expense and capital expenditure lines exactly as filed, which means a capitalization policy that shifts unusually between periods — or diverges from how a company's own segments or its peers treat the same cost category — is visible directly in the as-filed data rather than requiring a restatement to surface it.

That preservation is the whole precondition for this kind of work. A figure that has been normalized into a provider's own expense template before it reaches you has already had the classification decision made for it a second time, by someone who wasn't the filer and didn't sign the filing — which is the distinction the comparison against [ROIC.ai](/competitor-comparison/roic-ai) turns on. A reclassification is invisible in any dataset that has re-bucketed the lines the reclassification moved.

The [Custom Tables](/features#custom-tables) builder is where the actual check happens in practice: tracking a specific expense line as a percentage of revenue across multiple consecutive quarters, and comparing that trend against the same ratio at peer companies, is exactly the segment-versus-peer comparison that caught WorldCom's inconsistency before the company's own admission did.

---

## Frequently Asked Questions

### Does a rising cash flow always mean a company is healthy?

Not necessarily. Operating cash flow can be inflated temporarily through receivables factoring, unusually extended payables, or — in the most serious cases — outright misclassification of what should be an operating expense as a capital expenditure. A single period's cash flow figure is worth checking against its components and its trend, not taken at face value in isolation.

### What was WorldCom's accounting fraud, in one sentence?

WorldCom's executives improperly reclassified $3.8 billion in routine operating expenses — fees paid to other telecom carriers — as capital expenditures, which simultaneously inflated reported net income and operating cash flow by moving the same cash outflow into a different section of the cash flow statement.

### If net income and operating cash flow move together, does that rule out manipulation?

No, and WorldCom is the clearest historical proof. A reclassification of an operating cost as a capital expenditure boosts both figures through the same mechanism, which means the classic divergence check can be defeated by exactly the kind of manipulation it's designed to catch.

### How can an investor check for this kind of manipulation without forensic accounting training?

Track a company's major expense lines as a percentage of revenue over several consecutive quarters, and compare that trend against direct industry peers. A ratio that looks smoother at the consolidated level than it does at the segment level, or that diverges meaningfully from how peer companies treat the same cost category, is worth investigating further.

A number that looks calm at the consolidated level and a number that looks calm at the segment or peer level are two different claims, and most red-flag checklists only test one of them. WorldCom is the costliest reminder that the gap between those two views is where a real problem hides — in a cash flow statement, or anywhere else in the filing.

---

## Related Reading

- [Earnings Quality: Reading Accruals From Filings](/blog/earnings-quality-accruals-analysis) — the standard net-income-versus-cash-flow check covered in full.
- [Balance Sheet Red Flags: A Filing-Based Checklist](/blog/balance-sheet-red-flags-checklist) — the broader set of filing-based signals this one complements.
- [How to Find Restatements in Filings](/blog/how-to-find-restatements-in-filings) — the other half of this problem: locating the admission after a company has already made it.
- [8-K Item Codes: The Complete Reference List](/blog/8-k-item-codes-reference-list) — where an auditor change (Item 4.01) shows up as its own, separate warning signal.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Coca-Cola Q1 2026 10-Q: The 13-Year Revenue Illusion
source: https://www.geminiq.com/blog/coca-cola-10q-analysis-q1-2026

### Coca-Cola Q1 2026 10-Q: The 13-Year Revenue Illusion
Coca-Cola's Q1 FY2026 10-Q shows revenue has grown just 2.6% cumulatively since 2012, but that stagnation masks a deliberate transformation: operating margin has climbed from 22.4% to 29.3% as the company shed its capital-intensive bottling operations.

**[Coca-Cola](/stocks/KO) Company ($KO) just dropped its Q1 FY2026 10-Q (filed April 30, 2026). Pull up a standard screener and the stock looks like dead money: revenue has grown a cumulative 2.6% since 2012, barely distinguishable from flat once you account for over a decade of inflation. The raw filing data tells a different story. Coca-Cola spent that same period deliberately shedding its capital-intensive bottling business, and the margin engine that replaced it hasn't stopped running.**

| Field                     | Value          |
| ------------------------- | -------------- |
| Ticker                    | $KO            |
| Filing                    | Q1 FY2026 10-Q |
| Filed                     | April 30, 2026 |
| Period End                | April 3, 2026  |
| Operating Margin (TTM)    | **29.3%**      |
| Revenue Growth (2012–TTM) | **+2.6%**      |

## The Margin Engine Keeps Running

Thirteen years of near-zero revenue growth would sink most companies' margins. [Coca-Cola's](/stocks/KO) went the other way.

**The Data:** TTM revenue sits at **$49.28 Billion**, against **$48.02 Billion** in 2012 — a cumulative gain of **2.6%** across more than thirteen years. Over that same window, TTM Operating Income climbed from **$10.78 Billion** to **$14.46 Billion**, and Operating Margin (TTM) expanded from **22.4%** to **29.3%**. [Gross Margin](/metrics/margin-metrics/gross-profit-margin) (TTM) currently sits at **61.7%**.

**The GeminIQ Edge:** A revenue-only screen flags this as a growth-stalled business and moves on. Pulling [Calculated Metrics](/features#calculated-metrics) alongside the raw Income Statement shows the margin expansion has been sustained and gradual across more than a decade, not a single strong quarter — the kind of pattern that's much harder to explain away as noise.

<center><sup>GeminIQ Calculated Metrics showing Coca-Cola's Operating Margin (TTM) expanding from 22.4% (2012) to 29.3% (Q1 FY2026), while TTM revenue grew only 2.6% cumulatively over the same period.</sup></center>

## The Asset Dump Continues

The margin expansion isn't an accounting trick. It traces directly to a deliberate shift in what kind of company Coca-Cola chose to be.

**The Data:** [Coca-Cola's](/stocks/KO) Property, Plant, and Equipment (net) has fallen from **$14.48 Billion** in 2012 to **$9.52 Billion** as of this filing — a reduction of roughly **34%**. The decline reflects the company's long-running refranchising strategy: selling capital-intensive bottling operations to become primarily a brand owner and concentrate manufacturer.

**The GeminIQ Edge:** Pulling the historical [Financial Statements](/features#financial-statements) balance sheet trend shows this wasn't a one-time divestiture but a sustained, multi-year asset reduction running in parallel with the margin expansion above — the same strategic decision showing up on two different statements.

<center><sup>GeminIQ Financial Statements showing Coca-Cola's Property, Plant, and Equipment (net) falling from $14.48 Billion (2012) to $9.52 Billion (Q1 FY2026), a roughly 34% reduction.</sup></center>

## The Debt Figure That Needed Correcting

Not every number in this filing was straightforward to pull, and this one is worth flagging directly rather than quietly fixing in the background.

**The Data:** [Coca-Cola's](/stocks/KO) Total Debt sits at **$43.89 Billion** as of this filing — **$39.07 Billion** in Long-Term Debt, plus **$4.49 Billion** in current maturities and **$332 Million** in short-term notes and loans payable. Netted against cash, Net Debt comes to roughly **$32.9 Billion**.

**The GeminIQ Edge:** Coca-Cola reports its current debt maturities and short-term notes under combined line items rather than the more commonly used tag names, which is exactly the kind of company-specific labeling that a naive aggregation misses entirely. Pulling every debt-related line individually from the raw [Financial Statements](/features#financial-statements), rather than trusting a single pre-aggregated "total debt" figure, is the only way to catch a gap like this.

<center><sup>GeminIQ Financial Statements showing Coca-Cola's full debt structure: $39.07 Billion in Long-Term Debt, $4.49 Billion in current maturities, and $332 Million in short-term notes, totaling $43.89 Billion.</sup></center>

## Smart Money and the Insider Record

Two different signals around [Coca-Cola](/stocks/KO) worth checking separately rather than folding into one story.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has climbed modestly, from **68.4%** in December 2024 to **70.2%** as of the most recent 13F (March 2026, filed with the standard lag). [Insider Transactions](/features#insider-transactions) show a heavily sale-weighted record: 376 sales against 36 purchases in the available history.

**The GeminIQ Edge:** Neither figure tells a dramatic story on its own, and that's worth saying plainly rather than manufacturing tension that isn't there. A steady, unremarkable institutional base and a sale-heavy insider pattern are what you'd expect from a mature, widely-held dividend compounder, not a signal in either direction.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership climbing from 68.4% (December 2024) to 70.2% (March 2026, most recent 13F).</sup></center>

## Frequently Asked Questions

### What does GeminIQ's data show about Coca-Cola's revenue growth?

Coca-Cola's TTM revenue has grown just 2.6% cumulatively since 2012 ($48.02 Billion to $49.28 Billion), effectively flat once inflation is considered over more than thirteen years.

### How has Coca-Cola's operating margin changed despite flat revenue?

Operating Margin (TTM) has expanded from 22.4% in 2012 to 29.3% as of the Q1 FY2026 10-Q, driven by the company's shift away from capital-intensive bottling operations toward a brand-and-concentrate business model.

### What is Coca-Cola's actual total debt?

As of the Q1 FY2026 10-Q, Coca-Cola's Total Debt is $43.89 Billion: $39.07 Billion in Long-Term Debt, $4.49 Billion in current maturities, and $332 Million in short-term notes and loans payable.

### When did Coca-Cola last file its 10-Q, and what period does it cover?

Coca-Cola's most recent filing is a Form 10-Q filed April 30, 2026, covering the fiscal quarter ended April 3, 2026 (Q1 FY2026).

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference The Coca-Cola Company's Q1 FY2026 10-Q (filed April 30, 2026, period ending April 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000021344&type=10-Q).

---

## Blog: Companies Reducing Share Count: The Decade's Real Cannibals
source: https://www.geminiq.com/blog/companies-reducing-share-count

### Companies Reducing Share Count: The Decade's Real Cannibals
Companies reducing share count over the last decade are rare: across 2,076 firms with a full 10-K history, the median company's diluted share count rose 2.2%. This ranking names the real cannibals from as-filed SEC data.

**Every investor can name a "buyback stock." Far fewer can name a company that actually shrank itself. Those are different things, and the gap between them is the whole story.** A company can spend tens of billions repurchasing shares and end the decade with more shares outstanding than it started with, because stock-based compensation quietly issued them back. The only way to know who genuinely retired stock is to read the as-filed diluted share count in the 10-K, year by year, and watch where it actually ends up. We did that for the entire filing universe. The result overturns the popular list of "great capital allocators" — and reveals a base rate almost nobody talks about.

This is a GeminIQ Filing Data Study. The universe is every company with a 10-K in each fiscal year from **2015** through **2024** — **2,076** firms with a complete, rankable diluted-share history, drawn from **3,054** filers with at least one 10-K in the window. Every figure is the as-filed Weighted Average Number Of Diluted Shares Outstanding pulled directly from SEC EDGAR XBRL, split-adjusted, taken at its latest restated vintage for each fiscal year. Buyback and comp figures are the as-filed Payments For Repurchase Of Common Stock and Share Based Compensation. Post-filing returns are the 12-month cumulative move from each 10-K's filed date. No aggregator sits in between. The cleaning rules and excluded names are documented in the Data Appendix.

## The Base Rate: The Median Company Grew Its Share Count +2.2%

Start with the base rate, because it reframes everything that follows. Across all **2,076** companies, the median ten-year change in diluted share count was **+2.2%**. The typical public company did not shrink over the decade. It grew its share count. Buybacks are constant news; net share-count reduction over ten years is the exception, not the norm. Against that baseline, here are the companies that actually did it — the decade's real cannibals.

## The Leaderboard: 12 Companies That Cut Share Count 48.9% to 63.8%

| Rank | Company | Business Type | 10-Yr Diluted Share Change | 10-Yr Buyback | SBC as % of Buyback |
|------|---------|---------------|---------------------------|---------------|---------------------|
| 1 | [MBIA](/stocks/MBI) | Bond insurer in runoff | **-63.8%** | **$1.14B** | **0%** |
| 2 | [Navient](/stocks/NAVI) | Student-loan servicer winding down | **-61.8%** | **$4.69B** | **5%** |
| 3 | [AutoNation](/stocks/AN) | Operating business | **-56.7%** | **$7.04B** | **4%** |
| 4 | [Avis Budget](/stocks/CAR) | Operating business | **-55.6%** | **$7.21B** | **3%** |
| 5 | [Assured Guaranty](/stocks/AGO) | Capital-return machine | **-55.6%** | **$4.50B** | **0%** |
| 6 | [Dillard's](/stocks/DDS) | Department stores | **-55.0%** | **$2.90B** | **0%** |
| 7 | [DaVita](/stocks/DVA) | Capital-return machine | **-54.5%** | **$11.45B** | **7%** |
| 8 | [eBay](/stocks/EBAY) | — | **-53.4%** | **$37.20B** | **13%** |
| 9 | [Sleep Number](/stocks/SNBR) | Operating business | **-51.8%** | **$1.51B** | **10%** |
| 10 | [Louisiana-Pacific](/stocks/LPX) | Operating business | **-50.4%** | **$3.46B** | **2%** |
| 11 | [Synchrony](/stocks/SYF) | Capital-return machine (2014 spinoff) | **-49.1%** | **$16.76B** | **0%** |
| 12 | [White Mountains](/stocks/WTM) | — | **-48.9%** | **$3.22B** | **1%** |

Notice who is *not* here. The megacap "buyback champions" that dominate financial media never crack the list. [Apple](/stocks/AAPL), the most-cited repurchaser on earth, retired **-28%** of its diluted shares over the same decade — real, but roughly half the pace of every name above. The companies that shrank the hardest are not the household compounders. They are capital-return specialists, insurers, and a handful of operators willing to buy back stock relentlessly and let almost nothing leak back out through comp.

<center><sup>GeminIQ data study: distribution of ten-year diluted share-count change across the universe, median +2.2%. The real reducers sit in a thin left tail. Built from as-filed 10-K data via GeminIQ. n = 2,076 companies, fiscal years 2015-2024.</sup></center>

## The Deepest Cutters Aren't Compounders: MBIA (-63.8%) and Navient (-61.8%)

The two deepest reducers in the entire universe are [MBIA](/stocks/MBI) at **-63.8%** and [Navient](/stocks/NAVI) at **-61.8%** — and neither is a growth compounder. MBIA is a bond insurer in runoff. Navient is a student-loan servicer winding down its legacy book. Both shrank their share counts by returning capital as the underlying business contracted, not by compounding it. The top of the board is an immediate lesson in reading filings literally.

That distinction matters, and standard financial media doesn't read the footnotes closely enough to make it. A screener sorting by share-count reduction flags MBIA as an elite capital allocator. But by pulling the raw filings via GeminIQ, the picture sharpens: MBIA spent just **$1.14B** on repurchases with **zero** stock-based compensation offsetting it, shrinking a runoff entity. The reduction is real, and entirely buyback-driven — the arithmetic of a company handing capital back as it shrinks, not the signature of a business getting bigger per share. The number is the truth; the label "compounder" would be the lie.

<center><sup>GeminIQ Financial Statements showing MBIA's Payments For Repurchase Of Common Stock across fiscal years 2015-2024, totaling $1.14 Billion against zero Share Based Compensation.</sup></center>

## eBay: $37.20B, the Largest Buyback on This Leaderboard

If MBIA shows that a small buyback can shrink a small company, [eBay](/stocks/EBAY) shows what genuine scale looks like. eBay spent **$37.20B** repurchasing stock over the decade — the largest cumulative buyback of any name on the board — and cut its diluted share count **-53.4%**, from over a billion shares to roughly half that.

Its Share Based Compensation ran at **13%** of its buyback spend, the highest ratio on the leaderboard, and eBay still landed a top-tier reduction. The as-filed data shows how: the [Payments For Repurchase Of Common Stock](/features#financial-statements) line stayed far ahead of the comp line, year after year. What it looks like when issuance wins that race instead is the subject of the companion study on [companies that dilute shareholders](/blog/companies-that-dilute-shareholders).

<center><sup>GeminIQ Financial Statements showing eBay's Payments For Repurchase Of Common Stock of $37.20 Billion against Share Based Compensation over fiscal years 2015-2024.</sup></center>

## The Capital-Return Machines: DaVita, Synchrony, and Assured Guaranty

Three names on the board represent the purest form of the strategy: buy back relentlessly, issue almost nothing, let the share count fall in a straight line. [DaVita](/stocks/DVA) spent **$11.45B** to cut its diluted shares **-54.5%**. [Synchrony](/stocks/SYF) — a 2014 spinoff that could have spent its independence diluting shareholders — instead deployed **$16.76B** with **zero** net stock-based compensation drag, reducing its count **-49.1%**. And [Assured Guaranty](/stocks/AGO) produced one of the cleanest charts in the entire study: a **-55.6%** reduction on **$4.50B** of repurchases with **zero** SBC, its diluted share count stepping down every single year without a single interruption.

Assured Guaranty is worth pausing on because its filing history is what a textbook cannibal looks like in raw XBRL — no acquisition spikes, no reverse-split artifacts, no comp leakage, just a monotonic decline. When a screener shows a smooth, uninterrupted fall in Weighted Average Number Of Diluted Shares Outstanding with no offsetting comp, that is the signature to trust. The [tools that normalize and reclassify filing data](/competitor-comparison/sp-capital-iq) often smooth these very lines into ambiguity; the as-filed numbers keep them sharp.

<center><sup>GeminIQ Financial Statements showing Assured Guaranty's Weighted Average Number Of Diluted Shares Outstanding falling in every fiscal year from 2015 to 2024, a -55.6% reduction.</sup></center>

## The Operating Cannibals: AutoNation, Avis Budget, Louisiana-Pacific, and Dillard's

The rest of the board is where operating businesses — companies that actually sell things — turn free cash flow into a shrinking share count. [AutoNation](/stocks/AN) cut **-56.7%** on **$7.04B** of buybacks; [Avis Budget](/stocks/CAR) matched it at **-55.6%** on **$7.21B**, both concentrating enormous repurchases into the cash-rich pandemic-recovery years. [Louisiana-Pacific](/stocks/LPX) turned an OSB-pricing windfall into a **-50.4%** reduction, and [Sleep Number](/stocks/SNBR) ground its count down **-51.8%**.

Then there is [Dillard's](/stocks/DDS) — the department-store chain that has quietly become one of the most disciplined repurchasers in retail. Its diluted share count fell from **42.6 Million** to **16.5 Million**, a **-55.0%** reduction on **$2.90B** of buybacks with **zero** stock-based compensation. Dillard's is the operating-business version of Assured Guaranty: no comp, no games, just relentless retirement of stock, year after year. The share count tells the story the stock's quiet reputation never did.

<center><sup>GeminIQ Financial Statements showing Dillard's Weighted Average Number Of Diluted Shares Outstanding falling from 42.6 Million to 16.5 Million across fiscal years 2015-2024, with no offsetting Share Based Compensation.</sup></center>

## Did the Cannibals Outperform? No — the Sample Is Too Small to Say

Across the universe, the average 10-K was followed by a **+8.4%** twelve-month return (median **+3.0%**) across **47,746** annual filings, and the twelve companies on this board scatter around that baseline rather than clustering above it — from [MBIA](/stocks/MBI) at roughly the flat line to [Dillard's](/stocks/DDS) well above it, with several names landing below the universe average. With only twelve companies the sample sits far below the threshold at which a post-filing return pattern becomes a finding rather than noise, so we draw no conclusion from it: deep share-count reduction is a fact about capital allocation, not a signal about next year's price.

## The Method

Every figure here is the as-filed diluted share count read straight from the 10-K, split-adjusted, taken at its latest restated vintage per fiscal year, with implausible and internally inconsistent series excluded before ranking. Returns are cumulative from each filing's filed date and are never compounded. The full ruleset — base-rate adjustment, the sample-size minimum, outlier trimming — is documented in our [filing data study methodology](/blog/filing-data-study-methodology). The share-count-versus-comp dynamic behind the leaderboard is covered in more depth in [stock buybacks vs. stock compensation](/blog/stock-buybacks-vs-stock-compensation).

## Check Your Holdings

You can run this exact check on anything you own in about two minutes. Open the company in [Financial Statements](/features#financial-statements) and pull the Weighted Average Number Of Diluted Shares Outstanding across the last decade. If it falls in a straight line, you own a genuine cannibal. If it is flat while the company reports billions in buybacks, pull the Share Based Compensation line — the comp is eating the repurchases, and you are on the treadmill, not ahead of it. Then check the number against the base rate: the median company grew its share count **+2.2%** over the decade, so anything meaningfully negative is already rare. The narrative around a stock will tell you it "returns capital to shareholders." The as-filed diluted share count tells you whether it actually did.

## Frequently Asked Questions

### Which companies reduced their share count the most from 2015 to 2024?

[MBIA](/stocks/MBI) at **-63.8%** and [Navient](/stocks/NAVI) at **-61.8%** lead the ranking, followed by [AutoNation](/stocks/AN) (**-56.7%**), [Avis Budget](/stocks/CAR) and [Assured Guaranty](/stocks/AGO) (both **-55.6%**), and [Dillard's](/stocks/DDS) (**-55.0%**). All twelve names cut their diluted share count between **48.9%** and **63.8%** over the decade, measured as-filed from each company's 10-K.

### What is a cannibal stock?

A company that persistently buys back and retires its own shares, so that each remaining share represents a larger claim on the business. The label only earns itself in the filings: a genuine cannibal shows a falling Weighted Average Number Of Diluted Shares Outstanding year after year, not just a large repurchase line that stock-based compensation quietly offsets.

### Which companies buy back the most stock?

Those are two different lists. [eBay](/stocks/EBAY) spent **$37.20B** — the largest cumulative buyback on this leaderboard — but [Apple](/stocks/AAPL), the most-cited repurchaser on earth, retired only **-28%** of its diluted shares over the same decade, roughly half the pace of every name in the top twelve. Dollar volume and net reduction are not the same measurement.

### How much does the average company's share count change?

It rises. Across all **2,076** companies with a complete FY2015–FY2024 10-K history, the median ten-year change in diluted share count was **+2.2%**. Net reduction over a full decade is the exception, which is why anything meaningfully negative is already rare.

### Do buybacks always reduce share count?

No. A repurchase authorization is a ceiling rather than a commitment, and programs get paused, cancelled, or simply left unspent — we traced four companies' announced authorizations against what their filings actually show was spent in [do buybacks reduce share count](/blog/do-buybacks-reduce-share-count).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=companies-reducing-share-count)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 2,076 companies filing a 10-K in each fiscal year 2015-2024, drawn from 3,054 filers with at least one 10-K in the window. Diluted share counts are the as-filed Weighted Average Number Of Diluted Shares Outstanding from SEC EDGAR XBRL, split-adjusted, taken at latest restated vintage per fiscal year; ten-year change is measured on the median of the first three and last three available fiscal years to guard against a single stray vintage. Companies with an implausible (>50 billion) or internally inconsistent diluted-share series were excluded before ranking (62 companies flagged and removed). Buyback and comp figures are as-filed Payments For Repurchase Of Common Stock and Share Based Compensation. Post-filing returns are 12-month cumulative moves from each 10-K's filed date; universe base rate +8.4% mean / +3.0% median across 47,746 fiscal-year filings. Corporate-action artifacts (mergers, spinoffs, reverse splits) were vetted out of the named leaderboard by hand.</sup>

---

## Blog: Companies That Dilute Shareholders: The Worst Offenders
source: https://www.geminiq.com/blog/companies-that-dilute-shareholders

### Companies That Dilute Shareholders: The Worst Offenders
Companies that dilute shareholders show up in the raw SEC filing data long before the story reaches financial media, and the worst offenders cluster by sector rather than by any single bad habit.

Rank every public company by raw growth in diluted shares outstanding and the leaderboard fills with penny stocks and shell companies — a name with **1 million** shares that issues **10 million** more books an infinite-looking percentage gain that says nothing about a real business. Set a size floor, take out companies whose growth-through-equity-issuance is the entire business model, and shareholder dilution stops being one story and becomes seven: a different playbook in every sector, each one traceable to a specific line in a specific filing.

**Study Scope Statement.** This study covers **677 companies** with a complete FY2015-FY2024 10-K filing history and a diluted share count of at least **50 Million** shares in FY2015, pulled as-filed from SEC XBRL data via GeminIQ. This study excludes real estate investment trusts — REITs raise external equity as a structural requirement of their business model, not as a symptom of shareholder-hostile management, and mixing the two produces a misleading ranking. This analysis split-adjusts diluted share counts to control for stock splits, which multiply share count without diluting anyone's proportional ownership. This is a filing-data pattern study, not a forward-looking signal — nothing here predicts what any of these stocks will do next.

## The Universe Note

This study's **677-company** universe is not the same universe used in GeminIQ's companion study of [companies reducing share count](/blog/companies-reducing-share-count). The two studies apply different inclusion rules — this one sets a **50 Million** minimum diluted share count and excludes REITs — so the base rates the two studies report are not directly comparable, and neither ranking should be read as the mirror image of the other.

## Technology: AMD's Share Count Up 109% on $5.1 Billion of SBC

Software and semiconductor companies dominate this sector's leaderboard, and the pattern is almost entirely stock-based compensation rather than distressed financing.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [KOPN](/stocks/KOPN) | 63.5M | 132.9M | +109% |
| [AMD](/stocks/AMD) | 783M | 1,637M | +109% |
| [FIS](/stocks/FIS) | 289M | 555M | +92% |
| [RBA](/stocks/RBA) | 107.4M | 185.3M | +72% |
| [HQY](/stocks/HQY) | 51.9M | 87.0M | +68% |
| [CRM](/stocks/CRM) | 624.1M | 984.0M | +58% |
| [ADI](/stocks/ADI) | 316.9M | 498.7M | +57% |
| [MXL](/stocks/MXL) | 53.4M | 83.6M | +57% |

**The Data:** [AMD](/stocks/AMD)'s diluted share count grew **109%** over the window, from **783 million** to **1.637 billion**, against **$5.1 Billion** in cumulative Share Based Compensation. AMD also closed its all-stock acquisition of Xilinx in 2022, one of the largest stock-funded semiconductor deals on record — a real driver of share growth that sits alongside, not instead of, the SBC total.

**The GeminIQ Edge:** A screener built on trailing revenue growth or margin expansion would show AMD as an unambiguous success story over this window. Only pulling the raw share count directly from the filing — not a [processed "shares outstanding" figure smoothed by an aggregator](/competitor-comparison/sp-capital-iq) — shows the other side of that growth: the business scaled, their ownership didn't.

<center><sup>GeminIQ data study: diluted share count growth by sector, FY2015-FY2024, top offender per sector. Built from as-filed 10-K data via GeminIQ. n = 677 companies, FY2015-FY2024.</sup></center>

## Financials: Columbia Banking System Up 267% on an All-Stock Merger

Regional banks show up almost exclusively for one reason: using their own stock to pay for another bank.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [COLB](/stocks/COLB) | 57.0M | 209.3M | +267% |
| [ONB](/stocks/ONB) | 116.3M | 311.0M | +168% |
| [FHN](/stocks/FHN) | 236.3M | 544.3M | +130% |
| [UCB](/stocks/UCB) | 65.5M | 119.9M | +83% |
| [HBAN](/stocks/HBAN) | 817.1M | 1,476.4M | +81% |
| [TFC](/stocks/TFC) | 757.8M | 1,331.1M | +76% |
| [IBKR](/stocks/IBKR) | 250.0M | 436.0M | +74% |
| [PFS](/stocks/PFS) | 63.1M | 109.7M | +74% |

**The Data:** [Columbia Banking System](/stocks/COLB) leads the sector at **+267%**, with **$2.6 Billion** in cumulative stock issued for acquisitions against just **$108 Million** in Share Based Compensation over the same decade. That ratio is the tell: this isn't a stock-comp story. Columbia Banking System's 2023 combination with Umpqua Holdings was structured as an all-stock merger of equals, and the share count reflects exactly that.

**The GeminIQ Edge:** That **$2.6 Billion** sits under a single tag, `Stock Issued During Period Value Acquisitions` — the exact line an all-stock, tax-free merger press release never quotes, because the number that matters to existing shareholders isn't the deal's advertised terms, it's how many new shares got created to pay for it.

## Healthcare: Geron Up 297% Funding a Pipeline With New Stock

Every name on this list is a clinical-stage company funding a pipeline with no product revenue to lean on, and the pattern repeats with almost no variation.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [GERN](/stocks/GERN) | 162.7M | 646.0M | +297% |
| [PACB](/stocks/PACB) | 78.3M | 288.4M | +268% |
| [MNKD](/stocks/MNKD) | 81.2M | 283.8M | +249% |
| [BCRX](/stocks/BCRX) | 72.9M | 206.7M | +184% |
| [LCTX](/stocks/LCTX) | 79.7M | 200.2M | +151% |
| [CERS](/stocks/CERS) | 96.9M | 184.6M | +90% |
| [PKTX](/stocks/PKTX) | 198.0M | 358.6M | +81% |
| [GMED](/stocks/GMED) | 96.1M | 137.9M | +43% |

**The Data:** [Geron](/stocks/GERN) tops this sector at **+297%**, quadrupling its diluted share count from **162.7 million** to **646.0 million** shares, funded through **$130.8 Million** in new stock offerings layered on top of a decade of clinical trial costs. Geron had no approved product generating revenue for almost the entire window — its 2024 FDA approval of Rytelo came only at the very end of this study's period.

**The GeminIQ Edge:** Standard financial media covers clinical-stage biotech through the lens of trial results and FDA calendar dates. The dilution story runs underneath every one of those headlines the whole time — a company can clear every clinical hurdle and still hand existing shareholders a fraction of the company they started with, and that fact is sitting in the raw filing data years before any approval headline runs.

## Utilities & Telecom: PG&E Up 341% on $19.3 Billion of New Stock

This sector's leaderboard splits into two distinct stories: one bankruptcy-driven, the rest structural.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [PCG](/stocks/PCG) | 487.0M | 2,147.0M | +341% |
| [TRGP](/stocks/TRGP) | 53.6M | 221.3M | +313% |
| [FYBR](/stocks/FYBR) | 72.3M | 248.2M | +243% |
| [ECHO](/stocks/ECHO) | 93.5M | 274.1M | +193% |
| [AROC](/stocks/AROC) | 68.4M | 162.4M | +137% |
| [LUMN](/stocks/LUMN) | 555.1M | 987.7M | +78% |
| [WMB](/stocks/WMB) | 749.3M | 1,223.0M | +63% |
| [ATO](/stocks/ATO) | 101.9M | 152.7M | +50% |

**The Data:** [PG&E](/stocks/PCG) leads this sector at **+341%**, with **$19.3 Billion** in new stock issued against **zero** dollars of Share Based Compensation over the window — the entire increase is a single event, not creep. PG&E filed for Chapter 11 bankruptcy in January 2019 following California wildfire liability claims and emerged in 2020 funded substantially through new equity raised specifically to cover those liabilities.

**The GeminIQ Edge:** None of that **$19.3 Billion** shows up as an operating charge or a one-time writedown anywhere in PG&E's income statement — it's a balance sheet event, permanent and non-recurring, sitting in the equity issuance tags rather than anywhere an earnings-focused reader would think to look for a bankruptcy's cost.

## Consumer: Keurig Dr Pepper Up 611% on the 2018 Merger

Consumer is the thinnest story in this study — one company explains almost the entire sector's dilution.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [KDP](/stocks/KDP) | 192.4M | 1,368.3M | +611% |
| [PENN](/stocks/PENN) | 90.9M | 152.1M | +67% |
| [WYNN](/stocks/WYNN) | 101.7M | 110.3M | +8% |
| [ARMK](/stocks/ARMK) | 246.6M | 266.2M | +8% |
| [FIVE](/stocks/FIVE) | 218.3M | 222.5M | +2% |

**The Data:** [Keurig Dr Pepper](/stocks/KDP)'s diluted share count grew **611%**, from **192.4 million** to **1.37 billion** shares, against **$441 Million** in stock issued for acquisitions and **$642 Million** in cumulative Share Based Compensation. The bulk of that jump traces to the 2018 combination of Keurig Green Mountain and Dr Pepper Snapple Group, structured with a substantial new-equity component to fund the deal.

**The GeminIQ Edge:** After that, the sector goes quiet — every other name in Consumer moved in the single digits to low double digits over a full decade. That's not an accident of this sample; it reflects that mature consumer businesses with steady cash flow generally don't need to issue stock to fund operations, which makes KDP's number a merger artifact rather than a sector pattern.

## Energy: Diamondback Up 239% on $24.3 Billion of Stock-Funded M&A

Shale consolidation shows up here as clearly as the bank mergers do in Financials — stock, not cash, funded the decade's biggest deals.

| Ticker | FY2015 Diluted Shares | FY2024 Diluted Shares | Change |
|---|---|---|---|
| [FANG](/stocks/FANG) | 63.0M | 213.5M | +239% |
| [EQT](/stocks/EQT) | 152.9M | 514.6M | +236% |
| [PTEN](/stocks/PTEN) | 145.4M | 397.2M | +173% |
| [RIG](/stocks/RIG) | 363.0M | 925.0M | +155% |
| [CTRA](/stocks/CTRA) | 413.7M | 745.0M | +80% |
| [EGY](/stocks/EGY) | 58.3M | 103.7M | +78% |
| [SM](/stocks/SM) | 67.7M | 116.0M | +71% |

**The Data:** [Diamondback Energy](/stocks/FANG) leads at **+239%**, with **$24.3 Billion** in stock issued for acquisitions dwarfing **$407.5 Million** in Share Based Compensation and **$4.0 Billion** in buybacks over the same window. Diamondback's 2023 all-stock combination with Endeavor Energy Resources, valued near **$26 Billion**, is the single largest driver of that figure.

**The GeminIQ Edge:** Diamondback also ran a real buyback program in parallel — **$4.0 Billion** worth — which a shareholder-yield calculation would read as capital return. Read next to **$24.3 Billion** in stock issued for one acquisition, the buyback is a rounding error against the dilution, not an offset to it. Neither number alone tells the story; the ratio between them does.

## The Exception: Industrials Topped Out at +31%

Every sector above shows hundreds of percent of dilution somewhere near the top. Industrials tops out at **+31%** ([SXC](/stocks/SXC)), and most of the sector's largest, most recognizable names — Danaher, Roper, Keysight — moved in the low single digits over the full decade. That's not a data gap; it's a sector where mature, cash-generative businesses simply didn't need to issue stock at scale, and it's worth stating plainly rather than forcing a seventh villain leaderboard where the data doesn't support one.

## The Method

This study pulls `Weighted Average Number Of Diluted Shares Outstanding`, split-adjusted for stock splits, from as-filed 10-K data across the full GeminIQ filing universe, cross-referenced against `Share Based Compensation`, `Payments For Repurchase Of Common Stock`, and stock-issuance tags for cause attribution. Full methodology is covered in [The Filing Data Study Methodology](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any company's 10-K on GeminIQ's [Financial Statements](/features#financial-statements) view and look at `Weighted Average Number Of Diluted Shares Outstanding` across five or ten years. If it's climbing, check it against `Share Based Compensation` and `Payments For Repurchase Of Common Stock` over the same window — a buyback program that isn't outrunning the share count it's supposed to offset isn't actually returning capital, it's just slowing the leak. Ten seconds, any ticker.

## Frequently Asked Questions

### What counts as shareholder dilution in SEC filings?

Shareholder dilution shows up as growth in a company's diluted shares outstanding — the weighted-average share count used to calculate earnings per share, filed each period in the 10-K and 10-Q. A rising count means each existing share represents a smaller proportional claim on the company, regardless of what drove the increase.

### Do stock splits count as dilution?

No. A stock split multiplies the share count and divides the share price by the same factor, leaving every shareholder's proportional ownership unchanged. This study adjusts for splits specifically to avoid counting them as dilution.

### Is stock-based compensation always bad for shareholders?

Not inherently — it's a real form of employee pay, and some level of share issuance to fund it is normal even at well-run companies. It becomes a shareholder cost specifically when it isn't offset by buybacks large enough to hold the share count flat or falling, which is the comparison this study's Check Your Holdings method is built to run.

### How much dilution is normal?

There is no single number, and the honest answer from this data is that it depends almost entirely on the sector. Industrials topped out at **+31%** across a full decade, with Danaher, Roper and Keysight moving in the low single digits. Over the same window the Healthcare leader was up **+297%** and the Consumer leader **+611%**. Judge a holding against its own sector's range rather than against one universal threshold.

### What is all-stock merger dilution?

It is share-count growth created by paying for an acquisition in stock instead of cash. It shows up under the `Stock Issued During Period Value Acquisitions` tag rather than anywhere in the income statement, which is why a deal press release can describe a "merger of equals" while existing holders end up with a materially smaller proportional claim. [Columbia Banking System](/stocks/COLB) is the clearest case here: **+267%** on **$2.6 Billion** of stock issued for acquisitions against just **$108 Million** of Share Based Compensation.

### Why did my share count go up?

Three causes account for nearly all of it in this study: [stock-based compensation](/blog/stock-buybacks-vs-stock-compensation) accumulating year after year ([AMD](/stocks/AMD), **+109%**), stock used as acquisition currency ([COLB](/stocks/COLB), [KDP](/stocks/KDP), [FANG](/stocks/FANG)), and a one-time capital raise, usually distressed ([PCG](/stocks/PCG), **+341%** following its Chapter 11 emergence). Reading `Share Based Compensation` next to the stock-issuance tags in the same 10-K tells you which one you are looking at.

### Which stocks have the most dilution?

Within this **677-company** universe, [Keurig Dr Pepper](/stocks/KDP) leads outright at **+611%**, followed by [PG&E](/stocks/PCG) at **+341%**, [Geron](/stocks/GERN) at **+297%**, [PACB](/stocks/PACB) at **+268%**, [Columbia Banking System](/stocks/COLB) at **+267%**, and [Diamondback Energy](/stocks/FANG) at **+239%**. Companies whose entire business model is growth through equity issuance were excluded before ranking, as were REITs.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=companies-that-dilute-shareholders)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

**Data Appendix:** This study draws on GeminIQ's as-filed XBRL extraction across **677 companies** with complete FY2015-FY2024 10-K coverage and a minimum **50 Million** diluted share count in FY2015, using `Weighted Average Number Of Diluted Shares Outstanding`, split-adjusted, cross-referenced against `Share Based Compensation`, `Payments For Repurchase Of Common Stock`, and stock-issuance tags. This study excludes real estate investment trusts (SIC 6798) given their structurally different equity-financing model. Manual review also excluded companies with restated or implausibly-scaled share count figures.

---

## Blog: Companies That Restated Financials: What Followed
source: https://www.geminiq.com/blog/companies-that-restated-financials

### Companies That Restated Financials: What Followed
Companies that restated financials are identifiable directly in the arithmetic of their own as-filed quarterly data, and the twelve months that followed those restated filings underperformed the broader filing universe by a wide margin.

**[Emergent BioSolutions](/stocks/EBS)** filed a restated period in fiscal 2022, and the twelve months that followed produced a cumulative return of **-84.9%**. That is an extreme case, but not an isolated one: across GeminIQ's full as-filed universe, the twelve months following a flagged restated period returned a median of **-12.24%**, against a **+3.00%** median for the broader filing universe over the same forward window — a gap of over **15 percentage points** that widens the further out the window runs.

This study reads GeminIQ's as-filed annual filing universe, flagging restated periods directly in the arithmetic of each company's own quarterly-versus-annual revenue reconciliation. That is the same contamination-detection logic built for GeminIQ's revenue deceleration research, used here rather than any external restatement database. **95,653 annual filings** make up the base universe, of which **3,157** carry the restatement flag, drawn from **3,997 distinct companies** across the full historical record. This is a historical association measured over the sample window, not a forecast for any individual company.

## The Pattern

A restated period is detectable before the market necessarily reacts to it as one, because the underlying arithmetic — a fiscal year's reported total that doesn't reconcile cleanly against the sum of its own quarters — is visible in the filing data itself, independent of whether the company used the word "restatement" in its own disclosure. The safer framing is association, not prediction: restated periods in this sample were **followed by** materially weaker returns over the subsequent year, not caused by the restatement flag itself, and plenty of individual companies in the flagged cohort recovered. But the base-rate gap is wide enough, and holds at every checkpoint from one month out to twelve, to be worth screening for directly.

## The Data

| Forward Window | Restated-Period Cohort (median) | Universe Base Rate (median) | Excess |
|---|---|---|---|
| 1 month | **-1.51%** | -0.34% | -1.17 pts |
| 3 months | **-2.74%** | 0.00% | -2.74 pts |
| 6 months | **-4.78%** | +0.48% | -5.25 pts |
| 12 months | **-12.24%** | +3.00% | -15.24 pts |

Every checkpoint is measured against the broader universe base rate over the same window, not against zero, and every column is drawn from between **1,364** and **1,498** flagged filings — comfortably above the 200-filing floor this kind of comparison requires. The gap is not a one-quarter artifact; it widens steadily from the first month post-filing through the full year, consistent with a restated period being a genuine, persistent signal rather than a brief overreaction that fades.

<center><sup>GeminIQ data study: cumulative post-filing returns for restated-period filings versus the universe base rate, as-filed. Built from as-filed 10-K data via GeminIQ, and post-filing market reaction. n = 1,364–1,498 filings per checkpoint (restated cohort), 47,679–52,581 (base rate).</sup></center>

## The Ranking

Restricted to restated-period filings from companies with over **$50 million** in trailing annual revenue — filtering out micro-cap and shell-company noise — the ten steepest 12-month post-filing declines in GeminIQ's data are:

| Rank | Company | Ticker | Fiscal Year Flagged | 12-Month Forward Return |
|---|---|---|---|---|
| 1 | Exela Technologies, Inc. | [XELA](/stocks/XELA) | 2021 | **-99.4%** |
| 2 | Skillz Inc. | [SKLZ](/stocks/SKLZ) | 2020 | **-87.2%** |
| 3 | Cardlytics, Inc. | [CDLX](/stocks/CDLX) | 2021 | **-86.7%** |
| 4 | New Fortress Energy Inc. | [NFE](/stocks/NFE) | 2024 | **-86.0%** |
| 5 | Emergent BioSolutions Inc. | [EBS](/stocks/EBS) | 2022 | **-84.9%** |
| 6 | Accuray Inc | [ARAY](/stocks/ARAY) | 2025 | **-84.6%** |
| 7 | Owlet, Inc. | [OWLT](/stocks/OWLT) | 2020 | **-83.8%** |
| 8 | Onity Group Inc. | [ONIT](/stocks/ONIT) | 2013 | **-83.4%** |
| 9 | Katapult Holdings, Inc. | [KPLT](/stocks/KPLT) | 2020 | **-82.7%** |
| 10 | Purple Innovation, Inc. | [PRPL](/stocks/PRPL) | 2020 | **-79.0%** |

## The Extremes

**[Exela Technologies](/stocks/XELA)** carries a restated-period flag in two separate fiscal years in GeminIQ's data — 2020 and 2021 — with 12-month forward returns of **-70.5%** and **-99.4%** respectively, the kind of repeat appearance that separates a company working through a one-time accounting issue from one with a more persistent problem. [Skillz Inc.](/stocks/SKLZ), flagged in fiscal 2020, returned **-87.2%** over the following year. Neither case proves the restatement itself caused the decline — both companies faced other well-documented business pressures over the same period — but both are visible in the filing arithmetic well before either became a widely covered story.

## The Method

A period is flagged as restated when GeminIQ's contamination-detection logic finds the fiscal-year annual figure doesn't reconcile against the sum of the company's own reported quarters for that year, benchmarked against that specific company's own historical median quarterly share of its annual total. This is the same detection built for GeminIQ's revenue deceleration research. Post-filing returns are cumulative from each filing's own filed date and are never compounded or added across checkpoints; the 12-month figure is read directly from the filing's own twelfth-month cumulative return column, not derived by summing the shorter windows. Returns behind every checkpoint in this study are winsorized at the 1st and 99th percentile before medians are computed, so a handful of extreme filings do not carry the result. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's as-filed quarterly revenue on GeminIQ and check whether the four quarters actually sum to the reported annual total — a mismatch is a filing-level fact anyone can verify directly against the company's own numbers, independent of whether a restatement has been publicly announced. Running that reconciliation is a method, not a prediction: it flags what's worth a closer look, not what to buy or sell.

## Frequently Asked Questions

### How can a financial restatement be detected directly from filing data?

By checking whether a fiscal year's reported annual figure reconciles against the sum of that company's own four reported quarters. GeminIQ flags a period as restated when that arithmetic doesn't hold, benchmarked against the company's own historical quarterly pattern — independent of whether the company used the word "restatement" in its own disclosure.

### What happens to a stock's returns after a restated filing?

In GeminIQ's data, the twelve months following a flagged restated period returned a median of **-12.24%**, against **+3.00%** for the broader filing universe over the same window — a gap that widens steadily from one month out to twelve.

### Does a restatement always predict a stock decline?

No — this is a historical association measured across the sample, not a forecast for any individual company. Plenty of individual companies in the flagged cohort recovered, and the restatement itself does not cause the decline; both often trace to the same underlying business pressures.

### How many restated filings does this study cover?

**3,157** flagged restated periods out of **95,653** annual filings in the base universe, drawn from **3,997** distinct companies across GeminIQ's full historical record.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=companies-that-restated-financials)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Post-filing market reaction is measured from each filing's filed date. Restatement detection methodology is described above.

---

## Blog: Companies With Net Cash: Balance Sheets With No Debt
source: https://www.geminiq.com/blog/companies-with-net-cash-no-debt

### Companies With Net Cash: Balance Sheets With No Debt
Negative net debt means a company holds more cash and short-term investments than it owes in interest-bearing debt, and as-filed data ranks the largest companies currently running one of these balance sheets.

**[Oracle Corp](/stocks/ORCL)** holds **$31.3 billion** in cash against **$7.2 billion** in short- and long-term debt — a net cash position of **$24.1 billion**. Negative net debt is not a leverage ratio in the way a debt-to-EBITDA multiple is; it describes an entirely different kind of balance sheet, one where the interest-bearing liabilities side of the equation has effectively been erased by cash on hand. The as-filed data shows which large, real, revenue-generating companies are currently running one.

<center><sup>GeminIQ Custom Table for Oracle: cash and cash equivalents ($31,289 million) against total debt ($7.20B) as of May 31, 2026, with the prior five quarters.</sup></center>

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period, restricted to non-financial companies with **at least $5 billion in trailing revenue** and a market capitalization above **$1 billion**. Critically, it also requires a **verified nonzero debt figure** built from GeminIQ's Short-Term Debt and Long-Term Debt line items rather than a single pre-aggregated debt column, so a company only appears here because its cash actually exceeds real, confirmed debt, not because a data field returned zero.

## The Pattern

A company with negative net debt has effectively unlimited flexibility to fund growth, buybacks, or acquisitions from its own balance sheet without touching capital markets — the opposite risk profile of a company carrying multiples of its EBITDA in debt. This is not a story about weak, low-growth businesses avoiding leverage out of necessity; the largest names on this list include one of the biggest software companies in the world mid-buildout and one of the largest e-commerce and retail names on the planet. Net cash at this scale is a choice about capital structure, not a constraint on it.

## The Data

| Rank | Company | Ticker | Sector | Net Cash | Cash | Debt |
|---|---|---|---|---|---|---|
| 1 | Oracle Corp | ORCL | Services | **$24.1B** | $31.3B | $7.2B |
| 2 | Micron Technology, Inc. | MU | Manufacturing | **$19.3B** | $25.0B | $5.7B |
| 3 | Costco Wholesale Corp | COST | Retail Trade | **$13.3B** | $18.9B | $5.7B |
| 4 | MercadoLibre, Inc. | MELI | Services | **$10.3B** | $16.8B | $6.5B |
| 5 | Block, Inc. | XYZ | Services | **$5.9B** | $6.4B | $0.6B |
| 6 | Intuit Inc. | INTU | Services | **$5.8B** | $11.9B | $6.2B |
| 7 | Automatic Data Processing Inc | ADP | Services | **$5.7B** | $10.6B | $5.0B |
| 8 | Accenture plc | ACN | Services | **$5.0B** | $10.2B | $5.1B |
| 9 | NVIDIA Corp | NVDA | Manufacturing | **$4.8B** | $13.2B | $8.5B |
| 10 | Newmont Corp | NEM | Mining | **$4.0B** | $9.0B | $5.1B |
| 11 | Expedia Group, Inc. | EXPE | Transportation | **$3.6B** | $9.1B | $5.5B |
| 12 | Coupang, Inc. | CPNG | Retail Trade | **$3.6B** | $6.2B | $2.6B |
| 13 | Ross Stores, Inc. | ROST | Retail Trade | **$3.2B** | $4.2B | $1.0B |
| 14 | TJX Companies Inc. | TJX | Retail Trade | **$2.7B** | $5.6B | $2.9B |
| 15 | Fortinet, Inc. | FTNT | Manufacturing | **$2.4B** | $2.9B | $0.5B |

<center><sup>GeminIQ Stock Screener sorted by Net Debt, most negative first, before this study's universe filters. Net Revenue in this view is the latest quarter.</sup></center>

## The ASC 842 Caveat Worth Naming

Third-party aggregators routinely fold operating lease liabilities under ASC 842 into a "total debt" figure, which can turn what is actually a net-cash company into an apparently net-debt one purely from a classification choice. An operating lease is a contractual rental commitment, not a note payable, and GeminIQ's debt calculation excludes it for exactly that reason — the debt figures above are commercial paper and term debt only, not lease obligations. A company that looks levered on a platform that merges the two may be a genuine net-cash story once operating leases are separated back out, and this ranking is built specifically to avoid that distortion.

**[Costco](/stocks/COST)** and **[MercadoLibre](/stocks/MELI)** are useful illustrations of why the distinction matters. Both operate large physical or logistics-heavy footprints — the kind of business where lease obligations tend to be substantial — and both still clear this list on genuine interest-bearing debt versus cash alone.

## The Method

Net cash is computed as GeminIQ's as-filed cash and cash equivalents minus total debt. Total debt is Short-Term Debt plus Long-Term Debt as separately filed for each company — the same two-line construction documented in GeminIQ's [Net Debt](https://www.geminiq.com/metrics/calculated-values/net-debt) methodology, excluding operating lease liabilities. Companies where this debt figure resolved to exactly zero were excluded from the ranking rather than treated as verified zero-debt, since a zero can reflect either a truly debt-free balance sheet or an unresolved data field — this study only ranks companies with a confirmed, nonzero debt figure that cash still exceeds. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's Net Debt on GeminIQ and check the sign, then check the underlying Short-Term Debt and Long-Term Debt line items directly rather than trusting a single aggregated figure — the distinction between "zero debt" and "debt data not fully resolved" matters, and the as-filed line items are the only way to tell them apart. Every reader can run that same check for their own holdings.

## Frequently Asked Questions

### What does negative net debt mean?

It means a company holds more cash and short-term investments than it owes in interest-bearing debt. In GeminIQ's data, Oracle currently holds the largest net cash position among large non-financial companies at **$24.1 billion**.

### Do companies with net cash actually have no debt?

Not in this ranking. Every company listed carries real, confirmed debt — Oracle owes **$7.2 billion**, Micron **$5.7 billion** — but each holds more cash than it owes, so net debt is negative. Companies that report literally zero debt are a different, smaller group, and this study excludes them because a zero can also mean an unresolved data field.

### Why do some companies with net cash still appear leveraged on other platforms?

Third-party aggregators often fold operating lease liabilities under ASC 842 into a single "total debt" figure, even though a lease is a contractual rental commitment rather than a note payable. GeminIQ's debt calculation excludes operating leases for exactly that reason, which is why a company like Costco or MercadoLibre can clear this list on genuine interest-bearing debt versus cash alone.

### Is having no debt always a good sign for a company?

A net cash position reflects a capital-structure choice, not a guarantee of quality on its own — it gives a company flexibility to fund growth, buybacks, or acquisitions without touching capital markets, but it doesn't by itself say anything about the underlying business's growth or profitability.

### How many companies does this study cover?

This ranking covers the largest non-financial companies with at least **$5 billion** in trailing revenue, a market capitalization above **$1 billion**, and a verified nonzero debt figure that cash still exceeds, drawn from GeminIQ's current filing snapshot.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=companies-with-net-cash-no-debt)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Rankings are computed from GeminIQ's Financial Statements data across the described universe and snapshot window.

---

## Blog: Consecutive Revenue Growth: Companies Past a Decade
source: https://www.geminiq.com/blog/consecutive-revenue-growth-decade

### Consecutive Revenue Growth: Companies Past a Decade
Consecutive revenue growth for a full decade is rare enough that as-filed data can name every company that has actually done it, and most of the names on the list are not the megacaps most investors would guess first.

**[Sherwin-Williams](/stocks/SHW)** has grown revenue in every single fiscal year since 2010 — a **16-year** unbroken streak verified directly against its as-filed 10-Ks, with no year of decline anywhere in the record. "Compounder" is a word thrown around loosely enough in financial media that it has started to lose meaning; a decade or more of consecutive filed revenue growth, with no exceptions, is a fact that can actually be checked rather than a label that gets applied after the fact.

This study reads GeminIQ's as-filed universe of annual fiscal-year revenue figures, excluding financial-sector companies and periods flagged for contamination in the underlying filing data. It computes each company's current unbroken streak of consecutive fiscal years with positive year-over-year revenue growth, requiring the streak to still be active as of a fiscal year ending in 2024 or later. **160 companies** currently carry a streak of at least eight consecutive years; the table below ranks the twenty longest.

## The Pattern

Ten straight years without a single year of revenue decline is a much higher bar than it sounds. It runs through the 2020 pandemic shock, which knocked plenty of otherwise-strong businesses into a down year. The names that cleared it are concentrated in a specific kind of business: repeat-purchase distribution, subscription or recurring-fee services, and consumer staples with pricing power — categories where demand doesn't evaporate in a bad quarter so much as decelerate.

## The Data

| Rank | Company | Ticker | Sector | Consecutive Growth Years |
|---|---|---|---|---|
| 1 | Sherwin-Williams Co | SHW | Retail-Building Materials | **16 years** |
| 1 | Publix Super Markets Inc | — | Retail-Grocery Stores | **16 years** |
| 1 | Paychex Inc | PAYX | Services | **16 years** |
| 1 | W.W. Grainger, Inc. | GWW | Wholesale-Durable Goods | **16 years** |
| 1 | Verisign Inc | VRSN | Services-Software | **16 years** |
| 1 | Netflix Inc | NFLX | Services | **16 years** |
| 1 | Fastenal Co | FAST | Retail-Building Materials | **16 years** |
| 8 | Church & Dwight Co Inc | CHD | Consumer Products | **15 years** |
| 8 | Synopsys Inc | SNPS | Services-Software | **15 years** |
| 8 | AutoZone Inc | AZO | Retail-Auto Parts | **15 years** |
| 8 | Tractor Supply Co | TSCO | Retail-Building Materials | **15 years** |
| 8 | Eagle Materials Inc | EXP | Cement, Hydraulic | **15 years** |
| 8 | Monster Beverage Corp | MNST | Beverages | **15 years** |
| 8 | Universal Health Services Inc | UHS | Services-Hospitals | **15 years** |
| 8 | McCormick & Co Inc | MKC | Food Preparations | **15 years** |
| 8 | Simpson Manufacturing Co Inc | SSD | Manufacturing | **15 years** |
| 8 | Accenture plc | ACN | Services | **15 years** |
| 8 | Costco Wholesale Corp | COST | Retail-Variety Stores | **15 years** |
| 8 | O'Reilly Automotive Inc | ORLY | Retail-Auto Parts | **15 years** |
| 20 | FactSet Research Systems Inc | FDS | Services-Data Processing | **14 years** |

<center><sup>GeminIQ Financial Statements: Sherwin-Williams annual revenue, fiscal 2009 through 2025. Revenue rises in every year from 2010 on, the 16-year streak in the table above.</sup></center>

<center><sup>GeminIQ Calculated Metrics: Sherwin-Williams Net Revenue TTM Growth (1Y), fiscal 2014 through 2025. Growth is positive every year, from a 26% peak in 2017 to 0.2% in 2024.</sup></center>

## The Names Investors Would Guess, and the Ones They Wouldn't

**[Netflix](/stocks/NFLX)** at sixteen straight years fits the narrative most investors already have in their heads. **[Fastenal](/stocks/FAST)** and **[W.W. Grainger](/stocks/GWW)** — an industrial fastener distributor and a maintenance-and-repair supply wholesaler — almost certainly don't, and both matched Netflix's streak exactly. Neither company depends on a single hit product or a subscriber growth story; both simply sell unglamorous, repeat-purchase industrial supplies to a customer base that keeps buying regardless of the broader news cycle, and the filings show that model surviving 2020 and every other year in the record without a single down year.

## The Method

The streak is computed from GeminIQ's as-filed annual revenue figures, requiring positive year-over-year growth in every consecutive fiscal year with no gap in the filing record. Financial-sector companies and any fiscal year flagged for data contamination in the underlying extract are excluded. A streak counts only if it remains active through a fiscal year ending in 2024 or later, so a company that broke its streak recently does not still appear as a current compounder. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's annual revenue history on GeminIQ and count the consecutive years without a decline for yourself — "consistent grower" is a claim a company's own marketing can make regardless of whether the filings back it up, and the filed annual revenue line is the only way to check it directly rather than taking the claim on faith.

## Frequently Asked Questions

### Which companies have grown revenue every year for a decade or more?

In GeminIQ's data, seven companies currently share the longest active streak at 16 consecutive years: Sherwin-Williams, Publix Super Markets, Paychex, W.W. Grainger, Verisign, Netflix, and Fastenal.

### What kind of companies tend to sustain the longest revenue growth streaks?

Repeat-purchase distribution, subscription or recurring-fee services, and consumer staples with pricing power dominate the list — categories where demand tends to decelerate in a weak period rather than reverse outright.

### Does 2020 break most long revenue growth streaks?

Not for the companies on this list — every streak counted here runs through the 2020 pandemic shock, which is part of what makes an 8-plus-year unbroken streak a meaningfully higher bar than it first sounds.

### How many companies currently have an 8-plus year growth streak?

**160** companies in GeminIQ's data currently carry an active streak of at least eight consecutive fiscal years of positive revenue growth.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=consecutive-revenue-growth-decade)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K filings, publicly available on [SEC EDGAR](https://www.sec.gov/). The consecutive-growth-year ranking is computed from GeminIQ's as-filed annual revenue data across the described universe and snapshot window.

---

## Blog: Daloopa Alternative: As-Filed Model-Ready Data
source: https://www.geminiq.com/blog/daloopa-alternative-sec-data

### Daloopa Alternative: As-Filed Model-Ready Data
A Daloopa alternative for filing-level research. Daloopa extracts model-ready KPIs from filings, investor presentations, and press releases with source hyperlinks; this post explains the difference between auditability to a document and traceability to a tagged filing fact.

Daloopa is the closest thing on this list to a philosophical ally. Where most platforms treat traceability as a compliance footnote, Daloopa built the product around it: every data point carries a hyperlink to the document it came from, extraction runs through AI parsing plus expert review with a claimed accuracy rate above **99%**, and the output lands directly in an analyst's Excel model without breaking its structure. The company reports coverage of more than **6,000** tickers with around thirteen years of history, and markets four to ten times more data points per ticker than template-based providers.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=daloopa-alternative-sec-data)**

Anyone who has spent a weekend rebuilding a model after a restatement understands why hedge funds pay for that.

The distinction worth drawing is subtle and it matters more than the feature overlap suggests. Daloopa's extraction spans SEC filings, investor presentations, press releases, and select transcripts. That breadth is the product's central advantage for a modeler — and it means "auditable" describes a link to whichever document supplied the figure, which is not always the audited, tagged statutory filing.

## Table of Contents

- [Two Different Definitions of Traceable](#two-different-definitions-of-traceable)
- [The Datapoint Advantage Comes From Outside the Filing](#the-datapoint-advantage-comes-from-outside-the-filing)
- [Curated Coverage Versus the Filer Universe](#curated-coverage-versus-the-filer-universe)
- [The Unit of Work Is the Model](#the-unit-of-work-is-the-model)
- [What Tag-Level Sourcing Provides](#what-tag-level-sourcing-provides)
- [Which Problem You Are Solving](#which-problem-you-are-solving)
- [Frequently Asked Questions](#frequently-asked-questions)

## Two Different Definitions of Traceable

Both products use the word. They mean adjacent but distinct things, and the gap is where the comparison lives.

A source hyperlink answers: which document did this number appear in, and where on the page. That is a strong form of auditability, far stronger than the industry norm of a value with no lineage at all, and it lets an analyst click from a cell in a model to the sentence that produced it.

Tag-level traceability answers a narrower question: which XBRL fact, as tagged by the filer in its own submission, produced this value. The distinction is that the second one is the company's own machine-readable assertion, filed under the signature of its officers, rather than a figure a parser located inside a document and assigned a label to.

Neither is superior in the abstract. They serve different verification standards. If the question is "where did this come from," a hyperlink settles it. If the question is "is this the number the company reported to the SEC under this specific tag," you need the tag, because a parser reading a table has to decide what the row means and a filer tagging a fact has already declared it.

For most modeling work the hyperlink is sufficient and faster. For a conclusion that has to withstand somebody reconstructing it independently, the tag is the thing that does not require trusting an extraction.

## The Datapoint Advantage Comes From Outside the Filing

Daloopa's headline claim — several times the data points per ticker of a template-based provider — is credible and worth understanding mechanically, because it explains exactly where the extra data comes from.

A standardized fundamentals template captures the financial statements. Daloopa captures those plus guidance, non-GAAP KPIs, segment and geographic breakdowns, and disclosures pulled from investor presentations and press releases. Subscriber counts, same-store sales, bookings, adjusted margins, capacity metrics, management's forward guidance — the operating drivers that actually move a model and that no financial statement contains.

That is a real capability and a filings-only product does not replicate it. It is also, by construction, a body of data that sits outside the audited statutory record.

An investor presentation is management's own framing. Guidance is a forecast. A non-GAAP KPI is defined by the company and can be redefined by the company. All of it is first-party, and much of it is the most informative material available about how a business runs. None of it carries the same standing as an audited financial statement tagged in an XBRL submission.

A dataset that mixes both is more useful for modeling and requires the analyst to know which is which. The hyperlink tells you, if you click it. The cell does not.

## Curated Coverage Versus the Filer Universe

Coverage tells you who a product is built for.

Around **6,000** tickers is deep coverage of the companies institutional analysts actually model — the liquid, followed, modellable universe. It is a curation decision, not a limitation, because building comprehensive KPI extraction on a microcap that files once a quarter and holds no earnings call would cost more than anyone would pay for it.

The EDGAR filer population is considerably larger. Every registrant files, whether or not anyone models it, and the companies with no analyst coverage and no investor presentation are frequently the ones a fundamental investor is hunting through. A filings-first pipeline has no coverage decision to make: if it filed, it is in the dataset.

That is the practical divergence for anyone working below the institutional universe. Extraction products cover the companies worth extracting. Filings cover everyone.

## The Unit of Work Is the Model

Daloopa's design reveals its intended workflow at every level, and it is a sell-side and hedge-fund workflow.

The Updater keeps an existing Excel model current as new filings land. The Model Builder generates a starting structure. Custom templates match a firm's own conventions. The API and MCP integrations push data into agent and LLM workflows. All of it presumes that a model already exists, or is about to, and that the job is populating and maintaining it.

That is a correct design for a covering analyst who maintains thirty models and updates them every quarter. Data entry is a real cost center at that scale, and automating it is worth an enterprise contract.

A different workflow starts before the model. Reading a filing to decide whether the business is worth modeling at all, checking whether a caption changed between years, tracing how a liability behaved across a decade, or examining what a company reported before a collapse — none of that begins with a template to fill. The unit is the filing, not the cell.

## What Tag-Level Sourcing Provides

GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value. The scope is the statutory record: what was filed, as filed, tagged as the filer tagged it.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years. [Custom Tables](/features#custom-tables) assemble specific reported items into a view. [Visualizations](/features#visualizations) chart the reported structure over time, which is where reporting changes become visible rather than being smoothed away. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow](/metrics/calculated-values/free-cash-flow), and [Invested Capital](/metrics/calculated-values/invested-capital) are computed from those as-filed inputs, so a derived figure can be checked against the reported facts behind it. [Stock Screeners](/features#screener) run across the same layer, and there is no coverage tier that determines which companies made the cut.

What is absent is equally clear. No guidance, no non-GAAP KPIs sourced from presentations, no model sync, no Excel updater. If a metric was never tagged in a filing, it is not in the dataset.

## Which Problem You Are Solving

Frame the decision around what breaks your week.

If the bottleneck is maintaining models — thirty tickers, quarterly updates, a team that cannot afford a stale number in a book that trades — then extraction automation with source links is the correct purchase, and the enterprise price is measured against analyst hours rather than against a data subscription.

If the bottleneck is verification — establishing what a company reported, under which tag, in which filing, across a period long enough to see a pattern — then the model is downstream of the question and a filings-first pipeline is where the work happens.

For the version of this question where the extracted data is management's own framing rather than a filed statement, the [Quartr alternatives](/blog/quartr-alternative-sec-filing-data) post covers first-party material specifically.

Most institutional desks need both, which is why this comparison resolves as a sequence rather than a choice. The extracted KPI tells you how the business performed against how management framed it. The tagged filing tells you what the company put its name to — and only one of those two things is the same document a year from now.

## Frequently Asked Questions

### What are the best Daloopa alternatives?

It depends on the bottleneck. For automated model population and Excel updating, the substitutes are other extraction and model-sync products aimed at institutional analysts. For filing-level verification across the whole EDGAR registrant population, the alternative is a platform that extracts directly from SEC filings and preserves as-filed line items with XBRL tag traceability.

### What is the difference between source-linked and tag-level traceability?

A source link identifies the document a number appeared in and where on the page. Tag-level traceability identifies the specific XBRL fact the filer tagged in its own SEC submission. The first tells you where a figure was found; the second tells you what the company asserted under a defined tag in a signed filing.

### Does Daloopa data come only from SEC filings?

No, and that is intentional. Daloopa's published materials describe extraction spanning SEC filings, investor presentations, press releases, and select transcripts, which is how it captures guidance, non-GAAP KPIs, and segment detail that financial statements do not contain. Those additional data points are first-party but sit outside the audited statutory record.

### How much of the market do extraction platforms cover?

Daloopa reports coverage of more than **6,000** tickers. The EDGAR filer population is substantially larger, because every registrant files regardless of whether an analyst models it. Extraction coverage is a curation decision aimed at the companies institutional analysts actually cover.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=daloopa-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Daloopa coverage figures, history depth, source-document scope, accuracy claim, extraction methodology, and Excel and API product descriptions reviewed August 2, 2026 from Daloopa's own site and product pages plus third-party tool listings. Vendor-reported figures are stated as such.

---

## Blog: Days Inventory Outstanding: The Gross Margin Hit
source: https://www.geminiq.com/blog/days-inventory-outstanding-gross-margin-hit

### Days Inventory Outstanding: The Gross Margin Hit
Days Inventory Outstanding measures how long a company holds inventory before selling it, and in GeminIQ's filing data, a sharp year-over-year rise in that figure is followed by gross margin compression far more often than the broader filing universe experiences.

**[Diebold Nixdorf](/stocks/DBD)**'s Days Inventory Outstanding jumped from **69.98 days** to **224.31 days** — inventory that once turned over in about ten weeks was suddenly sitting on the books for more than seven months. One year later, the company's trailing gross profit margin had fallen from **48.11%** to **21.84%**, a decline of **26.27 percentage points**. Inventory piling up isn't just a working-capital footnote. It's frequently the first visible sign that a company is about to discount its way through a glut it can't sell at full price.

This study reads GeminIQ's as-filed universe of trailing-twelve-month Days Inventory Outstanding readings, computing each company's year-over-year change in DIO and matching it to that company's own trailing gross profit margin one quarter and one year later. **90,260** filing-periods carry a valid year-over-year DIO comparison after excluding companies without a real, in-range inventory balance. That's a natural filter for inventory-carrying businesses across manufacturing, hardware, and physical-goods sectors, rather than a hand-picked sector list. This is a historical association measured over the sample window, not a forecast for any individual company.

## The Pattern

Days Inventory Outstanding rising is not automatically a problem — a company can be stocking up ahead of a launch or a seasonal peak. But when DIO rises sharply relative to how the rest of the filing universe is moving in the same period, it tends to mean something specific: sales aren't clearing inventory at the pace the company expected. That gap usually gets closed with a markdown, a write-down, or both — both of which show up directly in gross margin. Whether that relationship actually holds up across thousands of filings, rather than in the handful of well-known cases most investors already know, is what this comparison tests.

## The Data

| Cohort | Median Gross Margin Change, 1 Quarter Later | Median Gross Margin Change, 1 Year Later | N (1yr) |
|---|---|---|---|
| Top-decile DIO increase | **-0.08 pts** | **-0.47 pts** | 7,620 |
| Rest of universe | +0.03 pts | +0.15 pts | 69,156 |

<center><sup>GeminIQ data study: median trailing gross profit margin change, one quarter and one year after a filing, for companies in the top decile of year-over-year Days Inventory Outstanding increase versus the rest of the universe. Built from as-filed 10-K/10-Q data via GeminIQ. n = 7,620 (top decile, 1yr window), 69,156 (rest of universe, 1yr window).</sup></center>

<center><sup>GeminIQ data study: median trailing gross profit margin change after a top-decile year-over-year Days Inventory Outstanding increase, versus the rest of the universe. Built from as-filed 10-K/10-Q data via GeminIQ.</sup></center>

The top decile of DIO increase — a median jump of **49.3 days** year-over-year — is followed by a median gross margin decline of **0.47 percentage points** a year later, against a median **gain** of **0.15 points** for the rest of the universe. On a mean basis, winsorized at the top and bottom 1%, the gap is wider still: **-1.56 points** for the top-decile cohort against **+0.40 points** for the base rate, a swing of nearly two full percentage points. The effect is present but modest at the one-quarter mark (-0.08 points versus +0.03 points). It widens by the one-year checkpoint, consistent with a markdown cycle that takes real time to work through a company's cost of goods sold rather than hitting in the same quarter the inventory builds.

## The Extremes

**[Diebold Nixdorf](/stocks/DBD)**, cited in the opening, shows the pattern at its most severe: a **154.33-day** jump in DIO followed by a **26.27-point** gross margin collapse within a year. That collapse was part of a multi-year margin struggle at the ATM and banking-hardware maker that would eventually contribute to a 2023 Chapter 11 restructuring. **[Wolfspeed](/stocks/WOLF)** (then trading as Cree) shows the more typical, less dramatic version: DIO rose **146.73 days** in a 2018 filing, and gross margin actually ticked up slightly one quarter later before falling **11.71 points** over the full year. That lag is the reminder — this pattern plays out over time, not immediately, and "followed by" is doing real work in that sentence rather than "predicts."

<center><sup>GeminIQ Custom Table showing Diebold Nixdorf's Days Inventory Outstanding rising to 224 days at September 2015 and trailing gross profit margin falling from 48.11% to 21.84% by September 2016.</sup></center>

<center><sup>GeminIQ Custom Table showing Wolfspeed's Days Inventory Outstanding and trailing gross profit margin from September 2018 to December 2019.</sup></center>

## The Method

[Days Inventory Outstanding](https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding) and [Gross Profit Margin](https://www.geminiq.com/metrics/margin-metrics/gross-profit-margin) are both GeminIQ's trailing-twelve-month calculated metrics. Year-over-year DIO change compares each filing's reading to the same company's reading from approximately one year earlier, validated to a 330–400 day gap to exclude irregular fiscal cadences. Forward gross margin change is computed the same way, comparing each filing's margin to that same company's next quarterly reading (validated to a 75–110 day gap) and to its reading roughly a year out (330–400 day gap). Both DIO values in a comparison are required to fall between 1 and 365 days, which serves as this study's inventory-carrying filter — a company with no real inventory balance doesn't produce a usable DIO reading in the first place. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any inventory-carrying position's Days Inventory Outstanding trend on GeminIQ's [Calculated Metrics](/features#calculated-metrics) view and check whether it's climbing meaningfully faster than its own recent history. A rising DIO alone isn't a verdict, but this study's data says it's worth watching the gross margin line over the following few quarters rather than assuming inventory and margin move independently of each other.

## Frequently Asked Questions

### What does a rising Days Inventory Outstanding mean for gross margin?

In GeminIQ's data, companies in the top decile of year-over-year DIO increase saw a median gross margin decline of 0.47 percentage points over the following year, against a median gain of 0.15 points for the rest of the universe — a gap consistent with inventory that isn't clearing at full price eventually getting marked down.

### Does a rising DIO always mean a company is in trouble?

No. A rising DIO can reflect a deliberate stock-up ahead of a launch or seasonal demand, not just unsold goods. The effect in this study is a median, base-rate-level pattern across a large sample — individual companies can and do buck it, which is why the trend is worth watching over several quarters rather than reacting to a single filing.

### How is the gross margin effect measured — one quarter or one year out?

Both, and the two windows tell different parts of the story. The effect is small at one quarter (-0.08 points for the top-decile cohort versus +0.03 points for the base rate) and widens substantially by one year (-0.47 versus +0.15), consistent with a markdown or write-down cycle that takes time to fully move through cost of goods sold.

### How many filings does this study cover?

**90,260** filing-periods with a valid year-over-year Days Inventory Outstanding comparison, of which the top decile — companies with the sharpest DIO increases — carries **7,620** filings with a matched one-year-forward gross margin reading.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=days-inventory-outstanding-gross-margin-hit)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 90,260 filing-periods with a valid year-over-year Days Inventory Outstanding comparison, built from GeminIQ's calculated Days Inventory Outstanding and Gross Profit Margin metrics. Forward gross margin changes are winsorized at the top and bottom 1%. Diebold Nixdorf's and Wolfspeed's cited figures predate the 3-year window shown on their current GeminIQ stock pages and are drawn from GeminIQ's full as-filed history. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Discounted Cash Flow (DCF) Model: Step-by-Step Walkthrough
source: https://www.geminiq.com/blog/dcf-valuation-model-step-by-step

### Discounted Cash Flow (DCF) Model: Step-by-Step Walkthrough
A discounted cash flow (DCF) model estimates a company's intrinsic value by projecting future free cash flow and discounting it back to the present at a required rate of return. This guide walks through every step — free cash flow, discount rate, terminal value — using NVIDIA's most recent 10-Q as a live example.

Most "how to build a DCF model" guides online skip the part that actually determines whether the output means anything: where the numbers come from. They hand you a formula, plug in a free cash flow figure that appears from nowhere, and arrive at a tidy intrinsic value. But standard financial media doesn't read the footnotes — and neither, it turns out, do most DCF tutorials. This guide builds a complete discounted cash flow model from scratch, using [NVIDIA's](/stocks/NVDA) Q1 FY2027 10-Q (filed May 20, 2026, period ending April 30, 2026) as a live, traceable example, with every input sourced directly from the as-filed cash flow statement rather than a pre-packaged number you have to take on faith.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=dcf-valuation-model-step-by-step)**

---

## Table of Contents

- [What Is a Discounted Cash Flow (DCF) Model?](#what-is-a-discounted-cash-flow-dcf-model)
- [The DCF Formula: Free Cash Flow, Discount Rate, and Terminal Value](#the-dcf-formula-free-cash-flow-discount-rate-and-terminal-value)
- [Step 1: Pulling the Free Cash Flow Inputs From the Filing](#step-1-pulling-the-free-cash-flow-inputs-from-the-filing)
- [Step 2: Projecting Future Free Cash Flow](#step-2-projecting-future-free-cash-flow)
- [Step 3: Choosing a Discount Rate](#step-3-choosing-a-discount-rate)
- [Step 4: Terminal Value and Discounting to Present Value](#step-4-terminal-value-and-discounting-to-present-value)
- [The Full Walkthrough: NVIDIA's Implied Value](#the-full-walkthrough-nvidias-implied-value)
- [Why Most DCF Models Are Wrong Before the Math Even Starts](#why-most-dcf-models-are-wrong-before-the-math-even-starts)
- [Building Your Own DCF With GeminIQ's Raw Filing Data](#building-your-own-dcf-with-geminiqs-raw-filing-data)

---

## What Is a Discounted Cash Flow (DCF) Model?

A discounted cash flow model values a business as the sum of all the cash it is expected to generate in the future, converted into today's dollars. The logic is simple even when the spreadsheet isn't: a dollar of free cash flow five years from now is worth less than a dollar today, because of inflation, opportunity cost, and risk. A DCF model projects a company's future free cash flow, discounts each year back to present value using a required rate of return, and adds a terminal value to capture everything beyond the explicit forecast window. The result is an estimate of intrinsic value — the present value of all future cash a business can distribute to its owners, independent of whatever the market happens to be paying for it on a given day. For a fuller treatment of how intrinsic value relates to book value and other valuation anchors, see our [Value Investing Glossary](/blog/value-investing-glossary).

The model has exactly three moving parts: free cash flow, a discount rate, and a terminal value. Get any one of them wrong — or worse, source it from a number you can't trace back to the filing — and the entire output is fiction dressed up as precision.

---

## The DCF Formula: Free Cash Flow, Discount Rate, and Terminal Value

In its full form, the DCF formula sums the present value of each projected year of free cash flow, then adds the present value of the terminal value:

**Intrinsic Value = Σ [FCF₍ₜ₎ / (1 + r)ᵗ] + [Terminal Value / (1 + r)ⁿ]**

Where FCF₍ₜ₎ is the projected free cash flow in year t, r is the discount rate, and n is the final year of the explicit forecast. Each component requires a separate decision, and each decision is a place where a model can quietly go wrong. Free cash flow needs a clean, traceable starting point. The discount rate needs to reflect the actual risk of the business. And the terminal value — which in most DCF models accounts for more than half of the total output — needs an assumption about long-run growth that won't fall apart under scrutiny.

### What Is the Discount Rate in a DCF Model?

The discount rate represents the minimum annual return an investor requires to compensate for the risk of owning the business, and it is usually estimated using the [weighted average cost of capital](/blog/how-to-calculate-wacc-from-10k) (WACC) — a blend of the cost of equity and the after-tax cost of debt, weighted by how much of each the company uses to finance itself. WACC is not a figure GeminIQ calculates or displays as a platform metric; it is an external assumption every analyst has to bring to the model independently, typically built from the company's [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), interest expense, and an estimate of the equity risk premium. What GeminIQ does provide is every one of the raw balance sheet and cash flow inputs needed to build that estimate yourself, sourced directly from the filing rather than smoothed by a third party.

---

## Step 1: Pulling the Free Cash Flow Inputs From the Filing

Every DCF model starts with a base year of free cash flow, and that number is only as good as its source. For the quarter, [NVIDIA's](/stocks/NVDA) Q1 FY2027 10-Q reports Net Cash Provided by Operating Activities of **$50.34 Billion**, tagged under the XBRL identifier `NetCashProvidedByUsedInOperatingActivities`. Capital expenditures ran **$1.76 Billion** against that, filed under the line item "Purchases Related to Property and Equipment and Intangible Assets" with the XBRL tag `PaymentsToAcquireProductiveAssets`. Stretch both figures to a trailing-twelve-month basis instead of a single quarter, and the gap widens: **$125.65 Billion** in TTM operating cash flow against just **$6.57 Billion** in TTM capital expenditures — the difference between those two numbers is the model's entire starting point.

GeminIQ's [Free Cash Flow](/metrics/calculated-values/free-cash-flow) metric calculates that subtraction automatically — TTM operating cash flow minus TTM capex — producing **$119.08 Billion** in trailing twelve-month free cash flow for the period ending April 30, 2026. Divide that by [NVIDIA's](/stocks/NVDA) basic shares outstanding and GeminIQ's [Free Cash Flow Per Share](/metrics/per-share-metrics/free-cash-flow-per-share) metric returns **$4.90** — the actual per-share cash base every projection in this walkthrough builds from. This is also the number most likely to be quietly altered by a third-party aggregator before you ever see it: some platforms sweep acquisition spending or capitalized software costs into the capex line, shrinking reported free cash flow without disclosing the change. GeminIQ takes capital expenditures exactly as filed, nothing added, nothing smoothed.

<center><sup>GeminIQ Financial Statements showing NVIDIA's `Net Cash Provided By Used In Operating Activities` and `Payments To Acquire Productive Assets` from the Q1 FY2027 10-Q, the two raw cash flow statement inputs every DCF model's base year depends on.</sup></center>

---

## Step 2: Projecting Future Free Cash Flow

A base year of free cash flow is only useful once it's extended forward, and that projection should be grounded in the company's actual growth trajectory rather than a number pulled from thin air. GeminIQ's [Revenue Growth](/metrics/growth-metrics/revenue-growth) metric shows [NVIDIA's](/stocks/NVDA) trailing-twelve-month revenue growth decelerating sharply over the past two years — from as high as **194.69%** in mid-2024 down to **70.68%** in the most recent quarter, with a slight reacceleration from **65.47%** the quarter prior. That deceleration curve is the entire justification for tapering a growth assumption forward rather than projecting a flat rate to infinity, which is the single most common error in amateur DCF models.

For this walkthrough, the explicit forecast applies a fading growth rate to the **$119.08 Billion** base: **40%** in Year 1, tapering to **30%**, **22%**, **16%**, and **12%** by Year 5. This taper is the analyst's own assumption, built to reflect a hyper-growth business normalizing toward a sustainable pace — it is not a GeminIQ-calculated output, and a different analyst could reasonably choose a different curve. Applied to the base, the projection very nearly triples free cash flow over five years: **$166.71 Billion** in Year 1, climbing to **$216.72 Billion**, **$264.40 Billion**, and **$306.70 Billion** through Years 2 to 4, before reaching **$343.50 Billion** in Year 5. That trajectory, not the discount rate, is where most of a DCF model's optimism actually lives.

<center><sup>GeminIQ Visualizations showing NVIDIA's TTM Free Cash Flow and Revenue Growth trend across the past eight quarters, the historical curve a defensible DCF growth taper should be anchored to.</sup></center>

---

## Step 3: Choosing a Discount Rate

With five years of projected free cash flow in hand, the next decision is the one most tutorials gloss over — and the one with the largest swing on the final output: the discount rate. For this walkthrough, the rate is set at **10%**, a reasonable starting estimate for a highly profitable, low-leverage company, but explicitly an assumption rather than a platform-calculated figure. [NVIDIA's](/stocks/NVDA) balance sheet supports a relatively low cost of capital: total debt of **$8.47 Billion** against total equity of **$195.47 Billion**, and a net cash position of **$4.77 Billion** once that debt is offset against cash on hand. A heavily leveraged company would warrant a higher discount rate to compensate for added financial risk; a balance sheet this clean argues for something closer to the equity risk premium alone.

A terminal growth rate of **3.5%** is applied beyond Year 5 — roughly in line with long-run nominal GDP growth, the standard ceiling for a perpetuity assumption, since no company can structurally outgrow the economy forever without eventually becoming the entire economy.

---

## Step 4: Terminal Value and Discounting to Present Value

The terminal value captures every dollar of free cash flow beyond the explicit five-year window, calculated using the Gordon Growth formula:

**Terminal Value = FCF₅ × (1 + g) / (r − g)**

Applying the **3.5%** terminal growth rate and **10%** discount rate to Year 5's **$343.50 Billion** in projected free cash flow produces an undiscounted terminal value of **$5.47 Trillion** — discounted back five years at **10%**, that shrinks to **$3.40 Trillion** in present-value terms. The same discounting applies to each of the five explicit years individually, dividing each by (1.10) raised to the power of its respective year; summed together, they contribute **$952.07 Billion** in present value. Together, the discounted cash flows and the discounted terminal value produce an implied [enterprise value](/metrics/valuation-metrics/enterprise-value) of **$4.35 Trillion**.

From enterprise value to equity value requires one more adjustment: subtracting net debt. Because [NVIDIA](/stocks/NVDA) carries a net cash position rather than net debt — confirmed directly by GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) metric at **-$4.77 Billion** — that cash is added back rather than subtracted, bringing implied equity value to **$4.35 Trillion**.

---

## The Full Walkthrough: NVIDIA's Implied Value

Divide that **$4.35 Trillion** implied equity value by [NVIDIA's](/stocks/NVDA) **24.39 Billion** diluted shares outstanding and the model produces an intrinsic value of **$178.47** per share. Compare that to the **$199.34** closing price embedded in this same filing snapshot, and the model implies the market is pricing in roughly **10.47%** more value than this base-case assumption set supports.

That gap is not a verdict on whether the stock is cheap or expensive — a DCF model is not a buy or sell signal, and no single discount rate or growth taper deserves that much confidence. It is a transparent record of which assumptions an investor would need to hold in order to justify the price the market is already paying, built from a free cash flow base that traces directly back to the filing rather than a black box.

---

## Why Most DCF Models Are Wrong Before the Math Even Starts

The textbook criticism of DCF models is that they are wildly sensitive to small changes in assumptions — and the math bears that out. Move the discount rate from **8%** to **12%** at a **2.5%** terminal growth rate, and the implied per-share value falls from **$220** to **$123**. Raise terminal growth from **2.5%** to **4.5%** instead, and the spread widens further: at an **8%** discount rate, fair value ranges from **$220** to **$328**; at **12%**, from **$123** to **$148**. A handful of percentage points in two assumptions can swing the output by more than **150%**.

That sensitivity is real, but it obscures a more practical problem that gets far less attention: garbage in, garbage out doesn't start at the discount rate. It starts at the free cash flow base. If the operating cash flow or capital expenditure figure feeding Year 1 of the model is itself wrong — smoothed by an aggregator, miscategorized, or pulled from a stale data source — every projected year inherits that error, compounding it forward five years and then baking it permanently into the terminal value. A discount rate assumption is at least visible and adjustable; a corrupted base-year cash flow figure usually isn't, because most platforms don't show their work. For a deeper look at how aggregator normalization choices distort the inputs that feed models like this one, see [Third-Party Financial Data: What Gets Lost When the Data Is Processed](/blog/third-party-financial-data-problems) and [What "Normalized" Financial Data Actually Means](/blog/financial-data-normalization-explained). The discount rate is the part of a DCF model you're supposed to argue about. The free cash flow base shouldn't be.

---

## Building Your Own DCF With GeminIQ's Raw Filing Data

Replicating this walkthrough for any company starts in the same place: GeminIQ's [Financial Statements](/features#financial-statements) view, pulled directly from the company's most recent 10-Q or 10-K, to source operating cash flow and capital expenditures exactly as filed. From there, the [Calculated Metrics](/features#calculated-metrics) tab surfaces Free Cash Flow, Free Cash Flow Per Share, Revenue Growth, and [Return on Invested Capital (ROIC)](/blog/roic-return-on-invested-capital-explained) — [NVIDIA's](/stocks/NVDA) ROIC currently sits at **99.15%** TTM, a useful sanity check on whether the growth taper assumed in Step 2 is consistent with how efficiently the company is actually deploying new capital. GeminIQ's [Visualizations](/features#visualizations) feature charts free cash flow and revenue growth across eight or more quarters in one view, which is the fastest way to build a defensible taper curve rather than guessing at one.

None of this replaces the judgment a DCF model requires — the discount rate, the growth taper, the terminal multiple are still yours to defend. But the free cash flow base, the capital structure, and the growth history that those judgments should be built on are not things worth guessing at. They're in the filing. The only question is whether the platform you're using shows them to you as filed, or as someone else decided to round them.

---

### Related Reading

- [Return on Invested Capital (ROIC) Explained](/blog/roic-return-on-invested-capital-explained) — ROIC measures whether a company's reinvested capital is actually earning a return above its cost, the same question a DCF's growth taper implicitly answers.
- [Free Cash Flow Yield Explained: How to Find Undervalued Stocks](/blog/free-cash-flow-yield-explained) — a simpler, single-number alternative to a full DCF that uses the same free cash flow base built in Step 1 of this guide.
- [Third-Party Financial Data: What Gets Lost When the Data Is Processed](/blog/third-party-financial-data-problems) — how aggregator capex and cash flow definitions quietly distort the base-year inputs every DCF model depends on.
- [NVIDIA 10-K Analysis (2026): 66% ROIC and the $120 Billion Cash Machine](/blog/nvidia-10k-analysis-2026) — a full capital-return audit of the same company using its prior annual filing.
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary) — full definitions of intrinsic value, book value, and the other valuation anchors referenced in this guide.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=dcf-valuation-model-step-by-step)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference NVIDIA Corporation's Q1 FY2027 10-Q (filed May 20, 2026, period ending April 26, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001045810/000104581026000052/nvda-20260426.htm).

---

## Blog: Gross Debt-to-EBITDA: Formula, Benchmarks, and Tiers
source: https://www.geminiq.com/blog/debt-to-ebitda-ratio-explained

### Gross Debt-to-EBITDA: Formula, Benchmarks, and Tiers
Gross Debt-to-EBITDA is the leverage metric credit analysts and private equity firms read first — the full debt load with no offset for cash. This post covers the formula, benchmark tiers, industry context, how it differs from the net ratio, and why the EBITDA definition your platform uses changes the number you see.

When private equity firms price a leveraged buyout, the first number they underwrite is Debt-to-EBITDA. When Moody's and S&P assign a credit rating to a publicly traded company, Debt-to-EBITDA is one of their primary quantitative inputs. When a lender funds an acquisition, the maximum allowable leverage ratio baked into the loan covenant is almost always expressed as a multiple of EBITDA. Yet most retail investors encounter the ratio as a single number on a data provider's dashboard and move on — without reading the fine print that determines whether that number is accurate. The formula is two inputs divided. The variables inside each of those inputs can change the result substantially depending on how they were defined.

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## Table of Contents
- [What Is the Debt-to-EBITDA Ratio?](#what-is-the-debt-to-ebitda-ratio)
- [The Debt-to-EBITDA Formula](#the-debt-to-ebitda-formula)
- [What Is a Good Debt-to-EBITDA Ratio?](#what-is-a-good-debt-to-ebitda-ratio)
- [Why Private Equity Uses Debt-to-EBITDA First](#why-private-equity-uses-debt-to-ebitda-first)
- [How Credit Rating Agencies Apply Debt-to-EBITDA](#how-credit-rating-agencies-apply-debt-to-ebitda)
- [Debt-to-EBITDA vs. Net Debt-to-EBITDA](#debt-to-ebitda-vs-net-debt-to-ebitda)
- [Debt-to-EBITDA Across Industries](#debt-to-ebitda-across-industries)
- [Why Your Platform's Number Might Be Wrong](#why-your-platforms-number-might-be-wrong)

---

## What Is the Debt-to-EBITDA Ratio?

### What Does Debt-to-EBITDA Measure?

The Debt-to-EBITDA ratio measures how many years of current earnings a company would need to pay off its total debt — assuming every dollar of EBITDA were devoted to debt repayment. A company with **$5 billion** in total debt and **$1 billion** in TTM EBITDA carries a Debt-to-EBITDA ratio of **5.0x**. It would theoretically need five years of full EBITDA to retire that debt.

No company actually operates that way. EBITDA is a pre-tax, pre-interest figure. The actual cash available for debt repayment after taxes, interest obligations, and capital expenditures is materially lower — which is why [Free Cash Flow](/metrics/calculated-values/free-cash-flow) is the more precise measure of what a business can actually apply toward obligations. But Debt-to-EBITDA remains valuable specifically because EBITDA standardizes across companies with different tax structures, interest burdens, and depreciation profiles. It compares earning power to debt load on a relatively level playing field, which is how it became the lingua franca of leveraged finance.

EBITDA appears as the denominator in two distinct analytical contexts that are frequently confused. In [EV/EBITDA](/blog/ev-ebitda-vs-pe-ratio-explained), it anchors a valuation multiple — [enterprise value](/metrics/valuation-metrics/enterprise-value) relative to earnings. In Debt-to-EBITDA, it anchors a leverage ratio — the debt burden relative to earnings capacity. The denominator is the same word. The question it answers is entirely different.

The ratio also moves intuitively with credit quality: as EBITDA grows, leverage falls naturally even if the nominal debt balance is unchanged. As debt increases, leverage climbs. Lenders, sponsors, and analysts find it useful because it maps directly to the question every creditor is asking — how long does this borrower need to cover this debt, and is that period tolerable given the earnings risk in the business?

---

## The Debt-to-EBITDA Formula

**Debt-to-EBITDA = Total Debt ÷ EBITDA (TTM)**

The "TTM" designation means trailing twelve months — the sum of the four most recent reported quarters of EBITDA. Using TTM rather than a single fiscal year smooths seasonal distortion and produces a more current picture of earnings capacity. Rating agencies and credit analysts standardly use TTM EBITDA as the denominator.

### What Counts as Total Debt?

Total Debt is the numerator, and it is less consistent across platforms than it appears. The baseline definition is short-term debt (obligations due within twelve months, typically found under current liabilities on the balance sheet) plus long-term debt (obligations due beyond twelve months). Many companies report a combined "Long-Term Debt, Including Current Maturities" line item in their 10-K or 10-Q that makes the debt figure directly readable from the filing.

The complication arrived with ASC 842, the lease accounting standard effective since 2019, which moved operating lease obligations onto the balance sheet as formal liabilities. Companies now carry right-of-use (ROU) lease liabilities representing multi-year rental commitments for offices, stores, equipment, and distribution facilities. Some data platforms include these operating lease liabilities in their definition of total debt. Others do not. For a capital-intensive retailer or airline with **billions** in lease obligations on the balance sheet, the difference between conventions is not marginal — it can shift the numerator by enough to move the company from one leverage tier to another entirely.

GeminIQ uses the as-filed balance sheet values for debt. If a company reports a single "Total Debt" line in its filing, GeminIQ uses that figure directly. If not, GeminIQ sums short-term and long-term debt from the balance sheet — preserving the company's own classification rather than imposing a normalized definition from outside the filing.

### How Is EBITDA Calculated When It's Not Reported Directly?

EBITDA — earnings before interest, taxes, depreciation, and amortization — is not a required GAAP line item. Most companies do not report it as a standalone figure in their SEC filings, which means it must be derived. The standard approach is:

**EBITDA = EBIT + Depreciation & Amortization**

EBIT (earnings before interest and taxes) is available from the income statement or derived from net income. Depreciation and amortization are disclosed on the cash flow statement, typically as a non-cash add-back under operating activities. The four most recent quarters of this EBITDA figure are summed to produce the TTM denominator.

Where aggregators routinely diverge is in what they add back to EBITDA beyond D&A. Many platforms strip out stock-based compensation, restructuring charges, impairment losses, and litigation costs under the premise that these are "non-recurring" items. The resulting figure — typically labeled "Adjusted EBITDA" — is inflated relative to the as-filed number, producing a larger denominator and a leverage ratio that appears lower. A company reporting **$1.2 billion** in as-filed EBITDA but **$1.6 billion** in platform-adjusted EBITDA after add-backs will display a Debt-to-EBITDA ratio that is **25%** lower on a standard screen than what the raw filing actually supports. GeminIQ derives EBITDA from the as-reported EBIT plus as-reported D&A — no adjustments, no normalization.

---

## What Is a Good Debt-to-EBITDA Ratio?

There is no single threshold that defines "good" across all companies in all sectors, but credit markets have established widely used reference tiers that structure how analysts read the ratio.

A ratio **below 2.0x** is considered low leverage. Companies here generate substantially more EBITDA than their debt burden and carry significant capacity to take on additional obligations or withstand an earnings downturn. Capital-light businesses, consumer staples companies with dominant competitive positions, and technology firms with recurring revenue models frequently maintain leverage in this range.

A ratio between **2.0x and 4.0x** is moderate leverage — the most common range for investment-grade public companies in capital-intensive industries. Large industrials, healthcare companies, and consumer brands frequently sit in this band as a function of their ongoing financing needs.

Elevated leverage runs from **4.0x to 6.0x**. This is the zone where leveraged buyouts are typically structured at close — high enough to amplify equity returns but low enough to service debt without immediate distress. Companies in this range carry meaningful refinancing risk if EBITDA contracts.

Above **6.0x**, a company is carrying significant stress. Debt at this level substantially exceeds several years of EBITDA, leaving almost no operational margin before covenant breach. Rating agencies typically assign speculative-grade ratings to companies above this threshold unless unusually strong liquidity or asset coverage backstops the credit.

The practical ceiling for investment-grade ratings is roughly **3.5x** across most agency frameworks. That is the point where the investment-grade conversation ends and the downgrade watch begins.

---

## Why Private Equity Uses Debt-to-EBITDA First

Private equity funds an acquisition with a combination of PE equity and debt — typically senior secured loans, subordinated notes, or high-yield bonds. The amount of debt a lender will provide is underwritten as a multiple of EBITDA. "We'll lend up to **5.0x** EBITDA" means the lender's entire credit thesis is built on the company's ability to service that debt from operating earnings.

The post-close Debt-to-EBITDA determines the deal's leverage profile, sets the covenant framework, and defines the equity cushion beneath the debt. A deal structured at **6.0x** leverage carries almost no room for EBITDA compression before covenant pressure begins. If EBITDA declines by **15%** at that entry leverage, the effective ratio can breach **7.0x**, triggering maintenance covenant violations and potentially accelerating default provisions. This is why senior lenders typically price and structure credit on trough EBITDA assumptions — not trailing peak figures.

The PE return thesis relies in part on organic deleveraging: as the portfolio company grows its EBITDA over the holding period through operational improvement or add-on acquisitions, the leverage ratio declines even if the nominal debt balance stays flat. A company acquired at **5.5x** EBITDA that grows EBITDA by **50%** over four years is a **3.7x** company at exit — a materially different credit profile that supports better refinancing terms and commands a higher exit multiple.

EBITDA definition also becomes a negotiating point in leveraged loan documentation. Borrowers and sponsors negotiate the specific definition of EBITDA used to calculate compliance with financial maintenance covenants — often including add-backs for projected synergies, cost savings not yet realized, and restructuring charges. The as-filed EBITDA in XBRL-tagged SEC filings carries none of those adjustments. It is what the company actually earned and reported, nothing more.

---

## How Credit Rating Agencies Apply Debt-to-EBITDA

Moody's and S&P both use Debt-to-EBITDA as a primary quantitative input in their corporate credit ratings methodology. For most sectors, it functions as a leverage anchor — companies seeking to maintain investment-grade ratings face explicit pressure to manage the ratio below defined thresholds.

S&P's financial risk profile framework maps leverage tiers to rating-relevant categories. A "Minimal" financial risk profile is associated with Debt-to-EBITDA below **1.5x**. "Modest" runs from **1.5x to 2.0x**. "Intermediate" covers **2.0x to 3.0x**. "Significant" spans **3.0x to 4.0x**. "Aggressive" covers **4.0x to 5.0x**. "Highly Leveraged" is above **5.0x**. Each tier is one input among many — business risk, liquidity, cash flow adequacy, and management track record all factor in — but the leverage tier sets the floor for what rating is achievable.

Both agencies also apply their own proprietary adjustments to the as-filed figures before computing the ratio. Moody's has historically capitalized operating leases using a rental expense multiple, adding back a rent-adjusted EBITDA figure in the denominator. S&P incorporates pension underfunding as a debt-equivalent in the numerator. The resulting "agency-adjusted" ratio can differ meaningfully from what the company reported in its SEC filing — neither version is wrong, but they answer different questions, and investors need to know which one they are looking at.

The [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) is the natural companion metric in this framework. Where Debt-to-EBITDA measures leverage as a stock of debt relative to earnings, Interest Coverage — EBIT divided by interest expense — measures whether current earnings are sufficient to service the interest cost of that debt. A company at **4.0x** Debt-to-EBITDA with an Interest Coverage Ratio of **8.0x** is in a fundamentally different position than one at **4.0x** leverage and a **2.0x** coverage ratio. Both metrics appear on agency scorecards as independent inputs, and the combination is more informative than either ratio alone.

---

## Debt-to-EBITDA vs. Net Debt-to-EBITDA

### What Is the Difference Between Debt-to-EBITDA and Net Debt-to-EBITDA?

Gross Debt-to-EBITDA treats the debt as it is — the full nominal face value of the obligation, without any offset for liquidity. [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) subtracts cash and cash equivalents from total debt before dividing by EBITDA:

**Net Debt-to-EBITDA = (Total Debt − Cash & Cash Equivalents) ÷ EBITDA (TTM)**

For companies holding significant cash relative to their debt, the two ratios can diverge sharply. A company with **$10 billion** in gross debt and **$8 billion** in cash has a net debt position of only **$2 billion** — a fundamentally different effective leverage profile than the gross figure implies. Technology companies with strong free cash flow generation frequently reach net cash positions, at which point net debt-to-EBITDA turns negative. A negative ratio means the company holds more cash than it owes in debt — a sign of financial strength, though persistently large cash balances also raise questions about capital allocation discipline.

### When Should You Use Each?

Gross Debt-to-EBITDA is the standard for covenant calculations and credit agreement definitions. Lenders care about the total obligation because cash on the balance sheet may not be truly available for debt repayment — it may be held in foreign subsidiaries under repatriation constraints, restricted as collateral for other facilities, or designated for a pending acquisition. The covenant package uses total debt because it represents the maximum legal claim on the business.

Net Debt-to-EBITDA gives a better read on effective financial flexibility — the practical leverage burden a company is actually carrying day to day. For comparing capital allocation capacity across companies — identifying which businesses have true balance sheet optionality to fund growth, buy back shares, or pursue acquisitions — the net figure is the more honest starting point.

GeminIQ calculates both. The [Net Debt](/metrics/calculated-values/net-debt) metric pulls cash and total debt directly from the as-filed balance sheet, and [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) divides that net figure by trailing twelve-month EBITDA using the same unmodified data. Both are available on the [Calculated Metrics](/features#calculated-metrics) dashboard without adjustments.

---

## Debt-to-EBITDA Across Industries

Leverage tolerance varies significantly by sector, and a raw ratio number without industry context produces misleading conclusions. A **4.0x** Debt-to-EBITDA in cable and telecommunications — a sector with recurring subscription cash flows and high switching costs — implies something very different than **4.0x** in software, where customer churn risk and sales cycle variability introduce more earnings uncertainty.

Capital-intensive industries with stable, contractual cash flows can sustain higher leverage because lenders accept lower cushion when revenue is predictable. Regulated utilities operate with long-run revenue certainty under rate-of-return frameworks, making leverage above **4.0x** commercially normal and analytically appropriate. Infrastructure operators — pipelines, airports, cell towers, toll roads — often finance construction phases at leverage well above **5.0x** because contracted revenues service the debt regardless of broader macro conditions.

Consumer staples and healthcare cluster at moderate leverage, typically **2.0x to 3.5x**, because these sectors sustain earnings through downturns while lacking the regulatory revenue certainty of utilities. Technology and software businesses, particularly those with subscription or SaaS models, often operate below **2.0x** or in net cash positions entirely — the asset-light business model provides limited collateral for debt, and lenders price that risk accordingly.

Cyclical industries require the most careful treatment. An energy company at **3.0x** during a commodity price peak can find itself at **7.0x or above** after a commodity downturn if EBITDA contracts faster than debt is retired. For these businesses, analysts stress-test the ratio against trough EBITDA assumptions — not trailing figures at the cycle's peak — to understand leverage at the bottom rather than the top. A company that appears conservatively financed on a trailing basis can be deep in covenant breach by mid-cycle. The trailing twelve-month figure is a point-in-time snapshot; in cyclical sectors, it is often the least informative one.

---

## Why Your Platform's Number Might Be Wrong

The Debt-to-EBITDA ratio displayed on a standard financial data platform is frequently not the number that results from reading the SEC filing directly. Standard financial media doesn't read the footnotes. The divergence typically comes from three sources, and understanding them is the difference between a leverage view and a leverage guess.

First, EBITDA adjustments. Major data providers normalize EBITDA by adding back stock-based compensation, restructuring charges, impairment losses, and other items they classify as non-recurring. The premise — that these are genuinely one-time — is frequently false in practice. A company that records a restructuring charge in six of its last eight quarters is not experiencing a one-time event; it is running a persistent cost base. But the normalized EBITDA is inflated regardless, which means the denominator is larger than the as-filed figure supports and the leverage ratio prints lower as a result.

Second, the total debt definition. Whether operating lease liabilities under ASC 842 are included in the numerator depends entirely on the platform's convention. For a large retailer with thousands of store leases, or an airline with significant equipment leases, this is not a rounding difference — it can shift the numerator by **billions** and move the company from moderate leverage to high leverage in a single definitional choice.

Third, TTM construction timing. Platforms that cache financial data can lag in updating TTM calculations, or may be using fiscal-year snapshots rather than true trailing four-quarter sums. For a company that has recently experienced material EBITDA growth or contraction, the fiscal-year-anchored figure and the true TTM can diverge enough to change the leverage tier entirely.

GeminIQ's pre-calculated [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda) derives every input from XBRL-tagged SEC filings — debt from the as-filed balance sheet, EBITDA from as-reported EBIT plus depreciation and amortization, with no normalization adjustments applied. Understanding why aggregator processing changes these figures is covered in [the data normalization problem](/blog/financial-data-normalization-explained). For a coordinated credit and quality framework that pairs Debt-to-EBITDA with interest coverage, free cash flow, and [return on invested capital](/blog/roic-return-on-invested-capital-explained), [financial metrics for value investors](/blog/financial-metrics-value-investors) covers the full set. Investors who want to screen for low-leverage, high-return businesses directly can start with GeminIQ's [High ROIC Low Debt Screener](/screens/stock-screeners/high-roic-low-debt).

The number on a dashboard is only as reliable as the decisions made inside the EBITDA denominator. Knowing which decisions were made — and having access to the as-filed figure to check — is what separates a credit view from a credit assumption.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Deep Value vs. Quality Investing: Which Wins and When
source: https://www.geminiq.com/blog/deep-value-vs-quality-investing

### Deep Value vs. Quality Investing: Which Wins and When
Deep value investing (P/E ≤ 10, P/B ≤ 1.5) and quality investing (ROIC ≥ 20%) do not outperform simultaneously — they outperform in alternating market regimes. This post maps the four conditions that determine which approach wins and how to run both screens on as-filed SEC data.

The investment industry frames deep value and quality investing as competing philosophies — as if choosing one means rejecting the other permanently. The academic record does not support that framing. Both approaches have documented, positive excess returns over long periods. Both have also produced multi-year stretches of significant underperformance. What separates investors who use these strategies effectively from those who don't is not which camp they belong to — it is whether they understand what conditions activate each strategy's edge. Deep value outperforms when interest rates are high or rising, valuation spreads between cheap and expensive stocks are wide, and cyclical businesses trade at trough earnings multiples. Quality outperforms when rates are low or falling, economic growth is scarce, and investors pay a premium for earnings visibility and durable compounding. The investor who reads these conditions correctly and reaches for the right screen has a systematic edge over one who commits permanently to either side. GeminIQ's [Deep Value Screener](/screens/stock-screeners/deep-value) and [Quality Compounder Screener](/screens/stock-screeners/quality-compounder) surface fundamentally different universes of companies — and knowing when to use each one is the analytical question this post answers.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=deep-value-vs-quality-investing)**

---

## Table of Contents

- [The Logic Behind Deep Value Investing](#the-logic-behind-deep-value-investing)
- [The Logic Behind Quality Investing](#the-logic-behind-quality-investing)
- [The Four Market Regimes That Determine the Winner](#the-four-market-regimes-that-determine-the-winner)
- [What Aggregator Data Gets Wrong in Each Screen](#what-aggregator-data-gets-wrong-in-each-screen)
- [How to Run Both Screens in GeminIQ](#how-to-run-both-screens-in-geminiq)
- [Reading the Results: Beyond the Filter Numbers](#reading-the-results-beyond-the-filter-numbers)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## The Logic Behind Deep Value Investing

Deep value investing measures the gap between what the market is willing to pay for a business today and what that business actually earns or owns. Benjamin Graham's foundational proposition was that this gap is exploitable: when the market prices a security below its intrinsic value, a disciplined investor who buys at a sufficient discount — the margin of safety — earns above-average returns as price eventually converges toward value. The simplest implementation targets two metrics: [Price-to-Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) and [Price-to-Book Ratio](/metrics/valuation-metrics/price-to-book-ratio). GeminIQ's [Deep Value Screener](/screens/stock-screeners/deep-value) operationalizes this with four filters: P/E at or below **10**, P/B at or below **1.5**, [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) at or below **1.5**, and a P/E floor of **1** to exclude loss-making businesses that appear cheap only because their earnings are negative.

The academic evidence for deep value is substantial and long-running. Fama and French's 1992 and 1993 research documented what became the value factor — the systematic tendency of low P/B stocks to outperform high P/B stocks over long periods, observed across nearly a century of US data and replicated across international markets. The value premium has averaged roughly **4–5%** per year over the long term, though this figure conceals enormous variance across decades. The value factor was notably weak from approximately 2007 through 2021, underperforming growth strategies by wide margins for fourteen consecutive years — the longest such drought in the historical record.

The structural explanations for that underperformance are real: declining interest rates made terminal value more important in business valuation, rewarding growth over cheapness; the rise of platform-economy businesses with few tangible assets made price-to-book a less meaningful signal; and the intangibles-heavy composition of the modern economy eroded the relevance of asset-based valuation frameworks. None of these explanations mean deep value is permanently broken. They mean its edge concentrates in specific conditions — and those conditions do return.

Deep value candidates surface naturally in cyclical industries: energy, basic materials, traditional manufacturing, and regional banking, where earnings fluctuate dramatically with commodity prices and economic cycles. A company trading at **7× trailing earnings** may be there because its earnings are at a temporary cyclical trough that will reverse — or because its core business model is in structural decline. Distinguishing between these two cases is the core analytical task, and it requires the trend data that raw SEC filings make available. For a systematic overlay that adds nine fundamental quality tests to a basic value screen, the [Piotroski F-Score framework](/blog/piotroski-f-score-value-trap) is the most widely used tool for separating genuine deep value candidates from value traps.

<center><sup>GeminIQ Stock Screener with Deep Value filters active: P/E TTM ≤ 10, P/E TTM ≥ 1, Price-to-Book Ratio ≤ 1.5, and Debt-to-Equity Ratio ≤ 1.5. Results sorted by P/E TTM ascending — cheapest on earnings first. Multiples sourced from as-filed GAAP net income, not adjusted earnings.</sup></center>

---

## The Logic Behind Quality Investing

Quality investing targets a different dimension of return entirely. Rather than buying businesses at a discount to what they are worth today, it buys businesses that will be worth dramatically more in the future — because they earn high returns on the capital they deploy and can reinvest those earnings at similarly high rates for extended periods. GeminIQ's [Quality Compounder Screener](/screens/stock-screeners/quality-compounder) defines this category through five filters: [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) at or above **40%**, [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) at or above **20%**, [Revenue Growth](/metrics/growth-metrics/revenue-growth) (3-year) at or above **10%**, Debt-to-Equity at or below **0.5**, and [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) at or above **10%**.

The academic evidence for the quality factor is more recent than the value literature but equally robust. AQR's work on the Quality Minus Junk (QMJ) factor demonstrated that stocks with high profitability, stable growth, low financial risk, and high payout ratios systematically outperform low-quality stocks — a premium that held across 24 international markets through nearly three decades of data. The quality premium has averaged roughly **4–6%** per year, with notably lower volatility than the value premium, because quality businesses tend to have more defensible earnings through contractions.

The compounding math is what makes quality investing structurally different from simple growth investing. A business earning **20% ROIC** and reinvesting **80%** of its earnings at that same rate grows its earnings base at **16%** annually. Over fifteen years, that compounds the earnings capacity of the business by roughly **9×**. The variable that separates a genuine compounder from a temporarily exceptional business is not the current ROIC — it is how long the business can sustain that return as competition responds. A business maintaining **20% ROIC** for fifteen years creates far more value than one earning **35% ROIC** for three years before competitors erode the margin. For a deeper treatment of the compounding math and how ROIC stability distinguishes genuine compounders from mean-reverting businesses, see [Quality Compounder Investing: Philosophy, Criteria, and Screener](/blog/quality-compounder-investing-explained).

Quality compounders almost never appear in deep value screens. The market recognizes exceptional economics and prices them accordingly. A genuine quality compounder typically trades at P/E multiples of **20×**, **30×**, or higher — which means it fails every deep value filter by a wide margin. This is not a screening error; it is the market correctly pricing the expectation of long-duration compounding. The analytical challenge for quality investors is not finding businesses that are cheap on current metrics but distinguishing businesses where the premium is justified by durable competitive advantage from ones where the premium reflects an advantage that has already peaked.

<center><sup>GeminIQ Stock Screener with Quality Compounder filters active: Gross Profit Margin TTM ≥ 40%, Return on Invested Capital (ROIC) TTM ≥ 20%, Revenue Growth 3Y ≥ 10%, Debt-to-Equity Ratio ≤ 0.5, Net Profit Margin TTM ≥ 10%. Results sorted by ROIC TTM descending — highest capital efficiency first. All metrics sourced from as-filed SEC filings.</sup></center>

---

## The Four Market Regimes That Determine the Winner

The performance divergence between deep value and quality investing tracks identifiable macroeconomic conditions with enough regularity to be analytically useful. Four regimes account for most of the observed variation.

### Rising Rates and Inflation: When Deep Value Leads

Higher interest rates compress the present value of distant cash flows — and quality compounders' business cases are built almost entirely on cash flows far in the future. A business worth **30× earnings** when the risk-free rate is **1%** may justify only **15× earnings** when the risk-free rate is **5%**. The math is direct: higher discount rates shrink terminal value, and terminal value is where most of a quality compounder's investment case lives. Deep value candidates are far less sensitive to this compression because their investment case rests on near-term earnings power, not a projection fifteen years forward.

The 2022–2023 rate cycle produced the clearest recent demonstration. The Federal Reserve raised rates from near-zero to over **5%** in fourteen months. Technology-heavy quality businesses that had traded at extreme multiples compressed sharply as the discount rate repriced their terminal value. Energy, commodity, and industrial companies — the natural habitat of deep value screens — outperformed significantly as inflation lifted their near-term earnings.

### Falling Rates and Low Growth: When Quality Leads

The inverse holds. When rates fall, terminal value becomes more valuable in present-value terms, which benefits long-duration earnings streams directly. When economic growth is scarce, investors pay a premium for businesses that grow reliably regardless of the macro environment — and quality compounders with structural revenue growth and high margins are the most defensible source of that growth. The 2010–2021 period combined both tailwinds simultaneously: rates fell toward zero, broad economic growth was modest, and businesses with structural recurring revenue became worth more with every rate cut. The result was fourteen years of quality outperforming value — not because deep value was broken, but because the rate environment made the quality premium rational.

### Post-Recession Recovery: When Deep Value Catches Up

Early economic recoveries produce sharp mean-reversion in the most beaten-down cyclical stocks — the natural occupants of deep value screens. Energy producers, industrials, and regional financials that compressed to low multiples during a recession recover fastest in the early expansion phase, because their earnings rebound is most dramatic from trough levels. The 2009–2011 recovery and the 2020–2021 pandemic-exit recovery both produced outsized returns for deep value candidates in their first twelve months. Quality businesses compounded through both recoveries without interruption. They did not, however, produce the same magnitude of near-term price appreciation, because they hadn't suffered the same magnitude of prior compression.

### Late-Cycle and High Uncertainty: When Quality Holds

Late in an expansion, when recession risk rises and earnings visibility deteriorates, investors rotate toward defensibility. Quality compounders — high margins, recurring revenue, zero or minimal net debt, and demonstrated consistency across cycles — outperform because the earnings stream investors are paying for is less likely to disappoint. The late-cycle quality premium reflects a simple risk preference: investors will pay more for an earnings dollar they are confident they will actually receive. Deep value candidates face the opposite dynamic — their trough-earnings argument requires a recovery that a slowing economy is increasingly unlikely to deliver on schedule. Neither screen is superior in the abstract. Market regime determines which one is the right tool to hold.

---

## What Aggregator Data Gets Wrong in Each Screen

Both screens are acutely sensitive to how the underlying metrics are calculated — and this is where normalized, aggregator-adjusted data introduces systematic error in opposite directions.

For deep value screens, the critical distortion is earnings normalization. The [Price-to-Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) is only as useful as the earnings figure beneath it. Most financial data platforms substitute "adjusted" earnings for GAAP net income, stripping out restructuring charges, impairment charges, acquisition costs, and litigation settlements as "non-recurring." A company with a P/E of **8×** on as-filed GAAP net income might show **16×** on the adjusted figure once recurring "one-time" charges are removed. GeminIQ calculates P/E from the net income figure as-filed with the SEC — the legally reported number, and the basis on which the foundational academic value research was originally conducted. When the deep value screener surfaces a company at **7× earnings**, that multiple reflects what the company actually reported, not what management chose to emphasize in the earnings release.

For quality screens, the critical distortion is ROIC calculation methodology. Third-party platforms frequently compute [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) using a statutory **21%** tax rate rather than the company's actual effective tax rate, strip goodwill from [invested capital](/metrics/calculated-values/invested-capital) to inflate apparent returns, and exclude stock-based compensation from NOPAT to overstate after-tax operating profit. Each choice makes ROIC appear higher than it is. A quality compounder that screens at **25% ROIC** on GeminIQ earned that return on the actual invested capital base at the actual tax burden the company bore in the filing period. On an aggregator platform using normalized inputs, the same company might show **32% ROIC** — a figure with no basis in the document filed with the SEC.

The practical consequence runs in both directions. A deep value screen built on adjusted earnings surfaces companies that look cheaper than they are, inflating the apparent opportunity. A quality screen built on normalized ROIC surfaces companies that look better than they are, understating the durability risk. Both errors produce conclusions built on numbers the company never actually reported. GeminIQ uses as-filed figures because that is what the academic research was built on, and it is the only version of the data that is legally traceable to the source document.

---

## How to Run Both Screens in GeminIQ

GeminIQ's [Deep Value Screener](/screens/stock-screeners/deep-value) requires four filters applied through the [Stock Screeners](/features#screener) feature: [Price-to-Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) TTM ≤ **10**, Price-to-Earnings Ratio TTM ≥ **1** (the floor that removes companies with negative earnings from results), [Price-to-Book Ratio](/metrics/valuation-metrics/price-to-book-ratio) ≤ **1.5**, and [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) ≤ **1.5**. Set the sort to P/E ascending to surface the cheapest earnings multiples first. The resulting universe will concentrate in cyclical sectors — energy, materials, industrials, regional financials — and the sector composition matters as much as the individual results. A screen dominated by energy companies during a commodity price peak is a very different analytical situation than the same screen populated during a multi-year commodity trough.

GeminIQ's [Quality Compounder Screener](/screens/stock-screeners/quality-compounder) requires five filters: [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) TTM ≥ **40%**, [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) TTM ≥ **20%**, [Revenue Growth](/metrics/growth-metrics/revenue-growth) 3Y ≥ **10%**, [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) ≤ **0.5**, and [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) TTM ≥ **10%**. Set the sort to ROIC descending to surface the highest-return businesses first. The result set will be small — this screen is designed to return a handful of candidates, not a long list. For highest-conviction work, a Revenue Growth 5Y ≥ **8%** filter confirms that growth has been sustained over a longer horizon rather than driven by a recent three-year surge. The companies that clear every filter across both the 3-year and 5-year growth thresholds represent the narrowest, most defensible end of the quality universe.

---

## Reading the Results: Beyond the Filter Numbers

Running either screen is the beginning of the research process, not the end of it. The filter numbers identify candidates; the trend behind those numbers determines whether the candidate is genuine.

For deep value results, the critical question is whether the current low multiple reflects a cyclical trough already reversing or a secular earnings decline with no floor in sight. GeminIQ's [Visualizations](/features#visualizations) view lets you chart revenue and net income across twelve or more quarters for any result in the screen. A company showing **7× P/E** because earnings dropped sharply last year but had been stable or growing for the five years prior is a different research question than one where earnings have declined for three consecutive years and every quarterly filing shows a lower run rate. The trailing multiple cannot distinguish between those two companies. The trend can.

For quality results, the defining check is ROIC stability over time — not just the current level. GeminIQ's [Calculated Metrics](/features#calculated-metrics) trend view plots ROIC across quarters, which immediately reveals whether a **20% ROIC** business has been compounding at that level for years or declining toward it from a higher peak. A business that showed **40% ROIC** three years ago and now shows **20%** is not a compounder — it is a business under competitive pressure, and its current multiple likely still prices in economics it no longer has. The business that showed **18% ROIC** three years ago and now shows **22%** is building a moat, not losing one. Both pass the screen on the current number. Only the trend reveals which is which.

The second quality check is stock-based compensation as a fraction of revenue. High-ROIC businesses often distribute significant value through equity compensation, which is a non-cash expense but represents real economic dilution. A business with **25% ROIC** and stock compensation running at **15%** of revenue has a fundamentally different economic picture than one with **25% ROIC** and **2%** stock compensation — the first is paying its employees far more than the income statement suggests. The screen treats them identically. The filing does not.

---

## Frequently Asked Questions

### Which strategy is better for long-term investors?

Neither approach dominates over all time periods in isolation. The Fama-French value factor and AQR's quality factor both document roughly **4–6%** annual excess returns over long horizons — but they underperform in different conditions and for different durations. Long-term investors who are regime-aware and willing to operate both screens systematically have historically achieved better risk-adjusted outcomes than those who commit permanently to either approach alone.

### Can a stock appear in both screens simultaneously?

Rarely. Genuine quality compounders earning **20%+** ROIC with **40%+** gross margins almost never trade at P/E multiples below **10** or P/B ratios below **1.5** — the market prices exceptional economics into the stock. The intersection of genuine quality and genuine cheapness does exist but is small, and typically reflects a temporary dislocating event in an otherwise excellent business. The [GARP investing framework](/blog/garp-investing-peter-lynch-explained) attempts to capture this middle ground systematically, targeting quality characteristics at reasonable rather than premium multiples.

### What is a value trap and how do I avoid it?

A value trap is a company that appears cheap on P/E or P/B metrics but is priced low because the business economics are structurally deteriorating — not temporarily depressed. The most reliable diagnostic is the earnings trend over time: a business with P/E of **8×** whose earnings have declined for three consecutive years is categorically different from one where earnings are at a cyclical trough but stable over the longer term. GeminIQ's visualization tools let you chart revenue and net income across twelve or more quarters for any screener result. For a systematic overlay that adds nine fundamental quality tests to flag structural impairment before it shows up in the multiple, the [Piotroski F-Score framework](/blog/piotroski-f-score-value-trap) is the most widely applied tool for separating deep value candidates from traps.

### Does quality investing require paying a premium valuation?

Quality compounders almost always carry premium valuations — that is the market's rational response to exceptional and durable economics. The question is not whether quality is expensive but whether the premium is warranted by the longevity of the competitive advantage. A business at **30× earnings** with **25% ROIC** sustained over ten years and a large remaining reinvestment runway can be a more compelling long-term holding than one at **8× earnings** with declining returns on capital. For a structured framework evaluating whether the premium is justified by the underlying business quality, see [Buffett Stock Criteria: What Makes a Quality Business Worth Owning](/blog/buffett-stock-criteria-quality-business).

### What is the difference between deep value and net-net investing?

Deep value investing screens for companies trading at low multiples of earnings and book value while requiring profitability and manageable debt. Net-net investing — Benjamin Graham's most extreme application of the margin of safety concept — screens for companies trading below their net current asset value, meaning the stock can be purchased for less than the liquidation value of working capital alone, ignoring all fixed assets entirely. Net-nets operate at a deeper discount with more distress risk and typically surface only in severe market dislocations. For a full treatment of the net-net approach and how it differs from standard deep value screening, see [Net-Net Stocks: Benjamin Graham's Deep Value Strategy](/blog/net-net-stocks-graham-strategy).

---

## Related Reading

- [Quality Compounder Investing: Philosophy, Criteria, and Screener](/blog/quality-compounder-investing-explained)
- [Return on Invested Capital (ROIC) Explained](/blog/roic-return-on-invested-capital-explained)
- [Piotroski F-Score: Separating Value from Value Traps](/blog/piotroski-f-score-value-trap)
- [Net-Net Stocks: Benjamin Graham's Deep Value Strategy](/blog/net-net-stocks-graham-strategy)
- [GARP Investing: Peter Lynch's Growth at a Reasonable Price](/blog/garp-investing-peter-lynch-explained)
- [Buffett Stock Criteria: What Makes a Quality Business Worth Owning](/blog/buffett-stock-criteria-quality-business)
- [Gross Profit Margin: Business Model Analysis](/blog/gross-profit-margin-business-model-analysis)

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Deferred Revenue Growth Falling Behind Revenue
source: https://www.geminiq.com/blog/deferred-revenue-growth-falling-behind-revenue

### Deferred Revenue Growth Falling Behind Revenue
Deferred revenue growth falling behind revenue growth is a filing-level warning sign for subscription and prepaid-service businesses, and in GeminIQ's data, filings where that gap was widest were followed by a median 12-month return of -1.4%, against +8.6% for the broader filing universe.

**[ChargePoint Holdings](/stocks/CHPT)** grew revenue **94.2%** in the fiscal year ended January 2023, a headline figure that looked like accelerating demand. `Deferred Revenue` grew only **15.1%** over the same period — a leading indicator for future revenue lagging far behind the revenue already booked. The twelve months that followed produced a cumulative return of **-79.83%**. Deferred revenue represents cash customers have already paid for services not yet delivered; when it stops keeping pace with reported revenue, growth is running ahead of the pipeline that is supposed to sustain it.

This study reads GeminIQ's as-filed universe of quarterly and annual filings for companies carrying a deferred revenue balance, comparing GeminIQ's pre-calculated `Deferred Revenue Growth` to `Net Revenue TTM Growth 1Y` for each filing, joined to GeminIQ's post-filing market reaction data. **35,575** filing-periods across **1,697** companies have both growth figures computed with at least **$10 Million** in deferred revenue and **$50 Million** in trailing revenue; **25,021** of those filings also have post-filing return data available. The comparison window runs from each filing's own filed date out to twelve months, and every figure below is measured against the broader universe base rate, not against zero. This is a historical association measured over the sample window — not a forecast for any individual company.

## The Pattern

Deferred revenue is normally framed as a positive signal — a subscription or prepaid-service business collecting cash ahead of delivering the product, which is exactly why GeminIQ's own metric documentation calls Deferred Revenue Growth a leading indicator of future recognized revenue. This study tests the flip side of that framing directly: when deferred revenue growth falls behind revenue growth, the pipeline funding tomorrow's reported revenue is expanding more slowly than the revenue already being booked today. That is the kind of gap that shows up in the filing itself before it shows up in a guidance cut.

## The Data

Filings were sorted by the spread between deferred revenue growth and revenue growth over the same period. The bottom decile — filings where deferred revenue growth fell furthest behind revenue growth — is compared against the top decile and the rest of the universe at four post-filing checkpoints.

| Checkpoint | Bottom-Decile Gap Cohort (median) | Top-Decile Gap Cohort (median) | Rest of Universe (median) |
|---|---|---|---|
| 1 month | **0.16%** | 0.97% | 0.83% |
| 3 months | **0.76%** | 2.84% | 2.49% |
| 6 months | **-2.02%** | 2.66% | 3.49% |
| 12 months | **-1.41%** | 6.78% | 8.59% |

<center><sup>GeminIQ data study: median post-filing return for filings where deferred revenue growth fell furthest behind revenue growth (bottom decile), against filings where it ran furthest ahead (top decile) and the universe base rate. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 2,460 (1 month) to 274 (12 months) in the bottom-decile cohort.</sup></center>

<center><sup>GeminIQ data study: median post-filing return for the bottom decile, top decile and universe base rate of the deferred revenue growth versus revenue growth gap. Built from as-filed 10-K/10-Q data via GeminIQ.</sup></center>

The bottom-decile cohort trails the base rate at every checkpoint, and the gap widens sharply after the first quarter: from roughly **1.7 percentage points** behind the base rate at three months to **10 percentage points** behind at twelve months. The cohort's own median return turns negative at both the six- and twelve-month marks, while the broader universe stayed positive. The top-decile cohort — deferred revenue growth running well ahead of revenue growth — tells a more mixed story: it modestly outperforms the base rate at one and three months, consistent with the leading-indicator framing, but falls behind the base rate at six and twelve months. Deferred revenue growth outpacing revenue looks like a short-term positive signal in this data. Deferred revenue growth falling behind revenue looks like a more persistent negative one. The top-decile cohort is defined identically — the top ten percent of filings by the same spread — so it carries the same order of sample size as the bottom-decile cohort at every checkpoint, from roughly 2,460 filings at one month down to 274 at twelve months; the remaining rest-of-universe cohort spans the other 80% of filings and is several times larger again at each checkpoint. All three cohorts clear this study's roughly 200-filing floor at every checkpoint shown.

## The Extremes

**[ChargePoint](/stocks/CHPT)**, cited in the opening, sits in a well-documented stretch for electric-vehicle charging infrastructure companies working through a slower-than-expected commercial buildout. **[BILL Holdings](/stocks/BILL)** shows a sharper version of the same gap: in the fiscal year ended June 2023, revenue grew **64.9%** while `Deferred Revenue` actually declined **17.4%** — not merely decelerating, but shrinking outright against still-fast-growing reported revenue. The following twelve months produced a **-52.68%** return. Both companies were widely covered for slowing growth in the following year; the deferred-revenue gap was visible in the filing arithmetic before either became a headline.

<center><sup>GeminIQ Calculated Metrics showing ChargePoint's Deferred Revenue Growth falling from roughly 88% at January 2022 to roughly 15% at January 2023.</sup></center>

<center><sup>GeminIQ Calculated Metrics showing BILL Holdings' Deferred Revenue Growth turning negative at June 2023 (about -17%).</sup></center>

## The Method

`Deferred Revenue Growth` and `Net Revenue TTM Growth 1Y` are both GeminIQ pre-calculated metrics, built directly from as-filed balance sheet and income statement data. The universe is restricted to companies carrying a deferred revenue balance of at least $10 Million and trailing revenue of at least $50 Million, to exclude small or newly-disclosed positions that can produce misleadingly large percentage swings. The growth-rate spread is winsorized at the top and bottom 1% before bucketing. Post-filing returns are cumulative from each filing's own filed date and are never compounded or added across checkpoints. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any subscription or prepaid-service position's `Deferred Revenue` on GeminIQ's [Financial Statements](/features#financial-statements) view or its pre-calculated [Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth) figure in [Calculated Metrics](/features#calculated-metrics), and compare it directly to Net Revenue TTM Growth 1Y for the same period. A deferred-revenue growth rate that has fallen meaningfully behind revenue growth isn't a guaranteed warning on its own, but it's a two-line comparison worth running before trusting a headline revenue number at face value.

## Frequently Asked Questions

### What does it mean when deferred revenue growth falls behind revenue growth?

Deferred revenue represents cash already collected for products or services not yet delivered, and it is widely treated as a leading indicator of future recognized revenue for subscription and prepaid-service businesses. When its growth rate falls behind the growth rate of revenue already being recognized, the forward-looking pipeline is expanding more slowly than the revenue currently being booked — a gap that can show up in filings before it shows up in guidance.

### How many filings does this finding cover?

**35,575** filing-periods across 1,697 companies have both growth figures computed, restricted to companies with at least $10 Million in deferred revenue and $50 Million in trailing revenue. **25,021** of those filings also have post-filing return data, with the bottom-decile cohort ranging from 2,460 filings at the one-month checkpoint to 274 at twelve months.

### Is a high deferred-revenue-growth-to-revenue-growth ratio always a good sign?

Not consistently. Filings where deferred revenue growth ran furthest ahead of revenue growth modestly outperformed the base rate at one and three months, but fell behind it at six and twelve months in this data — a shorter-lived effect than the persistent, widening underperformance seen when deferred revenue growth falls behind revenue.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=deferred-revenue-growth-falling-behind-revenue)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 1,697 companies drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 35,575 filing-periods were screened for the spread between GeminIQ's pre-calculated Deferred Revenue Growth and Net Revenue TTM Growth 1Y, restricted to companies with at least $10 Million in deferred revenue and $50 Million in trailing revenue; 25,021 filings had matching post-filing return data, drawn from GeminIQ's partial price-history coverage. The growth-rate spread is winsorized at the top and bottom 1% before bucketing. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Delta (DAL) Q3 2026 Earnings: EPS Down 47%, Investments Swung $529M
source: https://www.geminiq.com/blog/delta-earnings-q3-2026

### Delta (DAL) Q3 2026 Earnings: EPS Down 47%, Investments Swung $529M
Delta's Q3 2026 10-Q shows revenue of $20.19 billion (+21.1%) and diluted EPS of $1.15 (-47.0%). A $529 million swing in investment gains and losses drove most of the pre-tax decline.

**[Delta](/stocks/DAL) (DAL) reported Q3 FY2026 revenue of $20.19 billion, up 21.1% year over year, and diluted EPS of $1.15, down 47.0%, for the quarter ended September 30, 2026. The October 9 earnings release led with record revenue and adjusted EPS of $1.72, but the 10-Q filed the same day shows a $529 million swing in investment gains and losses behind 75% of the $703 million fall in pre-tax income, and refinery resales behind nearly a third of the revenue growth. The GAAP decline overstates the damage to the airline, while the adjusted figure hides how far margins fell short of what Delta guided in July.**

| Field | Value |
|---|---|
| Company | Delta ($DAL) |
| Quarter | Q3 FY2026, period ended September 30, 2026 |
| Earnings release | October 9, 2026 (Form 8-K) |
| 10-Q filed | October 9, 2026 |
| Revenue | **$20.19 Billion** (+21.1% YoY) |
| Diluted EPS | **$1.15** (-47.0% YoY) |
| Operating margin | 7.2% (-2.9 pts YoY) |
| Operating cash flow (TTM) | $8.00 Billion |
| Investment gain/(loss), net | **-$218 million (vs +$311 million)** |

## Delta Q3 2026 Revenue, EPS and Margins

[Delta](/stocks/DAL)'s Q3 2026 diluted EPS was $1.15, down 47.0% from $2.17 a year earlier, on revenue that rose 21.1% to $20.19 billion. Revenue was the highest of the last 16 quarters and the second-highest of the 66 since 2010, and a quarter like that would be expected to lift earnings. Instead operating income fell 13.7%, and the 7.2% operating margin was the fifth-lowest of the last 16 quarters.

**The Data:** Operating income was **$1.45 billion**, against $1.68 billion a year earlier, and net income fell 46.6% to $756 million. Of the $3.5 billion revenue increase, $1.1 billion was third-party refinery sales, which carry a matching expense line; the refinery itself posted a $33 million operating loss.

**Why:** Pre-tax income fell $703 million. Operating income accounts for $230 million of that and non-operating items for $473 million, so two-thirds of the decline sits below the operating line. The 10-Q attributes the swing to mark-to-market losses on equity investments: a **$218 million loss** against a $311 million gain a year ago. Net income fell further than pre-tax income (47% against 40%) because tax took about 29.6% of pre-tax income against 20.3% (derived), well above the 23% to 25% annual rate the filing projects excluding those marks.

<center><sup>GeminIQ Financial Statements shows `Revenues`, `Operating Income Loss`, `Net Income Loss` and `Earnings Per Share Diluted` for the last five quarters. The highlight marks the September 2026 diluted EPS of $1.15, against $2.17 in the September 2025 quarter.</sup></center>

## What Delta's Q3 2026 10-Q Shows Beyond the Press Release

The release led with adjusted EPS of $1.72, up 1% from $1.70, and the 10-Q carries GAAP diluted EPS of $1.15, down 47%. [Delta](/stocks/DAL) says its adjusted figures exclude primarily refinery sales, investment gains and losses, and Monroe hedge results. 

**The Data:** GAAP pre-tax income was $1,074 million against $1,497 million adjusted, so this year's adjustments added $423 million. A year ago GAAP pre-tax income was $1,777 million against $1,477 million adjusted, so the adjustments took away $300 million. The 10-Q itemizes the pieces: $208 million of hedge mark-to-market in fuel expense and the $218 million investment loss.

**Why:** The exclusions cut both ways. Adjusted operating margin was **9.4%**, down from 11.1%, and adjusted operating income fell 2%; adjusted pre-tax income rose 1% only because net interest expense fell $25 million. [Delta](/stocks/DAL) also guided September-quarter adjusted EPS of $2.00 to $2.50 on an 11% to 13% operating margin in July. Management attributes the shortfall to fuel costs more than $500 million above that guidance and to non-fuel unit costs up 7.3%. The filing supports the cost half: salaries and related costs rose 9% on flat capacity after 4% base pay increases.

<center><sup>GeminIQ Visualizations plots `Operating Income Loss` and `Equity Securities Fv Ni Gain Loss` for the last 12 quarters. The highlight marks the September 2026 investment loss of $218 million, against $1.45 billion of operating income.</sup></center>

## Delta Q3 2026 Free Cash Flow, Debt and Dividends

[Delta](/stocks/DAL) reported free cash flow of $463 million for Q3 2026, down 44% from $833 million a year earlier on the company's own definition in the 8-K, while operating cash flow was $1.71 billion, down 7.3%. Cash held up far better than earnings: operating cash flow was 2.3 times net income, against 1.3 times a year ago (derived).

**The Data:** Operating cash flow of **$1.71 billion** exceeded net income by $957 million. The quarter's $673 million of depreciation and the $218 million non-cash investment loss cover about $891 million of that gap. Capital expenditure was $1.41 billion. Total debt was $12.1 billion against $13.3 billion at year-end, while current maturities rose to $2.98 billion from $1.37 billion.

**Why:** Mark-to-market losses cut net income without touching cash, which is how operating cash flow fell 7.3% while EPS fell 47%. Dividends of $141 million, up 15.6%, took about 30% of the quarter's free cash flow (derived), and no shares have been repurchased under the $1.0 billion program.

<center><sup>GeminIQ Financial Statements shows `Net Cash Provided By Used In Operating Activities` and `Payments Of Dividends` for the last five quarters. The highlight marks September 2026 operating cash flow of $1.71 billion, set against net income of $756 million.</sup></center>

## Delta's 2026 Guidance After Q3

In its October 9 8-K, Delta guided December-quarter EPS of $1.15 to $1.65 and full-year EPS of $5.10 to $5.60, after adjusted September-quarter EPS of $1.72 came in below the July range of $2.00 to $2.50. Adjusted operating margin of 9.4% likewise landed under the 11% to 13% the prior release set.

**The Data:** The company guided December-quarter revenue growth of about 20%, up from 16% adjusted in September, on an operating margin of 7% to 9%, whose top end sits below September's 9.4%. The guide assumes fuel near $4.25 per gallon including a $0.40 refinery benefit, against $3.61 adjusted in September. Full-year free cash flow of about **$2.5 billion** against $1.9 billion year to date implies roughly $0.6 billion in the fourth quarter (derived).

**Why:** Revenue growth speeds up while the margin range falls because fuel absorbs the increment: the CEO says Delta expects to absorb a $6 billion fuel cost increase this year and still earn roughly $4.5 billion pre-tax.

## How DAL Stock Has Moved After Past Earnings Reports

Delta's stock has historically slipped in the first month after most of its 10-Q filings and recovered by month three.

**The Data:** Across its last 12 filings (October 2023 to July 2026), DAL's median one-month return was -1.8%, positive after 5 of 12, while the median three-month return was **+13.4%**, positive after 9 of 12. Past Q3 filings were followed by one-month returns of -5.1%, +16.1% and -3.4%.

**Why:** The recovery arrives in months two and three, which is how a -1.8% median becomes +13.4%. These figures describe how [Delta](/stocks/DAL)'s stock moved after its past filings; they are a historical association, not a forecast. The GeminIQ [Earnings Reaction Heat Map](/features#price-variance) shows the full grid, and this filing's window has not yet elapsed.

<center><sup>GeminIQ Earnings Reaction Heat Map shows DAL's cumulative return 1-3 months after each 10-Q filing. Cells for the September 2026 quarter show "-" because its window has not elapsed.</sup></center>

Institutions held 87.01% of Delta at the June 30, 2026 SEC Form 13F quarter end, up from 78.73% a year earlier and the highest of the last 16 quarters. In SEC Form 4 filings from May 2025 to May 2026, insiders made 32 sales totaling $98.8 million and no purchases, against $30.3 million of sales the year before; Glen Hauenstein accounted for $34.4 million. The insider data ends at filings through May 27, 2026, so it does not cover trades after the quarter's print.

<center><sup>GeminIQ Institutional Ownership charts the share of Delta held by institutions from SEC Form 13F filings. The highlight marks the June 30, 2026 quarter end at 87.01%, the latest available.</sup></center>

A company whose adjusted and GAAP earnings split by the sign of one non-operating line is best read from the cash flow statement outward, because that line is the one that never reaches it.

## Frequently Asked Questions

### When does Delta report earnings?

Delta reported its Q3 FY2026 results on October 9, 2026 and filed the 10-Q the same day. Last year it filed its Q3 10-Q on October 9, 2025 and its fourth-quarter results on February 11, 2026. That is a pattern from the filing record, not a forecast of the next date.

### Is Delta doing well financially?

Delta's trailing operating cash flow was $8.00 billion, in line with $7.98 billion a year earlier, and its Net Debt to EBITDA was 1.14x. Profitability weakened: GeminIQ's pre-calculated [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) was 4.58% on a trailing basis, down from 7.36%, and Return on Invested Capital was 12.41%, down from 16.16%.

### Does Delta pay a dividend?

Yes. Delta paid $141 million, or $0.2150 per share, on July 30, 2026, and $393 million over the first nine months. On September 24, 2026 the board approved another $0.2150 per share, payable November 5 to holders of record on October 15. Trailing dividends paid were $515 million, up 24.4%.

### Where can I verify Delta's Q3 2026 figures?

The figures come from Delta's [Q3 2026 Form 10-Q](https://www.sec.gov/ix?doc=/Archives/edgar/data/27904/000002790426000038/dal-20260930.htm) and its [October 9, 2026 earnings release](https://www.sec.gov/Archives/edgar/data/27904/000002790426000035/deltaairlinesannouncessept.htm) on SEC EDGAR. Adjusted and guidance figures appear only in the release.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=delta-earnings-q3-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference DELTA AIR LINES, INC.'s
Q3 2026 10-Q (filed October 9, 2026, period ending September 30, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed October 9, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/27904/000002790426000038/dal-20260930.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/27904/000002790426000035/deltaairlinesannouncessept.htm).</sup>

---

## Blog: Dividend Cuts: Payout Ratios Topped 66% First
source: https://www.geminiq.com/blog/dividend-cuts-what-filings-showed-first

### Dividend Cuts: Payout Ratios Topped 66% First
Dividend cuts rarely arrive without warning in the filings themselves, and in GeminIQ's data, companies that cut their trailing-twelve-month dividend by 20% or more had a median payout ratio of 66.3% a year earlier, against 38.2% for companies that kept paying.

**[Wells Fargo](/stocks/WFC)** was paying out **243.6%** of trailing net income in dividends a year before its trailing-twelve-month dividend payments fell **69.4%**. A payout ratio above 100% means a company is distributing more cash than it earned over the same period — a fact filed openly, quarter after quarter, well before any dividend-cut announcement makes headlines. Across GeminIQ's full filing universe, that pattern isn't limited to one bank in one stressed year.

This study reads GeminIQ's as-filed universe of quarterly and annual filings, identifying a dividend cut as a trailing-twelve-month `Dividends Paid` figure falling **20% or more** year over year at a company that paid at least **$5 Million** in dividends the year before. **87,218** filing-periods meet the base criteria for comparison, of which **12,858** are flagged as dividend cuts. For each, this study looks at the payout ratio, dividend coverage, and leverage as they stood one year before the cut, compared to companies that kept paying — a historical association measured over the sample window, not a forecast for any individual company.

## The Pattern

A dividend cut is rarely a surprise in the arithmetic, even when it's a surprise in the headline. The dividend itself is a cash outflow a board can choose to reduce at any point. The pressure that leads to that choice — earnings no longer comfortably covering the payment, cash flow tightening, or both — tends to show up in the filings well before the board acts on it. Whether that pressure is actually visible ahead of time, across thousands of cuts rather than one company's story, is what this comparison tests directly.

## The Data

| Metric (measured one year before) | Dividend-Cut Cohort (median) | No-Cut Cohort (median) |
|---|---|---|
| Payout Ratio | **66.3%** | 38.2% |
| Dividends Paid / Free Cash Flow | **33.2%** | 27.8% |
| Net Debt / EBITDA | **0.70x** | 0.96x |

<center><sup>GeminIQ data study: median payout ratio, dividend-to-free-cash-flow coverage, and leverage one year before a trailing-twelve-month dividend cut of 20% or more, against companies that maintained or grew their dividend. Built from as-filed 10-K/10-Q data via GeminIQ. n = 8,301-12,858 in the dividend-cut cohort per metric, 66,007-72,602 in the no-cut cohort.</sup></center>

Payout ratio carries the clearest signal: a year before a cut, the median company in the cut cohort was already paying out **66.3%** of net income in dividends, against **38.2%** for companies that kept paying — a gap of nearly **28 percentage points**, visible in the filings a full year ahead of the cut itself. The dividend-to-free-cash-flow coverage ratio shows a smaller gap in the same direction. Leverage runs the other way: companies that went on to cut actually carried lower [net debt to EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) a year earlier than companies that didn't. That argues against leverage itself being the leading indicator here — the pressure shows up first in earnings coverage of the dividend, not in the balance sheet's debt load.

## The Extremes

**[Wells Fargo](/stocks/WFC)**, cited in the opening, cut its dividend during a widely covered period of bank-sector stress, with the elevated payout ratio visible in its own filings well before the cut was announced.

<center><sup>GeminIQ Calculated Metrics showing Wells Fargo's trailing payout ratio spiking above 200% in 2020, ahead of the year-over-year decline in trailing dividends paid that followed.</sup></center>

**[Estée Lauder](/stocks/EL)** shows the same shape outside banking: a payout ratio of **231.5%** in the period a year before its trailing dividend fell **34.7%**, against a backdrop of a prolonged, publicly reported slowdown in its China and global travel-retail business. Both companies were already paying out more than their full net income in dividends before either cut became a headline.

<center><sup>GeminIQ Calculated Metrics showing Estée Lauder's trailing payout ratio climbing well above 100% through 2023 and 2024, ahead of the year-over-year decline in trailing dividends paid that followed.</sup></center>

## The Method

`Dividends Paid`, [Payout Ratio](https://www.geminiq.com/metrics/returns-and-profitability/payout-ratio), [Free Cash Flow](https://www.geminiq.com/metrics/calculated-values/free-cash-flow), and [Net Debt to EBITDA](https://www.geminiq.com/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) are all GeminIQ calculated figures, built directly from as-filed cash flow statement and income statement data. A dividend cut is flagged when trailing-twelve-month `Dividends Paid` falls 20% or more year over year at a company that paid at least $5 Million in dividends the year before. Each cut is matched to the same company's own filing from approximately one year earlier. Every ratio is winsorized at the top and bottom 1% before comparison to exclude divide-by-near-zero and single-quarter earnings-swing artifacts. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology); GeminIQ's [Dividend Growth Screener](/screens/stock-screeners/dividend-growth) covers the same payout-ratio and coverage principles from the opposite direction, screening for dividends more likely to keep growing.

## Check Your Holdings

Pull up any dividend-paying position's `Payout Ratio` and `Free Cash Flow` on GeminIQ's [Calculated Metrics](/features#calculated-metrics) view and check whether the payout ratio sits meaningfully above the roughly 40% median this study found for companies that kept paying. A payout ratio climbing toward or past 100% is a filing-level fact anyone can check directly, well before a dividend cut becomes a headline. It's a method for spotting the pressure, not a guarantee of what a board will decide to do about it.

## Frequently Asked Questions

### What payout ratio typically precedes a dividend cut?

In GeminIQ's data, companies that went on to cut their trailing-twelve-month dividend by 20% or more had a median payout ratio of 66.3% one year earlier, against 38.2% for companies that maintained or grew their dividend — a gap present a full year before the cut.

### How many dividend cuts does this study cover?

**12,858** filing-periods are flagged as a dividend cut — a 20%-or-greater year-over-year decline in trailing-twelve-month Dividends Paid at a company that paid at least $5 Million the year before — against a comparison base of **87,218** filing-periods total.

### Is high leverage a better warning sign than payout ratio?

No, not in this data. Companies that went on to cut their dividend actually carried lower net debt to EBITDA a year earlier (a median of 0.70x) than companies that kept paying (0.96x). The clearer warning sign in this study is an elevated payout ratio, not balance-sheet leverage.

### Is a payout ratio above 100% always followed by a dividend cut?

No. This study measures what payout ratios looked like before cuts that did happen, not the reverse — not every company with an elevated payout ratio goes on to cut its dividend, and some sustain a high payout ratio for extended periods without one.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=dividend-cuts-what-filings-showed-first)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 87,218 filing-periods with a prior-year dividend payment of at least $5 Million were screened for a 20%-or-greater year-over-year decline in trailing-twelve-month Dividends Paid; 12,858 met that threshold. Payout Ratio, Dividends Paid, Free Cash Flow, and Net Debt to EBITDA are all GeminIQ calculated metrics, winsorized at the top and bottom 1% before comparison. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Do Stock Buybacks Reduce Share Count? The Announcement vs. Reality
source: https://www.geminiq.com/blog/do-buybacks-reduce-share-count

### Do Stock Buybacks Reduce Share Count? The Announcement vs. Reality
Whether buybacks reduce share count depends on execution, not the announcement. GeminIQ traces four companies' board-authorized repurchase programs against what their 10-Ks and 10-Qs actually show was spent, and what happened to the share count as a result.

**A stock buyback, or share repurchase, is when a company uses its cash to buy its own shares, reducing the number of shares held by the public so each remaining share owns a larger slice of earnings.** Announcing a buyback is not the same as doing one, though: boards authorize programs far larger than they ever spend, and the share count only falls when the purchases outpace new stock issued to employees.

**Intel's board has authorized $110.0 Billion in cumulative stock buybacks since the company's repurchase program began in 1990. As of the most recent 10-Q, $7.24 Billion of that capacity sits completely unused — a sum the board has already given itself permission to spend, sitting idle through a stretch in which [Intel](/stocks/INTC) posted a trailing-twelve-month operating loss. A board authorization is a press release. Whether it turns into cash actually leaving the company, and whether the diluted share count actually falls as a result, is a separate question that only shows up months or years later in the 10-K and 10-Q — and GeminIQ's as-filed data shows those two questions get very different answers depending on which company is asked.**

## Do Buybacks Reduce Share Count? The Short Answer

Not always. A buyback reduces the diluted share count only if the company actually spends the money and doesn't reissue shares through equity compensation or a stock offering. A board authorization is a ceiling, not a commitment — Intel has **$7.24 Billion** approved and unspent, and Boeing's diluted share count is now higher than before its buyback era began.

## How This Study Was Built

This study traces four companies — [Apple](/stocks/AAPL), [Boeing](/stocks/BA), [General Electric](/stocks/GE), and Intel — across their full GeminIQ filing histories, fiscal years 2009 through each company's most recently filed 10-K or 10-Q, filed through 2026. Board-authorized repurchase ceilings, program pause and cancellation dates, and material capital-raising events referenced below are sourced externally from each company's own SEC 8-K filings and investor disclosures, since an authorization limit or a stock offering is a footnote and press-release fact rather than a discrete XBRL tag; every dollar actually spent and every share count figure below is read directly from GeminIQ's as-filed 10-K and 10-Q extraction. No forward-return data is used in this study — the question here is spend versus authorization, not price reaction.

## What Full Execution Looks Like: A $90 Billion Program Spent Down in About a Year

Every comparison needs a baseline for what full execution looks like. [Apple](/stocks/AAPL) is the illustration here, not the subject — the subject is execution.

**The Filing Data:** Apple's board approved a **$90 Billion** program in May 2023; by the following June, only **$4.1 Billion** remained unused, and the board authorized a fresh **$110 Billion** program in May 2024 while the prior one still had capacity left. The cash flow statement matches the authorizations: `Payments For Repurchase Of Common Stock` runs **$94.949 Billion** in FY2024 and **$90.711 Billion** in FY2025. Diluted shares fall in lockstep — **26.087 Billion** at the close of FY2013 to **15.005 Billion** at the close of FY2025, a decline of **42.5%** with no single year of reversal.

**The Signal:** An authorization spent down to **$4.1 Billion** inside about a year, replaced before it ran dry, is what zero gap between announcement and reality looks like. It is the standard the other three companies below get measured against — and none of them meet it.

<center><sup>GeminIQ Financial Statements, Apple's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` at **$94.949 Billion** in FY2024 and **$90.711 Billion** in FY2025, against a diluted share count that fell to **15.005 Billion** by FY2025 — down **42.5%** since FY2013.</sup></center>

## Boeing: $20 Billion Authorized in 2018, Terminated Outright in 2020

[Boeing](/stocks/BA) ran one of the most aggressive buyback programs of the last decade — then walked away from it so completely that the board didn't just pause the authorization, it terminated it.

**The Filing Data:** Boeing's 10-K reports `Payments For Repurchase Of Common Stock` climbing from **$2.801 Billion** in FY2013 to **$9.236 Billion** in FY2017 and **$9.0 Billion** in FY2018 — a cumulative **$43.441 Billion** spent from FY2013 through FY2019. In December 2018, the board approved a fresh **$20 Billion** repurchase authorization, replacing the prior one. Four months later, in April 2019, the company paused the program entirely following the 737 MAX groundings. FY2019's filed spend came in at just **$2.651 Billion** — a fraction of the prior year's pace, cut short mid-year. On March 21, 2020, Boeing's board didn't just extend the pause: it formally terminated the authorization outright, per the company's own 8-K. `Payments For Repurchase Of Common Stock` is absent from Boeing's 10-K in every fiscal year from FY2020 through FY2025 — six consecutive years of zero.

**The Signal:** Diluted shares bottomed at **565.4 Million** in FY2019, down **20.7%** from **713.4 Million** at the start of the buyback era in FY2009. The count crept up only modestly through FY2023, reaching **605.8 Million** — mostly the ordinary drift of equity compensation with the buyback line at zero. Then, in October 2024, Boeing priced a public offering of **112.5 Million** common shares to raise **$21.1 Billion**, shoring up its balance sheet amid a seven-week labor strike and a threatened credit downgrade — a fresh crisis, unconnected to the 737 MAX grounding that killed the buyback five years earlier. Diluted shares jumped to **762.3 Million** by FY2025, **6.9%** above where the count stood before the entire FY2013–FY2019 buyback era began. The **$20 Billion** authorization never ran dry. It was cancelled with room still on it, and the shares it retired came back through a doorway the original announcement never mentioned.

<center><sup>GeminIQ Financial Statements, Boeing's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` at **$2.651 Billion** in FY2019 — the final year with a filed repurchase figure before six consecutive years of $0.</sup></center>

## General Electric: $50 Billion Authorized, $20.9 Billion Never Spent

[General Electric](/stocks/GE) announced one of the largest buyback commitments of the decade in 2015. Three years later, its own CEO admitted most of it wouldn't be used.

**The Filing Data:** GE's 10-K reports **$21.429 Billion** under `Proceeds From Repurchase Of Equity` in FY2016 alone. That spending followed an October 2015 board authorization of **$50 Billion** in buybacks, part of a **$90 Billion** total shareholder-return commitment tied to the sale of GE Capital's financing businesses. By 2018, roughly **$20.9 Billion** of that **$50 Billion** authorization remained unused, and CEO John Flannery told investors the company was "not anticipating much" further buyback activity. GeminIQ's filed data confirms the retreat: `Treasury Stock Value Acquired Cost Method` shows just **$268 Million** in FY2018, **$57 Million** in FY2019, **$28 Million** in FY2020, and **$107 Million** in FY2021 — four straight years where the authorized capacity barely moved. `Payments For Repurchase Of Common Stock` doesn't reappear as a meaningful figure until FY2024's **$5.827 Billion** and FY2025's **$7.551 Billion**, following the split of GE into GE Aerospace, GE Vernova, and GE HealthCare.

**The Signal:** Diluted shares fell from **1.3205 Billion** in FY2012 to **1.086 Billion** in FY2017 — a real **17.8%** reduction during the years the **$50 Billion** program was actually being spent. Then the share count went essentially flat for six years, closing FY2023 at **1.099 Billion**, marginally higher than FY2017 despite a still-open authorization with billions of dollars of room left. The number the board announced in 2015 wasn't fake. It just stopped being acted on the moment the company's larger business hit real trouble, and the filings — not the original press release — are the only place that shows up.

<center><sup>GeminIQ Financial Statements, GE's Cash Flow Statement, showing `Treasury Stock Value Acquired Cost Method` collapsing to **$28 Million** in FY2020 against the **$50 Billion** authorization announced in 2015, before repurchases resume at **$7.551 Billion** in FY2025.</sup></center>

## Intel: $7.24 Billion of Authorized Buybacks Still Unspent

[Intel](/stocks/INTC)'s case is the one still unfolding in real time. The gap between what's authorized and what's spent isn't a historical footnote — it's on the books right now.

**The Filing Data:** Intel's 10-K reports `Payments For Repurchase Of Common Stock` at **$13.576 Billion** in FY2019 and **$14.229 Billion** in FY2020 — a five-year stretch, FY2019 through FY2023, totaling **$30.220 Billion** in filed repurchase spend. Then the figure collapses: **$2.415 Billion** in FY2021, an explicit **$0** in both FY2022 and FY2023, and the line item absent entirely from the FY2024 and FY2025 10-Ks. Intel's own disclosures show the company is authorized to repurchase up to **$110.0 Billion** cumulatively since the program's 1990 start. Of that, **$7.24 Billion** remained available as of the most recent 10-Q — capacity the board has approved and the company simply isn't using, in the same stretch this GeminIQ series has already shown produced a negative trailing-twelve-month [Free Cash Flow](/metrics/calculated-values/free-cash-flow) figure.

**The Signal:** Diluted shares fell from **5.645 Billion** in FY2009 to **4.090 Billion** in FY2021 — a **27.6%** reduction across the aggressive-spending years. From that FY2021 trough, the count has since climbed back to **4.530 Billion** by FY2025, a **10.8%** increase with the buyback line at zero and equity compensation still issuing new shares underneath it. The turnaround narrative and the AI-era struggles both got covered separately by the standard financial press — but the footnote showing **$7.24 Billion** in board-approved buyback capacity sitting untouched, while the share count quietly climbs back toward where it started, didn't make either story.

<center><sup>GeminIQ Financial Statements, Intel's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` at an explicit **$0** in both FY2022 and FY2023, against a cumulative **$110.0 Billion** authorization of which **$7.24 Billion** remains unused.</sup></center>

## Authorization vs. Execution: All Four Companies Compared

| Company | Ticker | Authorization | Filed Spend | Unspent / Status | Diluted Shares | Net Change |
|---|---|---|---|---|---|---|
| Apple | [AAPL](/stocks/AAPL) | $90 Billion (May 2023), replaced by $110 Billion (May 2024) | $94.949 Billion (FY2024); $90.711 Billion (FY2025) | $4.1 Billion left when the board replaced it | 26.087 Billion (FY2013) → 15.005 Billion (FY2025) | **-42.5%** |
| Boeing | [BA](/stocks/BA) | $20 Billion (December 2018) | $2.651 Billion (FY2019); $0 in FY2020–FY2025 | Terminated outright March 21, 2020 with room still on it | 713.4 Million (FY2009) → 762.3 Million (FY2025) | **+6.9%** |
| General Electric | [GE](/stocks/GE) | $50 Billion (October 2015) | $21.429 Billion (FY2016); $28 Million (FY2020) | ~$20.9 Billion still unused as of 2018 | 1.3205 Billion (FY2012) → 1.086 Billion (FY2017) → 1.099 Billion (FY2023) | **-17.8%** to FY2017, then flat |
| Intel | [INTC](/stocks/INTC) | $110.0 Billion cumulative since 1990 | $30.220 Billion (FY2019–FY2023); $0 in FY2022 and FY2023 | **$7.24 Billion unspent** as of the most recent 10-Q | 5.645 Billion (FY2009) → 4.090 Billion (FY2021) → 4.530 Billion (FY2025) | **-27.6%** to FY2021, then **+10.8%** |

Line all four up and the pattern isn't that buybacks are fake. Apple proves they aren't — a board can authorize a number and burn through nearly all of it within about a year, then do it again. The pattern is that an authorization is a ceiling, not a commitment, and the distance between the two only shows up in a filing that arrives long after the press release stopped generating headlines.

Boeing's **$20 Billion** authorization died with room still on it the moment a crisis hit. GE's **$50 Billion** promise went mostly quiet for four years the moment the broader business did. Intel's **$7.24 Billion** is sitting unused right now, in filings anyone can read this quarter. In every one of these three cases, the diluted share count eventually moved in the opposite direction from what the original announcement implied — not because the buyback was a lie when it was announced, but because nobody was still checking the follow-through once the headline faded.

<center><sup>GeminIQ data study: annual buyback spend against year-end diluted share count for Apple, Boeing, GE, and Intel, FY2009–FY2025. Built from as-filed 10-K `Payments For Repurchase Of Common Stock` and related repurchase-tag data via GeminIQ.</sup></center>

## Check Your Holdings

This is a check you can run on anything you own in a few minutes, and it doesn't require trusting the last buyback press release you read. Pull up the company's most recent 10-K or 10-Q and find the stock repurchase footnote — it discloses the total authorized amount and how much remains available, by regulation. Then open the Cash Flow Statement and find `Payments For Repurchase Of Common Stock` (or the equivalent repurchase-related tag the filer actually uses) for the last several fiscal years. If the remaining authorization is large and growing while the cash flow statement shows little or nothing being spent against it, that's not a violation of anything — but it does mean the buyback story investors may still be pricing in isn't the one currently showing up in the filings. Compare that trend against the diluted share count on the Balance Sheet or Income Statement footnotes across the same years: a rising share count next to an unused authorization is the clearest sign the announcement and the reality have quietly parted ways. The authorization footnote lives in the filing itself rather than in a normalized data field, which is one of the differences covered in our comparison with [BamSEC](/competitor-comparison/bamsec).

## Frequently Asked Questions

### Does a buyback always reduce shares outstanding?

No. A repurchase only reduces the diluted share count if the cash is actually spent and nothing reissues the shares afterward. Boeing spent **$43.441 Billion** from FY2013 through FY2019 and still ended FY2025 with **762.3 Million** diluted shares — **6.9%** more than it had in FY2009 — because the program was terminated and the company later sold **112.5 Million** new shares.

### How much of a buyback authorization actually gets spent?

It varies from nearly all of it to almost none. Apple ran a **$90 Billion** authorization down to **$4.1 Billion** in about a year. GE still had roughly **$20.9 Billion** of a **$50 Billion** authorization unused three years after announcing it, and Intel has **$7.24 Billion** available today with **$0** of filed repurchase spend in FY2022 and FY2023. The authorized figure is a ceiling, not a forecast.

### Can a company cancel a buyback program after announcing it?

Yes, and it doesn't require shareholder approval. Boeing's board paused its **$20 Billion** authorization in April 2019 after the 737 MAX groundings and formally terminated it on March 21, 2020, per the company's own 8-K. The cancellation shows up in a filing; the original authorization showed up in a press release.

### Why did my share count go up despite a buyback?

Because repurchases are only one side of the ledger. Equity compensation issues new shares continuously, and a capital raise can issue them in a single event — Intel's count climbed **10.8%** off its FY2021 trough with the buyback line at zero and comp still running underneath it. When issuance is the dominant force rather than the exception, that is the pattern we ranked in [companies that dilute shareholders](/blog/companies-that-dilute-shareholders).

### Which companies actually reduced their share count the most?

Not the ones with the biggest announcements. We ranked the decade's genuine share-count reducers from as-filed 10-K data in [companies reducing share count](/blog/companies-reducing-share-count) — the leaderboard is dominated by runoff insurers and capital-return specialists rather than the megacaps that dominate buyback headlines.

### How does a stock buyback work?

The board authorizes a maximum dollar amount, and the company then buys its own shares over time, usually on the open market, sometimes through a tender offer or an accelerated repurchase agreement with a bank. Repurchased shares are either retired or held as treasury stock, and either way they no longer count as outstanding.

### Do I lose my shares in a buyback?

No. An open-market buyback only buys shares from investors who choose to sell. If you keep your shares, you own a slightly larger percentage of the company afterward. Only in a tender offer are shareholders asked directly, and even then participation is voluntary.

### Is a stock buyback a good thing?

It depends on the price and the funding. A buyback adds value when the stock is bought below its intrinsic value with cash the business does not need. It destroys value when the company overpays, borrows to fund it, or simply offsets shares issued as stock-based compensation, which leaves the share count flat.

### Is there a tax on stock buybacks?

Yes. Since 2023, US public companies pay a 1% excise tax on the net value of shares they repurchase in a year, reduced by the value of new shares they issue. The tax is paid by the company, not by shareholders who sell.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=do-buybacks-reduce-share-count)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Filed buyback spend and diluted share count figures for Apple, Boeing, General Electric, and Intel are drawn from each company's as-filed 10-K and 10-Q filings, fiscal years 2009 through the most recent filing period, publicly available on [SEC EDGAR](https://www.sec.gov/). Board-authorized repurchase amounts, program pause/cancellation dates, and Boeing's October 2024 common stock offering are sourced from each company's SEC 8-K filings and investor disclosures rather than GeminIQ's own extracted dataset, since these are not filed as discrete XBRL facts. Methodology: [How GeminIQ Builds a Filing Data Study](/blog/filing-data-study-methodology).</sup>

---

## Blog: Quality of Earnings: Reading Accruals From Filings
source: https://www.geminiq.com/blog/earnings-quality-accruals-analysis

### Quality of Earnings: Reading Accruals From Filings
Two companies can report identical net income and mean entirely different things by it, depending on how much of that income is cash already collected versus accruals — revenue and expenses recognized under GAAP but not yet converted to cash. This guide covers what accruals actually measure, the two standard methods for calculating total accruals from a 10-K, the academic research showing high-accrual earnings predict weaker future performance than cash-based earnings, and where the accrual buildup shows up in a company's filings before the aggregate number would flag it.

Two companies can report the exact same net income and mean two completely different things by it — the gap is what analysts call quality of earnings. One earned that income in cash, collected and sitting in the bank. The other earned it on paper — recognized under GAAP, real and legal, but represented mostly by receivables not yet collected, inventory not yet sold, or estimates not yet tested against reality. The accounting term for that second component is accruals, and the size of it, relative to cash flow, is one of the most extensively studied predictors of which earnings figure to actually trust.

This guide covers what accruals actually measure, the two standard ways to calculate them, the academic finding — now three decades old and still cited constantly — that high-accrual earnings predict weaker future performance than low-accrual earnings, and where in a company's own filings the accrual buildup shows up first.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=earnings-quality-accruals-analysis)**

---

## Table of Contents

- [What Accruals Actually Are](#what-accruals-actually-are)
- [Calculating Total Accruals: Two Methods](#calculating-total-accruals-two-methods)
- [The Accruals Anomaly: What Sloan Found](#the-accruals-anomaly-what-sloan-found)
- [Why High Accruals Predict Weaker Future Earnings](#why-high-accruals-predict-weaker-future-earnings)
- [Reading the Accruals Ratio](#reading-the-accruals-ratio)
- [Where High Accruals Show Up First](#where-high-accruals-show-up-first)
- [Checking Earnings Quality on GeminIQ](#checking-earnings-quality-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What Accruals Actually Are

Every income statement is built on accrual accounting: revenue gets recognized when it's earned, not necessarily when cash arrives, and expenses get recognized when they're incurred, not necessarily when cash goes out. That's the entire point of accrual accounting — it's supposed to match economic activity to the period it actually happened in, rather than to whenever the cash happened to move. Most of the time, it does exactly that.

Accruals are the gap this creates between reported net income and the cash a business actually generated from its operations. A company can report rising net income quarter after quarter while its cash flow from operations stays flat or declines — and when that gap widens and persists, it's worth asking which of the two numbers is the more reliable description of what the business is actually doing.

---

## Calculating Total Accruals: Two Methods

The simpler method uses the cash flow statement directly:

```
Total Accruals = Net Income − Cash Flow from Operations
```

Both figures are reported line items, no further calculation required, which makes this the practical version for checking a single company quickly — net income at the bottom of the income statement, cash flow from operations at the bottom of the operating section of the cash flow statement, both exactly where [our guide to reading a 10-K](/blog/how-to-read-10-k) locates them.

The more rigorous method, used in most of the original academic research on this topic, works from the balance sheet. Accruals are the change in Net Operating Assets — total assets minus cash and short-term investments, minus total liabilities minus total debt — from one period to the next. The balance sheet approach strips out the effect of financing decisions and focuses purely on the operating side of the business, which makes it the more precise measure, though also the more work to calculate by hand. For a quick check on a specific filing, the cash flow method gets you most of the way there.

---

## The Accruals Anomaly: What Sloan Found

Richard Sloan's 1996 paper in *The Accounting Review*, "Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings?," remains the foundational research on this question three decades later. Sloan found that the accrual component of earnings is systematically less persistent than the cash flow component — meaning a dollar of accrual-based earnings this year is less likely to repeat next year than a dollar of cash-based earnings is. Companies with unusually high accruals tend to see earnings deteriorate in the following year; companies with low or negative accruals tend to see earnings hold up better than the market expected.

The finding that made the paper famous went beyond showing that accruals predict earnings — it showed that stock prices didn't fully reflect this at the time. A hedge strategy going long low-accrual companies and short high-accrual companies earned roughly **12% per year** in Sloan's original sample. That's evidence the market was systematically overweighting the accrual component of earnings and underweighting the cash component when pricing stocks. Later research found the effect weakened after the early 2000s, once the finding became widely known and, presumably, at least partly arbitraged away. That's a reminder documented market patterns tend to fade once everyone is watching for them — not a reason to dismiss the underlying accounting mechanism, which hasn't changed at all.

---

## Why High Accruals Predict Weaker Future Earnings

The mechanism is more mundane than it sounds. A company can boost this year's reported earnings by recognizing revenue aggressively, being slow to write down bad receivables or obsolete inventory, or making optimistic estimates anywhere GAAP requires judgment — none of which requires anything improper, and most of which is entirely within the bounds of standard accounting practice. What all of it has in common is that it borrows from future periods. Revenue recognized early this year is revenue that won't be recognized again next year. A receivable eventually has to convert to cash or get written off. An optimistic estimate eventually meets reality.

High accruals, in other words, often represent earnings quality being spent now rather than manufactured out of nothing. The reversal that follows is mechanical: accrued income eventually has to convert to cash or get written off, and that conversion is what shows up as weaker performance later. Still, a year of unusually high accruals is, on its own, a reasonable basis for lowering the confidence placed in that year's earnings growth continuing.

---

## Reading the Accruals Ratio

A reader scanning a single accruals ratio naturally looks for a cutoff — a number below which earnings are safe and above which they're worth doubting. No such fixed cutoff exists here; what actually separates a clean quarter from a warning sign is less the ratio's raw level than which of a few recognizable patterns it belongs to. Raw accrual dollars aren't comparable across companies of different sizes, so the standard practice is to scale total accruals by average net operating assets (or, in simpler versions, average total assets) to produce an accruals ratio. A low or negative accruals ratio — earnings roughly tracking cash flow, or cash flow actually exceeding reported earnings — is generally read as a sign of higher earnings quality. A high, sustained accruals ratio is the version worth investigating further, particularly when it's rising over several consecutive periods rather than reflecting one unusual quarter.

The four patterns worth telling apart, and what each one asks you to check next:

| Accruals pattern | What the filing shows | Standard read | Check next |
| --- | --- | --- | --- |
| Negative accruals | Operating cash flow exceeds net income | Highest earnings quality; reported profit is fully cash-backed | Whether the gap is structural (deferred revenue, depreciation-heavy model) or one-off |
| Low accruals | Net income and operating cash flow track closely | Earnings are a fair description of cash generation | Nothing further, unless the trend turns |
| High accruals, one period | Net income pulls ahead of operating cash flow for a single quarter | Not concerning on its own if the filing names a cause | The disclosed event — a large completed-contract receivable, for example |
| High accruals, rising over several periods | The gap between net income and operating cash flow widens quarter after quarter with no stated cause | Lower confidence that this year's earnings growth repeats | Receivables vs. revenue, inventory vs. sales, the allowance for doubtful accounts |

Context still matters here more than a single threshold. A single quarter of elevated accruals tied to a specific, disclosed event — a large one-time receivable from a completed contract, for instance — reads very differently from a steady multi-year climb with no stated cause. The mirror image of this check is valuing a business on the cash it actually produced rather than the earnings it reported, which is the ground [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) covers in full.

---

## Where High Accruals Show Up First

A rising accruals ratio looks like the earliest warning that an earnings-quality problem exists, but by the time the aggregate ratio actually moves, several of the balance sheet items that produce it are typically already visible individually — some for several quarters beforehand. Receivables growing faster than revenue is one component. Inventory building faster than sales is another. A declining allowance for doubtful accounts, or deferred tax assets growing without a clear operating reason, are both accrual-driving movements that show up in the filing's own footnotes before they show up as a single aggregate number.

That overlap exists because accruals are, in a real sense, the single number that several individual [balance sheet red flags](/blog/balance-sheet-red-flags-checklist) all roll up into. Checking the individual line items and checking the aggregate accruals figure amount to the same exercise, viewed at two different resolutions.

It's worth being precise about what this gap does and doesn't catch. A widening spread between net income and operating cash flow is a persistence signal, not a fraud detector, and there is at least one well-documented case where a large fraud left the two figures moving in perfect agreement because the same manipulation inflated both — the mechanics of that failure are covered in [reading the cash flow statement for fraud signals](/blog/cash-flow-statement-fraud-signals).

---

## Checking Earnings Quality on GeminIQ

Calculating total accruals requires exactly two figures, both reported directly on every 10-K and 10-Q: net income and cash flow from operations. GeminIQ's [Financial Statements](/features#financial-statements) view carries both, as-filed, for every period a company has reported — which means the calculation above is a two-line subtraction rather than a research project, for any company and any quarter in GeminIQ's coverage.

That matters more than it sounds, because a subtraction is only as trustworthy as its two inputs. Net income and operating cash flow that have been normalized, restated into a provider's own template, or reconciled across periods by someone other than the filer can quietly shift the gap this entire method depends on — the difference between as-filed and aggregator-processed figures is the comparison we run against [Fiscal.ai](/competitor-comparison/fiscal-ai).

The individual components behind that subtraction are just as directly available. GeminIQ's [Financial Statements](/features#financial-statements) view carries the receivables and inventory lines needed to check the underlying components directly, and the [Custom Tables](/features#custom-tables) builder tracks any of these relationships — net income versus operating cash flow, receivables versus revenue — across multiple quarters side by side, from the same as-filed source data the accruals calculation itself depends on.

---

## Frequently Asked Questions

### What is a "good" accruals ratio?

There's no universal threshold, but a low or negative accruals ratio — earnings tracking closely with or below operating cash flow — is generally read as higher earnings quality, while a high, sustained ratio warrants closer scrutiny of what's actually driving reported earnings growth.

### Are high accruals always a sign of earnings manipulation?

No. High accruals can result from legitimate business events — a large contract with delayed payment terms, rapid but genuine revenue growth outpacing collections — and don't require anything improper in the accounting. The finding is about persistence, not fraud: high-accrual earnings are statistically less likely to repeat, whatever caused them.

### How do I calculate accruals from a 10-K?

The simplest method: subtract cash flow from operations from net income, both reported directly on the filing. Total Accruals = Net Income − Cash Flow from Operations. For cross-company comparison, scale the result by average total assets or average net operating assets to get an accruals ratio.

### Is the accrual anomaly still effective as a trading strategy today?

Research suggests the original excess-return effect weakened after the early 2000s, likely because it became widely known and priced in. The underlying accounting relationship — that accrual-based earnings are less persistent than cash-based earnings — hasn't changed, but treat any historical trading-strategy return as a documented pattern, not a guarantee.

Net income tells you what a company reported. Cash flow tells you what it actually collected. The gap between them, tracked consistently, tells you which of the two to trust more this year.

---

## Related Reading

- [Balance Sheet Red Flags: A Filing-Based Checklist](/blog/balance-sheet-red-flags-checklist) — the individual signals that, in aggregate, are what accruals actually measure.
- [Reading the Cash Flow Statement for Fraud Signals](/blog/cash-flow-statement-fraud-signals) — where the net-income-versus-cash-flow gap stops being enough, and what catches what it misses.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — the cash-based counterpart to accrual-based earnings.
- [How to Read a 10-K](/blog/how-to-read-10-k) — where net income and cash flow from operations actually appear in the filing.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=earnings-quality-accruals-analysis)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: EDGAR Accession Numbers and Filing URL Structure
source: https://www.geminiq.com/blog/edgar-accession-number-url-structure

### EDGAR Accession Numbers and Filing URL Structure
An accession number — a string like 0000320193-23-000106 — is the unique identifier EDGAR assigns to a single filing, and understanding its structure is what turns it into a working URL rather than an opaque reference. This guide covers how EDGAR's Archives URLs are built from a CIK and an accession number, where the filing index page and primary document live, how the XBRL viewer's R-files are organized, and the hyphen and CIK-padding differences that break a manually constructed URL more often than anything else.

An accession number looks like a string of digits with two hyphens in it — 0000320193-23-000106 — the kind of string a reader's eye slides past on the way to the actual filing. Underneath that unremarkable format, it's the single identifier that resolves to the exact URL of a specific filing, every document inside it, and every rendered XBRL table the SEC generated from it. Knowing how to turn one into a working URL is the difference between citing "[Apple's](/stocks/AAPL) 2023 10-K" and citing the one document that number actually points to.

This guide covers how EDGAR's Archives URLs are built from a CIK — the Central Index Key, the permanent numeric identifier the SEC assigns to every filer — and an accession number, where the filing index page and the primary document live inside that structure, and how the R-files behind the XBRL viewer are organized. It also covers the handful of formatting differences — hyphens present here, stripped there, CIK padding required in one place and optional in another — that break a manually constructed URL more often than anything else.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=edgar-accession-number-url-structure)**

---

## Table of Contents

- [What an Accession Number Is](#what-an-accession-number-is)
- [The Archives URL Pattern: From Accession Number to Filing](#the-archives-url-pattern-from-accession-number-to-filing)
- [The Filing Index Page](#the-filing-index-page)
- [Finding the Primary Document](#finding-the-primary-document)
- [The R-Files: Where the XBRL Viewer Tables Live](#the-r-files-where-the-xbrl-viewer-tables-live)
- [CIK Padding: Where It Matters and Where It Doesn't](#cik-padding-where-it-matters-and-where-it-doesnt)
- [Full-Text Search Indexes Files, Not Filings](#full-text-search-indexes-files-not-filings)
- [Bulk Access: The Quarterly Full-Index Files](#bulk-access-the-quarterly-full-index-files)
- [Citing a Filing Precisely on GeminIQ](#citing-a-filing-precisely-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What an Accession Number Is

An accession number is the unique identifier EDGAR assigns to a single submission — one specific filing of any [form type](/blog/sec-filings-guide), submitted on a specific date. It has three parts, written with hyphens: the 10-digit CIK of the filer or filing agent that transmitted the submission, a two-digit year, and a sequence number for that submitter within the year.

| Part | Position in `0000320193-23-000106` | What it is | Worked example |
|---|---|---|---|
| CIK of the transmitter | `0000320193` | The 10-digit Central Index Key of the filer or filing agent that submitted it — zero-padded | `0000320193` = Apple |
| Two-digit year | `23` | The calendar year EDGAR accepted the submission | `23` = 2023 |
| Sequence number | `000106` | That submitter's submission count for the year | `000106` = the 106th submission that filer transmitted in 2023 |

A single accession number maps to one complete submission, which typically bundles the primary document together with every exhibit and, for a periodic report, the full set of XBRL data behind it. That specificity is what makes an accession number more precise than a company name and a filing date. Two 10-Ks filed by the same company in the same year, or a 10-K and a later 10-K/A covering the same fiscal year, each get their own accession number, and only the exact number resolves to the exact filing.

---

## The Archives URL Pattern: From Accession Number to Filing

Every filing lives at a URL built from three pieces: the base path, the filer's CIK, and the accession number with its hyphens removed:

```
https://www.sec.gov/Archives/edgar/data/{CIK}/{accession-no-dashes}/
```

That directory is where every document belonging to the submission lives — the primary filing, every exhibit, and the XBRL viewer files, all as separate files inside the same folder. The CIK in this path can be entered with or without its leading zeros; the Archives system doesn't require the strict 10-digit padding the XBRL API does, which is one of the few places EDGAR is more forgiving than it looks.

---

## The Filing Index Page

Appending the accession number back in — with its hyphens restored — plus `-index.htm` returns a human-readable page listing every document in the submission, each one linked:

```
https://www.sec.gov/Archives/edgar/data/{CIK}/{accession-with-dashes}/{accession-with-dashes}-index.htm
```

This is the single most useful URL in the entire structure, and it's the pattern GeminIQ uses to cite every filing referenced across the platform. It requires no guessing about the primary document's filename and no knowledge of how many exhibits the filing carries. The index page lists all of it, with a direct link to each document, in one page load.

---

## Finding the Primary Document

The primary document itself doesn't follow a predictable filename pattern the way the folder structure does. A company's 10-K might be named `aapl-20230930.htm`, following a ticker-plus-period-end convention, or something entirely different depending on the filer's own document-naming choices — there's no rule that guarantees the filename, only that the index page always lists it. [Tesla's](/stocks/TSLA) FY2021 10-K, for example, lives at:

```
https://www.sec.gov/Archives/edgar/data/1318605/000095017022000796/tsla-20211231.htm
```

This follows the ticker-plus-date pattern, but it's convention, not requirement. Treating the index page as the starting point, rather than guessing the primary document's filename directly, is the more reliable approach for any filing you haven't seen before.

---

## The R-Files: Where the XBRL Viewer Tables Live

Every periodic filing's directory also contains a set of files named `R1.htm`, `R2.htm`, `R3.htm`, and so on — one per rendered table the SEC's XBRL viewer generated from the filing's tagged data. These are the same tables a person sees when they open a filing's XBRL viewer directly on EDGAR: the balance sheet, the income statement, the cash flow statement, and each individual footnote table. Each one is broken out as its own numbered file in the same accession directory as the primary document and exhibits. They sit alongside a `MetaLinks.json` file and a `FilingSummary.xml` file, which together map which `R` file corresponds to which financial statement or footnote — useful context if you're trying to jump directly to, say, the debt footnote table rather than paging through the primary document manually.

---

## CIK Padding: Where It Matters and Where It Doesn't

CIK padding is the most common way a manually built EDGAR URL breaks, and the rule is inconsistent across the two URL systems investors are most likely to use. In Archives browse URLs — `/Archives/edgar/data/{CIK}/...` — the CIK can be entered with or without leading zeros; both `1318605` and `0001318605` resolve to the same company. In the XBRL data API — `data.sec.gov/api/xbrl/companyconcept/CIK{CIK}/...` — the CIK must be exactly 10 digits, zero-padded, with the literal string `CIK` prefixed directly onto the number. Passing an unpadded CIK to the API returns a 404 rather than falling back gracefully, which is the opposite of how the Archives URLs behave. Handling that padding in code is covered in [How to Pull SEC Financial Data With Python](/blog/pull-sec-financial-data-python).

---

## Full-Text Search Indexes Files, Not Filings

EDGAR's full-text search doesn't index at the accession level. It indexes individual files within an accession. A single 10-K submission can produce several separate search hits: the primary annual report document, an EX-23 auditor consent, an EX-10 material contract, and even individual XBRL viewer fragments, each indexed as its own searchable unit tied to the same accession number but a different filename. A full-text search result pointing to a specific exhibit rather than the primary 10-K document isn't unusual — it means the search term appeared in that exhibit specifically, not necessarily anywhere in the primary filing.

---

## Bulk Access: The Quarterly Full-Index Files

For anyone pulling filing lists across many companies rather than looking up filings one at a time, EDGAR publishes quarterly index files rather than requiring individual lookups:

```
https://www.sec.gov/Archives/edgar/full-index/{YYYY}/QTR{1-4}/{form|company|master|xbrl}.idx
```

Each index lists every filing submitted that quarter — company name, form type, CIK, filing date, and the file path — sorted differently depending on which of the four index types is requested. `form.idx` sorts by form type, `company.idx` sorts by company name, and `master.idx` combines both in filing order. For a job that needs "every 8-K filed in Q2 2026," pulling one quarterly index file is a single request in place of thousands of individual filing lookups.

---

## Citing a Filing Precisely on GeminIQ

Every figure on GeminIQ traces back to the exact filing it came from, and the accession number is the mechanism that makes that traceable. When GeminIQ's [Financial Statements](/features#financial-statements) view shows a number sourced from a specific 10-K or 10-Q, the underlying citation is built from precisely the pattern this guide covers: CIK plus accession number, resolved to the filing index page where the original document sits. That's a meaningfully different guarantee than a platform that cites "the company's most recent annual report" without a specific accession number attached — the difference between a citation you can click through to the exact document, and one you have to take on faith.

Everything above is the addressing scheme, not the research step built on top of it. Actually walking a figure back to the filing it came from is its own workflow, covered in [Verify Financial Data Against the Original SEC Filing](/blog/verify-financial-data-against-sec-filing). Filing-navigation tools sit in between: a document-reader layer rebuilds EDGAR's document tree into a cleaner reading interface but still hands you the document, while GeminIQ starts from the tagged data and keeps the accession number attached to every value it derives from it.

---

## Frequently Asked Questions

### What are the three parts of an accession number?

The filer or filing agent's 10-digit CIK, a two-digit year, and a sequence number for that submitter within the year — written as `CIK-YY-SEQUENCE`, for example `0000320193-23-000106`.

### Do EDGAR URLs use hyphens in the accession number or not?

Both, in different places. The folder in the Archives path strips the hyphens (`000032019323000106`), but the index page filename restores them (`0000320193-23-000106-index.htm`).

### Why does a CIK work without leading zeros in one EDGAR URL but not another?

Archives browse URLs accept a CIK with or without leading zeros. The XBRL data API requires the CIK zero-padded to exactly 10 digits with no exceptions, and returns a 404 rather than resolving an unpadded number.

### What are the R1.htm, R2.htm files in a filing's directory?

They're the individual rendered tables the SEC's XBRL viewer generates from a filing's tagged data — one file per financial statement or footnote table, sitting in the same accession directory as the primary document and exhibits.

The accession number itself is just three numbers separated by two hyphens. What it unlocks — the exact filing, the exact document, the exact table — is the entire reason EDGAR citations can be more precise than any other kind of financial sourcing.

---

## Related Reading

- [How to Pull SEC Financial Data With Python](/blog/pull-sec-financial-data-python) — the companion data.sec.gov API system, separate from the Archives browse URLs covered here.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — where each filing type covered here fits in the bigger picture.
- [Verify Financial Data Against the Original SEC Filing](/blog/verify-financial-data-against-sec-filing) — using the accession number to check a number for yourself.
- [When XBRL Tags Change Between Filing Years](/blog/xbrl-tag-changes-between-filing-years) — a case where the accession number is the only way to settle what a figure actually was.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: EV/EBITDA vs. P/E: Which Valuation Multiple Should You Use?
source: https://www.geminiq.com/blog/ev-ebitda-vs-pe-ratio-explained

### EV/EBITDA vs. P/E: Which Valuation Multiple Should You Use?
EV/EBITDA and P/E both measure what you pay relative to earnings — but from fundamentally different starting points. This guide covers what each multiple actually measures, where each misleads, and when to reach for EV/EBIT instead.

P/E is the ratio that every financial headline quotes, every brokerage app displays by default, and every new investor learns first. EV/EBITDA is the multiple that private equity firms, M&A advisors, and institutional analysts reach for when they are actually trying to determine whether a business is cheap. Both ratios answer the same surface-level question — what am I paying relative to what this company earns? — but they answer it from completely different starting points, and the difference matters far more than most investors realize. Understanding what each multiple actually measures, where each one misleads, and which to reach for in a given situation is one of the more practical upgrades a fundamental investor can make.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=ev-ebitda-vs-pe-ratio-explained)**

## What P/E Actually Measures — and Where It Breaks

The price-to-earnings ratio is deceptively simple: divide the company's market capitalization by its trailing twelve-month net income, and you have the number of dollars investors are paying for each dollar of annual earnings. A P/E of **20x** means investors are paying **$20** for every **$1** of net income — an implicit earnings yield of **5%**. The S&P 500 has historically traded in the **15x–18x** range; growth stocks routinely command **30x–50x** or higher. The ratio is intuitive, and for a company with a clean capital structure and stable earnings, it is a reasonable quick filter.

The problem is not the price side. The problem is the earnings side — specifically, what net income is and what it leaves out. Net income is calculated after interest expense, after taxes, and after depreciation and amortization. Each of those deductions is sensitive to choices that have nothing to do with how well the underlying business operates.

Consider two businesses with identical operations: each generates **$100 million** of operating profit per year from the same asset base. Company A is financed entirely with equity. Company B carries **$500 million** of debt at a **5% interest rate**, costing it **$25 million** per year in interest expense. After a **25% effective tax rate**, Company A reports net income of **$75 million**. Company B reports **$56 million**. If both trade at the same market capitalization of **$1.5 billion**, Company A shows a P/E of **20x** and Company B shows a P/E of roughly **27x** — making Company B look significantly more expensive despite having operationally identical earnings power. The entire difference is capital structure. The underlying business is the same.

This is the capital structure blindspot that standard financial media does not flag. A P/E comparison between two companies in the same sector can be entirely misleading if their debt loads differ — which, in telecommunications, energy, real estate, and media, they routinely do. But standard financial media doesn't read the footnotes.

Tax rates introduce a second distortion. A company with a **21% effective tax rate** reports different net income than an identical operation paying **28%**, even though operating performance is identical. For cross-border comparisons — European versus US companies in the same industry — P/E becomes nearly useless as a relative valuation tool. And non-recurring items are the third distortion: a large restructuring charge, an asset impairment, or a one-time gain from a property sale can swing net income dramatically in a single period, producing a P/E that bears no relationship to normalized earning power. A company absorbing a **$500 million** write-down in one year will show an astronomical P/E; after the charge rolls off the TTM window, the ratio reverts to normal. The headline number gets quoted regardless.

## What Enterprise Value Changes About the Equation

Enterprise value is the cleaner numerator. It is the theoretical total acquisition price for the business: market capitalization plus total debt minus cash and cash equivalents. The formula captures what a buyer would actually pay — you acquire the equity, you assume the debt, and you gain access to the cash. It is capital-structure-aware by construction.

GeminIQ's [Enterprise Value](/metrics/valuation-metrics/enterprise-value) is built directly from as-filed balance sheet data: market cap using period-end price and basic shares, plus short-term and long-term debt as reported, minus cash and cash equivalents as reported. Every input is traceable to the XBRL-tagged filing.

The EV framework dissolves the capital structure comparison problem. Return to Company A and Company B. If Company A has a market cap of **$1.5 billion** and no debt, its EV is **$1.5 billion**. If Company B carries the same **$1.5 billion** market cap but **$500 million** in debt, its EV is roughly **$2 billion**. Now compare both against their operating earnings — before the interest and tax decisions that distort net income — and the picture changes. The market cap said both were priced identically. The enterprise value reveals that Company B costs significantly more per dollar of underlying operating output.

This is why an acquirer always thinks in enterprise value. When one company buys another, the buyer assumes the target's debt. The market cap is not the full check being written.

## How EV/EBITDA Corrects for Capital Structure

EV/EBITDA pairs enterprise value with EBITDA — earnings before interest, taxes, depreciation, and amortization — to create a multiple that is capital-structure-neutral, tax-neutral, and largely accounting-method-neutral. The denominator removes the three sources of net income distortion described above: interest (capital structure), taxes (jurisdiction), and D&A (depreciation method and acquisition history).

A company with **$200 million** of EBITDA trading at **$2 billion** of enterprise value has a multiple of **10x**. A private equity firm evaluating that business knows it is paying ten years of pre-investment operating cash flow for the business as it stands. Whether the company is financed with equity or debt, headquartered in Texas or Frankfurt, whether it built its asset base organically or through a decade of acquisitions — the EV/EBITDA multiple provides a consistent comparison benchmark.

GeminIQ's [EV/EBITDA TTM](/metrics/valuation-metrics/ev-ebitda) is derived directly from SEC filing data — EBITDA taken from the filing or calculated as EBIT plus depreciation and amortization as reported, without adjustments for stock-based compensation, restructuring charges, or other items that platforms commonly strip out. Aggregators that report "adjusted EBITDA" can produce materially different multiples for the same company in the same period. A business with **$800 million** of GAAP EBITDA and **$1.2 billion** of adjusted EBITDA looks very different at the same enterprise value depending on which denominator your platform uses. GeminIQ uses the as-filed number. The multiple you see reflects what the company actually reported.

The ratio became standard in leveraged buyout analysis during the 1980s and remains the primary valuation tool in institutional M&A and private equity. The S&P 500 median EV/EBITDA has historically traded in the **12x–14x** range. Private equity firms typically target acquisitions in the **6x–10x** range, with **below 8x** generally considered value territory and **above 15x** requiring a compelling growth or quality argument to justify.

## The Capex Problem — When EV/EBITDA Misleads Too

Warren Buffett has asked, in substance, whether management believes the tooth fairy pays for capital expenditures. The point was directed at EBITDA specifically. The "DA" added back — depreciation and amortization — is treated as a non-cash accounting entry, but for businesses with significant physical assets, depreciation is not arbitrary. It approximates the real, recurring cost of replacing or maintaining the asset base that makes the business run.

For a software company or a consumer brand, this distinction barely matters. Software requires minimal physical reinvestment; maintenance capex might represent **5%–10%** of EBITDA. But for an airline carrying tens of billions of dollars of aircraft, a telecom operator maintaining thousands of miles of physical network, or an energy company running refining capacity, the D&A added back in the denominator represents genuine future cash expenditures the business cannot avoid. A company generating **$3 billion** of EBITDA with **$2 billion** of annual maintenance capex has very different economic earning power than a software company generating the same **$3 billion** of EBITDA with **$150 million** of capex. At the same EV/EBITDA multiple, the capital-intensive business is substantially more expensive on any cash-based measure.

This is the capex trap. EV/EBITDA adds D&A back and never returns to it. The multiple works well for asset-light businesses where capital expenditure is genuinely minimal relative to earnings. It misleads significantly for capital-intensive businesses — it makes expensive operations appear cheap.

The practical cross-check: compare EV/EBITDA against GeminIQ's pre-calculated [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield). A company with a low EV/EBITDA and a high FCF yield is one where EBITDA and free cash flow are reasonably aligned — depreciation is not concealing significant real capital requirements. A company with a low EV/EBITDA and a low FCF yield is one where the multiple is flattering a capex-heavy business. For a full treatment of FCF yield as a valuation lens, see [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained). That gap between the two signals is the information EV/EBITDA alone cannot show you.

## EV/EBIT: The More Conservative Alternative

EV/EBIT uses the same enterprise value numerator but does not add back depreciation and amortization in the denominator. Because EBIT deducts D&A, it produces a more conservative — and for capital-intensive companies, more honest — measure of operating earnings.

GeminIQ's [EV/EBIT TTM](/metrics/valuation-metrics/ev-ebit) is derived from TTM EBIT as filed or calculated as net income plus income tax plus interest expense. For any given company, EV/EBIT will always be higher than EV/EBITDA because EBIT is a smaller number — D&A remains in the denominator rather than being added back. The gap between the two multiples is itself informative: a company where EV/EBIT is **12x** and EV/EBITDA is **11.5x** has very low depreciation relative to EBITDA — a light-asset business where the add-back is genuinely modest. A company where EV/EBIT is **14x** and EV/EBITDA is **7x** carries very high D&A relative to its earnings — a capital-intensive or heavily acquisitive business where EV/EBITDA significantly overstates true earning power.

That gap is the single fastest read on how asset-heavy a business really is. Pulling both multiples side by side in a GeminIQ [Custom Table](/features#custom-tables) across a company's 10-K filing periods makes the pattern visible over time: where the two lines track closely, the depreciation add-back is immaterial; where they separate widely, EV/EBITDA is crediting the business for a cost it will keep paying. Transport, logistics, and other fleet-and-facility operators typically show the widest separation, because the depreciation being added back is running against aircraft, vehicles, and sorting infrastructure that has to be maintained and eventually replaced.

Joel Greenblatt's Magic Formula uses EBIT/EV — the inverse of EV/EBIT, expressed as an earnings yield — as its valuation component precisely because it normalizes for capital structure while keeping depreciation in the denominator. Greenblatt argues this is the most honest single number for comparing the cheapness of different businesses across sectors. For the full treatment of how the Magic Formula uses earnings yield alongside return on invested capital, see [Magic Formula Investing Explained](/blog/magic-formula-investing-explained).

GeminIQ's [High Earnings Yield Screener](/screens/stock-screeners/high-earnings-yield) runs on EV/EBIT below **10x** — a starting pool of businesses generating operating earnings at a rate substantially above their enterprise cost.

## Which Multiple to Use and When

No single multiple covers every situation. The choice depends on the type of business, the comparison being made, and which distortion is most likely to mislead.

For highly leveraged companies — where debt service consumes a large share of operating income — P/E is structurally unreliable. Interest expense directly inflates or deflates net income depending on the outstanding balance and prevailing rate, and the equity P/E gives no information about the cost relative to the whole business. EV/EBITDA or EV/EBIT is the appropriate lens.

For capital-intensive companies — airlines, telecom operators, manufacturers, energy producers — EV/EBITDA flatters by adding back depreciation that approximates real economic cost. EV/EBIT is the more conservative screen, and FCF yield is the most direct test of cash generation after capex is accounted for.

For asset-light businesses with minimal physical investment — software companies, consumer platforms, professional services firms — EV/EBITDA works well because D&A is genuinely small relative to earnings. In these businesses, EV/EBITDA and EV/EBIT will be close to each other, which is itself the confirmation that the add-back is not masking capex intensity.

For cross-border comparisons where tax rates differ materially, P/E comparisons are unreliable. EV/EBITDA neutralizes the tax variable entirely.

For loss-making companies, both P/E and EV/EBITDA break down — negative earnings produce meaningless multiples. Price-to-sales or EV/Revenue becomes the relevant anchor, supplemented by cash burn analysis. The same caution applies to any company with negative trailing EBITDA: a negative denominator divided into a negative enterprise value returns a positive-looking multiple that means nothing at all.

For banks, insurers, and other financial companies, EV/EBITDA breaks down for a different reason. Enterprise value subtracts cash on the assumption that cash is surplus to operations — but at a bank or an insurer, the deposit base and investment portfolio *are* the operating business, not idle balances. Netting them out collapses enterprise value and drives the multiple toward **1x** regardless of how the business is actually priced. First Community Corp is a clean illustration: a market capitalization of roughly **$268 Million** against **$218 Million** of cash leaves an enterprise value of just **$65 Million** and an EV/EBITDA near **1.05x**. That figure describes an accounting artifact, not a cheap bank. For financials, price-to-book and price-to-tangible-book are the appropriate anchors.

Within a single sector where companies share similar capital structures and effective tax rates, P/E is a reasonable quick filter — but a starting point, not a conclusion. The moment leverage, depreciation policies, or tax rates diverge between the companies being compared, the P/E comparison stops being informative and EV/EBITDA takes over.

GeminIQ's [Low EV/EBITDA Screener](/screens/stock-screeners/low-ev-ebitda) runs on EV/EBITDA below **8x** with positive EBITDA — a capital-structure-neutral value starting pool. Pairing it with a FCF yield overlay isolates companies where the low multiple reflects genuine cash generation rather than depreciation-heavy add-backs. For the quality dimension, [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) is the natural companion — a business with a low EV/EBITDA, a high FCF yield, and a high ROIC is the combination that value screens are built to surface.

<center><sup>GeminIQ Stock Screener running the Low EV/EBITDA filter — EV/EBITDA TTM between **1x** and **8x**, sorted ascending by cheapest multiple, with each company's most recent quarterly EBITDA shown alongside the trailing-twelve-month ratio. Note what the cheapest end of the screen actually contains: banks, insurers and REITs, where the large cash and investment balances that compress enterprise value are operating float rather than surplus cash — exactly the distortion described above. The screen is a starting pool, not a conclusion. All EV/EBITDA TTM figures sourced directly from as-filed SEC filings.</sup></center>

## Why the Data Behind the Multiple Matters

EV/EBITDA and P/E are formulas. The outputs are only as reliable as the inputs, and the inputs vary significantly depending on how and where they are sourced.

Enterprise value depends on how debt is defined. Does a platform include operating lease liabilities — which have appeared on the balance sheet since ASC 842 took effect in 2019 — in its debt figure? A large retailer with **$3 billion** of operating lease liabilities will show materially different enterprise values depending on whether those leases are included. A company with **$2 billion** of operating lease liabilities and **$500 million** of pension obligations can show EV/EBITDA of **6.5x** on one platform and **9.0x** on another based entirely on what each platform includes in enterprise value. GeminIQ constructs enterprise value from as-filed balance sheet components — short-term debt, long-term debt, and cash and equivalents as reported — with full visibility into each input.

EBITDA depends on whether a platform uses the GAAP-derived figure or an adjusted version. A company reporting **$800 million** of GAAP EBITDA alongside **$1.2 billion** of adjusted EBITDA — a gap driven by stock-based compensation and restructuring charges added back — looks very different on each basis. GeminIQ's EBITDA is derived from as-filed operating income plus as-filed depreciation and amortization. No adjustments. The number reflects what the company actually reported under GAAP.

P/E depends on share count methodology. GeminIQ uses period-end basic shares and TTM net income from the filing. Platforms using diluted share counts or forward consensus estimates produce different multiples for the same company in the same period.

These are not edge cases or rounding differences. A standard screener shows you a number labeled EV/EBITDA without disclosing how it was built. GeminIQ's [Calculated Metrics](/features#calculated-metrics) view exposes every component so the inputs are visible and verifiable, and the underlying [Financial Statements](/features#financial-statements) pull directly from XBRL-tagged SEC filings — the same source document the company filed. The metric tells the story. The filing confirms it.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: ExxonMobil Q1 2026 10-Q: The Real Gross Margin Revealed
source: https://www.geminiq.com/blog/exxon-mobil-10q-analysis-q1-2026

### ExxonMobil Q1 2026 10-Q: The Real Gross Margin Revealed
ExxonMobil's Q1 FY2026 10-Q produces an implausible near-100% gross margin on a naive data pull, because ExxonMobil reports its direct costs across two separate line items rather than a single 'cost of goods sold' tag. Properly combined, the real TTM figure is 30.5% — and the dividend cushion has narrowed considerably.

**[ExxonMobil](/stocks/XOM) ($XOM) just dropped its Q1 FY2026 10-Q (filed May 4, 2026). Most coverage of oil majors fixates on the daily crude price and ignores the underlying filing structure entirely. Pulling ExxonMobil's raw cost data naively produces a gross margin north of 99%, a number that's obviously wrong for a company that spends most of its revenue acquiring and processing crude oil. Combine the filing's actual cost components correctly and the real trailing-twelve-month figure is 30.5% — and once that's done properly, a second, more important story shows up: the dividend cushion that made this stock famous has narrowed considerably.**

| Field                         | Value            |
| ----------------------------- | ---------------- |
| Ticker                        | $XOM             |
| Filing                        | Q1 FY2026 10-Q   |
| Filed                         | May 4, 2026      |
| Period End                    | March 31, 2026   |
| Gross Margin (TTM, corrected) | **30.5%**        |
| FCF Coverage of Dividend      | **$1.6 Billion** |

## The Margin Structure Revealed

Naive data pulls on integrated oil majors produce a specific, predictable error, and ExxonMobil is a clean example of it.

**The Data:** [ExxonMobil](/stocks/XOM) reports its direct product costs across two separate filed line items rather than a single "cost of goods sold" tag: **Crude Oil And Product Purchases**, totaling **$189.26 Billion** on a trailing-twelve-month basis, and **Production And Manufacturing Expenses**, totaling **$43.04 Billion** TTM. Combined, that's **$232.30 Billion** in direct costs against **$334.25 Billion** in TTM revenue, for a real [Gross Margin](/metrics/margin-metrics/gross-profit-margin) of **30.5%** — not the implausible ~100% figure a single-tag pull produces when it misses both components entirely.

**The GeminIQ Edge:** A tool built to grab "cost of goods sold" off a standard tag list finds nothing for ExxonMobil, and either shows a blank field or, worse, silently defaults gross profit to equal revenue. Pulling every cost-related line individually from the raw [Financial Statements](/features#financial-statements), and understanding which lines genuinely belong together, is the only way to get a real, usable gross margin for an integrated energy company.

<center><sup>GeminIQ Financial Statements showing ExxonMobil's quarterly Crude Oil And Product Purchases, Production And Manufacturing Expenses, and Revenues, which sum across the four most recent quarters to $189.26 Billion, $43.04 Billion and $334.25 Billion respectively, for a Gross Profit Margin TTM of 30.50%.</sup></center>

## The Cash Flow Engine, Still Running

The headline "cash cannon" story around [ExxonMobil](/stocks/XOM) from prior filings still holds up, even if the exact numbers have moved.

**The Data:** TTM Operating Cash Flow sits at **$47.72 Billion**, against TTM CapEx of **$28.93 Billion**, for TTM Free Cash Flow of **$18.79 Billion**. Both operating cash flow and free cash flow have eased somewhat from prior peaks, consistent with a period of softer realized margins rather than any operational deterioration.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) cash flow data directly, rather than relying on a smoothed non-GAAP adjusted figure, shows the actual trailing trend rather than a single strong quarter presented in isolation.

<center><sup>GeminIQ Financial Statements showing ExxonMobil's TTM Operating Cash Flow of $47.72 Billion against TTM CapEx of $28.93 Billion, for TTM Free Cash Flow of $18.79 Billion.</sup></center>

## The Dividend Cushion Has Narrowed

This part of [ExxonMobil's](/stocks/XOM) story has shifted meaningfully since operating cash flow peaked, and it is worth stating plainly rather than glossing over.

**The Data:** TTM Dividends Paid stand at **$17.23 Billion** against TTM Free Cash Flow of **$18.79 Billion** — a coverage cushion of roughly **$1.6 Billion**. The dividend remains covered by free cash flow, but the margin of safety has compressed considerably from the wider cushion in prior periods, driven primarily by softer operating cash flow rather than any change in the payout itself.

**The GeminIQ Edge:** A single-period "dividend is covered" headline misses the trend. Pulling [Financial Statements](/features#financial-statements) dividends and free cash flow together across multiple periods shows the cushion shrinking in real time, which is a materially different risk picture than a comfortably wide, stable buffer.

<center><sup>GeminIQ Financial Statements showing ExxonMobil's Free Cash Flow TTM of $18.79 Billion against quarterly Payments Of Dividends Common Stock, which sum across the four most recent quarters to $17.23 Billion — a coverage cushion of roughly $1.6 Billion.</sup></center>

## Smart Money and the Insider Record

Two different signals around [ExxonMobil](/stocks/XOM) worth checking on their own terms.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has held in a fairly narrow band, from **62.7%** in December 2024 to **60.9%** as of the most recent 13F (March 2026, filed with the standard lag) — a modest decline, not a dramatic shift. [Insider Transactions](/features#insider-transactions) show a heavily sale-weighted record: 251 sales against 20 purchases in the available history.

**The GeminIQ Edge:** Neither figure is dramatic, and that's the honest read rather than a manufactured one. A modestly declining institutional base and a sale-heavy insider pattern are standard for a mature, dividend-paying energy major, not a signal worth over-reading in either direction.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership declining modestly from 62.7% (December 2024) to 60.9% (March 2026, most recent 13F).</sup></center>

## Frequently Asked Questions

### What is ExxonMobil's actual gross margin?

ExxonMobil's TTM Gross Margin is 30.5%, calculated by combining Crude Oil And Product Purchases ($189.26 Billion TTM) and Production And Manufacturing Expenses ($43.04 Billion TTM) against TTM revenue. A naive pull that misses both of these separately-reported cost lines can produce a misleadingly high figure near 100%.

### Does ExxonMobil's free cash flow still cover its dividend?

Yes, but with a narrower margin than in recent prior periods. TTM Free Cash Flow of $18.79 Billion covers TTM Dividends Paid of $17.23 Billion, a cushion of roughly $1.6 Billion, down from a considerably wider buffer previously.

### When did ExxonMobil last file its 10-Q, and what period does it cover?

ExxonMobil's most recent filing is a Form 10-Q filed May 4, 2026, covering the fiscal quarter ended March 31, 2026 (Q1 FY2026).

### Where can I verify ExxonMobil's cost and cash flow figures against the original filing?

The figures are drawn directly from ExxonMobil's Q1 FY2026 10-Q, filed with the SEC on May 4, 2026. The full filing is publicly available on SEC EDGAR (linked in the citation block below).

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Exxon Mobil Corporation's Q1 FY2026 10-Q (filed May 4, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0000034088/000003408826000067/xom-20260331.htm).

---

## Blog: FactSet Alternative for SEC Filing Research
source: https://www.geminiq.com/blog/factset-alternative-sec-filing-data

### FactSet Alternative for SEC Filing Research
A FactSet alternative for filing-level research. FactSet's core product is an identity layer that joins disparate datasets through proprietary entity IDs; this post explains what that buys, what it costs, and why the SEC already assigns a free universal identifier.

Ask what FactSet actually sells and most answers describe the workstation — screening, charting, portfolio analytics, estimates, comp tables. That is what users touch. It is not the moat.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=factset-alternative-sec-filing-data)**

The moat is identity. FactSet's Concordance Service and Symbology databases exist to map every locally managed identifier, every industry-standard ticker and security code, and every entity name onto a proprietary FactSet Entity ID. Their stated purpose is to link disparate sources of information to a master identifier. Once your holdings file, your risk model, your estimates feed, and your fundamentals all speak the same identifier language, they can be joined — and joining is the thing a large institution cannot do for itself without enormous effort.

Pricing follows the same modular logic. FactSet does not publish rates; access is quoted per user type, content set, analytics module, and contract term, with third-party reports commonly placing full workstation seats somewhere between roughly **$12,000** and **$50,000** per user per year depending on configuration.

## Table of Contents

- [The Product Is the Join, Not the Data](#the-product-is-the-join-not-the-data)
- [The SEC Already Assigned Everyone an ID](#the-sec-already-assigned-everyone-an-id)
- [Modular Pricing Means Nobody Knows the Price](#modular-pricing-means-nobody-knows-the-price)
- [What the Standardized Taxonomy Costs](#what-the-standardized-taxonomy-costs)
- [Working From the Filed Record Instead](#working-from-the-filed-record-instead)
- [Which Institution You Are](#which-institution-you-are)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Product Is the Join, Not the Data

Understanding this changes how the comparison should be framed.

A large asset manager runs dozens of data sources. Custodian holdings files, an order management system, a risk model, sell-side estimates, ESG scores, fixed income analytics, and internal research notes all describe the same securities using different identifiers, different entity hierarchies, and different conventions for corporate actions. Making them talk to each other is a permanent engineering problem, and getting it wrong produces reconciliation breaks that consume analyst time forever.

FactSet's entity master solves that. Map everything onto one ID and the joins hold. That capability is worth an enterprise contract in a way that any individual data field is not, and it explains why FactSet retains clients who complain about the price.

It also explains why "FactSet alternative" is a misleading search for most people who type it. An individual investor or a small fund does not have a concordance problem. They have one data source and a spreadsheet.

## The SEC Already Assigned Everyone an ID

Here is the part that rarely surfaces in a comparison, and it matters most for anyone whose universe is US public companies.

Every entity that files with the SEC receives a Central Index Key. It is permanent, it does not change when a company renames itself or changes ticker, it survives reincorporation, and it is the key every filing in EDGAR is stored under. It is also free and public.

For a US filings universe, the concordance problem is already solved by the regulator. Filings, insider transactions, institutional holdings, and registration documents are all keyed to the same identifier by design, because the SEC assigned it. There is no mapping layer to license, because there is nothing to map — a filing arrives already carrying its identity.

That is a narrower solution than a global entity master, and the narrowness is exactly the point. It does not resolve a Japanese subsidiary to its European parent, and it does not reconcile a custodian's internal security code. It does mean that anyone whose analysis lives inside the US filing universe is paying for a problem they do not have.

## Modular Pricing Means Nobody Knows the Price

FactSet's cost structure has the same property as other quote-only institutional platforms, and it produces the same information vacuum.

Because pricing varies by user type, content sets, analytics modules, delivery method, and contract length, there is no list price to publish. Third-party procurement trackers report widely varying figures — one commonly cited source lists workstation tiers around **$4,000**, **$12,000**, and **$30,000** per user per year while simultaneously presenting the same numbers as monthly rates elsewhere on its own page, which is a useful demonstration of how little weight these estimates carry.

The practical consequence is the same as with any modular enterprise contract. What you pay depends heavily on how precisely you scope the requirement before the conversation starts, and the modules you never open cost the same as the ones you live in. The [Capital IQ pricing](/blog/capital-iq-pricing-cost-explained) post covers the mechanics of quote-only pricing in more detail; the dynamics are close to identical.

## What the Standardized Taxonomy Costs

Every platform that compares companies across markets and accounting regimes has to map their reported line items into one template, and the trade is always the same.

Two distinct cash outflows can become one row because the template has one row where the filing has two. A single filed liability caption can be split into two so a component is separately trackable. Segment detail can be collapsed where a company reports across more segments than the template carries. A label can survive while its contents change, which is the version that costs the most, because the screen gives no signal that a decision was made.

For a global comp table across accounting standards, that mapping is not optional — it is the only way the comparison exists at all. For a single US company being modeled from its own filings, it is a layer to be undone, and undoing it requires knowing it happened.

That is the recurring boundary across this entire category. Standardization answers "how does this compare." Only the filing answers "what did this company report."

## Working From the Filed Record Instead

GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value. There is no entity resolution layer because the filings arrive keyed to the filer's own SEC identifier, and no mapping layer because the reported captions are kept intact.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years. [Custom Tables](/features#custom-tables) assemble specific reported items into a view. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Invested Capital](/metrics/calculated-values/invested-capital), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, so a metric can be audited against the numbers behind it. [Stock Screeners](/features#screener) run across the same layer, and [Insider Transactions](/features#insider-transactions) and [Institutional Ownership](/features#institutional-ownership) join to it on the quarterly cadence those filings actually have.

The scope stops where the SEC's does. No global coverage, no fixed income analytics, no risk models, no estimates, and no entity master — because none of that is required to answer what a US filer reported.

## Which Institution You Are

The decision is not about features and it is not really about price. It is about whether you have the problem the product was built to solve.

If you run multiple data sources that must reconcile, need global coverage across accounting regimes, depend on risk models and estimates alongside fundamentals, and have compliance requirements around data lineage at the firm level, FactSet is solving a genuine and expensive problem, and no filings archive substitutes for an entity master.

If your universe is US public companies and your work is reading what they filed, the concordance layer is overhead. You are buying a solution to a joining problem that the SEC handled for free when it issued the filer an identifier.

The [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) and [Bloomberg Terminal alternative](/blog/bloomberg-terminal-alternative-sec-data) posts run the same test against the other two institutional standards.

The most expensive thing in institutional data is not the seat. It is paying for a layer of abstraction that a smaller, narrower question never needed — and then having to reach back through it to find the number the company actually reported.

## Frequently Asked Questions

### What are the best FactSet alternatives?

It depends on which capability drives the contract. For global coverage, risk analytics, estimates, and entity resolution across multiple internal systems, the substitutes are other institutional platforms at comparable cost. For US public company fundamentals traced to the filing, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### How much does FactSet cost per user?

FactSet does not publish pricing. Cost is quoted based on user type, content sets, analytics modules, delivery method, and contract term. Third-party estimates commonly range from roughly **$12,000** to **$50,000** per user per year for full workstation access, and those estimates disagree with each other enough that any single figure should be treated as one firm's configuration rather than a market rate.

### What is a CIK and why does it matter?

A Central Index Key is the permanent identifier the SEC assigns to every filing entity. It does not change with a rename, a ticker change, or a reincorporation, and every filing in EDGAR is stored under it. For a US filings universe it functions as a free, universal identifier, which removes the entity-resolution problem that commercial symbology services exist to solve.

### Is FactSet data the same as SEC filing data?

It originates there for US companies, but it has been mapped into a standardized taxonomy so that companies across markets and accounting standards can be compared. That mapping can combine, split, or reclassify reported line items. The values are accurate as standardized figures while differing in classification from the captions in the filing.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=factset-alternative-sec-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- FactSet Concordance Service and Symbology product descriptions from FactSet's own marketplace and developer documentation, reviewed August 2, 2026.
- FactSet pricing structure (quote-based, varying by user type, content, modules, and term) from FactSet buyer guides; per-seat figures are third-party procurement estimates, not published vendor pricing.
- Central Index Key assignment and EDGAR filing storage conventions are SEC public record.

---

## Blog: Filing Data Study Methodology: How Our SEC Analysis Works
source: https://www.geminiq.com/blog/filing-data-study-methodology

### Filing Data Study Methodology: How Our SEC Analysis Works
The methodology behind every GeminIQ filing data study: how we measure post-filing stock returns across 17 years of SEC data, adjust for the base rate, and avoid the compounding and sample-size errors that make most earnings-reaction claims unreliable.

Every few weeks, a chart goes viral claiming that some pattern in earnings "predicts" what a stock does next. Almost none of them survive contact with the actual math. They compound returns that were never meant to be compounded, they compare a handful of cherry-picked quarters against nothing, and they call an association a prediction. The finding evaporates the moment anyone checks the baseline. This post is the methodology behind every GeminIQ filing data study — the fixed set of rules we apply before a single number goes into a post, so that when we tell you "quarters with X were followed by Y," the statement holds up. It exists for two reasons: so you can trust the studies, and so you can run the same checks yourself.

Every study in this series reads the same source: the as-filed 10-K and 10-Q filings in GeminIQ's database, going back **17 years**, joined to how each stock actually traded in the months after each filing hit SEC EDGAR. No normalized third-party feed sits in between. What follows are the five rules that govern how those filings become a finding.

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## Table of Contents

- [What a Filing Data Study Measures](#what-a-filing-data-study-measures)
- [The Numbers Are Cumulative — Never Compound Them](#the-numbers-are-cumulative)
- [Every Result Is Measured Against the Base Rate](#every-result-is-measured-against-the-base-rate)
- [Sample Size, Outliers, and Medians](#sample-size-outliers-and-medians)
- [Association, Not Prediction](#association-not-prediction)
- [Where the Data Comes From](#where-the-data-comes-from)
- [How to Run This Yourself](#how-to-run-this-yourself)

## What a Filing Data Study Measures

A filing data study asks a different question than a single-company teardown. A teardown audits one company's most recent filing. A study reads the whole shelf — thousands of filings across the market, or one company's entire filing history — to find a pattern that no single quarter reveals. The raw material is two things joined together: what a company reported in its filing, and what its stock did afterward.

The "afterward" comes from GeminIQ's [Earnings Market Reaction Heat Map](/features#price-variance), which records each stock's cumulative return over the months following a filing's filed date. A quarterly 10-Q carries the three months after filing; an annual 10-K carries the full twelve. That window is the spine of every study — the bridge between the number a company disclosed and the market's verdict on it.

<center><sup>GeminIQ Earnings Market Reaction Heat Map showing cumulative post-filing returns at the one-, two-, and three-month marks. Post-filing market reaction is measured from each filing's filed date on SEC EDGAR.</sup></center>

## The Numbers Are Cumulative — Never Compound Them

This is the single most common error in amateur earnings-reaction analysis, and it fabricates results out of thin air. The post-filing return figures are **cumulative** — each one already measures the total move from the filing date to that point. The three-month number is not the third month's return; it is the entire move across all three months, measured from the filing.

So you never multiply them together or add them up. If a stock is up 4% at month one and up 7% at month two, its second-month contribution is the difference — three points — not eleven. Compounding two cumulative figures double-counts the first month and inflates every result. When a study reports how a bucket of filings drifted over time, it plots the cumulative figures directly and derives any single month's move by subtraction. Getting this wrong is how a flat pattern gets turned into a "signal."

## Every Result Is Measured Against the Base Rate

Here is what the viral charts almost never show you: the baseline. The last **17 years** have been, on balance, a rising market. Pick any random basket of filings and the stocks mostly drifted up afterward, simply because most stocks drifted up in that period. "Stocks rose after companies did X" is therefore a meaningless sentence on its own. The only question that carries information is whether they rose *more or less than average*.

So every bucket in every study is reported against the universe base rate — the average post-filing drift across all filings over the same window — never against zero. If quarters with expanding margins were followed by a 5% three-month drift while the universe averaged 5%, that is not a finding; it is the market. If they were followed by 9% against a 5% baseline, now there is something to talk about. The base rate is what separates a real pattern from an artifact of the era.

## Sample Size, Outliers, and Medians

A pattern built on twenty filings is a story, not a study. Every bucket we draw a conclusion from clears a floor of roughly **200 filings**; below that, we either widen the definition or report the result as suggestive and say so plainly. A handful of quarters can look like anything.

Two more guards run on every study. We trim the most extreme **1%** of returns on each tail before averaging, because a single meme-stock quarter that ran up several hundred percent can single-handedly bend an average and manufacture a trend that describes one company, not a pattern. And we report the median alongside the mean, because when the two diverge sharply, the average is being carried by outliers and the median is the more honest center of the distribution.

## Association, Not Prediction

This is a discipline of language, and it is not optional. A study can establish that, historically, quarters exhibiting a certain characteristic were *followed by* a certain kind of move. It cannot establish that the characteristic *predicts* the move, *causes* it, or *signals* what any specific stock will do next. The past window is a record of what happened, not a forecast, and no filing data study on this site will ever tell you what a stock is going to do or what to do about it.

So the findings are always framed as association over the sample: "quarters with X were followed by Y." Never "X predicts Y." The distinction is the difference between reporting the historical record and pretending to see the future — and it is the line between analysis and a sales pitch dressed as analysis.

## Where the Data Comes From

The filing figures come straight from the XBRL-tagged 10-K and 10-Q filings on SEC EDGAR, surfaced through GeminIQ's [Financial Statements](/features#financial-statements) exactly as each company reported them. Nothing is normalized, re-templated, or reclassified on the way in. That matters for a study more than for anything else, because a study aggregates across thousands of companies — and if each of those numbers had been quietly reshaped by a third-party aggregator's house template, the pattern you found would be a pattern in the aggregator's decisions, not in what companies actually filed.

Insider and institutional signals, where a study uses them, come from SEC Form 4 and Form 13F. Both are **quarterly** by nature — they are not live or real-time feeds, and any study that leans on them treats them as periodic snapshots and pivots quickly back to the fundamentals. The market-reaction data is the post-filing price record described above. That is the entire input set: what was filed, and what happened next. No opinions, no estimates, no black box.

## How to Run This Yourself

The point of publishing the method is that none of it is proprietary magic — it is discipline applied to public data, and you can apply the same discipline to whatever you own. Pull any company's filing in [Financial Statements](/features#financial-statements) and read the line straight off the filing. Open the [Earnings Market Reaction Heat Map](/features#price-variance) to see how the stock actually traded after each of its filings, and remember the cumulative rule when you read those columns. Use the [Stock Screener](/features#screener) to define the characteristic you care about across the market, then always ask what the average filing did over the same window before you believe the pattern.

That last habit — comparing everything to the baseline — is the one that will save you from most of the bad charts on the internet. The filings are public and the price history is public. What a study adds is the refusal to let either one lie to you.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Financial Data Normalization: What It Is and Why It Matters
source: https://www.geminiq.com/blog/financial-data-normalization-explained

### Financial Data Normalization: What It Is and Why It Matters
Financial data normalization is the process third-party aggregators use to standardize SEC EDGAR filings into cross-company templates. This post explains the mechanics — what the mapping decisions are, why platforms rely on the process, and where it changes your data before you see it.

"Normalized" financial data sounds like a quality guarantee. The word suggests correction, cleanup, standardization toward something better. Most investors encounter it on financial research platforms and assume it means the data has been improved — errors corrected, filing quirks smoothed out, numbers made reliable.

That is not what normalization means.

Financial data normalization is the process by which third-party data providers translate company-specific SEC filing structures into generic, cross-company templates. It is not a cleaning process. It is a mapping process. The distinction matters because the two produce different outcomes: cleaning fixes genuine errors; mapping makes discretionary decisions about what counts as the same concept across thousands of different companies. Those decisions change the data — sometimes subtly, sometimes materially.

Understanding what normalization actually involves — what the decisions are, how they are made, and why they compound across platforms — is the first step toward knowing when to trust the number on your screen and when to verify the source.

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---

## Table of Contents

- [Why Normalization Exists: The Aggregator Business Model](#why-normalization-exists)
- [How Normalization Works: The Four Decision Types](#how-normalization-works)
- [The One-to-Many Problem](#the-one-to-many-problem)
- [Why Normalization Is Invisible](#why-normalization-is-invisible)
- [When Normalized Data Is Adequate — and When It Isn't](#when-normalized-data-is-adequate)
- [How GeminIQ Removes the Normalization Layer](#how-geminiq-removes-the-normalization-layer)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## Why Normalization Exists: The Aggregator Business Model

The aggregator layer in the financial data supply chain was built to stay invisible — and it has largely succeeded. The SEC requires every public company to file financial statements through EDGAR, and since 2009 those filings have come with XBRL tags: machine-readable identifiers that label every data point with its specific financial concept. Apple's revenue carries the tag `Revenues`. Its Vendor Non-Trade Receivables carries `NontradereceivablesCurrent`. Its operating income carries `OperatingIncomeLoss`. These tags are standardized, public, and maintained by the Financial Accounting Standards Board under the US GAAP taxonomy. The data is all there. The tags are all there. So why doesn't every financial platform pull directly from EDGAR?

The honest answer is scale and complexity. EDGAR publishes thousands of filings every week, each with its own structure, its own extension tags for company-specific line items, and its own XBRL idiosyncrasies. Parsing that volume into a reliable, queryable database is a significant technical undertaking. Most research platforms take the simpler path: license pre-processed data from third-party aggregators whose core business is exactly this.

These aggregators — the invisible middle layer in the financial data supply chain — ingest raw EDGAR filings and map every line item into a standardized template schema. The schema is proprietary, maintained by the aggregator, and designed for one primary purpose: cross-company comparability. If Apple's balance sheet and Microsoft's balance sheet both map to the same template rows, a platform can display them side by side, screen across them simultaneously, and compare them automatically — without any per-company configuration. That is the value proposition. Comparability at scale. And normalization is how they achieve it.

The problem is not that the product is useless — for broad market scanning across thousands of companies, normalized data serves its intended purpose. The problem is that achieving comparability requires making mapping decisions that no individual company's filing was designed to accommodate. Those decisions change the data.

---

## How Normalization Works: The Four Decision Types

When an aggregator processes a filing, every line item in the financial statements faces a mapping decision. The aggregator's template has a finite number of rows — standardized concepts like "Short-Term Debt," "Total Revenue," "Other Non-Current Liabilities" — and every line item in the filing has to land in one of them. That assignment is the core of normalization. There are four types of decisions made in that process, and each carries a different risk profile for the analyst on the receiving end.

### Decision Type 1: Consolidation

The most common normalization decision. Two or more XBRL-tagged line items from the filing are merged into a single template row because the template does not have separate slots for each.

[Apple's](/stocks/AAPL) balance sheet illustrates this precisely. Apple reports its debt as three distinct instruments: Commercial Paper, current Term Debt (the portion of long-term notes due within 12 months), and non-current Term Debt (fixed-rate bonds stretching as far as 2062). Each carries its own XBRL tag because each represents a fundamentally different type of obligation with different maturity profiles, rate structures, and refinancing risk. A standard aggregator template typically offers two slots — "Short-Term Debt" and "Long-Term Debt." The three instruments become two. The analytical distinction between continuously-rolling commercial paper and fixed-maturity bonds disappears.

The arithmetic survives consolidation — the values add up correctly. What is lost is the granularity that makes the arithmetic analytically useful.

### Decision Type 2: Absorption

More consequential than consolidation. A line item unique to the company — one for which the company created a XBRL extension tag to describe precisely — gets reclassified into a generic bucket and loses its identity as a separate entry.

[Apple's](/stocks/AAPL) **$33.2 billion** Vendor Non-Trade Receivables is the most documented case in public markets. These are receivables from Apple's contract manufacturers — components Apple has paid for that remain in the hands of supply chain partners, monetized as those partners sell finished products. The line item carries the extension tag `NontradereceivablesCurrent` because no standard US GAAP taxonomy concept covers it precisely. On a normalized platform, it is often absorbed into "Other Current Assets." The **$33.2 billion** doesn't disappear from the total — it reappears inside a larger aggregate — but its identity as a supply-chain-specific asset category is gone. Analysts using the platform to model Apple's working capital dynamics are working from a different picture than analysts reading the actual 10-K.

### Decision Type 3: Label-Preserving Reclassification

The most analytically dangerous normalization decision. The aggregator changes the value under a line item while preserving the original label — producing a number that reads like the filing but isn't.

The documented example from Apple's FY2025 annual report: "Other Non-Current Liabilities" is reported at **$41,549 million** in the filing. One widely-used normalized platform displays **$29,946 million** under the same label — an **$11.6 billion** difference — because the aggregator subtracted capital lease obligations from the line while keeping the label unchanged. For a complete breakdown of this and related documented discrepancies, see [Third-Party Financial Data Problems: What Gets Lost Before It Reaches You](/blog/third-party-financial-data-problems). An analyst comparing the platform against the 10-K finds the same words over two different numbers, with no explanation. The label matches. The values don't. The only mechanism to detect it is to independently pull the XBRL-tagged value from EDGAR and compare — and most analysts never do, because the label gives them no reason to suspect a discrepancy exists.

### Decision Type 4: Extension Tag Mapping

Companies use XBRL extension tags for line items that don't fit the standard US GAAP taxonomy. Every company with unusual assets, proprietary instruments, or non-standard working capital items creates extension tags to describe them with precision. When aggregators encounter these tags, they face a choice: map the extension to the nearest standard concept, or absorb it into a generic bucket.

Mapping to the nearest standard concept can be accurate when the extension closely resembles an existing taxonomy item. It can also lose precision when the extension was created precisely because the standard taxonomy lacked an adequate term. Absorbing into a generic bucket preserves the aggregate math but eliminates the individual item's analytical identity. Either way, the aggregator makes a judgment call that is not documented in the output. The analyst receives a number. The decision that shaped it is nowhere in the output.

---

## The One-to-Many Problem

Most investors who find a discrepancy between a platform's displayed value and the original filing assume the error originated on that platform. It usually didn't.

The aggregator layer sits upstream of every retail research platform that licenses its data. When an aggregator makes a normalization decision — merging three debt instruments into two, absorbing Vendor Non-Trade Receivables into Other Current Assets, subtracting capital leases from Other Non-Current Liabilities while keeping the label — that single decision propagates simultaneously to every platform licensing the same aggregator's output. Two platforms using the same data source will display the same reclassification, for the same company, at the same time, regardless of which platform the analyst is using.

This has a specific and underappreciated consequence for cross-platform verification. Many investors try to validate a data point by checking it on a second research tool. But cross-checking across two normalized platforms does not verify accuracy. It confirms only that both platforms received the same processed data from the same upstream source. The discrepancy between the normalized value and the as-filed value does not surface in that comparison — it only surfaces when one of the two comparators is the original SEC filing.

The one-to-many structure also creates a risk for historical analysis. When an aggregator revises its taxonomy and applies the update historically, strategy signals shift without any underlying corporate event — a regime change in the data, not the companies. For a stage-by-stage look at how this pipeline operates from EDGAR to investor screen, see [How Financial Data Reaches Investors and What Gets Lost Along the Way](/blog/how-financial-data-reaches-investors). As-filed XBRL data doesn't carry this risk: the filing doesn't change after it is submitted to the SEC. Normalization does.

---

## Why Normalization Is Invisible

Normalization would be far less analytically dangerous if it were visible. If a platform showed "Other Non-Current Liabilities (capital leases excluded): **$29,946M**," a careful analyst would know to check. No platform does this, and there are structural reasons why.

The first mechanism is XBRL tag replacement. When an aggregator normalizes a filing, the SEC's XBRL tags — which link every data point back to its verifiable identity in the filing — are replaced with the aggregator's proprietary identifiers. `OtherLiabilitiesNoncurrent` becomes the aggregator's internal code for its "Other Non-Current Liabilities" template row. The verifiable link between the displayed number and the original filing concept is severed. Even if an analyst wants to trace the number back, the trail ends at the aggregator's proprietary taxonomy — not the SEC filing. For a full explanation of how XBRL tags work and what their loss means for data traceability, see [What Is XBRL? How SEC Tagging Affects Your Investment Data](/blog/what-is-xbrl).

The second mechanism is label preservation. As illustrated in Decision Type 3, aggregators routinely retain the original label while changing the underlying value. This is the condition that makes discrepancies functionally undetectable without a direct filing comparison: the same terminology appears in both places, giving no visual signal that any adjustment occurred between the filing and the platform display.

The third mechanism is aggregator non-disclosure. Most retail research platforms do not identify which aggregator supplied their underlying data. The aggregator's normalization decisions — which template rows each filing maps into, how extension tags were handled, what subtraction was applied to which line item — are not documented in the platform's output. An analyst using the platform has no mechanism to determine which normalization decisions were applied to the specific company and period they are analyzing.

The adjustment is there. The mechanism that produced it is not.

---

## When Normalized Data Is Adequate — and When It Isn't

Normalization has a legitimate use case. Dismissing it entirely would misrepresent the real boundary between where it works and where it fails.

For broad initial screening, normalized data is adequate. Filtering thousands of companies to find candidates with revenue growth above **20%**, operating margins above **15%**, or [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) above **10%** — the normalized values will surface approximately the right candidates. Approximation is acceptable when the goal is ranking companies relative to each other, not verifying any individual figure against a filing. The same companies that rank highest in the normalized dataset will generally rank highest in the as-filed dataset, because systematic approximations affect comparisons less than they affect absolutes.

The precision requirement changes the moment you move from screening to analysis. Four specific workflows are where the gap between normalized and as-filed data becomes analytically consequential.

Financial modeling is the first. A model built on normalized inputs inherits the normalization decisions at the line-item level. If the balance sheet has absorbed Apple's **$33.2 billion** Vendor Non-Trade Receivables into Other Current Assets, the working capital calculation inherits that reclassification. If the debt structure merged three instruments into two, the refinancing risk section inherits that merge. Every metric the model derives — [Free Cash Flow](/metrics/calculated-values/free-cash-flow), Net Debt, interest coverage — carries the same inherited imprecision, compounded across every calculation that builds on the base inputs.

Quantitative backtesting is the second. When an aggregator revises its taxonomy and applies the update historically, strategy signals shift without any underlying corporate event. The dataset changes. The strategy doesn't know why.

Analysis of structurally unusual companies is the third. Companies with conventional reporting structures lose relatively little in normalization because the aggregator template was designed with them in mind. Companies with company-specific reporting structures, non-standard instruments, or proprietary asset categories — the companies where information advantage is typically highest — lose the most. Normalization strips the most information from precisely the companies where that information creates the greatest analytical edge.

Filing verification is the fourth. Auditing a platform's numbers against the source filing before committing capital is basic risk management. But if labels have been preserved while values changed, the comparison doesn't produce a clean match. Without knowing normalization occurred, the discrepancy looks like a filing error. It isn't — and that confusion is the most expensive outcome of all.

---

## How GeminIQ Removes the Normalization Layer

GeminIQ doesn't route financial data through an aggregator. The pipeline runs from SEC EDGAR directly to the platform, with every XBRL tag preserved at every step. There is no aggregator template, no proprietary taxonomy, no mapping decisions of the four types described above.

The practical consequence is that the number displayed on GeminIQ for any line item is the number the company filed with the SEC, carrying the tag the SEC assigned, traceable to the original EDGAR document. [Apple's](/stocks/AAPL) Other Non-Current Liabilities shows **$41,549 million** because the capital leases were never subtracted. The Vendor Non-Trade Receivables appears as its own line item at **$33.2 billion** because the `NontradereceivablesCurrent` extension tag was preserved. The three debt instruments remain three debt instruments, because that is how Apple reported them.

GeminIQ's [Calculated Metrics](/features#calculated-metrics) — including ROIC, Free Cash Flow, and 90+ other financial KPIs — are computed directly from this XBRL-tagged source data. Every metric inherits the precision of the underlying filing rather than the approximations of a normalization template. The [Financial Statements](/features#financial-statements) display each data point alongside its XBRL tag, so you can copy the tag, search it on EDGAR, and verify the match in under 30 seconds. That traceability is what the normalization process removes — and what sourcing directly from EDGAR restores.

---

## Frequently Asked Questions

### What is financial data normalization?

Financial data normalization is the process by which third-party data providers convert company-specific SEC filing line items into standardized, cross-company templates. Rather than presenting data in the structure the company chose to file, a normalized platform maps every line item into a proprietary schema designed for comparability across thousands of companies. The process involves four types of decisions: consolidating multiple line items into one template row, absorbing company-specific items into generic categories, reclassifying values while preserving original labels, and mapping XBRL extension tags to the nearest standard concept. Each decision type introduces a different form of information loss.

### Is normalized financial data always inaccurate?

Not always, and not for every use case. For broad market screening — comparing hundreds of companies on general metrics and ranking them relative to each other — normalized data is often adequate. The approximations introduced by normalization don't typically change which candidates surface at the top of a scan. The problems emerge when precision is required: building financial models from filing-matching inputs, backtesting quantitative strategies on historical data, auditing a specific figure against the source filing, or analyzing companies with unusual reporting structures. For those workflows, the gap between normalized and as-filed data is analytically consequential.

### Why do normalized platforms keep the same label when the value changes?

Aggregators design their templates for the most common case. Most of the time, a line item labeled "Other Non-Current Liabilities" on the platform maps cleanly to the same label in the filing. The label-value mismatch cases — where a platform keeps a filing label while applying a value that reflects a subtraction or reclassification — arise from edge-case handling. The aggregator may subtract capital lease obligations from a liability line to make balance sheets more comparable across companies with different lease accounting treatments. The platform inherits that decision, displays it under the original label, and has no mechanism to flag it because the adjustment is intentional from the aggregator's perspective. For a step-by-step workflow to detect these discrepancies yourself, see [How to Verify Financial Data Against an SEC Filing](/blog/verify-financial-data-against-sec-filing).

### Why do two different platforms sometimes show the same incorrect value?

Because they often source data from the same aggregator. The normalization decisions that produce a discrepancy are made upstream at the aggregator level — not by the individual platforms. When two platforms license from the same aggregator, they inherit identical mapping decisions simultaneously. Cross-checking a figure across two normalized platforms does not verify accuracy; it confirms only that both platforms received the same processed output. The verification that matters compares the displayed value against the original filing, not against a second platform.

### What is the difference between normalized data and as-filed data?

As-filed data is the exact output the company submitted to the SEC, presented in the structure the company chose, with the XBRL tags the SEC mandated. Every label, every line item, and every value is identical to the source document. Normalized data has been processed by an aggregator: line items are mapped into a standardized template, XBRL tags are replaced with proprietary identifiers, and some values differ from the filing due to consolidation or reclassification decisions. The difference is not always material, but it is always present — and it is never disclosed by the platform displaying the result.

### Does normalization affect historical data?

It can, and this is one of the least-discussed risks of aggregator-sourced data. When aggregators update their template schemas, those revisions are often applied retroactively across their full historical database. A line item that was mapped one way for the past five years may be mapped differently after a schema update — with no indication that the change occurred. For quantitative investors backtesting on historical financial data, this is a structural reliability problem: the dataset can shift under a running strategy without any corporate action triggering the change.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Section 9b: 50 Financial Metrics
source: https://www.geminiq.com/blog/financial-metrics-value-investors

### Financial Metrics for Value Investors: A Lululemon Case Study
Financial metrics for value investors work best as a sequence, not a checklist. This post walks through that workflow applied step by step to Lululemon's (LULU) Q1 FY2026 10-Q, with the formula and benchmark behind each metric.

**Most lists of "financial metrics every investor should know" are alphabetized junk drawers — ROIC next to dividend yield next to current ratio, with no indication of which one to check first or what a bad number actually means in context.** A real research process does not move alphabetically. It moves in a sequence: confirm the business is good before asking if it's cheap, confirm the cash is real before trusting the earnings, and confirm the balance sheet can survive a bad year before getting attached to the growth story. This post follows that sequence end to end on a stock currently splitting the value investing community down the middle: [Lululemon](/stocks/LULU) ($LULU), which filed its **Q1 Fiscal 2026 10-Q on June 4, 2026, for the quarter ended May 3, 2026**, with the stock down roughly **50%** over the trailing year. Every figure below traces to that filing.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=financial-metrics-value-investors)**

## Table of Contents
- [Step 1: Confirm the Business Is Actually Good](#step-1-confirm-the-business-is-actually-good)
- [Step 2: Follow the Cash, Not the Earnings](#step-2-follow-the-cash-not-the-earnings)
- [Step 3: Stress-Test the Balance Sheet](#step-3-stress-test-the-balance-sheet)
- [Step 4: Confirm the Growth Is Real](#step-4-confirm-the-growth-is-real)
- [Step 5: Determine Whether the Price Reflects the Business](#step-5-determine-whether-the-price-reflects-the-business)
- [Step 6: Check Operational Efficiency](#step-6-check-operational-efficiency)
- [Step 7: Check What Insiders and Institutions Are Doing](#step-7-check-what-insiders-and-institutions-are-doing)
- [Step 8: Verify Every Number Against the Filing](#step-8-verify-every-number-against-the-filing)
- [FAQ](#faq)

---

## Step 1: Confirm the Business Is Actually Good

A cheap stock attached to a mediocre business is not a value opportunity — it is a value trap with better marketing. Before any valuation work, the first metric to check is GeminIQ's pre-calculated [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital), which measures how many cents of after-tax operating profit a company generates for every dollar of capital — debt and equity combined — invested in the business. A ROIC consistently above **15%** is strong; above **25%** is exceptional.

[Lululemon's](/stocks/LULU) ROIC TTM, pulled directly from its Q1 FY2026 10-Q, sits at **42.94%** — far beyond the exceptional threshold, built on a **55.70%** [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) TTM and an **18.29%** [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) TTM. [Return on Equity (ROE)](/metrics/returns-and-profitability/return-on-equity) runs at **32.03% TTM**. The direction is where the real information sits: ROIC has compressed from **74.60%** at the January 2025 fiscal year end to **42.94%** now, with gross margin easing from **59.22%** to **55.70%** across the same six quarters. That is a business normalizing off an extraordinary peak, not one breaking down — a company destroying value does not post 42%+ returns on capital while it's allegedly falling apart.

ROIC is built from two further GeminIQ-calculated inputs: [Net Operating Profit After Tax (NOPAT)](/metrics/returns-and-profitability/net-operating-profit-after-tax), which comes to **$1.44 Billion TTM** for Lululemon, and [Invested Capital](/metrics/calculated-values/invested-capital), averaging **$3.36 Billion** over the trailing period. A standard screener stops at the headline stock chart. Pulling the raw income statement and balance sheet through GeminIQ's [Calculated Metrics](/features#calculated-metrics) is what separates a declining stock price from a declining business — and on this filing, those are two different things.

<center><sup>GeminIQ Calculated Metrics showing Lululemon's Return on Invested Capital (ROIC) at 42.94% TTM and Return on Equity (ROE) at 32.03% TTM, against a 55.70% Gross Profit Margin TTM, sourced from the Q1 FY2026 10-Q.</sup></center>

---

## Step 2: Follow the Cash, Not the Earnings

Net income is an opinion; cash is a fact. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) — operating cash flow minus capital expenditures — is harder to manage than an accrual-based earnings figure. [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield), which expresses FCF as a percentage of market capitalization, answers the valuation question directly. Above **5%** is generally attractive.

[Lululemon's](/stocks/LULU) Free Cash Flow runs to **$1.28 Billion TTM**, putting Free Cash Flow Yield at **8.05%** — above the attractive threshold despite the depressed share price, because the cash generation hasn't fallen nearly as far as the stock has. On a per-share basis, that's **Free Cash Flow Per Share** of **$11.09 TTM** and **Operating Cash Flow Per Share** of **$16.77 TTM** — the cash generation holds up at the per-share level, which is the level that actually matters to a shareholder.

[Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) is worth checking at this stage for any company, since SBC add-backs can flatter operating cash flow at capital-light tech businesses where it runs into the double digits as a percentage of revenue. For [Lululemon](/stocks/LULU), it isn't a story: [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) totals **$71.99 Million TTM**, just **0.64%** of revenue — the cash flow figure here is close to clean.

Free cash flow tells the story net income is structurally unable to tell.

---

## Step 3: Stress-Test the Balance Sheet

A great income statement does not matter if the company cannot survive its own balance sheet. [Current Ratio](/metrics/liquidity-ratios/current-ratio), [Quick Ratio (Acid-Test Ratio)](/metrics/liquidity-ratios/quick-ratio), and [Cash Ratio](/metrics/liquidity-ratios/cash-ratio) test short-term liquidity at progressively stricter levels. [Lululemon](/stocks/LULU) posts a **2.23x Current Ratio**, a **1.17x Quick Ratio**, and a **0.84x Cash Ratio** — current assets cover current liabilities more than twice over, and that holds even stripping out inventory entirely.

Leverage is where the as-filed data diverges hardest from the screener version. Lululemon carries **$0** in interest-bearing debt. [Net Debt](/metrics/calculated-values/net-debt) is therefore negative — **$1.51 Billion** of cash against no borrowings — which puts [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) at **-0.59x**, a net cash position rather than a leverage ratio. The **$2.14 Billion** that most sources report as Lululemon's debt is operating lease liabilities under ASC 842, split **$357.2 Million** current and **$1.78 Billion** non-current, and leases are not notes. GeminIQ's [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) of **0.77x** measures total liabilities against total equity, which is why it reads as leverage on a company that has none. The same fact explains why [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) returns nothing here: reported interest expense TTM is **$0**, and a ratio built around interest expense breaks when a company's debt doesn't generate any.

For a single composite read on bankruptcy risk, GeminIQ's pre-calculated [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) comes in at **5.70** — well clear of the **2.99** safe-zone threshold. A stock down **50%** is not, on this balance sheet, a distress situation.

<center><sup>GeminIQ Calculated Metrics showing Lululemon's Current Ratio (2.23x), Debt-to-Equity Ratio (0.77x), and Altman Z-Score (5.70) from the Q1 FY2026 10-Q — a balance sheet sitting well inside the safe zone despite the stock's decline.</sup></center>

---

## Step 4: Confirm the Growth Is Real

A business can look cheap on trailing earnings and still be a poor investment if it's shrinking. [Revenue Growth](/metrics/growth-metrics/revenue-growth), [Earnings Per Share Growth](/metrics/growth-metrics/earnings-per-share-growth), and [Net Income Growth](/metrics/growth-metrics/net-income-growth) checked across **1-year, 3-year, and 5-year** windows tell a more complete story than any single year.

[Lululemon's](/stocks/LULU) 1-year Revenue Growth is **4.22%** — still positive, but a sharp deceleration from its **31.84%** 3-year and **125.13%** 5-year growth rates. EPS Growth tells the sharper version of the same story: **-15.61%** over 1 year against **68.48%** over 3 years. [Net Income Growth](/metrics/growth-metrics/net-income-growth) is down **19.26%** over the trailing year, and [Net Profit Margin Growth](/metrics/growth-metrics/net-profit-margin-growth) is down **22.53%** — margin compression, not just a revenue slowdown, is what's actually driving the earnings decline. This is the one section where the bearish narrative is grounded in real numbers, not just sentiment: growth has decelerated and margins have compressed in the data, not just in the coverage.

[Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth) is a metric worth checking for subscription and prepaid-revenue businesses, but it doesn't apply here — Lululemon is a retailer with no meaningful deferred revenue balance, a reminder that not every metric in this workflow belongs in every analysis.

A real deceleration is not the same thing as a broken business. But it is the legitimate part of the bear case — which is exactly why quality (Step 1) and balance sheet survival (Step 3) carry more weight here than they would for a company simply growing more slowly from a position of strength.

---

## Step 5: Determine Whether the Price Reflects the Business

Only after quality, cash, balance sheet risk, and growth have been checked does the valuation question mean anything. [Price-to-Earnings Ratio (P/E)](/metrics/valuation-metrics/price-to-earnings-ratio) for [Lululemon](/stocks/LULU) sits at **10.89x TTM** — against a **42.94% ROIC** and a **32.03% ROE**, that's a quality business priced like a mediocre one.

[EV/EBITDA](/metrics/valuation-metrics/ev-ebitda) comes in at **5.60x**, and [EV/EBIT](/metrics/valuation-metrics/ev-ebit) at **7.02x** — both well inside the **8x** value-territory threshold, against an S&P 500 median running roughly **12x to 14x**. A full breakdown of when to lean on which multiple is covered in [EV/EBITDA vs. P/E: Which Multiple to Use](/blog/ev-ebitda-vs-pe-ratio-explained). [Price-to-Book Ratio (P/B)](/metrics/valuation-metrics/price-to-book-ratio) is **3.29x**, [Price-to-Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) is **1.42x**, and [Price-to-Cash-Flow Ratio](/metrics/valuation-metrics/price-to-cash-flow-ratio) is **8.21x** — every multiple in this section is measuring the same gap between price and business quality from a different angle. [Market Capitalization](/metrics/valuation-metrics/market-capitalization) stands at **$15.89 Billion** against an [Enterprise Value](/metrics/valuation-metrics/enterprise-value) of **$14.38 Billion** — enterprise value sits *below* market cap, because the net cash comes out rather than debt going in.

What's notable is the *path* the price took to get this cheap. GeminIQ's [Price Variance](/features#price-variance) tracker shows that after Lululemon's FY2025 10-K (filed March 17, 2026), the stock actually rose **2.88%** in the first month — then fell **17.64%** by month two and **28.28%** by month three. The steepest part of the decline happened well after the filing data was already public, which means a large share of the move was sentiment catching down to a re-rated narrative, not new fundamental information arriving in the interim.

No single valuation multiple settles the question, but four of them pointing the same direction is harder to dismiss than one.

---

## Step 6: Check Operational Efficiency

This is the section where Lululemon's own filing data confirms part of the bear case instead of refuting it. Operational efficiency metrics matter most for retailers, manufacturers, and distributors — businesses where management's handling of inventory and working capital doesn't show up in a margin figure at all. [Asset Turnover](/metrics/efficiency-and-turnover-ratios/asset-turnover) runs **1.40x TTM** and [Inventory Turnover](/metrics/efficiency-and-turnover-ratios/inventory-turnover) **2.97x TTM** — both unremarkable on their own, but the components beneath inventory turnover are where the real signal sits.

The number that stands out is [Days Inventory Outstanding](/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding): **122.77 days TTM** — inventory is sitting for roughly four months before it sells, which lines up directly with the heavier markdown activity and promotional discounting management has cited as a margin headwind. [Days Sales Outstanding](/metrics/efficiency-and-turnover-ratios/days-sales-outstanding) is just **4.99 days**, reflecting a retailer collecting cash at the point of sale, but [Days Payables Outstanding](/metrics/efficiency-and-turnover-ratios/days-payables-outstanding) of only **22.00 days** doesn't offset the slow inventory turn. Combined, GeminIQ's pre-calculated [Cash Conversion Cycle (CCC)](/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle) comes to **105.76 days TTM** — a meaningfully long stretch between paying for inventory and collecting cash from the sale.

This is the metric that confirms a real operational problem, not just a sentiment problem — and the workflow is just as useful for surfacing the legitimate part of a bear case as it is for refuting the exaggerated parts.

<center><sup>GeminIQ Calculated Metrics showing Lululemon's Cash Conversion Cycle (CCC) at 105.76 days TTM, driven primarily by Days Inventory Outstanding of 122.77 days — the balance sheet confirmation of the markdown and inventory pressure described in the Q1 FY2026 10-Q.</sup></center>

---

## Step 7: Check What Insiders and Institutions Are Doing

What are the people actually running the company doing with their own money? GeminIQ's [Insider Transactions](/features#insider-transactions) feature pulls every SEC Form 4 filing directly. For [Lululemon](/stocks/LULU), the honest read is mixed, not a clean signal in either direction: insider activity over the trailing 12 months shows **5 sales totaling roughly $9.91 Million** against **3 purchases totaling $1.99 Million**. The sales skew routine and compensation-related, and one line dominates the total: a **$6.38 Million** CEO disposal in June 2025, which alone is **64%** of the sold value. The purchases are the more interesting side. A director bought **6,090 shares at $164.20** on March 20, 2026, then bought **4,275 more at $117.05** on June 15 — averaging down into the decline with his own money — while the incoming Interim Co-CEO bought **3,275 shares at $151.02** on April 1. Form 4 data is filed per transaction rather than continuously, so this is a record of what has already happened, not a live feed.

On the institutional side, GeminIQ's [Institutional Ownership](/features#institutional-ownership) tracker shows the same lack of a clean signal: institutional ownership has fallen from **79.85%** in March 2025 to **71.39%** in March 2026, touching a low of **69.62%** in September 2025 before recovering to **72.72%** by December. That is net institutional reduction across the year, but the trough is behind it rather than ahead of it. A standard aggregator reports only the current percentage; the quarterly time series is what separates "institutions are still selling" from "institutions sold, then stopped" — and 13F data is quarterly and lagged, so it dates the reduction rather than tracking it in real time.

This step doesn't always produce a clean verdict, and Lululemon right now is the case in point — which is itself useful information, because a workflow that only ever confirms the bull case isn't actually checking anything.

<center><sup>GeminIQ Insider Transactions (SEC Form 4) for Lululemon, showing 5 sales totaling $9.91 Million against 3 purchases totaling $1.99 Million over the trailing 12 months, including a director purchase of 6,090 shares at $164.20 and a further 4,275 shares at $117.05.</sup></center>

<center><sup>GeminIQ Institutional Ownership tracker (SEC Form 13F) for Lululemon, showing ownership falling from 79.85% (March 2025) to a 69.62% low (September 2025) before recovering to 72.72% (December 2025) and settling at 71.39% (March 2026).</sup></center>

---

## Step 8: Verify Every Number Against the Filing

Every metric in this workflow is only as reliable as the data feeding it. Most financial platforms pull from third-party aggregators that normalize, smooth, or reclassify line items before a number ever reaches the screen. The fix isn't a better metric. It's a better source.

Every figure in Steps 1 through 7 above traces to a single document: [lululemon athletica inc.'s](/stocks/LULU) Q1 Fiscal 2026 10-Q, filed June 4, 2026, for the period ended May 3, 2026. GeminIQ's [Financial Statements](/features#financial-statements) feature pulls that filing's Income Statement, Balance Sheet, and Cash Flow Statement directly from its XBRL tags on SEC EDGAR, and [Custom Tables](/features#custom-tables) makes it possible to rebuild any of the comparisons above from the raw line items rather than taking a calculated metric on faith.

A workflow is only as good as the willingness to check it against the source. That's the step most research skips — and the one that actually separates a checklist from an audit.

---

## FAQ

### Do value investors need to check every metric in this list for every stock?

No. The order matters more than the completeness. Quality (Step 1) and balance sheet risk (Step 3) are close to non-negotiable for any company, while operational efficiency (Step 6) is largely irrelevant for asset-light businesses and deferred revenue growth only applies to subscription or prepaid-revenue models — it didn't apply to Lululemon at all in the walkthrough above. Skip what doesn't fit the business model rather than forcing every metric into every analysis.

### Which single financial metric matters most for value investors?

There isn't one, but [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) comes closest to a starting point, because it measures business quality independent of capital structure and valuation. A cheap stock attached to a low-ROIC business is rarely a genuine value opportunity — it's usually a value trap that happens to also be cheap.

### Why do the same financial metrics show different values on different platforms?

Differences usually come down to methodology rather than data errors — how invested capital is defined, whether a fixed or actual effective tax rate is used for NOPAT, how EBITDA is reconstructed when it isn't reported directly, or whether non-recurring items are stripped out before a ratio is calculated. GeminIQ uses as-filed figures from SEC XBRL tags and discloses the exact formula behind every calculated metric — the only way to know which version of a number you're actually looking at.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=financial-metrics-value-investors)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference lululemon athletica inc.'s Q1 FY2026 10-Q (filed June 4, 2026, period ending May 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001397187/000139718726000078/lulu-20260503.htm).

---

## Blog: Finbox Alternative: As-Filed Fundamental Data
source: https://www.geminiq.com/blog/finbox-alternative-sec-data

### Finbox Alternative: As-Filed Fundamental Data
A Finbox alternative for investors who build their own models. Finbox's DCF and fair value models run on standardized S&P Global data with consensus-estimate defaults; this post explains what a model inherits before you change a single assumption.

Finbox solved a real problem. Building a discounted cash flow model from scratch is slow, error-prone, and the part most investors skip — so Finbox prebuilt them. Discounted cash flow, dividend discount, earnings power value, comparable company analysis, each with a guided assumption builder, each exportable to Excel or Google Sheets with formulas intact, across more than 100,000 stocks and 1,000-plus metrics, starting around **$10** a month billed annually for US coverage.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=finbox-alternative-sec-data)**

At that price the platform is difficult to argue with on value. The argument worth having is about what a prebuilt model inherits before you touch it.

Finbox states that it partners with S&P Global Market Intelligence for its underlying data, and its documentation describes model default assumptions as being based on consensus analyst estimates where available. Both are sensible engineering decisions. Both also mean a Finbox DCF arrives carrying two sets of judgments that were made by someone else: how the filing was mapped into the dataset, and what the future is expected to look like.

## Table of Contents

- [A Model Is Downstream of Two Decisions](#a-model-is-downstream-of-two-decisions)
- [Inherited Inputs: What Standardization Does to a Line Item](#inherited-inputs-what-standardization-does-to-a-line-item)
- [Inherited Assumptions: A Consensus DCF Is a Consensus View](#inherited-assumptions-a-consensus-dcf-is-a-consensus-view)
- [Why Fair Value Estimates Cluster](#why-fair-value-estimates-cluster)
- [Building From Filed Inputs Instead](#building-from-filed-inputs-instead)
- [When Prebuilt Is the Right Answer](#when-prebuilt-is-the-right-answer)
- [Frequently Asked Questions](#frequently-asked-questions)

## A Model Is Downstream of Two Decisions

Any valuation model has two halves: what happened, and what happens next.

The historical half comes from the financial statements — revenue, margins, capital intensity, working capital behavior, the reinvestment the business actually requires. The forward half comes from assumptions about growth, margin trajectory, terminal value, and discount rate.

A prebuilt model hands you both halves pre-populated. That is the feature. It is also the exposure, because the pre-population is where the analysis quietly gets made. By the time you open the assumption builder and adjust a growth rate, the historical base you are growing from was set by a standardization layer, and the number you are adjusting away from was set by consensus.

Changing an assumption feels like taking control. It is taking control of one of four or five inputs, from a starting point you did not choose.

## Inherited Inputs: What Standardization Does to a Line Item

The historical half is the half nobody audits, because it looks like fact rather than judgment.

Standardized fundamentals are the product of mapping each company's reported line items into a comparable template, and that mapping has recognizable shapes. Two distinct cash outflows can become one row because the template has one row where the filing has two. A single filed liability caption can be split into two so a component is separately trackable. Segment detail can be collapsed when a company reports across more segments than the template carries. And a label can survive while its contents change, which is the version that costs the most, because the screen gives no signal that a decision was made.

Every one of those is defensible for cross-company comparison. Each one also lands somewhere specific in a model.

Capital expenditure classification moves free cash flow. Lease treatment moves net debt and therefore equity value. Where a compensation-related cash outflow sits determines whether it reduces the cash available to shareholders in your model or sits in a financing line you ignored. [Invested Capital](/metrics/calculated-values/invested-capital) moves with balance sheet classification, and [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) moves with it — which is a problem, because ROIC is usually what justifies the growth assumption in the first place.

A model built on mapped inputs is not wrong. It is a model whose foundation you cannot inspect.

## Inherited Assumptions: A Consensus DCF Is a Consensus View

The forward half carries a different problem, and it is the more interesting one.

When default assumptions are drawn from consensus analyst estimates, the model's starting output is, by construction, an expression of what the sell side already expects. Run it unmodified and the fair value it prints is roughly what the market has already priced, because consensus is what the market is pricing.

That is fine as a reference point and useless as an edge. The entire premise of a discounted cash flow is that your view of the future differs from the price. A DCF seeded with consensus and left alone answers a question nobody needed answered.

The subtler risk is anchoring. A number you start from exerts pull. An investor who opens a model showing a fair value and then adjusts assumptions is doing something psychologically different from an investor who builds the forecast before seeing an output. The first process tends to produce assumptions that justify a number. The second produces a number from assumptions.

Prebuilt models optimize for the first, because that is what makes them fast.

## Why Fair Value Estimates Cluster

There is an observable consequence of all of this, and it explains something investors notice without quite naming.

When multiple platforms license fundamentals from the same standardization layer and seed their models from the same consensus estimates, their fair value outputs converge. The interfaces differ. The methodology pages differ. The numbers land close together, because the inputs are shared.

Convergence gets mistaken for confirmation. Three platforms agreeing on a fair value feels like corroboration, and it is not — it is one dataset and one set of expectations, displayed three times. Independent verification requires a different starting point, not a different presentation of the same one.

That is the case for going back to the filing. Not because the filing produces a better fair value estimate, but because it is the only input that is not shared with everyone else running the same model.

## Building From Filed Inputs Instead

GeminIQ does not ship prebuilt valuation models, and that omission is the point rather than a gap in the roadmap. What it supplies is the layer underneath one: 10-K and 10-Q data extracted directly from SEC EDGAR with each company's reported line item structure preserved and the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, so the historical base of a model can be read from the document rather than from a template. [Custom Tables](/features#custom-tables) assemble exactly the reported line items a model needs. [Calculated Metrics](/features#calculated-metrics) including [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Invested Capital](/metrics/calculated-values/invested-capital), and [Net Debt](/metrics/calculated-values/net-debt) are computed from those as-filed inputs, which means a modeler can check the metric against the numbers that produced it rather than accepting a definition sight unseen. [Visualizations](/features#visualizations) chart the reported structure over time so a reinvestment or margin trend can be read off the filings themselves.

[Apple's](/stocks/AAPL) Q2 FY2026 balance sheet, from the 10-Q filed May 1, 2026, reports Commercial Paper at **$2.0 Billion**, Long Term Debt Current at **$8.3 Billion**, and Long Term Debt Noncurrent at **$74.4 Billion** — three separately filed instruments summing to **$84.7 Billion** of interest-bearing debt.

Whether the current portion belongs in invested capital is a methodology choice, and platforms differ. A calculation that excludes it shows a smaller capital base and, mechanically, a higher return on that capital. At Apple's scale a current-debt balance of **$8 Billion** or more can move the resulting ROIC by a full percentage point — which is frequently the difference between a business that clears a quality threshold and one that does not, and therefore the difference between a growth assumption that looks justified and one that does not.

Neither convention is wrong. They are simply not comparable, and a prebuilt model does not disclose which one it used. The [invested capital walkthrough](/blog/invested-capital-formula-step-by-step) covers the three filed inputs step by step.

For a full walkthrough of the mechanics, the [DCF valuation model guide](/blog/dcf-valuation-model-step-by-step) covers the build step by step, and [invested capital](/blog/invested-capital-formula-step-by-step) covers the input that standardization moves most often.

## When Prebuilt Is the Right Answer

There is a version of this decision where Finbox wins outright, and it deserves saying plainly.

Screening a large universe for candidates does not require audited inputs. Neither does orienting on an unfamiliar company, comparing valuation across a peer group, or getting a fast read on whether something is worth an afternoon. In those workflows a prebuilt model with sane defaults beats a blank spreadsheet every time, and 1,000-plus metrics at **$10** a month is a serious value proposition that no filing archive matches on breadth.

The break point is the moment a candidate becomes a position. Everything that made the prebuilt model efficient during screening — shared inputs, consensus defaults, standardized classification — becomes a liability once real capital is behind the conclusion, because none of it is yours and none of it is inspectable.

For the feature-level breakdown, see the [GeminIQ vs. Finbox comparison](/competitor-comparison/finbox). Because Finbox licenses the same S&P Global Market Intelligence fundamentals as several other platforms, the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) post applies to the data layer underneath it as well.

Use a prebuilt model to decide what deserves your attention. Build the real one from the filing, because a valuation you cannot trace to reported numbers is a valuation you inherited rather than reached.

## Frequently Asked Questions

### What are the best Finbox alternatives?

It depends on which half of Finbox you are replacing. For prebuilt valuation models and broad global screening, the substitutes are other model-first platforms, most of which license the same standardized fundamentals and differ on interface and price. For the data layer underneath a model you build yourself, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### Where does Finbox get its financial data?

Finbox states that it partners with S&P Global Market Intelligence for the data behind its models and metrics, and its documentation describes forecast data sourced from the same provider. That means Finbox's coverage is institutional in scale and that any standardization applied upstream is present in what Finbox displays.

### Are Finbox DCF models accurate?

Accuracy is the wrong frame for a DCF, because the output is entirely determined by assumptions. What matters is whose assumptions they are. Finbox's documentation describes model defaults as being based on consensus analyst estimates where available, so an unmodified model reflects sell-side expectations rather than an independent view — useful as a reference point, not as an edge.

### Can I build a DCF from SEC filings directly?

Yes, and the historical half of the model comes entirely from them. Revenue, margins, capital expenditure, working capital movement, and the debt and cash balances behind an equity bridge are all reported line items in the 10-K and 10-Q. What filings do not contain is the forecast, which is the half that should be yours regardless of which platform supplies the history.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=finbox-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Finbox data-provider attribution (S&P Global Market Intelligence), consensus-estimate model defaults, model library, coverage, and entry-tier pricing reviewed August 2, 2026 from Finbox's own site and help center plus third-party platform reviews. Verify current pricing on the Finbox site before republication.
- GeminIQ Finbox comparison page: /competitor-comparison/finbox

---

## Blog: Finviz Alternative for Fundamental Filing Data
source: https://www.geminiq.com/blog/finviz-alternative-fundamental-data

### Finviz Alternative for Fundamental Filing Data
A Finviz alternative for fundamental research. Finviz is a fast snapshot screener with financial history capped at three years free and eight on Elite; this post explains what a single row of ratios cannot tell you about a business.

Finviz earned its audience. The screener is fast, the free tier is a real product rather than a demo, the heatmap is the best market-overview visual anyone has built, and the quote page packs a chart, key ratios, analyst views, insider activity, and news onto one screen that loads instantly. Something like 25 million people a month use it, and the Elite tier runs **$39.50** monthly or **$299.50** a year for real-time data, export, backtesting, and alerts.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=finviz-alternative-fundamental-data)**

None of that is in dispute. What Finviz was built to be is a filter and a dashboard, and it is excellent at both.

The gap opens when a name survives the filter. Finviz's fundamental layer is a single row of ratios per company — a snapshot — with financial history capped at three years on the free tier and roughly eight on Elite. A ratio is the output of a calculation. The statements that produced it are not there.

## Table of Contents

- [A Snapshot Is a Number Without a Story](#a-snapshot-is-a-number-without-a-story)
- [What Three Years Cannot Show](#what-three-years-cannot-show)
- [Ratios Without Statements Hide Their Own Distortions](#ratios-without-statements-hide-their-own-distortions)
- [The Coverage Line Nobody Mentions](#the-coverage-line-nobody-mentions)
- [Where the Statements Live](#where-the-statements-live)
- [The Right Tool for the Right Half](#the-right-tool-for-the-right-half)
- [Frequently Asked Questions](#frequently-asked-questions)

## A Snapshot Is a Number Without a Story

The Finviz quote page shows a company's [current ratio](/metrics/liquidity-ratios/current-ratio)s in a dense grid. It is one of the fastest ways to form an impression of a business.

An impression is not an analysis, and the difference is direction. A margin of a given level tells you nothing about whether it arrived there by expanding for six years or collapsing from twice that. A leverage figure tells you nothing about whether debt was raised to fund growth or to cover a shortfall. A return on equity tells you nothing about whether equity shrank because of buybacks or because of accumulated losses.

Every one of those distinctions changes the conclusion completely, and none of them is visible in a current value.

That is not a defect in Finviz's execution. A screening grid has one row per company by design, because a screener has to render thousands of rows. Trajectory requires a series, and a series does not fit in a filter.

## What Three Years Cannot Show

History depth is the constraint that binds hardest, and it binds differently than most people expect.

Three years covers roughly one phase of a business cycle. Eight covers more but still misses the last two recessions for most companies. The questions that need longer records are the ones that separate a durable business from a lucky one: how margins behaved in the last downturn, whether management kept buying back stock when the price fell or only when it rose, how working capital moved when demand reversed, whether a leverage position that looks fine now looked fine the last time credit tightened.

There is a second problem with short history that gets less attention. A three-year window frequently starts inside an anomaly. Any company screened today on a three-year record is being judged against a base period that may have been distorted by conditions nobody expects to repeat, and the screen has no way to signal that.

Filings do not have this limitation. Every 10-K a company has filed is public, and the record runs as far back as the company does.

## Ratios Without Statements Hide Their Own Distortions

This is the specific failure mode, and it is the one that costs money.

A ratio has a numerator and a denominator, and either can be distorted by something the ratio does not disclose. A price-to-earnings figure computed on a year containing a large one-time gain looks cheap and is not. An earnings figure depressed by a single impairment makes a healthy business look broken. A return metric flattered by a shrinking asset base looks like improving efficiency and may be a business liquidating itself.

In every case the distortion is disclosed — in the statement, or in the note explaining the caption. It is simply not carried in the ratio.

An investor working from a snapshot has no way to detect any of this, because detecting it requires seeing the components. The screen returns the company as cheap, the quote page confirms it as cheap, and the reason it is cheap sits in a filing neither screen contains.

Screening on ratios is fine. Deciding on them is where the exposure is.

## The Coverage Line Nobody Mentions

There is a quieter constraint worth naming, and it applies to most screeners rather than Finviz alone.

Finviz covers roughly 8,000 to 10,000 US-listed stocks and ETFs — the major names, which is what nearly every user wants. The full population of SEC registrants is larger, and the companies outside a screener's coverage set are disproportionately small, illiquid, and unfollowed.

For a momentum trader that exclusion is irrelevant. For a value investor it removes part of the population where mispricing is most likely to survive, and the removal is invisible: a screen returns what it covers, and nothing indicates what was never eligible.

Filings have no coverage set. If a company registered with the SEC, it files.

## Where the Statements Live

GeminIQ covers the half that begins after the filter. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, which is where a ratio becomes a trajectory. [Visualizations](/features#visualizations) chart the reported structure over time, making an inflection visible instead of inferable. [Custom Tables](/features#custom-tables) assemble the specific reported items a question turns on. [Calculated Metrics](/features#calculated-metrics) including [Price to Earnings Ratio](/metrics/valuation-metrics/price-to-earnings-ratio), [Return on Equity](/metrics/returns-and-profitability/return-on-equity), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, so a figure that looks anomalous can be traced to the line items that made it so. For orientation, [how to read a 10-K](/blog/how-to-read-10-k) and [how to calculate financial ratios from a 10-K](/blog/how-to-calculate-financial-ratios-10k) cover the mechanics.

[Tesla's](/stocks/TSLA) June 2026 quarter is a clean illustration. Operating cash flow came in at **$4.697 Billion**, up **84.9%** year over year — a figure that reads as strength on any snapshot. Payments to acquire property, plant and equipment grew faster, up **141.8%** to **$5.789 Billion**, putting quarterly free cash flow at **-$1.092 Billion**, the first negative quarter since Q1 2024.

The trailing-twelve-month free cash flow figure, which is what an aggregated view typically displays, still read **$5.762 Billion**. Both numbers are correct. One of them shows the quarter the spending outran the cash and the other does not, and only reading the cash flow statement one filed period at a time distinguishes them. The [full breakdown](/blog/tesla-free-cash-flow-turns-negative) covers the quarter in detail.

There is no heatmap, no technical pattern recognition, no real-time quotes, and no market dashboard. The scope is the filed record.

## The Right Tool for the Right Half

Nobody should stop using Finviz, and the framing of "alternative" misleads here.

Screening and market context are a real job, done many times a day, and a fast free tool that does them well is worth keeping open in a tab permanently. Ten thousand companies reduced to twelve in under a minute is genuine value, and paying for that capability elsewhere would be waste.

The mistake is treating the twelve as analyzed rather than as selected. A screen produces candidates. A snapshot confirms they still look like candidates. Neither has opened a filing, and the questions that decide whether a candidate becomes a position — how the business behaved across a cycle, what a footnote says about a caption, whether a cheap multiple is cheap for a reason — all live in a document the screener never loaded.

For a deeper screener with the same underlying question about derived metrics, the [Stock Rover alternative](/blog/stock-rover-alternative-sec-data) post covers what metric count does and does not measure.

Use the fast tool to find the name in a minute. Use the filings to earn the position, because a ratio tells you where a company is and only the statements tell you how it got there.

## Frequently Asked Questions

### What are the best Finviz alternatives?

It depends on which half you need. For fast screening, heatmaps, and market context, the substitutes are other screeners and dashboards. For the financial statements behind a screen result, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability — which is a complement to a screener rather than a replacement for one.

### How much financial history does Finviz show?

Financial data is capped at roughly three years on the free tier, with Elite extending access to about eight years of company financial statements. That covers recent performance but generally not a full business cycle, and it excludes the downturns that reveal how a balance sheet behaves under stress.

### Is the Finviz free version good enough?

For screening and market context, the free tier is unusually capable and most casual users never outgrow it. Elite adds real-time data, extended-hours scanning, export, backtesting, and deeper financial history. Neither tier is built to deliver full statement history, because Finviz is a screener rather than a filings archive.

### Can you do fundamental analysis with only a stock screener?

A screener narrows a universe using current ratios; fundamental analysis requires the statements those ratios were computed from. Trajectory, one-time distortions, footnote detail, and behavior across a cycle are all invisible in a snapshot, and all of them are in the filings.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=finviz-alternative-fundamental-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Finviz coverage, screener filter counts, free-tier and Elite history limits, Elite pricing, and feature set reviewed August 2, 2026 from Finviz materials and third-party platform reviews. Verify current pricing and limits before republication.

---

## Blog: Fiscal.ai Alternative: As-Filed vs. Standardized Data
source: https://www.geminiq.com/blog/fiscal-ai-alternative-sec-data

### Fiscal.ai Alternative: As-Filed vs. Standardized Data
A Fiscal.ai alternative for investors who need line-item provenance. Fiscal.ai runs an AI research layer on standardized S&P Global Market Intelligence data; this post explains the difference between citing a document and tracing a number to its XBRL tag.

Fiscal.ai — the platform formerly known as FinChat, rebranded in mid-2025 alongside a Series A round — is one of the better-executed products in retail-facing equity research. It covers more than 100,000 global public companies, layers segment and KPI data that is difficult to assemble by hand, and puts a finance-tuned AI assistant on top that answers questions with citations rather than confident guesses. The free tier is usable, and paid access starts at a fraction of an institutional seat.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=fiscal-ai-alternative-sec-data)**

It also sits on top of S&P Global Market Intelligence data — the same standardized fundamentals layer that powers S&P Capital IQ Pro. That is not a hidden detail; Fiscal.ai says so, and it is a selling point, because institutional-grade coverage is expensive to build and licensing it is a reasonable decision.

But it means the question a careful investor has to ask about Fiscal.ai is not about the AI. It is about what the AI is reading.

## Table of Contents

- [What Sits Under the Interface](#what-sits-under-the-interface)
- [Citing a Document Is Not Tracing a Number](#citing-a-document-is-not-tracing-a-number)
- [Two Interpretive Layers, Stacked](#two-interpretive-layers-stacked)
- [Where the AI Layer Wins Outright](#where-the-ai-layer-wins-outright)
- [What Tag-Level Provenance Looks Like](#what-tag-level-provenance-looks-like)
- [Choosing Between Them](#choosing-between-them)
- [Frequently Asked Questions](#frequently-asked-questions)

## What Sits Under the Interface

A useful habit when evaluating any research platform is to ignore the front end for a moment and ask where the numbers came from.

Building a fundamentals dataset from primary filings is a sustained engineering commitment: parsing every filing, resolving tag changes as the US GAAP taxonomy is revised year over year, handling restatements and amended filings, and reconciling fiscal calendars that do not align with quarters. Most platforms sensibly decline that work and license a standardized dataset instead. The consequence is that a lineup of products that look independent are frequently reading from the same normalized layer, differentiated by interface, workflow, and price rather than by data.

Fiscal.ai is transparent about being one of them. That transparency is worth more than the marketing claims most competitors make, and it also makes the analysis simple: whatever standardization decisions exist in the underlying dataset are present in Fiscal.ai, unchanged, because Fiscal.ai did not make them and cannot unmake them.

## Citing a Document Is Not Tracing a Number

Fiscal.ai's AI responses come with citations, and higher tiers are reported to offer click-through auditability to filings for US stocks. That is a real feature and a meaningful one. It is also frequently mistaken for something it is not.

A citation answers the question "where did this claim come from." Provenance answers a different question: "which specific reported fact produced this specific number, and is the value on my screen the value in the filing?"

The gap between them is where models break. An AI response can correctly cite a 10-K while reporting a figure that the underlying dataset standardized before the AI ever saw it. The citation is accurate — the filing is the ultimate source — and the number still does not match the caption in the document. Nothing in the citation chain surfaces that, because the citation points at the filing rather than at the mapping decision that sits between the filing and the value.

That is not a flaw in Fiscal.ai's execution. It is a structural property of any product whose data comes from an upstream standardization layer. You can link to the source without being able to expose the transformation.

## Two Interpretive Layers, Stacked

There is a second consideration specific to AI-mediated research, and it compounds the first.

The first layer is normalization: a company's reported line items mapped into a comparable template. Two distinct cash outflows can become one row. A single filed liability caption can be split into two so a component is trackable. A label can persist while its contents change. Every one of those decisions is defensible in isolation and invisible on screen.

The second layer is language. An AI reads the standardized values and produces a sentence about what they mean. Independent reviewers of AI research tools consistently make the same recommendation — verify important figures against primary filings rather than relying on the generated summary — and they are right to, because summarization of accounting data is exactly where nuance around one-time items, classification changes, and restatements gets flattened.

Stack the two and an analyst is reading an interpretation of a transformation. Both steps are usually fine. Neither is inspectable from the answer.

The practical effect is that verification, which is supposed to be the cheap step, becomes the expensive one. If checking a number means leaving the platform and opening the filing manually, the platform has moved the work rather than removed it.

## Where the AI Layer Wins Outright

None of this argues that AI research tools are a bad idea, and pretending otherwise would be dishonest.

Segment and KPI data across thousands of companies is punishing to assemble from filings, and having it structured and queryable is a real advantage. Global coverage across European, Asian, and other non-US listings is something a US-filings product does not offer. Earnings transcripts, analyst estimates, and consensus revisions are not in any 10-K. Natural-language querying across a large universe is a genuine speed improvement for the discovery phase of research, and dashboards that surface a business's operating drivers beat manually rebuilding them every quarter.

For screening, for orientation on an unfamiliar company, and for anything outside US GAAP filings, that toolkit is strong.

The point of divergence is the last mile — the moment the work stops being exploratory and becomes something you have to defend.

## What Tag-Level Provenance Looks Like

GeminIQ takes the opposite starting position. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves the company's own reported line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) behind each value attached to it. There is no mapping layer between the filing and the display, which means the question "does this number match the document" has a mechanical answer rather than an investigative one.

That premise governs the rest. [Financial Statements](/features#financial-statements) show a company's own captions across quarters and years rather than a template's rows. [Custom Tables](/features#custom-tables) build views from specific reported items. [Calculated Metrics](/features#calculated-metrics) such as [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) are computed from as-filed inputs, so the metric can be audited against the numbers that produced it instead of trusted on reputation.

[Apple](/stocks/AAPL) reports a balance sheet line called Vendor Non-Trade Receivables — **$33.2 billion** owed back to Apple by the contract manufacturers that buy components on its behalf. It carries a company-specific extension tag rather than a standard US GAAP concept, because no standard concept describes it. On normalized platforms it is commonly absorbed into Other Current Assets.

The total does not change. The identity does. An analyst modeling Apple's working capital from a bucket that swallowed a supply-chain-specific asset is modeling a different business than the one in the 10-K, and an AI answer citing that filing can be accurate about its source while reading the bucket rather than the line. [Financial data normalization explained](/blog/financial-data-normalization-explained) walks through why extension tags are the first thing a template discards.

The tradeoff is explicit. The universe is US public companies only, there are no analyst estimates, and there is no conversational assistant writing the summary for you. What you get instead is the ability to prove a number.

## Choosing Between Them

The decision resolves on what breaks your work.

If the failure mode you fear is missing a company — not knowing that a European competitor exists, not having the segment breakdown, not seeing where consensus sits — then coverage and AI-assisted discovery are the right purchase, and Fiscal.ai does that job well at a price that makes sense.

If the failure mode you fear is building a thesis on a number you cannot tie to the filing, coverage does not help. A larger universe of standardized values is still a universe of standardized values, and an AI summary of them adds a second layer between you and the document.

Serious research usually wants both answers, and the mistake is assuming a single tool has to supply them. Use a broad platform to find the company. Use the filing to decide what it is worth. The [GeminIQ vs. Fiscal.ai comparison](/competitor-comparison/fiscal-ai) covers the feature-level detail, and [what investors miss in SEC filings](/blog/what-investors-miss-in-sec-filings) covers what the last mile actually contains. Because Fiscal.ai's fundamentals come from S&P Global Market Intelligence, the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) post applies to the data layer underneath it as well.

The best research stack is not the one with the most capable assistant. It is the one where you can still answer, for any number on the screen, exactly which line of which filing produced it.

## Frequently Asked Questions

### What are the best Fiscal.ai alternatives?

Which alternative fits depends on which part of Fiscal.ai you are replacing. For global coverage, analyst estimates, and transcripts, the substitutes are other platforms licensing institutional fundamentals — they differ on interface and price rather than on data. For US filing verification, the substitute is a filing-first platform that extracts from SEC EDGAR and preserves XBRL tag provenance, which is a different category rather than a cheaper version of the same one.

### What is the best Fiscal.ai alternative for US filing data?

For US public company fundamentals, the alternative worth evaluating is a platform that extracts directly from SEC EDGAR and preserves as-filed line items with XBRL tag traceability. Fiscal.ai's strength is breadth and AI-assisted research across a global universe; a filing-first platform trades that breadth for the ability to trace a displayed value back to the exact reported fact.

### Where does Fiscal.ai get its financial data?

Fiscal.ai sources its fundamentals from S&P Global Market Intelligence, the same data operation behind S&P Capital IQ Pro. That means Fiscal.ai's coverage is institutional in scale, and also that any standardization applied upstream is present in what Fiscal.ai displays.

### Is FinChat the same as Fiscal.ai?

Yes. FinChat rebranded to Fiscal.ai in mid-2025 alongside a Series A funding round. Plan names and product scope changed at the same time, so older reviews referencing FinChat tiers do not describe the current pricing structure.

### Do AI citations mean the number is verified?

No. A citation identifies the document a claim came from. It does not confirm that the displayed value matches the caption in that document, because standardization happens between the filing and the dataset the AI reads. Verification requires tracing the value itself to the reported fact, which is a different mechanism than linking to the source.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=fiscal-ai-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Fiscal.ai product positioning, coverage claims, data sourcing, plan structure, and the FinChat rebrand reviewed August 2, 2026 from the company's public materials and third-party platform reviews.
- Claims about tier-gated filing auditability are reported by third-party reviews and should be verified against Fiscal.ai's current pricing page before republication.
- GeminIQ Fiscal.ai comparison page: /competitor-comparison/fiscal-ai

---

## Blog: Form 144 Explained: Reading Planned Insider Sales
source: https://www.geminiq.com/blog/form-144-planned-insider-sales

### Form 144 Explained: Reading Planned Insider Sales
Form 144 is the notice an insider or other company affiliate must file with the SEC before selling restricted or control securities above a set size threshold, and it's a leading indicator almost nobody checks: it discloses a planned sale before the Form 4 confirms it actually happened. This guide covers who has to file, the exact thresholds and timing that trigger the requirement, how Form 144 differs from Form 4, and how to find any insider's Form 144 history on EDGAR.

Before an executive's stock sale shows up as a completed Form 4 transaction, in most cases there is an earlier filing that told the market the sale was coming — the order placed, the share count, the approximate date. That filing is Form 144, and almost nobody reads it. The Form 4 — the after-the-fact record of what already happened — is the version that gets attention. Form 144 is the notice that comes first: a public, dated statement of intent to sell, filed before the trade executes rather than after.

Form 144, formally the Notice of Proposed Sale of Securities Pursuant to Rule 144, is what corporate insiders and other affiliates file when they plan to sell restricted or control securities above a specific size threshold. It answers a question Form 4 cannot: not what an insider just did, but what an insider is about to do. Our [SEC filings guide](/blog/sec-filings-guide) covers Form 144 in a single paragraph as part of the full filing landscape — this guide is the deeper version, covering the thresholds and timing traps, how it differs from Form 4, and how to find any insider's Form 144 history on EDGAR.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=form-144-planned-insider-sales)**

## Table of Contents

- [What Is Form 144?](#what-is-form-144)
- [Who Has to File Form 144?](#who-has-to-file-form-144)
- [The Thresholds and Timing](#the-thresholds-and-timing)
- [What Form 144 Tells You That Form 4 Cannot](#what-form-144-tells-you-that-form-4-cannot)
- [What a Form 144 Doesn't Guarantee](#what-a-form-144-doesnt-guarantee)
- [Step 1: Search EDGAR for Form 144 Filings](#step-1-search-edgar-for-form-144-filings)
- [Step 2: Match the Filer to Their Form 4 History](#step-2-match-the-filer-to-their-form-4-history)
- [Step 3: Watch the 90-Day Window](#step-3-watch-the-90-day-window)
- [Reading Form 144 Alongside GeminIQ's Insider Data](#reading-form-144-alongside-geminiqs-insider-data)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is Form 144?

Form 144 is the notice a company affiliate files with the SEC before selling restricted or control securities in reliance on Rule 144 — the safe harbor that lets otherwise unregistered shares be resold into the public market without a full Securities Act registration. Filing Form 144 does not authorize the sale by itself. It is a disclosure obligation layered on top of a sale the affiliate has already decided — and is legally permitted — to make.

Restricted securities are typically shares acquired directly from the company or in a private transaction — pre-IPO equity, shares from a private placement, founder stock — that were never registered for public resale. Control securities are shares held by an affiliate, regardless of how they were originally acquired, simply because that person's relationship to the company gives them influence over it. An executive's open-market-purchased shares can be control securities for Rule 144 purposes even though they were bought like any other investor's shares, purely because of who is holding them.

---

## Who Has to File Form 144?

Form 144 applies to affiliates: executive officers, directors, and beneficial owners of more than 10% of a company's outstanding shares — the same population that files [Section 16 reports on Forms 3, 4, and 5](/blog/how-to-read-sec-form-4). Immediate family members of an affiliate, and entities the affiliate controls, are typically swept in as well when they hold or sell the affiliate's securities.

Non-affiliates are generally exempt from filing, even when selling restricted securities, once they've cleared the applicable Rule 144 holding period. That asymmetry is the point of the rule. An affiliate's sale carries more informational significance to the market than an equivalent sale by an outside investor with no relationship to the company, so the affiliate's sale gets a public notice requirement the outside investor's does not.

---

## The Thresholds and Timing

Not every affiliate sale triggers a Form 144. The filing is required only when the amount sold during any rolling three-month period exceeds **5,000 shares** or **$50,000** in aggregate sale price — whichever threshold the sale reaches first. A sale of 4,000 shares clears neither threshold on its own and requires no Form 144. A sale of 5,001 shares does, regardless of price.

Timing is where the filing requirement is easy to misjudge: Form 144 is not filed after the sale, and it is not filed a comfortable buffer of days in advance. It must be filed concurrently with placing the sell order with a broker, or with executing the sale directly with a market maker, under Rule 144(h)(3). The affiliate then has 90 days from that filing date to actually complete the sale. If the securities aren't sold within the window, the notice expires and a new Form 144 is required before selling any remaining shares.

Filing itself became fully electronic on **April 13, 2023**. Before that date, Form 144 was almost always filed on paper or by email directly to the SEC, not published to EDGAR in the same structured, immediately searchable way Form 4 has been for years. That single rule change is why Form 144 only recently became usable at all as a public research tool, rather than a compliance formality buried in SEC paper files.

---

## What Form 144 Tells You That Form 4 Cannot

The two forms cover the same population of people and often the same shares, but they answer different questions at different points in time. Form 144 is filed at or before the moment the sell order goes in — a statement of intent, filed on the affiliate's own estimate of what they plan to sell and by when. [Form 4](/blog/how-to-read-sec-form-4) is filed within two business days after a transaction actually executes, and it reports what happened, not what was planned.

That gap between intent and execution is where Form 144 earns its place as a real leading indicator. A large Form 144 filing tells you a sale of a specific approximate size is coming within the next 90 days, before the market has any confirmed record that it occurred. The eventual Form 4 — more precisely, the [S transaction code](/blog/form-4-transaction-code-list) on that Form 4 — is where you find out whether the plan was executed in full, partially, or not at all. Reading Form 144 without eventually cross-checking the corresponding Form 4 tells you what an insider intended. Reading Form 4 without ever having seen the Form 144 tells you what happened, with no visibility into how far in advance the decision became public.

| | Form 144 | Form 4 |
|---|---|---|
| What it reports | A proposed sale — a statement of intent | A transaction that has already executed |
| Timing | Filed concurrently with placing the sell order with a broker, or executing with a market maker, under Rule 144(h)(3) | Filed within two business days after the transaction executes |
| Who files | Affiliates: officers, directors, and beneficial owners above **10%** | The same Section 16 population |
| Size threshold | Required only above **5,000 shares** or **$50,000** in any rolling three-month period | No size threshold |
| What it tells you | A sale of a specific approximate size is coming within the next 90 days | Whether the sale executed, and at what price |
| If the sale never happens | The notice simply expires at 90 days — no amendment or explanation required | No filing exists at all; the absence is the only record |

---

## What a Form 144 Doesn't Guarantee

Filing a Form 144 does not obligate the affiliate to actually sell. The 90-day window can lapse with the shares never sold, and no amendment or explanation is required when that happens — the notice simply expires. An affiliate who changes their mind, or whose broker never executes the order because a price target isn't met, leaves no separate record that the planned sale didn't happen. The only way to know is the absence of a matching Form 4 within the window, which requires actively checking rather than assuming.

Volume is also capped, not just noticed. Under Rule 144(e), an affiliate's sales of an exchange-listed reporting company's stock in any three-month period generally cannot exceed the greater of **1%** of the company's total outstanding shares or the average weekly trading volume over the four calendar weeks preceding the filing. A Form 144 that names a share count near that ceiling is disclosing close to the maximum the affiliate is legally permitted to sell in the period, which caps the pace of an exit even for an affiliate looking to sell everything at once.

---

Finding an insider's Form 144 filings takes the same EDGAR workflow as pulling their Form 4 history, now that the form is filed electronically.

## Step 1: Search EDGAR for Form 144 Filings

Use SEC EDGAR's company or person search and filter by form type 144. Because Form 144 has been disseminated alongside Section 16 ownership filings since electronic filing became mandatory on **April 13, 2023**, it now surfaces in the same search flow used to pull a company's Form 3, 4, and 5 history rather than sitting in a separate paper archive.

## Step 2: Match the Filer to Their Form 4 History

Cross-reference the affiliate's name against their own Form 4 filing history for the 90 days following the Form 144's filing date. A matching S transaction confirms the planned sale executed; its absence means the notice expired unfulfilled.

## Step 3: Watch the 90-Day Window

Note the filing date and count 90 days forward. Any completed sale tied to that specific Form 144 has to land inside that window — a Form 4 sale that shows up well outside it belongs to a separate, later notice, not the one you started with.

---

## Reading Form 144 Alongside GeminIQ's Insider Data

GeminIQ's [Insider Transactions](/features#insider-transactions) feature is built on Form 4 and Form 5 data — the completed, executed transactions insiders actually made, with the transaction code, price, and post-transaction holding preserved exactly as filed. Form 144 sits one step earlier in that chain, and it isn't part of that dataset — for the same structural reason SEC comment letters aren't part of GeminIQ's financial statement data. A notice of proposed sale is a forward-looking statement of intent, not a completed, comparable transaction record.

That makes Form 144 a complementary research step, not a redundant one. Pulling an affiliate's Form 144 filings directly from EDGAR before reviewing their Insider Transactions history on GeminIQ tells you what to watch for over the following 90 days. Once the window closes, the completed sale, if it happened, shows up on GeminIQ exactly as it was reported on the eventual Form 4 — the notice of intent and the completed record, checked against each other rather than read alone.

---

## Frequently Asked Questions

### Does everyone selling company stock have to file Form 144?

No. Only affiliates — officers, directors, and beneficial owners above **10%** — filing sales of restricted or control securities above the threshold have to file. Even affiliates are exempt below **5,000 shares** or **$50,000** in a rolling three-month period.

### Is a Form 144 filing a guarantee the sale will happen?

No. It's a notice of intent filed at the time the sell order is placed, and the 90-day window can lapse without a matching sale ever showing up on a Form 4. Checking for that matching Form 4 is the only way to confirm the sale actually executed.

### How is Form 144 different from a Rule 10b5-1 trading plan disclosure?

They can overlap but aren't the same thing. A 10b5-1 plan is a pre-scheduled trading arrangement disclosed in Form 4 footnotes once transactions execute under it. Form 144 is the separate notice of proposed sale required once the size threshold is crossed, whether or not the underlying sale is part of a 10b5-1 plan.

### When did Form 144 become searchable on EDGAR like other insider filings?

Electronic filing became mandatory on **April 13, 2023**. Before that, most Form 144s were paper or email filings to the SEC rather than structured, immediately searchable EDGAR records.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=form-144-planned-insider-sales)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Free Bloomberg Terminal Alternatives That Actually Work
source: https://www.geminiq.com/blog/free-bloomberg-terminal-alternatives

### Free Bloomberg Terminal Alternatives That Actually Work
Free Bloomberg Terminal alternatives exist for fundamental research, and this post names the ones that hold up: Finviz, StockAnalysis.com, Koyfin, GeminIQ, and SEC EDGAR itself, along with what a $31,980-a-year terminal does that none of them can.

A Bloomberg Terminal runs roughly **$31,980** a seat per year in 2026, typically on a two-year minimum commitment, and searching for a free version of it is one of the most common queries in this entire category. The honest answer is that a free alternative exists for part of the job and not for the rest of it, and knowing which part is which saves a lot of wasted evaluation time.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=free-bloomberg-terminal-alternatives)**

The terminal bundles two very different products into one subscription: a real-time trading desk (cross-asset pricing, a messaging network, dealer quoting, execution) and a research and data layer sitting on top of it. Nothing free replaces the first. Several genuinely good free tools cover real ground on the second, and one of them is the only free tier on this list built on as-filed source data instead of a standardized representation of it.

## Table of Contents

- [What "Free" Actually Covers](#what-free-actually-covers)
- [Finviz: Free Screening and Market Context](#finviz-free-screening-and-market-context)
- [StockAnalysis.com: Free Statements and Ratios](#stockanalysiscom-free-statements-and-ratios)
- [Koyfin Free: A Real Zero-Dollar Tier](#koyfin-free-a-real-zero-dollar-tier)
- [GeminIQ Free: As-Filed Data at Zero Cost](#geminiq-free-as-filed-data-at-zero-cost)
- [SEC EDGAR Directly: The Original Free Source](#sec-edgar-directly-the-original-free-source)
- [What No Free Tool Replaces](#what-no-free-tool-replaces)
- [When the Free Tier Runs Out: What Each Paid Tier Costs](#when-the-free-tier-runs-out-what-each-paid-tier-costs)
- [What the Paid Options Cost: Capital IQ, Bloomberg, BamSEC](#what-the-paid-options-cost-capital-iq-bloomberg-bamsec)
- [Frequently Asked Questions](#frequently-asked-questions)

## What "Free" Actually Covers

Bloomberg's price supports a network, not a dataset. Real-time pricing across hundreds of global exchanges, a messaging system that functions as the industry's directory, dealer quoting for instruments with no public order book, and execution wired into all of it are what a terminal seat actually buys. Every free tool below is silent on every one of those.

What a free tool can cover is research: screening a universe, reading a company's ratios and statements, and getting oriented on a name before spending real time on it. That is a genuine, well-served slice of the terminal's price tag, just not the slice most terminal subscribers are actually paying for.

## Finviz: Free Screening and Market Context

[Finviz's](/blog/finviz-alternative-fundamental-data) free tier is a real product, not a demo. It is used by roughly **25 million** people a month, and it packs a fast screener, the best market heatmap available anywhere, and a quote page with chart, ratios, insider activity, and news onto one screen that loads instantly. Elite adds real-time data and backtesting for **$299.50** a year, which is still a rounding error against a terminal seat.

The fundamental layer is thinner than the screener. It is a single row of ratios per company, with financial history capped at three years free and roughly eight years on Elite, which covers recent performance but generally not a full business cycle.

## StockAnalysis.com: Free Statements and Ratios

[StockAnalysis.com](/blog/stockanalysis-com-alternative-filing-data) is the cleanest free research site available, with coverage past **130,000** symbols and free-tier statement history running to roughly five years. Pro extends that for **$79** a year and Unlimited for **$199**, still well under one percent of a terminal seat.

The site is unusually candid about where its numbers come from: its published data-sources page names S&P Global Market Intelligence and Fiscal.ai as providers and tells users to confirm critical figures against the original filing before acting on them. That instruction is correct, and almost nobody follows it, because doing it by hand takes roughly fifteen minutes per figure.

## Koyfin Free: A Real Zero-Dollar Tier

[Koyfin](/competitor-comparison/koyfin) publishes an actual **$0/month** tier, not a time-limited trial, with **2** years and **12** quarters of statement history alongside dashboards, watchlists, and macro data across equities, ETFs, currencies, and commodities. Paid tiers start at **$39** a month and extend history to **10** years and **40** quarters.

For a generalist who wants market context in one place at zero cost, this is a genuinely strong free tier. Finviz, StockAnalysis.com, and Koyfin all share one property underneath, though: even at the free level, the fundamentals sit behind a licensed, standardized dataset rather than the filing itself.

## GeminIQ Free: As-Filed Data at Zero Cost

[GeminIQ's Free plan](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=free-bloomberg-terminal-alternatives) is also a genuine **$0/month** tier, not a trial, and it breaks the pattern above in one specific way. Every figure is still pulled directly from SEC EDGAR with the same XBRL traceability as the paid product, just scoped down rather than swapped for a different dataset. The free plan carries **3 years** of historical financial data, **24** calculated metrics, next-day filing availability, and limited access to visualizations, insider transactions, institutional ownership, and price-reaction data. The Stock Screener and Custom Watchlists are reserved for paid plans.

That scoping matters less than what did not get scoped away. On Finviz, StockAnalysis.com, and Koyfin, the free tier and the paid tier sit on the same standardized data underneath, so upgrading buys more of a representation. On GeminIQ, the free tier sits on the same as-filed, XBRL-tagged pipeline as the paid product, just with three years of history and 24 metrics instead of the full library. It is the only tool on this page where a free-tier number is a reported fact rather than a standardized version of one.

## SEC EDGAR Directly: The Original Free Source

For fundamental research specifically, the actual source material has always been free. Every 10-K and 10-Q is public on [SEC EDGAR](https://www.sec.gov/) the moment it is filed, complete with the XBRL data behind every reported figure. No subscription gates any of it, on Bloomberg or anywhere else.

What is not free is making that data usable. Parsing a filing, resolving tag changes as the taxonomy is revised year over year, handling restatements, and assembling comparable statement history across a decade of filings is a sustained extraction problem. Free covers the documents. It does not cover the dataset, and that gap is what every research platform on this page, GeminIQ's own free tier included, is actually built to close.

## What No Free Tool Replaces

None of the tools above, free or paid, touch the reason most Bloomberg subscribers actually pay. A stale quote is a losing quote for a trader, and a bond desk needs a counterparty in seconds rather than after an email thread. Large parts of the fixed income market have no public order book at all, so price discovery happens through relationships the terminal indexes. Free research tools were never built to solve that problem, and no comparison that pretends otherwise is worth reading.

If you trade, need real-time execution, or depend on the terminal's messaging network to reach counterparties, the terminal is not an expensive option. It is the job, and this post is not about that job.

## When the Free Tier Runs Out: What Each Paid Tier Costs

Every free tool above eventually hits a ceiling, and the ceilings differ by what you are optimizing for. Finviz Elite and StockAnalysis Pro or Unlimited buy more history and features on top of the same licensed data underneath, so upgrading pays for convenience rather than traceability. Koyfin's paid tiers work the same way, extending statement history from **2** years and **12** quarters to **10** years and **40** quarters on the same [Capital IQ-sourced](/competitor-comparison/sp-capital-iq) fundamentals.

GeminIQ's Annual (**$29**/month billed annually) and Monthly (**$39**/month) plans extend the free plan along the same as-filed pipeline rather than switching to a different one. The upgrade unlocks **17+** years of historical data instead of three, **90+** calculated metrics instead of 24, plus the [Stock Screener](/features#screener), [Custom Watchlists](/features#custom-watchlists), and full [Insider Transactions](/features#insider-transactions) and [Institutional Ownership](/features#institutional-ownership) tracking that the free tier only shows in limited form. The upgrade adds depth and functionality. It does not add a standardization layer between the filing and the display, because there was never one to add.

[Financial Statements](/features#financial-statements) and [Calculated Metrics](/features#calculated-metrics) work identically on the free and paid GeminIQ plans in one respect: every figure traces to its SEC source either way. What changes with a subscription is how much history and how many metrics are unlocked, not whether the number on screen is the one the company actually filed. That is the distinction every free-versus-paid comparison on this page ultimately comes down to: more of the filing, never a different version of it.

For the fuller comparison against the terminal itself, the [GeminIQ vs. Bloomberg Terminal comparison](/competitor-comparison/bloomberg-terminal) covers it in depth.

## What the Paid Options Cost: Capital IQ, Bloomberg, BamSEC

Put side by side, the price ladder in this category spans four orders of magnitude, and the two most expensive rungs are the two that publish nothing. Every figure below is the one cited in the sections above; where a vendor does not publish a number, the table says so rather than estimating one.

| Platform | What the price buys | Published cost |
|---|---|---|
| Bloomberg Terminal | Real-time cross-asset pricing, messaging, dealer quoting, execution | Not published; widely reported near **$31,980** per seat per year, roughly **$28,320** per seat at two or more |
| [S&P Capital IQ](/competitor-comparison/sp-capital-iq) | The licensed, standardized fundamentals layer sitting under Koyfin and others | Not published — see our [Capital IQ pricing breakdown](/blog/capital-iq-pricing-cost-explained) |
| Finviz Elite | Real-time data and backtesting on top of the free screener | **$299.50** a year |
| StockAnalysis.com Pro / Unlimited | More history and features on the same licensed data | **$79** / **$199** a year |
| Koyfin (paid) | **10** years and **40** quarters of statement history | From **$39** a month |
| [BamSEC](/competitor-comparison/bamsec) | Fast navigation of one company's filings and exhibits | Not listed here |
| GeminIQ Annual / Monthly | **17+** years, **90+** metrics, Screener, Watchlists, on as-filed data | **$29** / **$39** a month |
| GeminIQ Free | **3 years**, **24** metrics, same as-filed pipeline | **$0** |

The pattern in that table is worth stating plainly: the products that do not publish a price are the ones selling access to a network and a licensing relationship, not to a dataset you could otherwise assemble. Everything below them is priced against what it costs to process filings that were already free.

## Frequently Asked Questions

### Are there really free Bloomberg Terminal alternatives?

For fundamental, filing-based research, yes. Finviz, StockAnalysis.com, Koyfin, and GeminIQ all offer real, permanent free tiers covering screening, ratios, statements, and market context at no cost, and the underlying SEC filings themselves have always been free on EDGAR. None of them touch the terminal's real-time trading, messaging, or execution functions, which is what most of a terminal seat's price actually pays for.

### What does a Bloomberg Terminal cost in 2026?

Bloomberg does not publish pricing, but widely reported figures put a single seat near **$31,980** per year in 2026, dropping to roughly **$28,320** per seat for firms running two or more, typically on a two-year minimum commitment.

### Is GeminIQ free?

Yes, in a genuine and permanent form. GeminIQ's Free plan is **$0** a month with no trial required, covering **3 years** of as-filed financial history and **24** calculated metrics, sourced directly from SEC EDGAR with the same XBRL traceability as the paid product. The Stock Screener, Custom Watchlists, and full 17-plus-year history are reserved for the Annual (**$29**/month billed annually) and Monthly (**$39**/month) plans, both of which include a 7-day free trial.

### Which free tool is closest to a Bloomberg Terminal for stock research?

None of them are close on breadth, and that is the wrong comparison to make. For screening and market context, Finviz and Koyfin's free tier are the strongest no-cost options. For statement-level research with source traceability rather than standardized data, GeminIQ's free tier and SEC EDGAR directly go deepest, though EDGAR requires doing the extraction work by hand.

### Is there a free alternative to S&P Capital IQ?

Not to the full institutional stack, but the part most individual investors actually want from it — standardized statement history — is available free from several tools on this page. Koyfin's free tier runs on Capital IQ-sourced fundamentals directly, and GeminIQ's Free plan covers **3 years** of as-filed history and **24** calculated metrics at **$0**. What Capital IQ itself costs is a separate question with a longer answer, covered in our [S&P Capital IQ pricing breakdown](/blog/capital-iq-pricing-cost-explained).

### What should QuickFS users switch to now that it has shut down?

QuickFS has shut down, and its homepage now carries a farewell note from founder Ted Cooper pointing users to FastFS.org. For anyone rebuilding a workflow around it, the choice comes down to the same split this page is about. If what mattered was standardized statement history in a fast interface, StockAnalysis.com and Koyfin's free tier cover that at no cost. If what mattered was being able to trace a figure back to the filing that produced it, that is a different category, and GeminIQ's Free plan carries **3 years** of as-filed, XBRL-tagged history and **24** calculated metrics at **$0**.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=free-bloomberg-terminal-alternatives)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Bloomberg Terminal per-seat cost figures are widely reported third-party estimates compiled from procurement trackers and subscriber reports; Bloomberg does not publish pricing.
- Finviz, StockAnalysis.com, and Koyfin free-tier features, history limits, and paid-tier pricing are drawn from GeminIQ's own published comparison research on each platform (linked above), reviewed August 2, 2026 from each platform's public materials.
- GeminIQ Free, Annual, and Monthly plan features, limits, and pricing confirmed directly from https://www.geminiq.com/pricing, retrieved August 7, 2026.
- GeminIQ Bloomberg Terminal comparison page: /competitor-comparison/bloomberg-terminal

---

## Blog: Free Cash Flow Inflection: The Quarter It Turns Positive
source: https://www.geminiq.com/blog/free-cash-flow-inflection

### Free Cash Flow Inflection: The Quarter It Turns Positive
Free cash flow inflection is the quarter a company's trailing-twelve-month Free Cash Flow first turns positive after a run of negative readings, and this study tracks 4,491 of those crossings across the SEC filing universe to see whether the market reaction depended on what happened in the four quarters that followed.

**Crossings where Free Cash Flow (TTM) stayed positive through the following four quarters were followed by a median three-month return of +4.11%, against a universe base rate of +2.36%. Crossings that relapsed back negative within four quarters returned a median of +0.00%.**

[GoPro](/stocks/GPRO) spent 17 straight quarters posting negative trailing-twelve-month Free Cash Flow before that figure finally crossed positive in the third quarter of 2020 — and the stock moved 33.08% over the next three months. That is a good story on its own. It is also, by itself, worthless, because the question a "first positive FCF quarter" study actually has to answer isn't whether the market reacted. It's whether the reaction meant anything once the next four quarters played out.

This is a Filing Data Study built from GeminIQ's as-filed 10-K and 10-Q pipeline. It scanned 15,067 companies for each one's first-ever crossing from negative to positive Free Cash Flow (TTM), excluded financial-sector issuers, and found 4,491 crossings filed between March 2010 and June 2026. Of those, 2,076 carry both a resolved four-quarter fundamentals outcome and a three-month post-filing return, and that subset is what the buckets below are built from.

## Why One Positive Quarter Isn't the Finding

A single crossing quarter tells you almost nothing on its own. Some companies flip positive because the underlying business turned a real corner — margins expanded, a cost program landed, growth caught up to fixed costs. Others flip positive because a working-capital swing, an asset sale, or a light capex quarter flattered the number for one period before reality reasserted itself. Both look identical on the day of the filing. The only way to tell them apart from the outside is to wait and see whether the positive reading held.

So this study splits every crossing into two outcomes measured four quarters later: did Free Cash Flow (TTM) stay positive, or did it dip back negative at least once. That single follow-up check turns out to carry real information about how the market treated the crossing at the time it happened — not because the market can see four quarters into the future, but because a crossing built on something durable tends to look different, even in month one, from a crossing built on a one-time item that both the company and attentive investors can already sense won't repeat.

The mirror case is worth keeping in mind while reading this: [Tesla](/stocks/TSLA)'s Q2 2026 quarter, [which crossed the same line in the opposite direction](/blog/tesla-free-cash-flow-turns-negative). A company sliding into negative Free Cash Flow (TTM) raises the identical question this study asks about a company climbing out of it — was the quarter that moved the number a genuine shift, or a one-time item working against the trend instead of for it.

## Held vs. Relapsed: Three-Month Returns After the Crossing

The split is clean. Crossings that held Free Cash Flow (TTM) positive through the following four quarters were followed by a median three-month return of **+4.11%** — **1.75 points** above the universe base rate of **+2.36%** established across 76,908 filings in GeminIQ's [revenue growth slowdown study](/blog/revenue-growth-slowdown-stock-returns). Crossings that relapsed back negative within four quarters were followed by a median of **+0.00%**, a full **2.36 points** below that same base rate.

| Outcome | Filings (N) | Median 3-Mo Return | vs. Base Rate | Share Positive |
|---|---|---|---|---|
| Held past 4 quarters | **1,092** | **+4.11%** | **+1.75 pts** | **59.4%** |
| Relapsed within 4 quarters | **984** | **+0.00%** | **-2.36 pts** | **46.5%** |

Both buckets clear the 200-filing floor by a wide margin. The share-positive column is the more honest read of the two: **59.4%** of filings in the held bucket posted a positive three-month return, against just **46.5%** in the relapsed bucket — the only one of the two buckets to fall below a coin flip.

<center><sup>GeminIQ data study: median three-month post-filing return for Free Cash Flow (TTM) crossings that held positive for four quarters versus those that relapsed, against the universe base rate. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 2,076 filings, 2010–2026.</sup></center>

The mean tells a stranger story, and it's worth showing why the median is doing the real work here. The raw mean three-month return in the relapsed bucket is **+484.98%** — a number driven entirely by a handful of penny-stock and micro-cap filings that happened to rip higher for reasons that had nothing to do with their cash flow statement. Winsorized at the top and bottom 1%, that mean collapses to **+6.72%**, still well above the median of **+0.00%**. When the mean and the median disagree by that much even after trimming outliers, the median — not the mean — is the number that describes what happened to the typical filing.

<center><sup>GeminIQ data study: share of Free Cash Flow (TTM) crossings followed by a positive three-month return, held vs. relapsed. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 2,076 filings, 2010–2026.</sup></center>

This is a historical association measured over the 2010–2026 sample window, not a forecast; a crossing that holds doesn't predict anything about the next filing, only what tended to follow crossings like it in the past.

## GoPro, 3M, Coca-Cola, Devon Energy, and AMERCO

Five named crossings put faces on those two buckets, starting with the one that opened this piece.

[GoPro](/stocks/GPRO) had run **17** consecutive quarters of negative Free Cash Flow (TTM) before the Q3 2020 crossing took the figure from **-$78.964 Million** to **+$69.182 Million** in a single reading, and the stock moved **33.08%** over the three months that followed. A four-year negative run ending in one filing is the version of this event most investors picture when they hear "inflection." The four crossings after it show how differently the same event can land.

<center><sup>GeminIQ Calculated Metrics showing GoPro's Free Cash Flow (TTM) crossing from -$78.964 Million to +$69.182 Million in Q3 2020, the end of a 17-quarter negative stretch.</sup></center>

[3M](/stocks/MMM) and [Coca-Cola](/stocks/KO) crossed in the exact same quarter — Q3 2025 — and neither one needed much of a streak to get there. Both had been negative for just two consecutive quarters: 3M's Free Cash Flow (TTM) went from **-$1.983 Billion** to **+$1.588 Billion**, and Coca-Cola's went from **-$722 Million** to **+$5.570 Billion**. Two of the steadiest cash generators in the market, both briefly underwater, both back positive within half a year. The market's response was proportionate to how unremarkable the dip actually was: 3M moved **+1.00%** in the first month and drifted to **-0.41%** by month three; Coca-Cola stayed close to flat the whole way, **+1.74%** then **+1.52%**. Neither reaction looked anything like GoPro's — because neither crossing was resolving four years of doubt about the business.

[Devon Energy](/stocks/DVN) shows the limit of what "held" actually promises. Devon crossed positive in Q1 2015 after **18** consecutive negative quarters, with Free Cash Flow (TTM) swinging from **-$481 Million** to **+$5.288 Billion** — and by the four-quarter fundamentals test, it held. The market did not care. The stock fell **-3.35%** in the first month and was down **-26.52%** by month three, because the crossing landed in the middle of a collapsing oil price that no single quarter of cash flow data was going to offset. Held and rewarded are two different questions, and this is the cleanest case in the dataset where they came apart.

[AMERCO](/stocks/UHAL), U-Haul's parent, runs the opposite mismatch. AMERCO crossed positive in its December 2020 quarter after **30** consecutive negative quarters, then relapsed back negative within the next four — the same outcome that dragged the relapsed bucket's median down to flat. Its own stock didn't get the memo: **+19.23%** in the first month, **+23.58%** by month three. A relapse in the data and a rally in the price, at the same time, in the same filing.

## How the First FCF Crossing Was Identified

None of those five names are outliers picked to flatter the finding — they're what the same dataset looks like at the individual-company level, including the ones where the four-quarter fundamentals test and the market's verdict pulled in opposite directions. This universe excludes financial-sector issuers — banks, insurers, broker-dealers — entirely. Their Operating Cash Flow reflects trading-book and deposit financing activity, not the kind of operating cash a non-financial company generates. An early pass at this study confirmed why: [Goldman Sachs](/stocks/GS) alone produced 25 sign crossings in Free Cash Flow (TTM), from swings in the tens of billions per quarter, none of which had anything to do with an "inflection" in the ordinary sense.

Free Cash Flow (TTM) is GeminIQ's pre-calculated metric — Operating Cash Flow (TTM) minus Capital Expenditures (TTM), built from the as-filed cash flow statement. The dataset counts only each company's first-ever crossing from negative to positive; later crossings for the same company are excluded so repeat flippers don't crowd the sample. Roughly **61%** of identified crossings are left-censored, meaning the negative run extends back to the start of that company's available filing history. The true pre-crossing duration may be longer than the data shows for those cases. They're included in the return buckets, since the crossing event itself is still fully observed, but excluded from any streak-length comparison. Full methodology, including the winsorization and base-rate rules applied throughout, is covered in [filing data study methodology](/blog/filing-data-study-methodology).

## How to Check a Crossing in Your Own Holdings

Open any company you're tracking in [Calculated Metrics](/features#calculated-metrics) and pull [Free Cash Flow](/metrics/calculated-values/free-cash-flow) (TTM) across its last eight quarters. If it just turned positive after a run of negative readings, this study says the crossing itself isn't the finding — what happens over the next four quarters is. Before assuming a turnaround, open the [Financial Statements](/features#financial-statements) view for that same stretch and check what actually moved. Look for a genuine improvement in operating cash flow, not a one-time drop in capital expenditures that simply delayed spending into a future quarter. The first kind of crossing tends to hold. The second kind is exactly what this data calls a relapse waiting to happen.

## Frequently Asked Questions

### What is a free cash flow inflection point?

It is the quarter a company's trailing-twelve-month Free Cash Flow first crosses from negative to positive after a run of negative readings. This study counts only each company's first-ever crossing; later crossings for the same company are excluded so repeat flippers don't crowd the sample.

### How many free cash flow crossings does this study cover?

**15,067** companies were scanned, producing **4,491** first crossings filed between March 2010 and June 2026. The bucket analysis runs on the **2,076** of those that carry both a resolved four-quarter held-or-relapsed outcome and a clean three-month post-filing return — **1,092** that held and **984** that relapsed.

### Does a first positive free cash flow quarter mean the turnaround is real?

Not on its own. Crossings that held positive for four quarters were followed by a median three-month return of **+4.11%** and were positive **59.4%** of the time; crossings that relapsed within four quarters returned a median **+0.00%** and were positive just **46.5%** of the time. That is a historical association measured over the 2010–2026 window, not a forecast — a working-capital swing, an asset sale, or a light capex quarter can produce a crossing that looks identical on filing day to one built on a durable improvement.

### Why does this study report the median rather than the mean?

Because the mean is distorted. The raw mean three-month return in the relapsed bucket is **+484.98%**, driven by a handful of penny-stock and micro-cap filings that ripped higher for reasons unrelated to their cash flow statement. Winsorized at the top and bottom 1% it falls to **+6.72%**, still far from the **+0.00%** median. When the two disagree by that much after trimming, the median is the number describing the typical filing.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=free-cash-flow-inflection)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 15,067 companies scanned for a first negative-to-positive Free Cash Flow (TTM) crossing, drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Financial-sector issuers (SIC 6000–6799) were excluded before crossings were computed. Free Cash Flow (TTM) is GeminIQ's pre-calculated metric (Operating Cash Flow TTM minus Capital Expenditures TTM), built from the as-filed cash flow statement. 4,491 first crossings were identified, filed March 2010 through June 2026; the bucket analysis uses the 2,076 crossings carrying both a resolved four-quarter held/relapsed outcome and a three-month post-filing return. Approximately 61% of identified crossings are left-censored (the negative run extends to the start of the company's available filing history) and are included in the return buckets but excluded from streak-length comparisons. Post-filing returns are cumulative from each filing's filed date, winsorized at the top and bottom 1%, and never compounded. The universe base rate (+3.49% mean / +2.36% median three-month return) is reused from GeminIQ's prior study of 76,908 filings, December 2004–June 2026, covered in [revenue growth slowdown and stock returns](/blog/revenue-growth-slowdown-stock-returns). Methodology: [filing data study methodology](/blog/filing-data-study-methodology).</sup>

---

## Blog: GameStop Q1 2026 10-Q: The $4 Billion Debt Nobody Priced In
source: https://www.geminiq.com/blog/gamestop-10q-analysis-q1-2026

### GameStop Q1 2026 10-Q: The $4 Billion Debt Nobody Priced In
GameStop's Q1 FY2026 10-Q shows a materially different balance sheet than the 'zero debt' story that made the rounds last year — $4.17 billion in convertible notes, real dilution risk, and an institutional base that's been shrinking, not accumulating.

**[GameStop](/stocks/GME) Corp. ($GME) just dropped its Q1 FY2026 10-Q (filed June 11, 2026). The financial media spent years calling this a dying retailer. Then a "debt-free $9 billion war chest" narrative took over, with GameStop cast as a quiet acquisition vehicle waiting to strike. The raw filing data tells a third story: the company has real debt now, real dilution risk attached to it, and an institutional base that's been shrinking for a year, not accumulating.**

| Field      | Value             |
| ---------- | ----------------- |
| Ticker     | $GME              |
| Filing     | Q1 FY2026 10-Q    |
| Filed      | June 11, 2026     |
| Period End | May 2, 2026       |
| Total Debt | **$4.17 Billion** |
| ROIC (TTM) | **25.1%**         |

## The Debt That Wasn't Supposed to Exist

For years, [GameStop's](/stocks/GME) balance sheet genuinely did carry close to zero debt. That changed in 2025, and the shift doesn't show up in most retail coverage of this name.

**The Data:** [GameStop](/stocks/GME) closed two rounds of 0.00% Convertible Senior Notes in 2025 — **$1.5 Billion** due 2030 (closed April 1, 2025) and **$2.25 Billion** due 2032 (closed June 17, 2025). Combined, the raw Balance Sheet shows **Long-Term Debt** of **$4.17 Billion** as of this filing, up from total debt of just **$16.90 Million** as recently as January 2025 (**$6.6 Million** of long-term notes payable plus **$10.3 Million** of current maturities). Against **$7.41 Billion** in cash, that still nets out to **$3.25 Billion** in net cash — a real cushion, just not a debt-free one.

**The GeminIQ Edge:** A screener that only reports a single "debt" figure would have missed both the near-zero baseline and this year's shift entirely. Pulling the raw [Financial Statements](/features#financial-statements) shows the exact instruments — Long-Term Notes Payable, not a revolving credit facility or legacy retail debt — which matters, because these notes carry conversion terms, not just a repayment schedule.

<center><sup>GeminIQ Financial Statements showing GameStop's Total Debt rising from $16.90 Million (January 2025) to $4.17 Billion (Q1 FY2026), against $7.41 Billion in Cash And Cash Equivalents At Carrying Value, for Net Debt of -$3.25 Billion.</sup></center>

## The Dilution Math Nobody's Pricing In

Convertible notes aren't ordinary debt. GameStop's specific notes convert into stock, at a set price, if the holder chooses — and that math is already showing up in the share count.

**The Data:** [GameStop's](/stocks/GME) diluted share count sits at **592.3 Million**, against **448.4 Million** basic shares — a gap of roughly **32%**. The 2030 notes alone carry an initial conversion price near **$29.85** per share. GameStop's cover page also lists **Warrants to Purchase Common Stock** (ticker GME WS) as a separately registered, NYSE-listed security.

**The GeminIQ Edge:** Most retail coverage quotes market cap or share count off the basic figure, understating the real ownership dilution baked into the capital structure. GeminIQ's [Financial Statements](/features#financial-statements) surfaces both share counts side by side, so the gap is visible rather than buried in a footnote.

<center><sup>GeminIQ Financial Statements showing GameStop's diluted share count of 592.3 Million against 448.4 Million basic shares, a roughly 32% gap tied to the convertible notes' conversion terms.</sup></center>

## What's Actually Working

None of the debt or dilution story changes the fact that [GameStop's](/stocks/GME) underlying business has genuinely turned a corner.

**The Data:** Quarterly net income hit **$389.6 Million** in Q1 FY2026, up from **$44.8 Million** in the same quarter last year. GeminIQ's pre-calculated [ROIC](/blog/roic-return-on-invested-capital-explained) (TTM) sits at **25.1%**, a sharp recovery from **negative 11.2%** as recently as the October 2024 quarter.

**The GeminIQ Edge:** A GAAP-only view would blend interest income from the cash pile with core retail performance into one number. Pulling [Calculated Metrics](/features#calculated-metrics) alongside the raw Income Statement shows this isn't just interest income padding the total — the turn to positive ROIC predates most of the 2025 capital raise. The collectibles and trading-card pivot the company has talked about is showing up in the numbers, independent of the war chest.

<center><sup>GeminIQ Calculated Metrics showing GameStop's ROIC (TTM) recovering from -11.2% (October 2024) to 25.1% (Q1 FY2026), alongside quarterly net income of $389.6 Million, up from $44.8 Million a year earlier.</sup></center>

## Institutional Money Is Leaving, Not Accumulating

The "smart money is quietly accumulating" story around [GameStop](/stocks/GME) doesn't hold up against the most recent 13F data.

**The Data:** [Institutional Ownership](/features#institutional-ownership) peaked at **38.7%** in the June 2025 quarter and has fallen in every reading since, down to **33.4%** as of the most recent 13F (March 2026, filed with the standard 45-day lag).

**The GeminIQ Edge:** A single point-in-time ownership figure can support almost any narrative. Pulling the full trailing trend via GeminIQ's [Institutional Ownership](/features#institutional-ownership) tracker instead of one quarter shows a year of net outflows, not accumulation — the opposite of what circulated when the capital raise first happened.

<center><sup>GeminIQ Institutional Ownership tracker showing institutional ownership declining from a 38.7% peak (June 2025) to 33.4% as of the most recent 13F (March 2026).</sup></center>

## The Insiders Are (Mostly) Still Buying

Insider activity is the one piece of this story that mostly held up under verification — with one correction.

**The Data:** [GameStop's](/stocks/GME) [Insider Transactions](/features#insider-transactions) feed shows Ryan Cohen, Lawrence Cheng, and Alain Attal have made open-market purchases only, every year, going back to 2020-2022. Cohen alone has bought roughly **$71.4 Million** across seven separate purchases. CFO Jim Grube, sometimes grouped with this same cohort, has one purchase on record (June 2025) and one sale (June 2021) — not the unbroken buying pattern sometimes attributed to him.

**The GeminIQ Edge:** GeminIQ's Insider Transactions feed pulls every Form 4 individually rather than a pre-summarized "insider sentiment" score, which is the only way to catch a detail like the Grube correction. Separately, and outside what any filing discloses: press reports this spring linked GameStop to a roughly $56 billion non-binding bid for eBay, which eBay reportedly rejected, and reported that Michael Burry — an investor who had publicly compared GameStop's setup to early Berkshire Hathaway — exited his position citing leverage concerns tied to that specific deal. The insiders are still buying. The one prominent bull who compared this to Buffett's early Berkshire isn't anymore. Both are true at the same time, and neither is something a filing discloses.

<center><sup>GeminIQ Insider Transactions tracker showing Ryan Cohen, Lawrence Cheng, and Alain Attal's purchase-only history since 2020-2022, alongside Jim Grube's single 2021 sale.</sup></center>

## Frequently Asked Questions

### What does GeminIQ's data show about GameStop's debt?

GameStop's Q1 FY2026 10-Q shows $4.17 billion in Long-Term Debt, almost entirely 0.00% Convertible Senior Notes issued in 2025 ($1.5 billion due 2030, $2.25 billion due 2032). This is a substantial change from the near-zero debt GameStop carried as recently as January 2025.

### Does GameStop's convertible debt create real dilution risk?

Based on the filing data, yes, potentially. GameStop's diluted share count (592.3 million) already runs about 32% above its basic share count (448.4 million), reflecting the shares the convertible notes and other instruments could convert into.

### When did GameStop last file its 10-Q, and what period does it cover?

GameStop's most recent filing is a Form 10-Q filed June 11, 2026, covering the fiscal quarter ended May 2, 2026 (Q1 FY2026).

### Where can I verify GameStop's debt figures against the original filing?

The figures are drawn directly from GameStop's Q1 FY2026 10-Q balance sheet, filed with the SEC on June 11, 2026. The full filing is publicly available on SEC EDGAR (linked in the citation block below).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gamestop-10q-analysis-q1-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference GameStop Corp.'s Q1 FY2026 10-Q (filed June 11, 2026, period ending May 2, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1326380/000132638026000025/gme-20260502.htm).

---

## Blog: GameStop Before the Squeeze: Enterprise Value Went Negative
source: https://www.geminiq.com/blog/gamestop-fundamentals-before-squeeze

### GameStop Before the Squeeze: Enterprise Value Went Negative
GameStop before the squeeze was a collapsing retailer with a strengthening balance sheet. This forensic study reads 17 consecutive 10-K and 10-Q filings from April 2018 to March 2022 to show that total debt fell 70.6% to $241.0 Million while the market priced the enterprise at $321.0 Million, and that at the July 2020 quarter close GeminIQ's Enterprise Value for the company read negative $247.0 Million.

<center><sup>GeminIQ data study: GameStop's total debt and filed cash balance against its quarter-end market capitalization, April 2018 through October 2020. Built from as-filed 10-K/10-Q data via GeminIQ. n = 17 filings, 2018–2022.</sup></center>

**[GameStop](/stocks/GME) Corp. ($GME) closed the January 2021 quarter at a market capitalization of $21.13 Billion. Nine months earlier the same company was worth $369.6 Million. The story that hardened around that move is that fundamentals had nothing to do with it, that GameStop was a dying retailer priced for bankruptcy and the filings were beside the point. Half of that is true and the filings confirm it: revenue fell from $8,607.9 Million to $5,089.8 Million across four fiscal years, and goodwill went to zero. The other half does not survive the documents. Across the same stretch, GameStop retired 70.6% of its total debt, and at the July 2020 quarter close the market valued its entire operating business at negative $247.0 Million. The bankruptcy thesis was not contradicted by a forum. It was contradicted by the balance sheet, in filings published months before anything happened to the price.**

| Study Scope | Detail |
|---|---|
| Company | GameStop Corp. ($GME) |
| Filing window | April 2018 – March 2022, 17 filings |
| Filing types | 10-K and 10-Q, as filed |
| Insider records | 23 Form 4 records in window |
| Outcome examined | Quarter-end market capitalization from **$260.7 Million** (July 2020) to **$21.13 Billion** (January 2021) |
| Forward-return window | 1–3 months after each 10-Q; 12 months after each 10-K |

Every figure below comes from GameStop's own filings, read in the order they reached EDGAR and joined to how the stock traded in the one to twelve months afterward. A [10-Q](/blog/10-k-vs-10-q-differences-explained) carries roughly three months of post-filing reaction; a 10-K carries twelve. These periods predate the three-year window shown on GeminIQ's stock pages and were pulled from the full as-filed history. GameStop's price series is split-adjusted for the four-for-one split of July 2022; Form 4 prices are shown as filed and are not.

**At the July 31, 2020 quarter close, GameStop's Enterprise Value read -$247.0 Million: $735.1 Million of cash and $23.5 Million of restricted cash against a $260.7 Million market capitalization and $250.9 Million of total debt. Over the same year, aggregated [13F filings](/blog/how-to-read-13f-filing) reported more GameStop shares than GameStop had issued — 122.62% of shares outstanding at March 2020, and above 100% for four consecutive quarters.**

## GameStop Revenue Fell 40.9% and Goodwill Went to Zero

The retailer was dying, and the filings say so without hedging. Nothing in this study argues otherwise.

**The Filing Data:** GameStop's annual Revenues fell from **$8,607.9 Million** in the fiscal year ended January 2017 to **$8,547.1 Million**, then **$8,285.3 Million**, then **$6,466.0 Million**, and finally **$5,089.8 Million** in the year ended January 2021 — a decline of **40.9%** across four years. Operating Income Loss went from a positive **$557.7 Million** to **-$702.0 Million**, **-$399.6 Million**, and **-$237.8 Million**. Asset Impairment Charges ran **$395.1 Million**, then **$1,015.9 Million**, then **$385.6 Million** across three consecutive years. Goodwill Impairment Loss took **$970.7 Million** and then **$363.9 Million**, carrying Goodwill from **$1,725.2 Million** down to **$0.0 Million** by January 2020.

**The Signal:** A company that writes its entire goodwill balance to zero is stating in an SEC filing that the acquisitions behind it will not produce the cash they were bought for. Stockholders Equity fell from **$2,254.1 Million** to **$436.7 Million** over the same four years. The bear case had a documentary basis and it was right about the income statement. It was wrong about the only claim the price was actually making.

<center><sup>GeminIQ Financial Statements showing GameStop's Revenues falling from $8,607.9 Million to $5,089.8 Million across four fiscal years alongside Asset Impairment Charges of $395.1 Million, $1,015.9 Million, and $385.6 Million.</sup></center>

## GameStop Total Debt Fell 70.6% to $241.0 Million

A stock priced for insolvency implies obligations the company cannot meet. GameStop spent the entire decline making that harder to argue.

**The Filing Data:** At January 31, 2019, GameStop carried Long Term Debt Current of **$349.2 Million** and Long Term Notes Payable of **$471.6 Million**, for total debt of **$820.8 Million** — the peak in this window. Twenty-one months later, at October 31, 2020, the balance sheet showed Lines Of Credit Current of **$25.0 Million** and Long Term Debt Noncurrent of **$216.0 Million**, for total debt of **$241.0 Million**. The company retired **$579.8 Million** of borrowings, **70.6%** of the peak, while its revenue was still falling. The cash flow statements show how: Repayments Of Long Term Debt of **$404.5 Million** in the year ended January 2020 and a further **$130.3 Million** the year after.

**The Signal:** GeminIQ's [Total Debt](/metrics/calculated-values/total-debt) reads **$241.0 Million** at that quarter and reconciles exactly to the two filed line items above, which matters because the same balance sheet also carried Operating Lease Liability Current of **$212.9 Million** and Operating Lease Liability Noncurrent of **$456.7 Million**. The lease obligations were larger than the borrowings. A reader working from a single summary debt figure sees neither the composition nor the direction. The direction was down, quarter after quarter, through the worst of the decline.

<center><sup>GeminIQ Calculated Metrics showing GameStop's Total Debt falling from $820.8 Million at January 2019 to $241.0 Million at October 2020, a reduction of 70.6%.</sup></center>

## GameStop's Enterprise Value Read Negative $247.0 Million in July 2020

Deleveraging into a collapsing top line is a defensible thing to be skeptical about. Pricing the operating business at less than nothing is a different claim, and the filings date exactly when the market made it.

**The Filing Data:** At the July 31, 2020 quarter close, [GameStop's](/stocks/GME) market capitalization was **$260.7 Million**. The balance sheet in the 10-Q filed September 9, 2020 showed Cash And Cash Equivalents At Carrying Value of **$735.1 Million**, plus Restricted Cash Current of **$11.0 Million** and Restricted Cash Noncurrent of **$12.5 Million**, against total debt of **$250.9 Million**. GeminIQ's [Enterprise Value](/metrics/valuation-metrics/enterprise-value) for that quarter reads **-$247.0 Million**. Trailing twelve-month free cash flow was **$320.9 Million**, putting the [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) at **123.12%**.

**The Signal:** The cash balance alone was **2.8 times** the entire equity value. An acquirer paying every shareholder in full and assuming every borrowing would have been handed more cash than the transaction cost. That is what a negative enterprise value means, and it is computed from three filed numbers with no assumptions in it. The market was not pricing a hard fundamental question about whether the retailer would shrink. It was pricing a solvency outcome the balance sheet did not describe.

<center><sup>GeminIQ Calculated Metrics showing GameStop's Enterprise Value of -$247.0 Million at the July 2020 quarter against a market capitalization of $260.7 Million and Free Cash Flow Yield of 123.12%.</sup></center>

## GameStop's Altman Z-Score Never Fell Below 1.9755

If the market was pricing bankruptcy, the standard academic measure of bankruptcy risk should have agreed with it.

**The Filing Data:** GeminIQ's [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) for GameStop reads **2.4765** at January 2019, **1.9755** at July 2019, **2.4280** at January 2020, **2.4831** at July 2020, and **2.1816** at October 2020. Across the entire window its lowest reading was **1.9755**. The conventional distress threshold sits at **1.81**, with the grey zone running from there to **2.99**.

**The Signal:** GameStop spent three years in the grey zone and never crossed into the distress zone, in a period when its equity traded at a [Price-to-Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) of **0.0466**. The Z-Score is not a forecast and a grey-zone reading is not an all-clear — it is a statement that the five filed inputs did not combine into a distress signature. The market's implied verdict and the model's computed one had been diverging for two full years by the time this mattered. Anyone could have run the comparison from public documents.

<center><sup>GeminIQ Calculated Metrics showing GameStop's Altman Z-Score across 2018 to 2020, with a floor of 1.9755 at July 2019 against a distress threshold of 1.81.</sup></center>

## The 10-Q Filed December 8, 2020: $445.9 Million Cash Against $241.0 Million Debt

One document sits directly on the fault line. It was published seven weeks before the January move and it contained no surprises at all.

**The Filing Data:** The 10-Q for the quarter ended October 31, 2020, filed December 8, 2020, reported quarterly Revenues of **$1,004.7 Million** and an Operating Income Loss of **-$63.0 Million** against a Net Income Loss of **-$18.8 Million**. The balance sheet showed Cash And Cash Equivalents At Carrying Value of **$445.9 Million**, with a further **$140.7 Million** in Restricted Cash Current and **$16.0 Million** in Restricted Cash Noncurrent. Against that sat Lines Of Credit Current of **$25.0 Million** and Long Term Debt Noncurrent of **$216.0 Million**. Total Stockholders Equity was **$332.2 Million** and Inventory Net was **$861.0 Million**. GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) for GameStop reads **-$361.6 Million**, a [net cash position](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) on a trailing basis was **$149.5 Million**.

**The Signal:** At that quarter's close the whole company was priced at **$682.6 Million**, with an Enterprise Value of **$321.0 Million** against trailing revenue of **$5,161.8 Million** and a [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) of **21.90%**. The [Current Ratio](/metrics/liquidity-ratios/current-ratio) was **1.0477**. Every one of those figures was published on December 8, 2020, in a document available to anyone with a browser. The filing did not predict what happened next and nothing in it could have. What it did do was describe a company holding more cash than debt, generating positive free cash flow, and priced as though neither were true.

<center><sup>GeminIQ Financial Statements showing GameStop's October 2020 balance sheet — Cash And Cash Equivalents At Carrying Value of $445.9 Million against total debt of $241.0 Million and Total Stockholders Equity of $332.2 Million.</sup></center>

## GameStop Institutional Ownership Read 122.62%, Over 100% for Four Straight Quarters

There is one filing-sourced number that speaks directly to the mechanics everyone argued about afterward, and it is not short interest, which does not exist in XBRL at all.

**The Filing Data:** GeminIQ's [Institutional Ownership](/features#institutional-ownership) aggregate for [GameStop](/stocks/GME) reads **122.62%** at March 2020, **110.13%** at June 2020, **117.67%** at September 2020, and **113.06%** at December 2020. The underlying figures are **293,950,864** institutional shares reported at December 2020 against **260,000,000** shares outstanding. By March 2021 the reading falls to **38.95%** on **102,816,796** reported shares.

**The Signal:** Aggregated 13F filings reported more GameStop shares than GameStop had issued, for four consecutive quarters. That happens when shares are lent and both the lender and the buyer report holding them, so the aggregate double-counts. One caution governs the reading: 13F data is quarterly and arrives with a filing lag of up to 45 days, so it was never live, and the March 2021 collapse describes positions already weeks old when published. [Most platforms](/competitor-comparison/tikr) cap the figure at 100% or quietly normalize it away. GeminIQ shows what the filings add up to, because four consecutive quarters above **100%** is a structural fact about who held the stock, not a rounding artifact to be tidied.

<center><sup>GeminIQ Institutional Ownership showing GameStop's aggregated 13F reported shares exceeding shares outstanding across 2020, peaking at 122.62% in March 2020 and reading 113.06% in December 2020.</sup></center>

## Ryan Cohen's RC Ventures Bought 1,226,400 Shares in December 2020

What are the people actually running the company doing with their own money? For a five-week stretch spanning December 2020 and January 2021, the Form 4 record answers in two opposite directions.

**The Filing Data:** On December 17 and 18, 2020, RC Ventures LLC, Ryan Cohen's investment vehicle, filing as a ten percent owner, purchased **470,311** shares at **$14.77** and **756,089** shares at **$15.96** — **1,226,400** shares for **$19.01 Million**, carrying the reported position to **9,001,000** shares. Between January 12 and January 15, 2021, four directors filed seven sale records totaling **903,119** shares for **$20.16 Million**, at prices from **$19.99** to **$37.43**. Across all of 2019 and 2020, the only other purchases in the record are **six** small director buys in September 2019 totaling **$0.48 Million** at **$4.62** to **$5.38**, and buys by the Chief Executive Officer and Chief Financial Officer in April 2020 totaling **$0.14 Million**.

**The Signal:** Form 4 prices are as filed and predate the July 2022 four-for-one split, so the **$14.77** purchase corresponds to roughly **$3.69** on GeminIQ's adjusted price series (derived). The largest committed buyer and the sitting board moved in opposite directions inside five weeks, and both are visible in the raw feed with the [transaction code](/blog/form-4-transaction-code-list) on every line rather than collapsed into a single sentiment score. Ownership disclosures land with a lag and are never a live read, which makes this a hook rather than a trigger. The hook sends you back to the balance sheet, which is where the argument always was.

<center><sup>GeminIQ Insider Transactions showing GameStop's Form 4 record — RC Ventures purchasing 1,226,400 shares for $19.01 Million in December 2020 against 903,119 director shares sold for $20.16 Million in January 2021.</sup></center>

## Post-Filing Returns: +861.85% Twelve Months After the March 2020 10-K

The filings were followed by price behavior that bears no proportion to the news inside them, and the sequence is the point.

**The Filing Data:** The 10-K filed March 27, 2020 — the annual report carrying a **$470.9 Million** net loss and goodwill written to zero — was followed by cumulative returns of **+15.64%** at one month, **+11.85%** at three, and **-1.42%** at five. Then the curve breaks: **+81.28%** at six months, **+281.04%** at nine, and **+861.85%** at twelve. The 10-Q filed September 9, 2020 was followed by **+27.76%**, **+42.45%**, and **+118.78%**. The 10-Q filed December 8, 2020 was followed by **+11.22%** at one month and **+1,818.54%** at two (the late-January 2021 peak falls inside that two-month window), settling to **+500.59%** at three. The next annual report, filed March 23, 2021, was followed by **-33.13%** over twelve months.

**The Signal:** These are cumulative figures from each filing date, and they are historical associations for one company across a small number of filings — not a base rate, not a forecast, and not evidence that any filing caused anything. What the sequence establishes is timing. For five months after the worst annual report GameStop ever filed, the stock did approximately nothing. The balance sheet described in that document had already turned. The repricing arrived a full year later, and the twelve months after the market finally agreed produced **-33.13%**.

<center><sup>GeminIQ data study: cumulative post-filing returns for GameStop's 10-K filed March 27, 2020 and the 10-Qs filed September 9 and December 8, 2020. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 3 filings, 2020–2021.</sup></center>

## Three Filed Facts GameStop's 2020 Price Ignored

Three facts sat in public documents through the second half of 2020, and none of them required a thesis about anything.

Total debt had fallen from **$820.8 Million** to **$241.0 Million**, a **70.6%** reduction disclosed across eight consecutive filings. Enterprise Value had gone negative, reading **-$247.0 Million** at the July 2020 quarter close, when **$735.1 Million** of cash stood against a **$260.7 Million** market capitalization. And the Altman Z-Score, computed from five filed inputs, had never once entered the distress zone, bottoming at **1.9755** while the equity traded at **0.0466** times sales.

Against that, the retailer was still shrinking in fact, not just in narrative. Revenue fell **40.9%** in four years, equity fell from **$2,254.1 Million** to **$436.7 Million**, and goodwill went to zero. Both descriptions are accurate, and the market had committed to only one of them. The filings never said GameStop was a good business. They said it was a shrinking business that could pay its bills, and it was priced as a business that could not. That gap was published, timestamped, and free, in a 10-Q filed on December 8, 2020.

## Check Your Holdings

The calculation that flagged this takes three filed numbers and no forecast. Pull a company's market capitalization, add its total debt from the individually filed balance sheet lines rather than a single summary figure, and subtract cash and cash equivalents. The result is enterprise value — what the market is charging for the operating business after the cash and the borrowings net out. When that number approaches zero or goes below it, the market is pricing the business itself at nothing, and the claim is precise enough to check.

Then divide trailing free cash flow by market capitalization. A company with a negative enterprise value and positive free cash flow is a [specific and rare configuration](/screens), and it is the one GameStop occupied at the July 2020 quarter close. In GeminIQ, both figures already sit in the same [Calculated Metrics](/features#calculated-metrics) table as [Enterprise Value](/metrics/valuation-metrics/enterprise-value) and [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield), computed across a company's full filing history rather than the most recent quarter. Sort by period end and read down the two columns together. Where they diverge, the market and the balance sheet are telling different stories, and only one of them is sourced.

## Frequently Asked Questions

### What was GameStop's enterprise value in 2020?

Negative. At the July 31, 2020 quarter close, GeminIQ's [Enterprise Value](/metrics/valuation-metrics/enterprise-value) for GameStop reads **-$247.0 Million**. It is computed from figures in the 10-Q filed September 9, 2020: a market capitalization of **$260.7 Million** plus total debt of **$250.9 Million**, less Cash And Cash Equivalents At Carrying Value of **$735.1 Million**, Restricted Cash Current of **$11.0 Million** and Restricted Cash Noncurrent of **$12.5 Million**. By the October 2020 quarter close the reading was positive again at **$321.0 Million**.

### Why did GameStop's institutional ownership read over 100%?

Because aggregated 13F filings reported more GameStop shares than GameStop had issued. GeminIQ's [Institutional Ownership](/features#institutional-ownership) aggregate reads **122.62%** at March 2020, **110.13%** at June 2020, **117.67%** at September 2020 and **113.06%** at December 2020 — **293,950,864** institutional shares reported at December 2020 against **260,000,000** shares outstanding. That happens when shares are lent and both the lender and the buyer report holding them, so the aggregate double-counts. 13F data is quarterly and arrives with a filing lag of up to 45 days, so it was never a live read.

### Was GameStop actually at risk of bankruptcy in 2020?

The standard academic measure of bankruptcy risk did not say so. GeminIQ's [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) for GameStop bottomed at **1.9755** in July 2019 and never crossed the conventional distress threshold of **1.81**, spending the window in the grey zone that runs from **1.81** to **2.99**. The Z-Score is not a forecast and a grey-zone reading is not an all-clear — it is a statement that the five filed inputs did not combine into a distress signature. The underlying business was contracting for real: revenue fell **40.9%** in four years and goodwill went to **$0.0 Million**.

### How much debt did GameStop pay off before the squeeze?

**$579.8 Million**, or **70.6%** of the peak. Total debt fell from **$820.8 Million** at January 31, 2019 — Long Term Debt Current of **$349.2 Million** plus Long Term Notes Payable of **$471.6 Million** — to **$241.0 Million** at October 31, 2020, being Lines Of Credit Current of **$25.0 Million** and Long Term Debt Noncurrent of **$216.0 Million**. The cash flow statements show Repayments Of Long Term Debt of **$404.5 Million** in the year ended January 2020 and a further **$130.3 Million** the year after. Operating lease liabilities of **$212.9 Million** current and **$456.7 Million** noncurrent sat alongside and were larger than the borrowings.

### What did GameStop's last balance sheet before January 2021 show?

The 10-Q for the quarter ended October 31, 2020, filed December 8, 2020, reported Cash And Cash Equivalents At Carrying Value of **$445.9 Million**, Restricted Cash Current of **$140.7 Million** and Restricted Cash Noncurrent of **$16.0 Million**, against Lines Of Credit Current of **$25.0 Million** and Long Term Debt Noncurrent of **$216.0 Million**. Total Stockholders Equity was **$332.2 Million**, Inventory Net was **$861.0 Million**, and the [Current Ratio](/metrics/liquidity-ratios/current-ratio) was **1.0477**. GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) reads **-$361.6 Million** — a net cash position — with trailing [Free Cash Flow](/metrics/calculated-values/free-cash-flow) of **$149.5 Million**.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures in this article are drawn from GameStop Corp.'s 10-K and 10-Q filings, filed April 2018 through March 2022 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001326380&type=10-K). Insider figures are drawn from Form 4 filings and institutional figures from aggregated Form 13F filings over the same period.</sup>

---

## Blog: GARP Investing: Peter Lynch's PEG Ratio Strategy Explained
source: https://www.geminiq.com/blog/garp-investing-peter-lynch-explained

### GARP Investing: Peter Lynch's PEG Ratio Strategy Explained
GARP investing — Growth at a Reasonable Price — is Peter Lynch's framework for finding companies with strong earnings growth at moderate P/E multiples. This guide explains how the PEG ratio works, where most GARP screens fail, and how to run the screen correctly using as-filed SEC data.

Peter Lynch ran the Magellan Fund at Fidelity from 1977 to 1990, generating approximately **29%** average annual returns over that period. He did not do it by buying the cheapest stocks in the market or by chasing the fastest-growing ones. He did it by finding growth companies that were not priced for perfection — businesses expanding earnings at double-digit rates while trading at P/E multiples that did not reflect that trajectory. He called this Growth at a Reasonable Price, and the heuristic he built around it — the PEG ratio — remains the most widely cited growth-adjusted valuation tool in equity analysis. The framework is sound. The problem is the inputs. Most investors running GARP screens today are not running them on the data Lynch was using. They are running them on adjusted, normalized earnings that financial aggregators process before the figures ever reach a screening tool — and that processing changes which companies show up as GARP candidates. This guide covers how GARP investing works, where the PEG ratio breaks, and how to run the screen correctly on clean, as-filed SEC data.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=garp-investing-peter-lynch-explained)**

---

## Table of Contents

- [What Is GARP Investing?](#what-is-garp-investing)
- [The PEG Ratio: GARP's Central Tool](#the-peg-ratio-garps-central-tool)
- [GARP vs. Pure Growth vs. Pure Value](#garp-vs-pure-growth-vs-pure-value)
- [Why Most GARP Screens Return the Wrong Results](#why-most-garp-screens-return-the-wrong-results)
- [How to Run the GARP Screen in GeminIQ](#how-to-run-the-garp-screen-in-geminiq)
- [Reading Your Results: What to Verify Beyond the Filters](#reading-your-results-what-to-verify-beyond-the-filters)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is GARP Investing?

Growth at a Reasonable Price is an investment philosophy that rejects the binary choice between pure growth and pure value. Lynch's argument was practical: the best companies to own are ones growing earnings consistently at high rates, but only if you are not paying an irrational premium for that growth. A company growing at **25%** per year is a great business — but if investors have already priced in five years of that growth, the stock will disappoint even as the business thrives. GARP investors look for companies where the market has not yet fully recognized the growth trajectory, meaning the P/E multiple remains moderate relative to the earnings growth rate.

Lynch developed this thinking during his tenure at Magellan, and his results were extraordinary. Over 13 years, he turned an **$18 million** fund into a **$14 billion** one. The strategy was not mechanical — Lynch was a fundamentally qualitative investor who read thousands of annual reports and visited companies directly — but the PEG ratio was his numerical shorthand for filtering the investment universe down to businesses worth investigating. Any company where the growth rate substantially exceeded the P/E multiple was worth a closer look. Any company where the multiple was more than double the growth rate was, in his view, priced for perfection.

GARP is not an academic framework with a formal derivation. Greenblatt's Magic Formula has a specific ranking methodology and a documented backtest. Graham's net-net strategy has a precise NCAV formula. GARP is a heuristic — a rule of thumb that captures a reasonable intuition about how to balance growth and valuation. Its empirical record outside of Lynch's specific period is mixed, which matters. But the underlying logic — that you should receive something in return for the premium you pay for a growth company — is difficult to argue against. Strategies that fail tend to do so by ignoring either the quality of the growth or the reasonableness of the price paid for it.

---

## The PEG Ratio: GARP's Central Tool

The PEG ratio divides the [P/E Ratio](/metrics/valuation-metrics/price-to-earnings-ratio) by the [EPS Growth Rate](/metrics/growth-metrics/earnings-per-share-growth). Its purpose is to normalize valuation for the growth rate — making it possible to compare a company growing at **30%** with one growing at **8%** on a consistent basis.

**Formula:** PEG Ratio = P/E Ratio ÷ EPS Growth Rate (%)

Lynch's benchmarks were direct: a PEG below **1.0** indicated a company growing faster than its P/E multiple implied, which he considered an attractive entry point. A PEG above **2.0** indicated a company where the growth premium had become excessive. The intuition is simple: if a company grows earnings at **20%** annually, a P/E of **20x** is "reasonable" — you are paying one dollar of multiple for each percentage point of growth. A P/E of **40x** for the same company is not.

Consider two companies to see why this matters in practice. Company A earns **$2.00** per share, trades at **$30** (P/E of **15x**), and is growing earnings at **15%** annually. PEG = **15 ÷ 15 = 1.0** — Lynch's fair value. Company B earns **$1.00** per share, trades at **$50** (P/E of **50x**), and is growing earnings at **20%** annually. PEG = **50 ÷ 20 = 2.5** — Lynch's danger zone. On pure growth rate, Company B wins. On P/E, Company B is far more expensive. The PEG normalizes both inputs and reveals that despite Company B's faster growth, investors are paying a substantially higher premium per unit of that growth.

The PEG ratio has three known limitations worth internalizing before applying it. First, it treats the relationship between P/E and growth as linear when compounding is nonlinear — a company compounding at **30%** is not simply three times as valuable per unit of multiple as one compounding at **10%** over a long horizon. Second, different implementations use different growth rate periods — trailing one-year, trailing three-year, forward consensus estimates — and that choice moves the PEG ratio substantially for individual companies. Third, and most importantly, PEG does not measure the quality or sustainability of growth. A company growing EPS at **20%** through aggressive share buybacks at a stagnant business is treated identically to one growing earnings organically at **20%** on rising revenue. Those are not the same investment, and the PEG ratio cannot distinguish between them. None of these limitations invalidate PEG as a screening tool. They mean it must be used as a starting point — a filter that reduces the universe — rather than a final verdict on cheapness.

---

## GARP vs. Pure Growth vs. Pure Value

Even with those limitations, the PEG ratio does something pure growth and pure value investing both refuse to do: it forces a trade-off between price and growth instead of ignoring one of them entirely. Pure growth investing starts from the premise that the best businesses are worth owning regardless of price — that if you identify a company growing earnings at **40%** annually for a decade, the returns will be exceptional no matter what multiple you paid at entry. This is correct in hindsight for the biggest secular winners. It is catastrophically wrong at peaks. When consensus already expects five years of **40%** growth and discounts it into the current price, the stock becomes a hostage to growth expectations rather than growth itself. Any deceleration — even to a still-impressive **25%** — produces significant multiple compression. Pure growth investors suffered this destruction during the 2000 technology bust and again during the 2021–2022 growth drawdown.

Pure value investing starts from the premise that cheap is cheap — that a company trading at **6x** earnings is safer than one at **30x** regardless of what those earnings are doing. The empirical support for this view is substantial over very long time horizons: the Fama-French value factor is one of the most documented return premiums in academic finance. But value investing requires patience measured in years, tolerance for multi-year underperformance that most investors do not maintain, and a willingness to systematically miss secular growth businesses that appear expensive throughout their entire compounding phase. A pure value investor applying Graham's criteria in 2012 would not have owned [Apple](/stocks/AAPL) at any point during its extraordinary subsequent run — the multiple was never cheap enough to qualify.

GARP accepts lower upside than pure growth in exchange for a valuation cushion, and accepts lower apparent cheapness than pure value in exchange for actual earnings growth. The strategy does not identify the next Amazon at **10x P/E** or the next deep value turnaround at **0.5x** book. What it identifies is a class of businesses growing earnings at double-digit rates that are not yet priced for perfection — companies where the multiple has room to expand as growth continues and where the downside from multiple compression is bounded by the P/E ceiling.

The evidence for GARP specifically is harder to evaluate than for pure value or pure growth, because there is no single authoritative backtest of the framework the way there is for the Fama-French factors or for Greenblatt's [Magic Formula](/blog/magic-formula-investing-explained). Lynch's own record at Magellan is the primary empirical data point. It was extraordinary. But it was a single fund over a specific 13-year period, managed by a skilled stock picker who was not running a mechanical screen — GARP was his analytical instinct made explicit, not a strategy that could be passively replicated. What can be said is this: the underlying logic holds. Paying a moderate multiple for genuine, sustained earnings growth is a more defensible position than either extreme.

---

## Why Most GARP Screens Return the Wrong Results

GARP screens are more sensitive to data quality than almost any other systematic strategy, because the central input — the earnings growth rate — is precisely where aggregator platforms diverge most from the SEC filing data.

The core issue is how "earnings" gets defined. Lynch was working with reported GAAP earnings. The [EPS Growth](/metrics/growth-metrics/earnings-per-share-growth) rates he calculated came from as-filed income statements. Most aggregator platforms today use "adjusted" or "non-GAAP" EPS as the numerator — figures that strip out restructuring charges, stock-based compensation, impairment charges, and other items management would prefer analysts to set aside. Platforms rarely disclose this adjustment process, and no two aggregators apply it the same way. Two different aggregators applying their own normalization procedures to the same company's filing can produce materially different [adjusted EPS](/metrics/per-share-metrics/adjusted-eps) figures — and therefore materially different growth rates for the same company. The GARP screen you run on an aggregator is a different screen than one running on as-filed data. The companies that appear at the top of each list are not the same companies.

This gap matters for GARP in three specific ways. First, base effects on EPS growth. A company that took a large restructuring charge in the prior year will show artificially elevated [EPS Growth 1Y](/metrics/growth-metrics/earnings-per-share-growth) in the current year when measured off a depressed base — not because the business has actually accelerated, but because the prior-period figure was distorted by a one-time event. Aggregators applying adjusted EPS eliminate this base effect, smoothing the growth rate toward something that looks more like the underlying business trajectory. GeminIQ's [EPS Growth](/metrics/growth-metrics/earnings-per-share-growth) is computed from as-filed GAAP EPS, which preserves the base. That is not a bug — it is the feature. Checking the absolute EPS figure over multiple periods, not just the one-year growth rate, is how you distinguish a genuine compounder from a base-effect mirage.

Second, buyback-driven EPS growth. A company shrinking its share count through aggressive buybacks can show double-digit [EPS Growth](/metrics/growth-metrics/earnings-per-share-growth) with flat or even slightly declining [Net Income Growth](/metrics/growth-metrics/net-income-growth). The EPS figure rises as fewer shares divide the same earnings pool. This is real in an accounting sense, but it is a fundamentally different kind of growth than a company expanding revenue and margins. The [Net Revenue TTM Growth 1Y](/metrics/growth-metrics/revenue-growth) filter in GeminIQ's GARP screen addresses this directly: requiring revenue growth above **5%** ensures the top line is actually expanding, not just the per-share math. A standard screener running on normalized data may apply this filter too, but against a revenue figure that has itself been reclassified or smoothed. GeminIQ's [Revenue Growth](/metrics/growth-metrics/revenue-growth) uses as-filed revenue from the SEC filing — the unprocessed number.

Third, revenue recognition reclassifications. Companies that adopted ASC 606 — the updated revenue recognition standard — in 2018 and 2019 often showed apparent revenue growth or decline in the transition year that reflected an accounting reclassification rather than a genuine change in business volume. Platforms that normalized revenue templates to smooth the transition show continuity in the revenue series where the as-filed data shows a step change. GeminIQ's data follows the as-filed figures, which means the transition period is visible and traceable — exactly the kind of data hygiene that matters when revenue growth is functioning as a quality filter on an earnings-driven screen.

Standard financial media applies these adjustments so routinely that most investors do not know they exist. The inputs to the PEG ratio look clean. They are not.

---

## How to Run the GARP Screen in GeminIQ

GeminIQ's pre-configured [GARP Screener](/screens/stock-screeners/garp-screener) runs all four filters simultaneously on data extracted directly from XBRL-tagged SEC EDGAR filings. Open the screener and confirm the following filters are active:

| Filter | Operator | Value |
|--------|----------|-------|
| [EPS TTM Growth 1Y](/metrics/growth-metrics/earnings-per-share-growth) | ≥ | 10% |
| [Net Revenue TTM Growth 1Y](/metrics/growth-metrics/revenue-growth) | ≥ | 5% |
| [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) | between | 10 and 30 |
| [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) | ≥ | 1 |

The **10%** EPS growth floor reflects Lynch's minimum threshold — he was not interested in businesses growing at **3%** regardless of how moderate their P/E appeared. The **5%** revenue growth floor is the buyback check: it screens out companies where the entire EPS growth story is coming from share count reduction rather than business expansion. The P/E range of **10x to 30x** captures Lynch's "reasonable price" zone — a floor at **10x** screens out businesses in structural distress where the low multiple reflects genuine impairment, and a ceiling at **30x** enforces valuation discipline against businesses where years of future growth are already priced in. Set the Sort By to [EPS TTM Growth 1Y](/metrics/growth-metrics/earnings-per-share-growth), direction Descending, so the fastest-growing companies within the GARP valuation band appear first.

For investors focused on longer-duration compounders — companies sustaining growth across multiple years rather than a single strong period — add one additional filter:

| Filter | Operator | Value |
|--------|----------|-------|
| [EPS TTM Growth 3Y](/metrics/growth-metrics/earnings-per-share-growth) | ≥ | 8% |

This requires the trailing three-year earnings growth rate to also be positive and meaningful. A company posting **20%** EPS growth in the most recent year but **−5%** over three years is recovering from a bad period, not sustaining a compounding trajectory. The three-year filter distinguishes between them.

> **GeminIQ Tip:** The PEG ratio is not a native screener field, but it takes seconds to calculate manually from the results. Take the [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) figure and divide it by [EPS TTM Growth 1Y](/metrics/growth-metrics/earnings-per-share-growth) for each company in the [Custom Tables](/features#custom-tables) view. A P/E of **20x** with **20%** growth = PEG of **1.0**. A P/E of **25x** with **12%** growth = PEG of **2.1** — outside Lynch's preferred zone. This manual calculation identifies which screener results are genuinely within Lynch's PEG target range and which are sitting at the edges.

<center><sup>GeminIQ Stock Screener showing the GARP filter set: EPS TTM Growth 1Y ≥ 10%, Net Revenue TTM Growth 1Y ≥ 5%, P/E TTM between 10x and 30x, sorted by EPS TTM Growth 1Y descending. All inputs sourced directly from XBRL-tagged SEC filing data (`Earnings Per Share Basic`, `Revenues`, `Net Income Loss`).</sup></center>

---

## Reading Your Results: What to Verify Beyond the Filters

The screener returns a filtered universe. What it cannot do is evaluate whether the growth is real, durable, and of the quality Lynch was looking for. That evaluation requires pulling each company's data and asking several specific questions.

The first question is whether revenue and earnings growth are moving in the same direction. A company posting **15%** EPS growth with **6%** revenue growth is expanding margins — which is a positive sign, but finite. Margin expansion cannot continue indefinitely. A company posting **15%** EPS growth with **18%** revenue growth is expanding the business itself, which is a more durable foundation. GeminIQ's [Financial Statements](/features#financial-statements) view shows both trends across multiple filing periods simultaneously.

The second question concerns the absolute EPS trajectory, not just the one-year growth rate. A company that earned **$0.20** per share three years ago, **$0.50** two years ago, and **$1.00** last year is a different story than one that earned **$4.00**, fell to **$0.30** after a large impairment, then recovered to **$0.50**. Both could show high one-year EPS growth rates. They are not the same investment. GeminIQ's [Calculated Metrics](/features#calculated-metrics) panel shows [EPS Growth](/metrics/growth-metrics/earnings-per-share-growth) across one-year, three-year, and five-year periods simultaneously, making the trajectory visible without building a spreadsheet.

The third question is the share count trend. Pull GeminIQ's [Financial Statements](/features#financial-statements) and check Basic Shares Outstanding across the last eight quarters. If the share count is declining by **5–10%** annually, a meaningful portion of the EPS growth is coming from buybacks rather than operational expansion. That is not automatically disqualifying — Lynch owned companies doing buybacks — but it changes the character of the growth story and should affect how you weight the EPS growth figure in your manual PEG calculation.

The fourth question is whether the current growth rate is sustainable. The P/E ceiling at **30x** limits the damage if growth decelerates, but it does not eliminate it. A company at **28x P/E** growing at **15%** has a PEG of **1.87** — acceptable. If growth decelerates to **8%**, the PEG recalculates to **3.5** and the multiple will compress significantly. Understanding whether the drivers of growth are cyclical, structural, or tied to a single product cycle is the qualitative judgment no screen can make. Lynch's differentiation was his ability to evaluate growth durability, not just identify companies with current growth. The GeminIQ screen gets you to the right starting list. The work of verifying quality happens in the [Financial Statements](/features#financial-statements) view, one company at a time.

---

## Frequently Asked Questions

### What is a good PEG ratio?

Peter Lynch considered a PEG below **1.0** attractive — the company is growing earnings faster than its P/E multiple implies. A PEG between **1.0 and 2.0** is generally considered fair value for a growth company. Lynch treated a PEG above **2.0** as a signal that the stock is priced for perfection, meaning continued high execution is required to justify the current valuation at any growth rate that appears. These thresholds are heuristics, not hard rules — they should be evaluated alongside the quality and sustainability of the growth and the strength of the underlying balance sheet.

### Is GARP investing still viable today?

The GARP framework is viable, but the size of the investable universe narrows and widens with market conditions. In periods when growth stocks broadly command elevated multiples, finding companies that clear both the **10%** growth floor and the **30x** P/E ceiling simultaneously becomes harder. The screener result count reflects this directly. In periods of broader multiple compression — as happened in 2022 — the GARP universe expands as growth companies reprice toward more moderate valuations. The framework does not stop working; the available candidates change. When the screener returns a small universe, that is itself a signal about market pricing, not a failure of the methodology.

### What is the difference between GARP and the Magic Formula?

Both strategies combine a growth or quality element with a valuation element, but they use different metrics and different logic. GARP uses the P/E ratio as the valuation input and earnings growth rate as the quality input, combined via the PEG ratio. Greenblatt's [Magic Formula](/blog/magic-formula-investing-explained) uses EV/EBIT as the valuation input and [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) as the quality input, combined via composite ranking rather than division. GARP is focused on growth trajectory; the Magic Formula is focused on capital efficiency at a cheap price. They surface materially different companies. A business with high ROIC and low EV/EBIT will appear in the Magic Formula results; if it has slow earnings growth, it will not appear in GARP results. Understanding what each screen selects for is how you use them effectively together.

### Does GeminIQ calculate the PEG ratio directly?

GeminIQ does not include a native PEG ratio filter in the screener, because the PEG is most useful as a calculation performed on the filtered output rather than as a filter itself. The GARP screen's P/E and EPS growth filters implicitly constrain the PEG range: a company clearing the **10%** growth floor with a **30x** P/E ceiling has a maximum possible PEG of **3.0**, and a company growing at **25%** with a P/E of **15x** has a PEG of **0.6**. The manual calculation — [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) ÷ [EPS TTM Growth 1Y](/metrics/growth-metrics/earnings-per-share-growth) — takes seconds in GeminIQ's [Custom Tables](/features#custom-tables) view. What takes longer, and matters more, is making sure the P/E and growth figures feeding that calculation came from the filing rather than from someone else's adjustments.

---

### Related Reading

- [Magic Formula Investing Explained](/blog/magic-formula-investing-explained) — Greenblatt's strategy uses Return on Invested Capital and EV/EBIT earnings yield rather than PEG-based growth, offering a complementary systematic approach for identifying quality businesses at cheap prices.
- [Buffett Stock Criteria: Quality Business at a Fair Price](/blog/buffett-stock-criteria-quality-business) — Buffett's framework, like GARP, cares about growth sustainability and capital efficiency, but applies a qualitative overlay that Lynch's quantitative PEG ratio does not capture.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — FCF yield pairs naturally with GARP because it tests whether earnings growth is producing actual cash generation. A GARP candidate with high EPS growth but deteriorating FCF yield deserves additional scrutiny.
- [Piotroski F-Score: The Value Trap Filter](/blog/piotroski-f-score-value-trap) — the nine-point financial health checklist is a useful overlay on any screener output, including GARP results, to eliminate companies passing quantitative filters despite deteriorating fundamentals.
- [EV/EBITDA vs. P/E: Which Multiple to Use](/blog/ev-ebitda-vs-pe-ratio-explained) — P/E is GARP's primary valuation tool, but understanding its limitations — and when EV/EBIT or FCF yield provides a cleaner picture — makes the full GARP analysis more reliable.
- [Value Investing Glossary](/blog/value-investing-glossary) — plain-English definitions of every metric referenced in this post, including PEG ratio, P/E, earnings growth, and ROIC.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Gross Profit Margin: What It Reveals About Business Model Strength
source: https://www.geminiq.com/blog/gross-profit-margin-business-model-analysis

### Gross Profit Margin: What It Reveals About Business Model Strength
Gross profit margin is the structural fingerprint of a business model — the metric that reveals pricing power and competitive position before operating expenses enter the picture. This post covers the formula, benchmarks by industry sector, trend signals, and the COGS reclassification problem that makes the same number look different across platforms.

Gross profit margin is the first number on the income statement that tells you what a business actually is. Not what it claims to be. Not what its revenue trajectory suggests. What it actually is — at the level of pricing power, cost structure, and competitive position. A software company and a grocery chain can generate the same revenue, but their gross margins will differ by fifty percentage points or more, and that gap is not noise. It is the direct expression of how each business creates and captures value. Most financial analysis focuses on what gross margin is. The more useful question is what it reveals — and why that number can look very different depending on where you find it.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gross-profit-margin-business-model-analysis)**

---

## Table of Contents

- [What Is Gross Profit Margin?](#what-is-gross-profit-margin)
- [Why Gross Margin Is a Business Model Fingerprint](#why-gross-margin-is-a-business-model-fingerprint)
- [Industry Benchmarks: What "Good" Actually Means by Sector](#industry-benchmarks-what-good-actually-means-by-sector)
- [Strategic Low Margins: When a Thin Margin Is the Moat](#strategic-low-margins-when-a-thin-margin-is-the-moat)
- [What Gross Margin Trends Signal About Business Health](#what-gross-margin-trends-signal-about-business-health)
- [Why Gross Margin Numbers Differ Across Platforms](#why-gross-margin-numbers-differ-across-platforms)
- [Gross Margin and ROIC: The Combination That Tells the Full Story](#gross-margin-and-roic-the-combination-that-tells-the-full-story)

---

## What Is Gross Profit Margin?

Gross profit margin measures what percentage of revenue remains after subtracting the direct cost of producing goods or services sold. The formula is:

**Gross Profit Margin = Gross Profit ÷ Revenue**

Where:

**Gross Profit = Revenue − Cost of Goods Sold (COGS)**

A company with **$1 billion in revenue** and **$600 million in COGS** generates **$400 million in gross profit** — a **40% gross margin**. Those **40 cents** of every revenue dollar remain to cover operating expenses — sales, marketing, research and development, general and administrative costs — and ultimately produce operating income. Everything below the gross profit line is overhead. Gross margin determines how much the business has to work with before overhead enters the equation.

The metric comes directly from the income statement in a company's 10-K or 10-Q filing. Revenue is tagged in SEC EDGAR under the XBRL identifier `Revenues` or `RevenueFromContractWithCustomerExcludingAssessedTax`. Cost of goods sold typically carries the tag `CostOfGoodsSold` or `CostOfRevenue`. Where a company reports gross profit as a separate line item, it is tagged directly as `GrossProfit`. GeminIQ's [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) is calculated from these as-filed values — the exact figures the company reported to the SEC, not a reclassified or normalized version of them.

Gross margin is calculated before any operating expense below the gross profit line. It measures the economics of the product or service itself — not the economics of running the business around it. Two companies can share identical gross margins and produce entirely different operating margins depending on what each spends on sales teams, R&D labs, or executive infrastructure. Gross margin isolates the most foundational question in business analysis: not how much revenue this business generates, but how much of each revenue dollar survives to the gross profit line before overhead takes its share.

---

## Why Gross Margin Is a Business Model Fingerprint

The insight most standard financial commentary misses is that gross margin is not primarily a performance metric. It is a structural one.

A software company with **80% gross margin** is not "performing better" than a grocery chain with **20% gross margin**. They are operating entirely different businesses, governed by different economic laws. Digital products have near-zero marginal cost — once the software exists, distributing it to one more customer costs essentially nothing. That economics produces **70–90%** gross margins almost inevitably. A grocery chain must pay for inventory, refrigeration, spoilage, and supplier costs on every unit sold, every single day. A **20% margin** in that context may represent exceptional operational discipline.

This is the structural fingerprint: gross margin encodes how the business creates value at the unit level — whether it scales without proportional cost increases (software, pharmaceuticals, consumer brands) or whether every incremental dollar of revenue requires close to a dollar of input (manufacturing, logistics, raw materials processing). That structural reality does not bend significantly with management talent or operational discipline. You cannot cost-cut your way from grocery margins to software margins. The business model is the margin.

Where this becomes actionable is when a company's reported gross margin sits outside what its stated model would predict. A hardware company reporting software-like margins is either doing something structurally unusual with its product mix — or its reported COGS is obscuring costs that should be visible. [Apple's](/stocks/AAPL) gross margin of approximately **47%** for FY2025 sits well above what a pure hardware manufacturer would normally achieve, and the explanation is not iPhone manufacturing efficiency alone. It is the shift in revenue mix toward Services — iCloud, Apple TV+, the App Store, Apple Pay — where gross margins run materially higher than on any physical device. The gross margin is carrying the evidence of a business model transformation hiding inside a headline revenue number.

---

## Industry Benchmarks: What "Good" Actually Means by Sector

Gross margin is only meaningful within an industry. A **25% gross margin** is exceptional for a grocer and catastrophic for a pharmaceutical company. Across 2,781 non-financial US companies, GeminIQ's as-filed data puts the median gross margin at **43.3%**, with sector medians running from **20.5%** in construction to **61.8%** in transportation, communications and utilities. The full sector table, with interquartile ranges, is in [Gross Profit Margin by Industry](/blog/gross-profit-margin-by-industry-benchmarks).

The business model explains most of that spread. Software, with near-zero marginal cost, sits at the top, though sales, marketing and R&D can still consume the whole gross profit. Branded pharmaceuticals follow because patents support pricing well above production cost, until generics turn the product into a commodity. Consumer brands sit in the middle, since brand equity lifts price but physical production, packaging and distribution all land in cost of goods sold. Manufacturers vary with how engineered and differentiated the product is. Grocers, retailers and distributors sit at the bottom, and win or lose on inventory turns and purchasing scale rather than on the gross margin line.

---

## Strategic Low Margins: When a Thin Margin Is the Moat

The most counterintuitive case in gross margin analysis is when low gross margin is not a weakness but a deliberate competitive weapon.

[Costco](/stocks/COST) reported a **12.87% gross margin TTM** through Q3 FY2026 — roughly half the margin of Walmart, well below Target, and lower than almost every major retailer in the market. Standard screeners flag this as a structural deficiency. But standard screeners do not read the footnotes.

Costco intentionally prices merchandise at near-breakeven. The gross margin on the warehouse business is kept as thin as possible because the merchandise business is not the real business. The real business is the annual membership. Every renewal is essentially pure revenue with near-zero incremental cost. By pricing merchandise at the thinnest possible margin, [Costco](/stocks/COST) drives membership value: members perceive they are capturing the full retail price premium every time they shop, which makes the membership worth renewing. The gross margin suppression is the moat.

The data confirms this. Despite its **12.87% gross margin**, GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) shows [Costco](/stocks/COST) earning **33.4% ROIC** — elite capital efficiency that rivals software-only businesses. A low gross margin and a high ROIC in the same company is the signal that something structurally unusual is happening. In Costco's case, that something is a subscription model disguised as a warehouse retailer. The gross margin alone would never tell you that.

---

## What Gross Margin Trends Signal About Business Health

The level of gross margin at a single point in time is less informative than how it moves. A stable or expanding gross margin tells you one story. A compressing gross margin tells you another — and it tells you earlier than almost any other metric.

Expanding gross margins — where the percentage climbs over successive quarters or years — typically indicate improving pricing power, favorable input cost trends, or a shift in product mix toward higher-margin offerings. [Apple's](/stocks/AAPL) gross margin expansion from the mid-30s a decade ago toward the high-40s today reflects all three, but the dominant driver is Services revenue mix. The company has been replacing lower-margin hardware revenue with higher-margin recurring software and services revenue, and the gross margin is the clearest evidence of that transformation in the income statement.

Compressing gross margins — where the percentage declines — are frequently the earliest warning sign of a business under structural pressure. Competition forcing price reductions shows up first at the gross profit line. Input cost inflation appears in COGS before it fully flows through to operating income. A shift toward lower-margin product mix compresses gross margin while revenue growth may still look healthy in the headlines. By the time margin compression surfaces in EPS misses or analyst guidance cuts, it has typically been building for several quarters. A company with a **40% gross margin** that has quietly declined from **47%** over three years is a fundamentally different business than one holding steady at **40%** — even if current-quarter revenue growth looks identical.

Tracking the gross margin trend from raw SEC filing data — rather than a platform that smooths or reclassifies items quarter to quarter — gives investors earlier visibility into the deterioration. GeminIQ's [Financial Statements](/features#financial-statements) feature pulls the income statement directly from each filed 10-K and 10-Q, making the quarterly gross profit and revenue trend visible from the raw XBRL data without aggregator adjustments.

---

## Why Gross Margin Numbers Differ Across Platforms

The same company can report materially different gross margins on different financial data platforms. This is not a data error. It is a consequence of how COGS is classified — and what aggregators choose to do with those classifications.

The COGS line in an SEC filing is whatever the company reports as COGS. Some companies include stock-based compensation attributed to production employees in COGS. Others include depreciation on manufacturing equipment. Some report certain supply chain costs within COGS; others place them below the gross profit line in operating expenses. The filing discloses these classification choices in the footnotes, and they are part of how each individual company defines its own production economics.

Aggregators that normalize financial data frequently reclassify these items — moving depreciation out of COGS, stripping stock-based compensation from the production cost line, or repositioning certain overhead costs. The result is a reported gross margin that diverges from the as-filed figure. For a software company like [Palantir](/stocks/PLTR), whose FY2025 10-K showed **82.3% gross margin**, the reclassification impact may be modest. For companies where the as-filed COGS includes significant depreciation, production-level stock compensation, or supply chain overhead, the difference between the as-filed margin and the normalized margin can run several percentage points in either direction.

Several percentage points of gross margin difference between platforms compounds into every downstream calculation that depends on it — operating leverage estimates, scenario analysis, competitive benchmarking, and any screener using a gross margin threshold as a filter. When the input is wrong, every output built on it is wrong in the same direction.

GeminIQ's [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) preserves the company's as-filed COGS figure. The metric on the platform reflects exactly what the company reported to the SEC — traceable to a specific line item and XBRL tag in the actual filing. But standard financial media doesn't read the footnotes.

---

## Gross Margin and ROIC: The Combination That Tells the Full Story

Gross margin in isolation is a useful but incomplete picture of business quality. The combination that unlocks the most analytical value is gross margin paired with [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital).

A high gross margin with a high ROIC is the gold-standard combination: the business captures pricing power at the unit level and converts that pricing power into exceptional capital efficiency. This combination appears in the best-quality businesses — ones with durable competitive advantages producing both pricing power and disciplined use of capital.

A high gross margin with a low ROIC signals a business burning gross margin dollars on operating expenses, working capital, or capital expenditures before they produce returns. A pharmaceutical company with **70%+ gross margins** but a low ROIC is typically spending those margins on R&D pipelines, sales force infrastructure, or acquired goodwill that hasn't generated proportional returns. The gross margin is strong; the business model has a capital efficiency problem.

A low gross margin with a high ROIC — the Costco pattern — is the most analytically interesting case, because it reveals a structural advantage that pure margin analysis would classify as weakness. The low gross margin is not the story; the capital velocity is. Costco turns its [invested capital](/metrics/calculated-values/invested-capital) at a rate that more than compensates for thin unit economics. The ROIC is the corrective lens that margin analysis alone cannot provide.

A low gross margin with a low ROIC is the straightforward bad case: the business lacks pricing power, converts margin dollars inefficiently, and earns poor returns on what it deploys. This combination often appears in commodity businesses operating in competitive markets where neither the product nor the business model carries any structural advantage.

For a full treatment of the ROIC framework, see [ROIC: Return on Invested Capital Explained](/blog/roic-return-on-invested-capital-explained), which covers the NOPAT-based calculation, invested capital decomposition, and the ROIC-versus-[WACC](/blog/how-to-calculate-wacc-from-10k) value creation test. GeminIQ's pre-calculated [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) and [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) both pull directly from SEC filing data, with no reclassification between the filing and the dashboard. The business model that reads cleanly in the data is the one that actually holds up under analysis.

---

### Related Reading

- [ROIC: Return on Invested Capital Explained](/blog/roic-return-on-invested-capital-explained) — the full NOPAT and invested capital framework, with ROIC-vs-WACC as the value creation test.
- [EV/EBITDA vs. P/E Ratio Explained](/blog/ev-ebitda-vs-pe-ratio-explained) — how the margin waterfall from gross to EBITDA to net income determines which valuation multiple applies.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — how high-gross-margin businesses convert margin dollars into actual cash generation, and how to value that conversion rate.
- [Costco Stock Analysis: How a 3.8% Margin Business Earns 42% on Capital](/blog/costco-stock-analysis-2026) — the complete structural analysis behind the gross margin paradox in practice.
- [Piotroski F-Score: Using It to Avoid Value Traps](/blog/piotroski-f-score-value-trap) — how gross margin improvement functions as one of nine binary signals in the F-Score financial health screen.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gross-profit-margin-business-model-analysis)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).<br>
All financial figures cited in this article reference Costco Wholesale Corporation's Q3 FY2026 10-Q (filed June 3, 2026, period ending May 10, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/909832/000090983226000051/cost-20260510.htm).<br>
All financial figures cited in this article reference Palantir Technologies Inc.'s Q1 FY2026 10-Q (filed May 5, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000028/pltr-20260331.htm).</sup>

---

## Blog: Gross Profit Margin by Industry: 20% to 62%, by Sector
source: https://www.geminiq.com/blog/gross-profit-margin-by-industry-benchmarks

### Gross Profit Margin by Industry: 20% to 62%, by Sector
Gross profit margin by industry varies less between sectors than it does within them, and as-filed data shows the typical company's peer range is often wider than the gap between industries.

**[Constellation Energy](/stocks/CEG)** runs a gross profit margin of **95.6%**. **[Boeing](/stocks/BA)** runs **4.7%**. Both are large, real, profitable-adjacent industrial companies, and the gap between them is the kind of number that makes "typical margin by industry" tables feel useful — until the same exercise is run one level deeper, inside a single sector, and the range turns out to be almost as wide as the one separating industries from each other entirely.

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period for **2,781 non-financial companies** — companies without a usable [gross profit margin](/metrics/margin-metrics/gross-profit-margin) calculation, and companies in Finance, Insurance & Real Estate, are excluded, since "cost of revenue" is not a comparable concept for a bank or an insurer. Every figure is trailing-twelve-months [Gross Profit Margin](https://www.geminiq.com/metrics/margin-metrics/gross-profit-margin) computed directly from GeminIQ's as-filed revenue and cost-of-revenue line items, with the top and bottom **1%** of each sector's distribution trimmed.

## The Pattern

Sector medians for gross margin run from **20.5%** in Construction to **61.8%** in Transportation, Communications & Utilities — a spread of roughly 41 percentage points, which looks like exactly the kind of number a "typical margin by industry" table is built to capture. The problem is that several individual sectors carry an interquartile range almost as wide as that entire inter-sector gap on their own. Mining runs from a 25th percentile of 21.4% to a 75th percentile of 83.3% — a 62-point spread inside one sector, wider than the distance between the lowest- and highest-margin sectors in the whole study. A single "typical margin" number for any sector is describing a distribution, not a company, and the distribution is usually the more useful fact.

## The Data

| Sector | N | Median Gross Margin | Q1–Q3 | Intra-Sector Spread |
|---|---|---|---|---|
| Transportation, Communications & Utilities | 204 | **61.8%** | 35.1%–78.5% | 43.4 pts |
| Services | 717 | **60.1%** | 35.0%–77.6% | 42.5 pts |
| Manufacturing | 1,385 | **40.0%** | 23.9%–59.5% | 35.6 pts |
| Mining | 97 | **40.1%** | 21.4%–83.3% | 61.9 pts |
| Retail Trade | 191 | **38.1%** | 25.8%–56.8% | 31.0 pts |
| Agriculture, Forestry & Fishing | 28 | **28.5%** | 10.5%–45.4% | 34.9 pts |
| Wholesale Trade | 98 | **25.3%** | 11.5%–32.7% | 21.2 pts |
| Construction | 61 | **20.5%** | 14.0%–30.2% | 16.2 pts |
| **Universe (ex-financials)** | **2,781** | **43.3%** | 25.3%–68.6% | 43.2 pts |

Mining, Retail Trade, Agriculture, Forestry & Fishing, Wholesale Trade, and Construction sit under or near the 200-company floor GeminIQ applies to Filing Data Study buckets and should be read as directional rather than settled. The comparison worth sitting with is in the last column: the universe-wide interquartile spread, at **43.2 percentage points**, is nearly identical to the gap between the lowest- and highest-median sectors. Knowing a company's sector narrows the range of plausible margins by less than intuition suggests.

<center><sup>GeminIQ data study: gross profit margin by SIC sector across 2,781 non-financial companies, as-filed. Built from as-filed 10-K/10-Q data via GeminIQ. n = 2,781 companies, trailing-twelve-months as of the most recent filing within the last 15 months.</sup></center>

## The Extremes

**[Constellation Energy](/stocks/CEG)**'s **95.6%** gross margin sits at the high end of a Transportation, Communications & Utilities sector that a single "typical margin" table would lump in with capital-intensive pipelines and telecoms running half that figure. "Utilities" is not one business model — a nuclear-heavy power generator selling into a market with surging data-center demand looks nothing like a regulated gas distributor on the income statement. At the other pole, **[Boeing](/stocks/BA)**'s **4.7%** gross margin reflects a large-scale manufacturer absorbing program cost overruns directly into cost of revenue — the filings show the margin compression before any earnings headline does.

The distributors make the same point from a different angle. **[McKesson Corp](/stocks/MCK)** runs a gross margin of **3.6%**, and **[Cencora, Inc.](/stocks/COR)** runs **4.0%** — both real, large, investment-grade companies whose business model is passing pharmaceutical volume through at thin markup rather than manufacturing anything themselves. A "typical margin by industry" table that doesn't separate distributors from manufacturers inside the same broad sector will misprice both.

## The Method

Every figure above is trailing-twelve-months gross profit margin — gross profit divided by net revenue, both as-filed — read from GeminIQ's [Gross Profit Margin](https://www.geminiq.com/metrics/margin-metrics/gross-profit-margin) metric layer for each company's most recent filing period within the last fifteen months. Sectors are grouped by SIC division rather than a proprietary industry taxonomy, so every company's placement traces back to its own filed SIC code. This is a historical distribution measured across the current filing snapshot, not a forecast, and the top and bottom **1%** of each sector's distribution is trimmed before computing medians and quartiles so a single outlier cannot move an entire sector's benchmark. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position on GeminIQ's [Stock Screener](/features#screener) and check its gross margin against its own SIC sector. Then check where it sits inside that sector's range rather than against the median alone — a company at its sector's 25th percentile is telling a very different story than one at the median, even when both get filed under the same "typical margin" label. Rebuild that comparison for any holding directly from GeminIQ's as-filed data, and the sector average stops being the number that decides whether a margin looks healthy.

## Frequently Asked Questions

### What is a typical gross profit margin by industry?

It varies widely — in GeminIQ's data, sector medians run from **20.5%** in Construction to **61.8%** in Transportation, Communications & Utilities. But sector alone narrows the range less than a single sector-median figure suggests, since the spread inside individual sectors is often nearly as wide as the gap between sectors.

### Why is the range of gross margins within a single sector often wider than the gap between sectors?

Because sector groupings still bundle very different business models together — a nuclear-heavy power generator and a regulated gas distributor both sit in Utilities, and a pharmaceutical distributor passing volume through at thin markup sits in the same broad category as companies that manufacture what they sell. In GeminIQ's data, the universe-wide interquartile spread (43.2 points) is nearly identical to the gap between the lowest- and highest-median sectors.

### Does a low gross margin always mean a weaker business?

Not necessarily. Distributors like McKesson and Cencora run gross margins in the single digits by design — their business model is passing volume through at thin markup, not manufacturing — while still being large, investment-grade, cash-generative companies.

### How many companies does this study cover?

**2,781** non-financial companies in GeminIQ's current filing snapshot, after excluding companies without a usable gross margin calculation and trimming the top and bottom **1%** of each sector's distribution.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gross-profit-margin-by-industry-benchmarks)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Sector medians and quartiles are computed from GeminIQ's Gross Profit Margin metric layer across the described universe and snapshot window.

---

## Blog: GuruFocus Alternative: Raw SEC Filing Data
source: https://www.geminiq.com/blog/gurufocus-alternative-sec-data

### GuruFocus Alternative: Raw SEC Filing Data
A GuruFocus alternative built on as-filed SEC data. GuruFocus layers guru 13F tracking and proprietary scores over licensed fundamentals; this post separates what a company reported from what a model concluded about it.

GuruFocus built its reputation on a specific idea: the best investors in the world have already done the research, so follow what they own. That premise produced a strong product — guru portfolio tracking, a screener with hundreds of filters, decades of financial history, and named strategy screens built around Graham, Buffett, Lynch, and Piotroski. For a value investor who wants ideas sourced from proven allocators, it works.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gurufocus-alternative-sec-data)**

But look at what a GuruFocus screen is actually made of and you find three separate layers, none of which is the filing. The guru holdings come from 13F filings, which are quarterly and lagged. The company fundamentals are licensed — GuruFocus's own disclosures state that company fundamental data is provided by Morningstar, with analyst estimates from Refinitiv and Morningstar and quotes from QuoteMedia. And the headline signals, GF Score and GF Value, are proprietary calculations layered on top of both.

Every one of those layers is somebody else's conclusion. None of them is what the company reported.

## Table of Contents

- [Three Layers Between You and the Filing](#three-layers-between-you-and-the-filing)
- [What Guru Tracking Can and Cannot Tell You](#what-guru-tracking-can-and-cannot-tell-you)
- [Proprietary Scores Are Opinions With Arithmetic](#proprietary-scores-are-opinions-with-arithmetic)
- [Licensed Fundamentals Carry Someone Else's Mapping](#licensed-fundamentals-carry-someone-elses-mapping)
- [What a Filing-First Alternative Changes](#what-a-filing-first-alternative-changes)
- [Which Job You Are Actually Hiring For](#which-job-you-are-actually-hiring-for)
- [Frequently Asked Questions](#frequently-asked-questions)

## Three Layers Between You and the Filing

Stack them in order and the distance becomes obvious.

At the bottom sits the 10-K or 10-Q — the document the company signed and filed. Above it sits a licensed fundamentals dataset, which has mapped that filing's line items into a comparable template. Above that sits a proprietary score, which has weighted selected values from the template into a single number. And running alongside all of it sits guru position data, extracted from institutional filings that describe holdings as of a date that has already passed.

An investor reading a GF Score is reading the output of every layer at once. That is not a criticism of the arithmetic. It is a description of how far the number sits from the source, and of how many decisions made by other people are baked into it before it reaches the screen.

The useful question is not whether those layers are wrong. It is whether you can inspect them when something looks off.

## What Guru Tracking Can and Cannot Tell You

Institutional position data comes from Form 13F, and the mechanics of that form set a hard ceiling on what any guru tracker can deliver.

A 13F reports long US equity positions as of the last day of a quarter, and it is due within **45 calendar days** after that quarter ends. A manager who accumulated a position through February and March files by mid-May, describing a portfolio as it stood on March 31. By publication, the market has had up to **45 days** to price whatever prompted the trade. The [institutional ownership guide](/blog/institutional-ownership-13f-filing-explained) covers the lag mechanics in full, and the [13F portfolio concentration study](/blog/13f-portfolio-concentration-signal) covers what the filings do reliably reveal.

Nothing about that is a defect in GuruFocus's implementation. It is the data. Anyone displaying 13F holdings is displaying a quarterly snapshot with a built-in delay, and no interface removes it.

What guru data is good for is pattern recognition across time. A business that appears in concentrated quality portfolios quarter after quarter is telling you something durable about its characteristics. What it cannot be is a current signal, and the entry point implied by a fresh 13F is usually already gone.

That shifts the question from "what did they buy" to "what is this business, and does it still look the way it looked when they bought it." Answering the second question requires the filings.

## Proprietary Scores Are Opinions With Arithmetic

GF Score and GF Value are the product's most visible outputs, and they are also the layer where the most gets decided on your behalf.

A composite score selects inputs, weights them, and normalizes the result into a rank. Each of those steps is a judgment about what matters. A valuation estimate goes further: it assumes a relationship between historical multiples, growth, and fair value, then prints a number that looks like a measurement. Users of any scoring platform learn quickly that the score is a starting point, and the platform's own documentation typically says so.

The problem is not that composite scores are useless. It is that a score compresses a company into one number and discards the thing that made the analysis worth doing — the specific line items that produced it. When two companies score the same, the score cannot tell you that one earned it through margin expansion and the other through a balance sheet that has not been tested in a downturn.

Building the same conclusion from filed inputs takes longer. It also survives being questioned.

## Licensed Fundamentals Carry Someone Else's Mapping

The layer that draws the least attention is the one that affects every number on the page.

When fundamentals come from a licensed provider, that provider has already mapped each company's reported line items into a standardized template. Two distinct cash outflows can become one row because the template has one row where the filing has two. A single filed liability caption can be split into two so a component is separately trackable. A label can persist while its contents change — the version that costs the most, because nothing on screen signals that anything was decided.

Those choices make cross-company comparison possible, which is exactly why licensing them is a reasonable decision for a screener-first product. They also mean the value in a GuruFocus cell answers "what is the standardized figure" rather than "what did this company file."

For screening across thousands of companies, that is the right answer. For deciding whether a specific business is worth owning, it is one remove from the document that would settle the question.

## What a Filing-First Alternative Changes

GeminIQ removes the layers rather than adding a better one. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value — so any figure on screen traces to the specific reported fact that produced it.

That premise runs through the product. [Financial Statements](/features#financial-statements) show a company's own captions across quarters and years. [Custom Tables](/features#custom-tables) build views from specific reported items rather than template rows. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, which means a metric can be audited against the numbers behind it instead of accepted on reputation. Named strategy logic runs the same way: the [Buffett-Style Screener](/screens/stock-screeners/buffett-style) and the [Piotroski F-Score Screener](/screens/stock-screeners/piotroski-f-score) apply published criteria to filed data rather than to a composite rank. [Insider Transactions](/features#insider-transactions) and [Institutional Ownership](/features#institutional-ownership) sit alongside the fundamentals, with the quarterly cadence of the underlying filings stated plainly rather than dressed up as live.

[Peloton's](/stocks/PTON) filings show what the layers cannot. In the September 2021 quarter revenue growth had fallen to **6.2%** year over year while Inventory Net hit a then-record **$1,269.2 Million** and Days Inventory Outstanding reached **111.2 days**, up from **66.9 days** two quarters earlier. By December 2021 inventory peaked at **$1,541.3 Million** at **130.2 days** outstanding, against **6.5%** growth. Two quarters after that, cost of goods sold of **$708.5 Million** exceeded revenue of **$678.7 Million** outright and gross profit went negative at **-$29.8 Million**.

Every one of those figures sat in a filed statement while the composite view of the company still had a growth story attached. A score compresses that divergence into a rank; the filings kept the two series apart. The [Peloton post-mortem](/blog/peloton-stock-collapse-warning-signs) traces the full record quarter by quarter.

The trade is explicit. There is no guru portfolio tracker, no proprietary score, and no fair value estimate printed for you. What there is instead is the ability to build those conclusions yourself from inputs you can point at.

## Which Job You Are Actually Hiring For

The decision comes down to where you want other people's judgment to sit in your process.

If you want ideas — a list of what respected allocators own, ranked by a model that has already weighed the tradeoffs — GuruFocus does that job well, and the guru dataset is the deepest of its kind. Idea generation benefits from someone else's shortlist.

If you want conviction, borrowed judgment is a liability. A thesis you cannot trace to filed numbers is a thesis you cannot defend when the position moves against you, and a composite score offers nothing to fall back on. The [GeminIQ vs. GuruFocus comparison](/competitor-comparison/gurufocus) covers the feature-level detail, the [Finbox alternative](/blog/finbox-alternative-sec-data) post covers the same inherited-inputs problem inside prebuilt valuation models, and [what investors miss in SEC filings](/blog/what-investors-miss-in-sec-filings) covers what the last mile contains.

Use a guru tracker to find the name. Use the filing to decide what it is worth — because the score tells you what a model concluded, and only the filing tells you what the company reported.

## Frequently Asked Questions

### What are the best GuruFocus alternatives?

It depends on which part of GuruFocus you are replacing. For guru portfolio tracking, the substitutes are other 13F aggregators, all subject to the same quarterly reporting lag. For fundamental screening, most alternatives license standardized data and differ on interface and price rather than on the underlying dataset. For filing verification, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability, which is a different category rather than a cheaper version of the same one.

### Where does GuruFocus get its financial data?

GuruFocus's own disclosures state that company fundamental data is provided by Morningstar, analyst estimates come from Refinitiv and Morningstar with Refinitiv taking priority when both are available, and stock quotes are provided by QuoteMedia. The guru holdings data is derived from institutional 13F filings.

### How current is GuruFocus guru portfolio data?

It is quarterly, not live. Form 13F reports positions as of a quarter-end date and is due within **45 calendar days** after that quarter closes, so the holdings shown describe a portfolio as it stood on a date that has already passed. No platform can shorten that window, because the filing deadline sets it.

### Is the GF Score based on SEC filings?

Indirectly. A composite score is calculated from fundamental data that has already been standardized by a third-party provider, and the score itself applies its own selection and weighting on top of that. The inputs originate in filings, but the number displayed is several transformations removed from any line item you could look up in a 10-K.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=gurufocus-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- GuruFocus data-provider attributions (Morningstar for company fundamentals; Refinitiv and Morningstar for analyst estimates; QuoteMedia for quotes) are drawn from GuruFocus's published site disclosures, reviewed August 2, 2026.
- Form 13F reporting deadline of 45 calendar days after quarter end is set by SEC rule.
- GeminIQ GuruFocus comparison page: /competitor-comparison/gurufocus

---

## Blog: How to Build a Defensible Peer Comparison Set
source: https://www.geminiq.com/blog/how-to-build-peer-comparison-set

### How to Build a Defensible Peer Comparison Set
A peer comparison is only as good as the peers in it, and an industry-label peer group can fail before a single ratio gets calculated — because the companies being compared share an industry label and little else that actually matters. This guide covers why SIC and even GICS classification codes alone aren't sufficient to build a peer set that actually holds up, a real, underused source of professionally-vetted peer groups disclosed in every company's own proxy statement, and the specific filters — revenue scale, growth profile, margin structure, and capital structure — that separate an actual comparable from a company that merely shares a sector.

A peer comparison is only as good as the peers in it, and an industry-label peer group can fail before a single ratio gets calculated — not because the math is wrong, but because the companies being compared were never actually comparable in the first place. Two companies can share the same industry classification and describe meaningfully different businesses: different scale, different growth trajectory, different margin structure, different capital intensity. Averaging them together doesn't produce a benchmark; it produces a number that looks precise and describes nothing real.

This guide covers how to build a peer comparison set that actually holds up: why industry classification codes alone aren't sufficient, a real, underused source of professionally-vetted peer groups sitting in plain sight in every company's own proxy statement, and the specific filters that separate an actual comparable from a company that merely shares a sector label.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-build-peer-comparison-set)**

---

## Table of Contents

- [Why "Same Industry" Isn't the Same as "Comparable"](#why-same-industry-isnt-the-same-as-comparable)
- [The SIC Code Problem](#the-sic-code-problem)
- [GICS: A Better Starting Point, Still Not the Answer](#gics-a-better-starting-point-still-not-the-answer)
- [The Underused Source: A Company's Own Disclosed Peer Group](#the-underused-source-a-companys-own-disclosed-peer-group)
- [Four Filters That Separate a Real Peer From a Same-Sector Name](#four-filters-that-separate-a-real-peer-from-a-same-sector-name)
- [How Many Peers Is Enough](#how-many-peers-is-enough)
- [Building the Comparison Correctly](#building-the-comparison-correctly)
- [Building the Peer Set on GeminIQ](#building-the-peer-set-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Why "Same Industry" Isn't the Same as "Comparable"

Industry membership is a necessary filter and a wildly insufficient one on its own. A regional community bank and a global systemically important bank share a sector classification and almost nothing else that matters for comparison — different risk profiles, different regulatory capital requirements, different growth ceilings, different cost of capital. A diversified industrial conglomerate and a pure-play manufacturer in one of that conglomerate's segments might share the same primary industry code while running businesses with almost no operational overlap.

The gap between "same industry" and "actually comparable" is exactly where peer analysis goes wrong, and it goes wrong quietly. A comparison built on a flawed peer set doesn't produce an obviously broken number — it produces a plausible-looking multiple or margin benchmark that's simply measuring the wrong thing.

---

## The SIC Code Problem

Every SEC filer discloses a primary SIC (Standard Industrial Classification) code on the cover page of its registration statements, and that code is the most immediately available starting point for finding companies in a similar business. It's also a badly outdated system. The SIC classification structure was last substantively revised in 1987, and the federal government stopped maintaining or updating it for new industry categories in 1997, when it was formally replaced by NAICS for economic statistics purposes. The SEC never made the same switch — SIC codes are still what's on the filing's cover page today, frozen in a taxonomy built for an economy that looked meaningfully different than the one companies operate in now.

The practical consequence is that SIC codes systematically undercount services-heavy, technology-heavy business models that didn't exist in their current form when the taxonomy was last updated, and they group companies by product category rather than by the underlying economics of how those companies actually compete and get valued.

---

## GICS: A Better Starting Point, Still Not the Answer

GICS (Global Industry Classification Standard), developed jointly by MSCI and S&P starting in 1999, groups companies by economic activity and end markets rather than by the product-category logic SIC was built around — a meaningfully better proxy for real economic comparability, before any company-specific filter gets applied. GICS organizes companies hierarchically, from **11** broad sectors down to over a hundred specific sub-industries, which allows for a much finer-grained starting filter than a single SIC code provides.

GICS still assigns each company to exactly one classification based on its primary business activity, which remains a real limitation for any company operating meaningfully across more than one business line. A diversified company gets filed under whichever segment generates the largest share of its revenue, even when a second segment is large enough to matter for real comparability — the classification system, however refined, is still a single label applied to what's sometimes two or more distinct businesses running under one ticker.

---

## The Underused Source: A Company's Own Disclosed Peer Group

There's a source of peer group data that skips the classification-code problem entirely: the compensation peer group disclosed in nearly every company's own [DEF 14A proxy statement](/blog/what-is-def-14a). Public companies routinely disclose the specific, named list of companies their compensation committee — often working with an outside consultant — selected as comparable for executive pay benchmarking purposes, chosen explicitly on criteria like revenue range, market capitalization, business model, and operational complexity, not on an industry code alone.

[Carvana's](/stocks/CVNA) 2025 proxy statement, filed March 25, 2025, makes the underlying logic explicit — and shows how far a board-selected peer set can diverge from a classification code. Carvana's committee said it chose peers on "size, industry focus, growth rates, customer base, and market for talent," and further weighted "our online business model, revenue size, and complexity of operations." The list it produced:

| Peer | What a code-based screen would have said |
|---|---|
| [AutoNation](/stocks/AN), [CarMax](/stocks/KMX), [Lithia Motors](/stocks/LAD), [Penske Automotive](/stocks/PAG), [Genuine Parts](/stocks/GPC) | The auto-retail peers a SIC or GICS lookup finds on its own |
| [Chewy](/stocks/CHWY), [Wayfair](/stocks/W), [eBay](/stocks/EBAY), [Expedia](/stocks/EXPE) | E-commerce and online marketplaces — a different industry code entirely |
| [DoorDash](/stocks/DASH), [Uber](/stocks/UBER), [Lyft](/stocks/LYFT) | Consumer platforms, matched on business model rather than product |
| [Zillow](/stocks/ZG), [Opendoor](/stocks/OPEN) | Online transaction platforms for a large, infrequent, high-ticket purchase — the closest structural analogues, in an unrelated sector |

Only five of those names come from Carvana's own industry classification. The other nine were selected because the committee judged the *business model* comparable, and the last pair is the most instructive: Zillow and Opendoor sell houses, not cars, but they share the thing that actually determines how Carvana's economics behave — moving a large, infrequent, high-consideration purchase online. That is a board-level judgment about comparability, made by people with every incentive to get it right, sitting in a public filing most equity research never reads for this purpose.

The caveat is real: a compensation peer group is selected for pay benchmarking, not equity valuation, so company size and role complexity get more weight than a valuation-focused peer set might use. Genuine Parts is a distribution business with little in common with Carvana operationally. But as a starting universe of board-vetted comparables, it is a stronger foundation than a raw industry code lookup — and it is free. For what the underlying business actually did over this period, our [analysis of Carvana's crash and recovery](/blog/carvana-stock-crash-recovery) covers the filings behind it.

---

## Four Filters That Separate a Real Peer From a Same-Sector Name

Once a starting universe exists — from GICS, from a disclosed compensation peer group, or both combined — four filters, checked against actual filed data rather than assumed from the industry label, separate the actual comparables from the companies that merely share a sector.

| Filter | What you compare | Range the filter allows | What it distorts when ignored |
|---|---|---|---|
| Revenue scale | Peer revenue against the subject company's revenue | Roughly a half to two times the subject company's revenue — close enough to share similar operating leverage and market position | Well outside that range, scale effects start dominating the comparison more than the underlying business quality does |
| Growth profile | Revenue growth rate | Within roughly **10 percentage points** of the subject company's TTM revenue growth rate | A double-digit grower measured against low-single-digit growers produces a multiple comparison that's really measuring the growth premium, not relative valuation |
| Margin structure | Gross margin and operating margin | Gross margin within roughly **10 points** of the subject company's | A broad industry classification spans very different margin profiles, so mismatched margins signal a different underlying business model |
| Capital structure | Leverage | Net Debt-to-EBITDA within roughly **1.5x** of the subject company's, or both companies on the same side of the net-cash line | Wildly different leverage produces distorted equity multiples, unless the comparison is built on an enterprise-value basis that neutralizes the difference in the first place |

A peer that clears the industry filter and fails two or more of these four checks isn't a peer; it's a same-sector company that happens to also be public.

### Running the filters: Carvana's own peer group

The four filters are easy to agree with in the abstract. Applied to a real board-selected peer group, they are less forgiving than they look.

Carvana's TTM figures at the quarter ended June 30, 2026: revenue of **$25.06 Billion**, revenue growth of **+54%**, a **19%** gross margin, and [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) of **1.11x**. That sets the four bands: revenue between **$12.5B and $50.1B**, growth between **44% and 64%**, gross margin between **9% and 29%**, and Net Debt-to-EBITDA between **-0.39x and 2.61x**.

| Peer | Revenue scale | Growth profile | Margin structure | Capital structure | Filters passed |
|---|---|---|---|---|---|
| [AutoNation](/stocks/AN) | Pass | Fail | Pass | Pass | 3 of 4 |
| [CarMax](/stocks/KMX) | Pass | Fail | Pass | Pass | 3 of 4 |
| [Lithia Motors](/stocks/LAD) | Pass | Fail | Pass | Pass | 3 of 4 |
| [Penske Automotive](/stocks/PAG) | Pass | Fail | Pass | Pass | 3 of 4 |
| [Genuine Parts](/stocks/GPC) | Pass | Fail | Fail | Fail | 1 of 4 |
| [Chewy](/stocks/CHWY) | Pass | Fail | Fail | Fail | 1 of 4 |
| [Wayfair](/stocks/W) | Pass | Fail | Fail | Fail | 1 of 4 |
| [Expedia Group](/stocks/EXPE) | Pass | Fail | Fail | Fail | 1 of 4 |
| [DoorDash](/stocks/DASH) | Pass | Fail | Fail | Fail | 1 of 4 |
| [eBay](/stocks/EBAY) | Fail | Fail | Fail | Pass | 1 of 4 |
| [Uber](/stocks/UBER) | Fail | Fail | Fail | Pass | 1 of 4 |
| [Opendoor](/stocks/OPEN) | Fail | Fail | Fail | Pass | 1 of 4 |
| [Lyft](/stocks/LYFT) | Fail | Fail | Fail | Fail | 0 of 4 |
| [Zillow Group](/stocks/ZG) | Fail | Fail | Fail | Fail | 0 of 4 |

**None of the fourteen clears all four.** Every one of them fails the growth filter, for a single reason: Carvana grew revenue **54%** over the trailing twelve months and not one company on its own disclosed peer list grew faster than **34%**. The four auto retailers — AutoNation, CarMax, Lithia and Penske — pass scale, margin and leverage cleanly and fail only there.

That result is not an argument against using the proxy peer group. It is the argument for screening it. The compensation committee was solving for market for talent and operational complexity, and by that standard DoorDash and Uber belong on the list. For a valuation comparison they do not, and the filters say so in one pass. What the disclosed list gives you is a defensible starting universe of fourteen names, assembled by people with real accountability for getting comparability right; what the filters give you is the subset that survives a different question.

The practical read for Carvana specifically: there is no clean peer set. A grower at **54%** in a sector where the nearest comparable business models grow in the low single digits does not have peers on a multiples basis, and any comparison built anyway is measuring the growth premium rather than relative valuation. Knowing that before running the comparison is more useful than a peer-average multiple that quietly encodes it.

---

## How Many Peers Is Enough

There's a real tension between a peer set narrow enough to be actually comparable and one large enough to average out company-specific noise. A set of two or three peers is vulnerable to one company's idiosyncratic situation — a recent acquisition, a one-time charge, a temporary demand spike — distorting the whole comparison. A set of twenty or more, built by relaxing the four filters above until enough companies qualify, usually means the comparison has drifted back toward "same industry" rather than "actually comparable." A peer set in the range of five to ten companies, each of which clears all four filters rather than most of them, is generally the more defensible middle ground — small enough that each company's inclusion can be individually justified, large enough that no single company's noise dominates the average.

---

## Building the Comparison Correctly

Once the peer set itself is defensible, the comparison still has to control for scale by using ratios and margins rather than absolute dollar figures, and it has to account for fiscal year misalignment. Comparing a company's most recently reported trailing twelve months against a peer's stale, six-month-old trailing figure understates the comparison's precision even when every other filter was applied correctly. Checking the actual period each peer's most recent figures cover, not just pulling the latest number each platform happens to display, is the final step that turns a defensible peer set into a defensible comparison. Platforms differ in how they handle that period alignment, and a platform that recalculates or normalizes older figures can quietly break exactly this kind of comparison in a way that as-filed data does not.

---

## Building the Peer Set on GeminIQ

Every filter covered here requires comparing filed data across multiple companies side by side: revenue, growth rates, margins, and capital structure for a candidate list, checked against the subject company's own figures before any company gets included. GeminIQ's [Custom Tables](/features#custom-tables) builder assembles exactly this kind of multi-company comparison from as-filed data, and [Calculated Metrics](/features#calculated-metrics) like [Revenue Growth](/metrics/growth-metrics/revenue-growth) and [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) are pre-built from the same tags across every company in the database, which means the four filters above can be checked directly rather than reconstructed by hand for each candidate peer.

For the compensation peer group specifically, the actual named list lives in the subject company's own DEF 14A on EDGAR — a five-minute read that often does most of the initial screening work a raw industry code search would otherwise leave undone.

---

## Frequently Asked Questions

### Why isn't SIC code enough to build a peer group?

SIC codes were last substantively revised in 1987 and haven't been updated by the federal government since 1997, when NAICS replaced them for general economic classification. The SEC still requires SIC codes on filing cover pages, but the taxonomy reflects an economy that looked meaningfully different than the one companies compete in today.

### What is a compensation peer group, and can I use it for valuation?

It's the specific list of companies a company's own compensation committee — often with an outside consultant — selects as comparable for executive pay benchmarking, disclosed in the DEF 14A proxy statement. It's a useful starting universe of professionally-selected comparables in its own right, but it's built for pay benchmarking, not equity valuation, so company size and role complexity carry more weight in that selection than a pure valuation comparison might use.

### How many companies should be in a peer comparison set?

Somewhere around five to ten is generally the more defensible range. Fewer than that leaves the comparison vulnerable to any one company's idiosyncratic noise; more than that usually means the selection criteria were relaxed enough to blur back toward "same industry" rather than "actually comparable."

### What's the difference between SIC and GICS codes?

SIC is the older classification system, still required on SEC filing cover pages but not updated since 1987. GICS, developed by MSCI and S&P starting in 1999, organizes companies by economic activity and end markets rather than product category, with finer-grained sub-industry categories that group companies whose stock returns move together more closely than a SIC-based grouping does.

A peer comparison built on an industry code alone answers "who's nearby." A peer comparison built on revenue scale, growth, margin, and capital structure — checked against actual filed data — answers the harder and more useful question: who's actually comparable.

---

## Related Reading

- [What Is a DEF 14A? The Proxy Statement Explained](/blog/what-is-def-14a) — the full walkthrough of the filing that discloses the compensation peer group covered above.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-build-peer-comparison-set)**

<sup>Sources: Carvana Co.'s compensation peer group and the committee's stated selection criteria are drawn from its definitive proxy statement (DEF 14A) filed March 25, 2025, publicly available on [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1690820/000169082025000105/cvna-20250321.htm). GICS sector and sub-industry counts reflect the classification structure maintained by MSCI and S&P Dow Jones Indices.</sup>

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: How to Calculate Financial Ratios From a 10-K: Step-by-Step
source: https://www.geminiq.com/blog/how-to-calculate-financial-ratios-10k

### How to Calculate Financial Ratios From a 10-K: Step-by-Step
Learning how to calculate financial ratios from a 10-K starts with locating the right line item, not memorizing the formula. This guide builds a liquidity, leverage, profitability, and valuation ratio step by step from Apple's most recent 10-K, tracing every input back to its exact XBRL tag.

Type "how to calculate financial ratios" into a search engine and most of what comes back is a formula sheet: Current Ratio equals this divided by that, Debt-to-Equity equals this over that. What almost none of those guides show is where those inputs actually live inside a real filing — which line, under which header, reported under which XBRL tag — and that gap is exactly where most self-taught investors get the math wrong. This guide closes it. Using [Apple's](/stocks/AAPL) most recently filed 10-K — FY2025 (filed October 31, 2025, fiscal year ending September 27, 2025) — we will build four ratios directly from the as-filed balance sheet, income statement, and cash flow statement: one liquidity ratio, one leverage ratio, one profitability ratio, and one valuation ratio. Every input traces to a specific filing line. Every formula is built by hand before it gets checked against the platform number.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-calculate-financial-ratios-10k)**

---

## Table of Contents

- [Step 1: Find the Filing and the Exact Line Item](#step-1-find-the-filing-and-the-exact-line-item)
- [Step 2: Calculate a Liquidity Ratio — The Current Ratio](#step-2-calculate-a-liquidity-ratio-the-current-ratio)
- [Step 3: Calculate a Leverage Ratio — The Debt-to-Equity Ratio](#step-3-calculate-a-leverage-ratio-the-debt-to-equity-ratio)
- [Step 4: Calculate a Profitability Ratio — Gross Profit Margin](#step-4-calculate-a-profitability-ratio-gross-profit-margin)
- [Step 5: Calculate a Valuation Ratio — Free Cash Flow Yield](#step-5-calculate-a-valuation-ratio-free-cash-flow-yield)
- [Step 6: Reconcile Your Number Against the Platform](#step-6-reconcile-your-number-against-the-platform)
- [Where This Process Breaks Down at Scale](#where-this-process-breaks-down-at-scale)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## Step 1: Find the Filing and the Exact Line Item

Before any formula gets touched, two decisions determine whether the resulting ratio is accurate or quietly wrong: which filing, and which line within it. A 10-K is the annual report — audited, comprehensive, filed once a year. A 10-Q is the quarterly update — unaudited, narrower in scope, filed three times a year between annual reports. The line items and the math are the same in both; what changes is the reporting period and the level of detail surrounding it. For a full breakdown of what each filing includes, see [10-K vs. 10-Q: What's the Difference?](/blog/10-k-vs-10-q-differences-explained)

The reason "which line" matters as much as "which filing" is that companies do not all label the same concept the same way — one company's "Term Debt" is another's "Long-Term Debt, Current Portion." The only way to know you have the right number is to match it to its XBRL tag, the machine-readable identifier every public company attaches to every reported figure under SEC rules. For a primer on how this tagging system works, see [What Is XBRL?](/blog/what-is-xbrl) The on-screen label can shift between filings; the tag does not.

For this walkthrough, every figure comes from [Apple's](/stocks/AAPL) FY2025 10-K, pulled directly from GeminIQ's [Financial Statements](/features#financial-statements) view rather than a normalized summary. The balance sheet figures below reflect the fiscal year ending September 27, 2025.

---

## Step 2: Calculate a Liquidity Ratio — The Current Ratio

### What Is the Current Ratio?

The [Current Ratio](/metrics/liquidity-ratios/current-ratio) answers a narrow question: for every dollar a company owes in the next twelve months, how many dollars of short-term assets does it have on hand to cover it? It is the most commonly cited liquidity ratio because it requires only two inputs, both of which sit near the top of every balance sheet.

**Current Ratio = Current Assets / Current Liabilities**

**The Data:** On [Apple's](/stocks/AAPL) FY2025 balance sheet, Total Current Assets ("Total Current Assets," XBRL tag `Assets Current`) total **$147.96 Billion**, and Total Current Liabilities ("Total Current Liabilities," XBRL tag `Liabilities Current`) total **$165.63 Billion**. Divide one by the other:

**$147.96 Billion / $165.63 Billion = 0.89**

A current ratio of **0.89** means Apple holds **$0.89** in current assets for every **$1.00** of current liabilities due within the year — below the **1.0** line that a textbook would flag as a liquidity concern. For most companies that reading would matter. For Apple it is a feature of the model, explained in "When it breaks" below.

<center><sup>GeminIQ Financial Statements showing Apple's FY2025 Balance Sheet, with Total Current Assets (`Assets Current`: $147.96 Billion) and Total Current Liabilities (`Liabilities Current`: $165.63 Billion) highlighted. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** The current ratio treats every current liability as an equally urgent cash obligation, which is not always true. Apple is the clearest possible illustration: its **0.89** ratio sits below **1.0** not because it is short of cash, but because it collects from customers and holds vendor payables in ways that keep current liabilities high without threatening liquidity. A subscription or hardware-and-services business with large deferred revenue on the balance sheet can show a current ratio that looks weaker than its actual liquidity, because deferred revenue represents cash the company has already collected — not cash it still owes. The ratio is also not comparable across industries without context. A grocery chain operating with a current ratio below **1.0** is often showing operating efficiency, not distress — it collects cash from customers before it has to pay suppliers.

---

## Step 3: Calculate a Leverage Ratio — The Debt-to-Equity Ratio

### What Is the Debt-to-Equity Ratio?

The [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) measures how much of a company's asset base is financed by liabilities versus by shareholders' own capital. A ratio above **1.0** means liabilities exceed equity; below **1.0**, equity exceeds liabilities.

**Debt-to-Equity Ratio = Total Liabilities / Total Shareholders' Equity**

**The Data:** Apple's balance sheet reports Total Liabilities ("Total Liabilities," XBRL tag `Liabilities`) of **$285.51 Billion** and Total Shareholders Equity ("Total Shareholders Equity," XBRL tag `Stockholders Equity`) of **$73.73 Billion**.

**$285.51 Billion / $73.73 Billion = 3.87**

[Apple's](/stocks/AAPL) debt-to-equity ratio of **3.87** means total liabilities run nearly four times shareholders' equity.

<center><sup>GeminIQ Financial Statements showing Apple's Total Liabilities (`Liabilities`: $285.51 Billion) and Total Shareholders Equity (`Stockholders Equity`: $73.73 Billion) from the FY2025 Balance Sheet. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** Debt-to-equity lumps every liability together, but most line items inside Total Liabilities have nothing to do with financial leverage in the way the ratio's name implies. Of Apple's **$285.51 Billion** in Total Liabilities, only about **$98.66 Billion** — Commercial Paper (`Commercial Paper`: **$7.98 Billion**) plus Term Debt, current and non-current (`Long Term Debt Current` and `Long Term Debt Noncurrent`: **$12.35 Billion** and **$78.33 Billion**) — is actual interest-bearing debt. The remaining roughly **$186.85 Billion** is operating liabilities: Accounts Payable (`Accounts Payable Current`: **$69.86 Billion**), Deferred Revenue (`Contract With Customer Liability Current`: **$9.06 Billion**), and other current and non-current obligations that carry no interest rate at all. A standard screener flags a high debt-to-equity ratio as financial risk, but pulling the raw balance sheet shows a company can carry a high ratio almost entirely through operating liabilities rather than borrowed money. The ratio is also undefined for companies with negative equity — a position several large, profitable companies have reached through aggressive buyback programs — at which point it loses its interpretive value entirely.

---

## Step 4: Calculate a Profitability Ratio — Gross Profit Margin

### What Is Gross Profit Margin?

[Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) measures what share of revenue survives after the direct cost of producing the goods or services sold. GeminIQ's Gross Profit Margin is a trailing-twelve-month calculated metric. In a 10-K, where the income statement already covers a full fiscal year, the annual figure and the trailing-twelve-month figure converge — one of the practical advantages of building this ratio from an annual filing rather than a single quarter.

**Gross Profit Margin = Gross Profit / Revenue**

**The Data:** [Apple's](/stocks/AAPL) FY2025 income statement reports a "Gross Margin" line (XBRL tag `Gross Profit`) of **$195.20 Billion** against Total Revenues (`Revenues`) of **$416.16 Billion**. Because this is an annual filing, these are already full-year figures — no trailing-four-quarter summation is required. Divide the two:

**$195.20 Billion / $416.16 Billion = 46.91%**

The **46.91%** figure reflects a complete operating cycle by construction. This is the specific reason a 10-K is the cleaner starting point for a margin calculation than a 10-Q: a single quarter can be distorted by whatever seasonal mix happened to land in a thirteen-week window, and the annual figure removes that distortion without any manual aggregation.

<center><sup>GeminIQ Calculated Metrics showing Apple's Gross Profit Margin (46.91%), derived from Gross Profit (`Gross Profit`: $195.20 Billion) and Total Revenues (`Revenues`: $416.16 Billion) for FY2025. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** Gross margin comparisons break down across companies that classify costs differently. Some fold depreciation and amortization into Cost of Goods Sold; others report it separately below the gross profit line. Two businesses with identical underlying economics can show different gross margins purely because of where a non-cash charge gets classified — a distinction the ratio itself never reveals.

For a deeper look at what gross margin reveals about business model strength across industries, see [Gross Profit Margin: What It Reveals About Business Model Strength](/blog/gross-profit-margin-business-model-analysis).

---

## Step 5: Calculate a Valuation Ratio — Free Cash Flow Yield

### What Is Free Cash Flow Yield?

[Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) expresses a company's free cash flow as a percentage of its market capitalization — effectively, how much cash the business generates for every dollar of its current price tag. It requires building one calculated metric, [Free Cash Flow](/metrics/calculated-values/free-cash-flow), before dividing it by Market Capitalization.

**Free Cash Flow = Operating Cash Flow − Capital Expenditures**
**Free Cash Flow Yield = Free Cash Flow / Market Capitalization**

**The Data:** Apple's cash flow statement reports Cash Generated By Operating Activities (XBRL tag `Net Cash Provided By Used In Operating Activities`) and Payments For Acquisition Of Property, Plant And Equipment (XBRL tag `Payments To Acquire Property Plant And Equipment`). For FY2025 these are full-year figures: Operating Cash Flow totals **$111.48 Billion** and Capital Expenditures totals **$12.72 Billion**:

**$111.48 Billion − $12.72 Billion = $98.77 Billion in Free Cash Flow**

With [Apple's](/stocks/AAPL) Market Capitalization at **$3.80 Trillion**, dividing free cash flow by market cap gives:

**$98.77 Billion / $3.80 Trillion = 2.60%**

A Free Cash Flow Yield of **2.60%** means Apple generates roughly **2.6 cents** of free cash for every dollar of its current market value.

<center><sup>GeminIQ Calculated Metrics showing Apple's Free Cash Flow ($98.77 Billion) and Free Cash Flow Yield (2.60%), sourced from `Net Cash Provided By Used In Operating Activities` minus `Payments To Acquire Property Plant And Equipment`, divided by Market Capitalization. Source: 10-K filed October 31, 2025.</sup></center>

**When it breaks:** Market capitalization moves every trading day; the cash flow data behind it updates only once a quarter. A stock that has rallied sharply since its last filing will show an artificially compressed FCF yield against a current price, even though nothing about its underlying cash generation has changed — the denominator moved, not the business. The ratio can also penalize capital-intensive growth companies unfairly, since it makes no distinction between maintenance capex (spending required just to sustain the business) and growth capex (discretionary spending to expand it).

---

## Step 6: Reconcile Your Number Against the Platform

The discipline that separates a reliable by-hand calculation from a guess is checking it against a second source before trusting it. Every figure built above — Current Ratio **0.89**, Debt-to-Equity **3.87**, Gross Profit Margin **46.91%**, Free Cash Flow Yield **2.60%** — matches exactly what appears in GeminIQ's [Calculated Metrics](/features#calculated-metrics) view for [Apple](/stocks/AAPL), because both the manual math and the platform figure trace back to the same as-filed line items.

That reconciliation is not guaranteed on every platform. Two financial websites showing different debt-to-equity or FCF yield figures for the same company in the same period are not necessarily making an error — they may simply be using different definitions of "total debt" or "capex" without labeling the difference. For a deeper walkthrough of how to spot-check a platform's figures line by line, see [How to Verify Financial Data Against an SEC Filing](/blog/verify-financial-data-against-sec-filing) — and for a closer look at where those definitional gaps come from in the first place, see [Third-Party Financial Data: What Gets Lost When the Data Is Processed](/blog/third-party-financial-data-problems).

---

## Where This Process Breaks Down at Scale

Building four ratios for one company by hand, as above, takes maybe twenty minutes once the filing is open. Building the same four ratios for fifty companies — correctly, with correctly matched current vs. non-current debt, correctly separated operating and interest-bearing liabilities — does not scale linearly. It scales into hours of manual line-item hunting, and every hour adds another opportunity for a misread label or a wrong tag to slip into the math.

This is the specific problem GeminIQ's [Calculated Metrics](/features#calculated-metrics) library solves. The same as-filed inputs and the same formulas used in this walkthrough run automatically, consistently, across every company in the database — current ratio, debt-to-equity, gross profit margin, free cash flow yield, and more than fifty other metrics, recalculated the moment a new filing posts. Once you can calculate a ratio by hand, the [Stock Screener](/features#screener) becomes the tool for asking the same question across the entire market: which companies clear a current ratio above **1.5**, a debt-to-equity below **1.0**, or a free cash flow yield above **5%**, all at once.

For the metric that goes one level deeper than any single ratio here — combining profitability and capital efficiency into a single number — see [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained).

---

## Frequently Asked Questions

### Does this process work the same way for a 10-Q as it does for a 10-K?

Yes. The line items, the XBRL tags, and the formulas are identical between the two filing types. The only difference is reporting cadence — a 10-K covers a full, audited fiscal year, while a 10-Q covers one unaudited quarter with year-over-year comparisons. The advantage of building flow ratios like Gross Profit Margin or Free Cash Flow Yield from a 10-K is that the full year is already in the filing, so no trailing-four-quarter summation is needed.

### Why do some ratios use a single period and others use a full year?

Balance sheet ratios like the current ratio and debt-to-equity ratio are snapshots — they describe a company's position on one specific date, so a single period is correct by definition. Income statement and cash flow ratios like gross profit margin and free cash flow yield are flow measures. In a 10-K the flow figure already covers a full fiscal year; in a 10-Q you would sum the trailing four quarters to get the equivalent trailing-twelve-month figure and smooth out seasonality.

### Can I calculate these ratios without a paid data platform?

Yes. Every input in this guide is publicly available on SEC EDGAR for free. The tradeoff is time: locating the correct line item across dozens of possible label variations, and repeating the process for every company under analysis. A platform that pre-calculates these metrics from the same as-filed data removes the manual labor without changing the underlying math.

### Why might my by-hand calculation differ from a number I see on a different financial website?

The formula is rarely the source of disagreement — the definition of an input usually is. "Total debt" can mean only interest-bearing instruments or it can mean total liabilities, depending on the platform. "Capex" can include or exclude capitalized software development costs. If a by-hand calculation built from as-filed figures does not match a platform's displayed number, the input definitions disagree — not the filing.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-calculate-financial-ratios-10k)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Blog: How to Find Restatements in SEC Filings
source: https://www.geminiq.com/blog/how-to-find-restatements-in-filings

### How to Find Restatements in SEC Filings
Restatements rarely announce themselves clearly. This guide covers five practical ways to find one in SEC filings — from the Item 4.02 8-K that formally flags one, to the comparative-period arithmetic that catches the ones that never get flagged at all.

Most investors assume a restatement always comes with a loud announcement — a company standing up and saying its old numbers were wrong. Some do, in the form of an Item 4.02 [8-K](/blog/what-is-8-k) that explicitly withdraws reliance on prior financial statements. Many don't. A large share of restatements are corrected quietly inside the next periodic filing, disclosed in a footnote most readers never open. They're visible only if you compare the same fiscal period's figures across two different filings and notice they don't match. Standard financial media covers the loud kind and misses the quiet kind almost entirely.

This guide covers both. Five practical checks, from the filing that formally flags a restatement to the comparative-period arithmetic that catches the ones that never get flagged at all.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-find-restatements-in-filings)**

---

## Table of Contents

- [What Is a Restatement in an SEC Filing?](#what-is-a-restatement-in-an-sec-filing)
- [Big R vs. Little r Restatements](#big-r-vs-little-r-restatements)
- [Step 1: Check for an Item 4.02 8-K](#step-1-check-for-an-item-402-8-k)
- [Step 2: Check the 8-K/A Amendment History, Even Without a 4.02](#step-2-check-the-8-ka-amendment-history-even-without-a-402)
- [Step 3: Compare the Same Fiscal Period Across Two Filings](#step-3-compare-the-same-fiscal-period-across-two-filings)
- [Step 4: Search the Footnotes for "Restatement" or "Revision" Language](#step-4-search-the-footnotes-for-restatement-or-revision-language)
- [Step 5: Weigh an Auditor Change as a Leading Indicator, Not Proof](#step-5-weigh-an-auditor-change-as-a-leading-indicator-not-proof)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is a Restatement in an SEC Filing?

A restatement is a correction to financial statements a company has already filed. The period is closed, the numbers were reported, and the company is now telling the market that one or more of those figures was wrong and is being replaced. It is a statement about the past, not a change in outlook.

What produces one varies enormously in severity, which is why the word alone tells you almost nothing. At one end sits an error that moves cash between sections of the cash flow statement without changing the total — New Fortress Energy's reclassification of vendor payments from investing to financing activities is exactly that. At the other end sits fabricated revenue or hidden liabilities, where the corrected figures describe a materially different business. Both are restatements. Establishing which one you are looking at is the first thing to do after finding one, and the answer is usually in the affected line items rather than in the announcement.

The other thing to establish is which of two categories the correction falls into, because that determines where it will be disclosed — and whether it will be disclosed anywhere prominent at all.

## Big R vs. Little r Restatements

The SEC's informal shorthand splits corrections into two categories. The distinction is not about the dollar size of the error. It is about whether the original filing can still be relied upon.

| | Big R restatement | Little r restatement |
|---|---|---|
| What the company concludes | Specific previously issued financial statements should no longer be relied upon | The error is material enough to correct, but reliance on the original filing is not withdrawn |
| What gets filed | An Item 4.02 8-K, following the audit committee's determination | No standalone 8-K at all |
| Where the correction appears | Restated prior-period statements, with the auditor re-examining the corrected figures | Inside the next periodic filing — a footnote, and a comparative column that no longer matches what was originally reported |
| Knock-on consequences | Previously issued audit opinions can no longer be relied on for those periods; management must reassess whether the errors reflect a broader internal control weakness | None of the above is triggered |
| How you find it | Step 1 below — the 4.02 announces itself | Steps 3 and 4 below — arithmetic and footnote language, because nothing announces it |

The asymmetry is the whole reason this guide has five steps instead of one. A Big R restatement is a filing you can search for. A little r restatement is a discrepancy you have to notice.

## Step 1: Check for an Item 4.02 8-K

**Action: pull the company's EDGAR filing history and look for any 8-K carrying Item 4.02.**

An Item 4.02 8-K is the single clearest restatement signal a company can file. It's a formal statement that the company's own audit committee has concluded specific prior financial statements should no longer be relied upon. That's the SEC's informal term for a "Big R" restatement — the more severe of two restatement categories.

[New Fortress Energy's](/stocks/NFE) Item 4.02 8-K, filed March 17, 2026, is a clean example of what this looks like in practice. The company's Audit Committee determined that its audited FY2024 and FY2023 financial statements, along with every 2024 and 2025 quarterly filing, should no longer be relied upon. The stated cause: the company had been delaying payments to vendors on development projects to manage working capital. Those delayed payments had been classified as investing activities on the cash flow statement, when accounting rules required them to be classified as financing activities instead. A separate interest-capitalization error affected the 2025 quarters. The restatement would move cash flow between statement sections rather than change the company's total cash position — a real distinction from a restatement caused by fabricated revenue or hidden liabilities. That distinction is worth checking for specifically once you've found the 4.02.

A Big R restatement carries consequences beyond the numbers themselves. Filing the 4.02 means the company can no longer rely on its previously issued audit opinions for those periods. Its auditor has to re-examine the corrected figures, and management is required to reassess whether the errors reflect a broader weakness in internal controls. That's exactly what happened at New Fortress Energy, where the company disclosed it expected to identify additional material weaknesses as a direct result.

## Step 2: Check the 8-K/A Amendment History, Even Without a 4.02

**Action: filter the same filing history to 8-K/A and read the ones filed shortly after an earnings-related 8-K.**

A formal Item 4.02 isn't the only place a correction shows up. An 8-K/A — an amendment to a previously filed 8-K — can quietly restate a figure without ever invoking the non-reliance language that triggers a 4.02. Most 8-K/A filings are routine: a missing exhibit, a signature page, a formatting fix. The ones worth reading closely are the ones that change a number or materially revise the description of an event that already happened.

The practical check: pull up a company's full filing history on EDGAR, filter to 8-K/A, and read the ones filed in the weeks after an earnings-related 8-K rather than skipping past them as paperwork. A pattern of amendments that alter figures, especially several in a short window, is itself a signal. Either the original disclosure controls weren't catching errors before filing, or the company is correcting things in stages rather than all at once.

## Step 3: Compare the Same Fiscal Period Across Two Filings

**Action: put a fiscal year's originally reported figures next to the same year's comparative column in the following year's filing, and look for any line that moved.**

This is the check that catches what Item 4.02 misses entirely: the "little r" restatement. A little r correction is material enough to fix but not severe enough to require withdrawing reliance on the original filing — so it never generates an 8-K at all. It simply shows up as a different number the next time that period appears as a comparative column.

The method is direct arithmetic, not detective work. Pull a specific fiscal year's figures as originally reported in that year's own 10-K, then pull the same fiscal year's figures again from the comparative column of next year's 10-K. Every annual and quarterly report carries prior-period columns alongside the current one — that repetition is what makes the check possible, and it's one of the [structural differences between the 10-K and the 10-Q](/blog/10-k-vs-10-q-differences-explained) worth knowing before you start. For a well-run company, the two should match exactly. When they don't — a revenue line that shifts, a liability that grows, a cash flow category that moves between sections the way New Fortress Energy's did — that discrepancy is the restatement. It doesn't matter whether the company ever used the word.

This is also the check most data providers quietly make impossible. A normalized financial database maintains one value per line item per period, and when a company restates, that value is overwritten with the restated figure. The history looks clean because the disagreement has been resolved on your behalf — the original number, the one you need for the comparison, is simply no longer in the record. It's the practical cost of normalized data, and worth understanding before you rely on any single source for this; our [comparison with S&P Capital IQ](/competitor-comparison/sp-capital-iq) covers where that trade-off shows up. GeminIQ's [Financial Statements](/features#financial-statements) feature preserves every filing in a company's history rather than showing only the latest version, which is what makes this specific comparison possible without pulling two separate PDFs and lining up the rows by hand.

## Step 4: Search the Footnotes for "Restatement" or "Revision" Language

**Action: run a full-text search of the company's filings for "restated" and "revision," and read the early notes of the 10-K or 10-Q.**

When a little r correction is disclosed at all, it's almost always in the footnotes rather than the headline financial statements. It's typically under a note titled something like "Revision of Previously Issued Financial Statements" or simply "Restatement," tucked into the first several notes of the 10-K or 10-Q. These notes state the affected line items, the dollar impact by period, and usually a brief explanation of the underlying error.

Searching a specific company's filing history for the word "restated" or "revision" surfaces these corrections even when nothing else calls attention to them. Do this either directly on EDGAR's full-text search, or within the footnotes of whatever filing you're already reading. A company that used the word "restated" three times in its footnotes over two years, and never filed a single Item 4.02, has a materially different correction history than a company with no such language anywhere. Neither would be visible from the headline numbers alone.

## Step 5: Weigh an Auditor Change as a Leading Indicator, Not Proof

**Action: check for an Item 4.01 8-K, and treat a resignation differently from a mutual parting.**

An Item 4.01 8-K disclosing an auditor change, particularly an auditor resignation rather than a mutual parting, often precedes a restatement — but not always, and treating the two as equivalent produces false positives.

[Super Micro Computer's](/stocks/SMCI) October 2024 8-K, disclosing Ernst & Young's resignation as its auditor, is the case worth knowing precisely because it complicates the simple version of this rule. The resignation triggered a special committee investigation, months of delinquent filings, and real market alarm. The company's own account, laid out in its subsequent 10-K, states plainly that the Special Committee did not find the concerns EY raised in its resignation letter to be supported by the facts the committee examined. No Item 4.02 restatement followed. An auditor change is a reason to look harder at everything else on this list, not a substitute for actually checking it.

## Frequently Asked Questions

### What SEC filing shows a restatement?

An Item 4.02 8-K formally discloses a "Big R" restatement — a determination that specific prior financial statements should no longer be relied upon. Smaller "little r" corrections often appear only in the footnotes of the next 10-K or 10-Q, with no dedicated 8-K at all.

### What's the difference between a "Big R" and "little r" restatement?

A Big R restatement requires the company to withdraw reliance on previously issued financial statements, triggering an Item 4.02 8-K and a re-examination by the auditor. A little r restatement corrects a material error within the next periodic filing without withdrawing reliance on the original one, so it never generates a standalone 8-K. See [Big R vs. Little r Restatements](#big-r-vs-little-r-restatements) above for the full comparison, including where each one is disclosed.

### Does a restatement mean fraud?

Not by itself. Restatements cover a wide range of severity. A classification error that moves cash between sections of the cash flow statement without changing the company's total cash position — the situation New Fortress Energy disclosed — is a different event from a restatement caused by fabricated revenue or hidden liabilities, even though both carry the same label. The affected line items, and whether the corrected figures describe a materially different business, are what settle the question.

### What's the difference between a restatement and a revision?

Less than the words suggest. Companies disclose little r corrections under notes titled "Revision of Previously Issued Financial Statements" or simply "Restatement," and the choice of word is not a reliable guide to severity. That is precisely why Step 4 searches for both terms rather than one: the label tells you where the disclosure is, not how serious it is. What settles severity is whether an Item 4.02 was filed — that is, whether reliance on the original statements was formally withdrawn.

### Does an auditor resignation always mean a restatement is coming?

No. An auditor resignation, disclosed under Item 4.01, is a reason for closer scrutiny, but it doesn't guarantee a restatement follows. Super Micro Computer's 2024 auditor resignation led to an extensive investigation that concluded without an Item 4.02 restatement.

### How can I compare a company's reported figures across two different filings?

Pull the same fiscal period's figures from the filing where they originally appeared and from the comparative column of a later filing covering that same period. Any difference between the two, where one exists, is the restatement — whether or not the company used that word anywhere in either document.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-find-restatements-in-filings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference New Fortress Energy Inc.'s Current Report on Form 8-K (filed March 17, 2026, reporting an event dated March 15, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1749723/000174972326000008/nfe-20260315.htm).

The Super Micro Computer example references the company's Current Report on Form 8-K filed October 30, 2024, disclosing Ernst & Young LLP's resignation as its independent registered public accounting firm. All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1375365/000137536524000036/smci-20241024.htm).

---

## Blog: How to Read 13F Filings: Institutional Holdings Explained
source: https://www.geminiq.com/blog/how-to-read-13f-filing

### How to Read 13F Filings: Institutional Holdings Explained
A Form 13F filing discloses what institutional investment managers with at least $100 million in assets held in U.S. equities as of the prior quarter's end, but reading it correctly means understanding eight specific columns, three required components, and several disclosure gaps most coverage never mentions.

A Form 13F filing tells you what an institutional investment manager held in U.S. equities as of the last day of a calendar quarter — nothing more, nothing less. Financial media treats every 13F season like a live leak from inside a hedge fund, but the filing itself is a structured document with eight specific columns, three required components, and several disclosure gaps that most "13F tracker" headlines never mention. This guide walks through the form field by field: who has to file it, what each column in the Information Table actually means, where the data's blind spots are, and how to separate a real conviction signal from a reporting artifact.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-13f-filing)**

---

## Table of Contents

- [What Form 13F Is and Who Has to File It](#what-form-13f-is-and-who-has-to-file-it)
- [The Three Parts of a 13F Filing](#the-three-parts-of-a-13f-filing)
- [The Information Table: Reading Each Column](#the-information-table-reading-each-column)
- [Investment Discretion and the Other Managers Field](#investment-discretion-and-the-other-managers-field)
- [13F vs. Schedule 13D and 13G: A Common Point of Confusion](#13f-vs-schedule-13d-and-13g-a-common-point-of-confusion)
- [What a 13F Filing Doesn't Tell You](#what-a-13f-filing-doesnt-tell-you)
- [How to Track Institutional Ownership Without Reading Every 13F Manually](#how-to-track-institutional-ownership-without-reading-every-13f-manually)

---

## What Form 13F Is and Who Has to File It

Form 13F-HR is a quarterly report required under Section 13(f) of the Securities Exchange Act of 1934. Any institutional investment manager who exercises investment discretion over **$100 million** or more in Section 13(f) securities — the SEC's official list of roughly **17,500** qualifying stocks, ETFs, and certain equity options — must file. The SEC tests the threshold as of the last trading day of any month during the calendar year, not just the quarter-end. Cross it once, and the filing obligation continues for that quarter plus the following three, even if the manager's assets drop back below **$100 million** in the meantime.

The population of filers is broader than "hedge funds." It includes registered investment advisers, mutual fund companies, bank trust departments, insurance company investment divisions, pension fund managers, and broker-dealers exercising discretion. The SEC estimates more than **5,000** institutions file a 13F every quarter, ranging from managers with a handful of positions to those reporting tens of thousands of line items.

The filing is due within **45 days** after each calendar quarter ends. For 2026, that puts the deadlines at February 17 (Q4 2025 positions), May 15 (Q1), August 14 (Q2), and November 16 (Q3). There are no extensions — the SEC does not grant them. A manager that fails to file, or files late, faces possible enforcement action and penalties that can reach **$750,000**.

Not every 13F is a Holdings Report. A manager whose positions are entirely managed by another filer submits a Form 13F-NT — a notice filing confirming it has no holdings of its own to report because another manager is reporting on its behalf. A manager that both holds its own positions and reports on behalf of others files a Combination Report. Knowing which variant you're looking at before reading the data matters: an NT filing with a ticker search will return nothing, by design.

---

## The Three Parts of a 13F Filing

Every Form 13F-HR has three required components, and most of the analytical confusion around 13F data comes from treating the filing as a single document rather than three.

The **Cover Page** establishes who is filing, for which reporting period, and whether the submission is an original or an amended filing (13F-HR/A). It also discloses whether the manager has requested confidential treatment for any positions — a detail that matters more than it sounds like it should, covered below.

The **Summary Page** condenses the entire filing into two numbers: the total count of Information Table entries and the aggregate market value of everything reported. If the manager is filing jointly with other managers, the Summary Page also lists every "Other Included Manager" covered by the same submission.

The **Information Table** is where the actual position-level data lives, and it's the part every 13F tracker is really built around. Each row represents one security held at quarter-end, broken into eight required columns.

---

## The Information Table: Reading Each Column

**Column 1 (Name of Issuer)** and **Column 2 (Title of Class)** identify the security and the specific class — common stock, a preferred series, an ETF unit. Reasonable abbreviations are permitted, which is why the same company can appear with slightly different naming across different managers' filings.

**Column 3 (CUSIP Number)** is the nine-digit identifier for the security. Managers may optionally add a twelve-character Financial Instrument Global Identifier (FIGI) alongside it, though CUSIP remains the primary lookup field.

More readers misread **Column 4 (Value)** than any other field in the table. It reports the market value of the position **in thousands of dollars** — a row showing "275" means **$275,000**, not **$275**. Aggregators that fail to apply this scaling, or that round it inconsistently across filers, produce position-size comparisons that are off by three orders of magnitude. This is a basic data-hygiene check worth running on any 13F source before trusting its totals.

**Column 5 (Amount and Type of Security)** reports the total share count or principal amount, tagged "SH" for shares or "PRN" for principal amount. If the holding is an option, the column also carries a "PUT" or "CALL" designation — one of the only places in the form where directional positioning shows up explicitly.

**Column 6 (Investment Discretion)** and **Column 7 (Other Managers)** establish who actually controls the decision behind the position — covered in detail in the next section, since this is where the signal quality of a 13F filing is decided.

**Column 8 (Voting Authority)** splits the share count into Sole, Shared, and None — how much control the manager has over how those shares are voted, independent of who made the investment decision. A large "None" figure typically indicates the shares are held through a structure — a sub-advisory mandate, a model portfolio — where voting rights sit with someone else entirely.

---

## Investment Discretion and the Other Managers Field

Column 6 only accepts three values: SOLE, DFND, or OTR. The distinction between them determines whether a position represents one manager's independent conviction or a shared decision spread across a reporting structure.

**SOLE** means the filing manager alone made the investment decision — no other entity shares discretion over that position. This is the cleanest signal in the entire form. When a manager reports a large SOLE position, the conviction behind it belongs entirely to that manager.

**DFND** applies when discretion over a position is shared with another manager who is also a filer included in the same Form 13F submission — typically a parent firm and a subsidiary, or multiple entities under common control filing jointly. **OTR** applies when discretion is shared with a manager or person *outside* the current filing group entirely. Both codes require the filer to identify the other party in **Column 7 (Other Managers)**, cross-referenced by a number tied to the Summary Page's list of Other Included Managers.

The practical implication: a position marked DFND or OTR is not solely attributable to the headline filer. A position tagged "BlackRock — DFND" might represent a single index fund's mechanical allocation, not an active portfolio manager's bet. Standard 13F aggregators report the headline manager and the share count and stop there. Pulling the raw Information Table is the only way to see whether a position is a SOLE conviction call or a shared mandate spread across a reporting group — a distinction that changes what the filing actually tells you about institutional sentiment.

---

## 13F vs. Schedule 13D and 13G: A Common Point of Confusion

Financial media reports "a fund just disclosed a stake" the same way regardless of which filing triggered it, but Form 13F and Schedules 13D/13G are answering completely different questions. Crossing **5%** beneficial ownership in a single company triggers Schedule 13D or 13G — filed by any investor, institutional or individual, the moment that specific threshold is crossed for that specific issuer. A 13D signals the investor may seek to influence the company; a 13G signals a passive stake.

Form 13F has nothing to do with the **5%** threshold. It's an aggregate quarterly snapshot of *every* qualifying equity position a manager holds, regardless of whether any single position represents **5%** of that company's shares or **0.005%**. A manager with **$50 billion** spread across 4,000 small positions files a 13F. A manager with one concentrated **6%** stake in a single small-cap files a 13D — and may also separately need to file a 13F if its total assets clear the **$100 million** threshold. For the full breakdown of how 13D, 13G, and the rest of the SEC's disclosure regime fit together, see [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide). The two filings can overlap for the same manager, but they answer entirely different questions and exist for entirely different reasons.

---

## What a 13F Filing Doesn't Tell You

The gap between what a 13F shows and what financial media implies it shows is where most of the misreading happens. Form 13F never discloses short positions, and it never nets them against the long positions a manager reports. A manager showing a large long stake in a name could simultaneously be running an offsetting short elsewhere in the same portfolio — invisible, by design, in every 13F that manager files.

The **45-day** reporting lag means every 13F is a snapshot of a position that's already six-plus weeks old by the time it's public. A manager could have closed the entire position the day after quarter-end, and the filing reporting it as a large holding would still be technically accurate the day it's released.

Confidential treatment requests let a manager petition the SEC to temporarily withhold specific positions from public disclosure — typically while the manager is still accumulating a stake and doesn't want to signal its own buying pressure into the market. Those positions appear later, once treatment is denied or expires, often well after the rest of that quarter's filing is public.

The Information Table only contains what's on the official Section 13(f) securities list. Non-convertible bonds, cash, real estate, private placements, and most over-the-counter derivatives never appear — a manager's full balance sheet exposure is always larger than what its 13F shows. And the form reports shares and market value at quarter-end only. No cost basis, no entry price, no realized gain. A 13F tells you what a manager holds. It does not tell you whether that manager is up or down on the position, or by how much.

---

## How to Track Institutional Ownership Without Reading Every 13F Manually

None of that diminishes the value of tracking 13F data systematically — it just means systematic tracking has to account for the lag and the gaps rather than treating any single filing as gospel. More than **5,000** managers file every quarter, and a single large fund's Information Table alone can run to thousands of rows. Reconstructing a single stock's institutional ownership trend — who's accumulating, who's trimming, how the aggregate percentage held by institutions has moved over the last two years — means cross-referencing the Information Table of every manager that holds the stock, every quarter, by hand.

The analytical value compounds the same way it does with insider transaction data. A single quarter's 13F tells you almost nothing on its own — it can't distinguish a manager that's been steadily building a position for two years from one that opened it last week. Only the trend across multiple quarters separates genuine accumulation from a data point that happens to look interesting in isolation, and assembling that trend manually from individual filings is impractical at any meaningful scale.

<center><sup>GeminIQ 13F Institutional Holdings tracker showing institutional ownership percentage aggregated from quarterly Form 13F filings, plotted over time against total shares outstanding.</sup></center>

GeminIQ's [Institutional Ownership](/features#institutional-ownership) feature aggregates the raw Form 13F data across every quarter automatically, tracking institutional ownership as a percentage of shares outstanding over time — so a multi-year accumulation or distribution trend that would otherwise require manually compiling thousands of individual filings becomes visible immediately. Because the data is sourced directly from the SEC filings rather than a third-party aggregator, the underlying percentage reflects the actual reported positions, not a smoothed or estimated figure. The trend is only as trustworthy as the filings it's built from. For a closer look at how institutional ownership trends interact with other filing signals — insider transactions, balance sheet shifts, post-filing price reactions — see [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings).

---

## Related Reading

Form 13F is one piece of a broader disclosure system. For the rest of the picture:

- [Institutional Ownership: What It Means and How to Track It](/blog/institutional-ownership-13f-filing-explained) — once you can read a single filing, this covers how to read the ownership trend across quarters and what the percentage actually signals.
- [Form 13F](/glossary/form-13f) — the one-line definition, filing threshold, and deadline, in the SEC filings glossary.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — covers 10-K, 10-Q, 8-K, DEF 14A, S-1, Form 4, and 13D/13G in a single reference.
- [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4) — the companion filing that shows what insiders, rather than institutions, are doing with their own capital.
- [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings) — how institutional ownership trends combine with insider activity and balance sheet shifts for a complete picture.

## Frequently Asked Questions

### What are 13F filings?

13F filings are quarterly reports that institutional investment managers with at least $100 million in qualifying US equities must file with the SEC. Each one lists the manager's long positions in those securities as of quarter-end, which is why investors use them to see what hedge funds and other large investors own.

### When are 13F filings due?

Within 45 days after the end of each calendar quarter. In 2026 that puts the deadlines at February 17, May 15, August 14, and November 16, so the holdings shown are already six weeks to four and a half months old when they become public.

### Where can I look up 13F filings?

Every 13F is free on the SEC's EDGAR system: search for the manager's name and filter for form type 13F-HR. GeminIQ also aggregates the institutional holdings they report into ownership data for each company, so you can see which institutions hold a stock without opening each filing.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-13f-filing)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: How to Read a Balance Sheet: A Line-by-Line Guide
source: https://www.geminiq.com/blog/how-to-read-a-balance-sheet

### How to Read a Balance Sheet: A Line-by-Line Guide
A balance sheet is the equation Assets = Liabilities + Equity, frozen on one date. Learning to read it means learning what each side is really telling you about solvency, liquidity, and how the business is financed — using Apple's latest 10-Q as the working example.

A balance sheet is the one financial statement that isn't about a span of time. The income statement covers a quarter or a year; the cash flow statement covers the same window. The balance sheet is a single photograph taken on the last day of the period — everything the company owned, everything it owed, and whatever was left over for shareholders, all frozen at one instant. Most investors glance at the total assets number, note that it's big, and move on. That's the number that matters least.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-a-balance-sheet)**

What matters is the relationship between the three pieces, and the order in which the line items are listed — because that order is not arbitrary. It encodes exactly how quickly each asset turns into cash and how soon each obligation comes due. Once you can read that ordering, the balance sheet stops being a wall of numbers and starts telling you whether a company can survive a bad year.

This guide walks through a balance sheet line by line, using **[Apple's](/stocks/AAPL) Q3 FY2026 10-Q** (filed July 31, 2026, for the period ending June 28, 2026) as the working example, and shows you how [GeminIQ](/) pulls every one of these line items straight from the SEC filing with its XBRL tag intact — so the number you analyze is the number the company actually reported.

---

## Apple's Balance Sheet at a Glance (Q3 FY2026)

| Line item | Value | What it tells you |
|---|---|---|
| Total assets | **$383.27 Billion** | Everything the company owns |
| Total liabilities | $275.75 Billion | Everything it owes |
| Shareholders' equity | $107.52 Billion | The residual left for owners |
| Current assets | $149.82 Billion | Assets convertible to cash within a year |
| Current liabilities | $149.33 Billion | Obligations due within a year |
| Total debt | $84.34 Billion | Interest-bearing debt (short- + long-term) |
| Net debt | $44.80 Billion | Total debt minus cash |

<sup>*All figures from Apple's Q3 FY2026 10-Q, period ending June 28, 2026. Point-in-time balance as reported to the SEC.*</sup>

---

## Table of Contents

- [What Is a Balance Sheet?](#what-is-a-balance-sheet)
- [Step 1: Start With the Accounting Equation](#step-1-start-with-the-accounting-equation)
- [Step 2: Read the Assets, Top to Bottom](#step-2-read-the-assets-top-to-bottom)
- [Step 3: Read the Liabilities the Same Way](#step-3-read-the-liabilities-the-same-way)
- [Step 4: Understand Shareholders' Equity](#step-4-understand-shareholders-equity)
- [Step 5: Turn the Statement Into Ratios](#step-5-turn-the-statement-into-ratios)
- [Reading the Balance Sheet Across Time](#reading-the-balance-sheet-across-time)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is a Balance Sheet?

A balance sheet is a statement of financial position at a single point in time. Where the income statement answers "how much did the company make?" and the cash flow statement answers "where did the cash go?", the balance sheet answers "what does the company own, what does it owe, and what's left for the owners — right now?"

It is called a balance sheet because it must balance: the two sides of the accounting equation are always equal, by construction. Every dollar of assets was financed either by a creditor (a liability) or by an owner (equity). There is no third source. That constraint is what makes the statement so useful — it forces every financing decision a company has ever made to show up somewhere on the page.

Public companies report a balance sheet in every 10-K (annual, audited) and every 10-Q (quarterly, unaudited). The 10-K version is signed off by an independent auditor, which is the highest reliability standard corporate financial data gets. If you're new to the filings themselves, our guide on [how to read a 10-K](/blog/how-to-read-10-k) covers where the balance sheet sits inside the larger document.

---

## Step 1: Start With the Accounting Equation

Before you read a single line item, hold the whole statement in one equation:

**Assets = Liabilities + Shareholders' Equity**

Everything on a balance sheet is one of those three things, and the left side always equals the right side. Rearranged, it says something more intuitive: **Equity = Assets − Liabilities.** Shareholders' equity is simply what would be left for the owners if the company sold every asset at its recorded value and paid off every debt. It is the residual, not the starting point — which is why it sits at the bottom of the statement, after both assets and liabilities have been laid out.

This is also why a company can have enormous assets and still be fragile: if the liabilities financing those assets come due faster than the assets can be converted to cash, the size of the asset base doesn't help. The equation balances on paper while the company runs out of money in practice. Reading a balance sheet well is mostly about reading *timing* — and timing is encoded in the ordering of the line items, which is Step 2.

---

## Step 2: Read the Assets, Top to Bottom

Assets are listed in order of liquidity — how quickly each one can be turned into cash. This ordering is the single most important thing to understand about the asset side, because it splits the section into two halves that mean very different things.

**Current assets** come first: cash and cash equivalents, short-term marketable securities, accounts receivable (money customers owe you), and inventory. These are the assets expected to convert to cash within twelve months. In [Apple's](/stocks/AAPL) Q3 FY2026 10-Q, current assets total **$149.82 Billion** — including $39.54 billion in cash, $31.40 billion in receivables, and $11.09 billion in inventory — the resources available to cover near-term obligations.

**Non-current (long-term) assets** come below: long-term marketable securities, property, plant and equipment (PP&E), and intangible assets. Apple carries $51.43 billion in PP&E and $233.45 billion in non-current assets overall — the resources the business runs on but can't quickly liquidate without disrupting operations. Two long-term line items deserve special attention. **Goodwill** appears only when a company has acquired another business for more than the fair value of its identifiable assets — it is the premium paid, and it never turns into cash; it can only sit there or be written down. A large goodwill balance tells you a company grew by acquisition, and a goodwill impairment in a later filing tells you it overpaid. (Apple is a useful counter-example here: it grows almost entirely by building rather than buying, so goodwill is a negligible part of its balance sheet — the opposite of an acquisition-driven roll-up.) Intangible assets (patents, developed technology, customer relationships) are similar: real to the business, but not a source of liquidity.

The practical read: add up current assets, note how much of the total asset base is truly liquid versus locked into operations and acquisitions, and remember that the total is the least informative number on the section. A company with $400 billion in assets that are 90% illiquid is in a very different position from one with $400 billion that is half cash.

---

## Step 3: Read the Liabilities the Same Way

Liabilities follow the mirror-image logic of assets: they're listed in order of when they come due.

**Current liabilities** come first — obligations due within twelve months: accounts payable (money owed to suppliers), accrued expenses, short-term debt, and the current portion of long-term debt. In Apple's Q3 FY2026 10-Q, current liabilities total **$149.33 Billion**, including $64.53 billion in accounts payable and $13.00 billion in short-term debt. This is the section that determines whether a company has a near-term liquidity problem, because these are the bills landing inside the next year.

**Non-current liabilities** come below: long-term debt, deferred tax liabilities, and long-term lease obligations. Apple carries $71.34 billion in long-term debt within $126.42 billion of non-current liabilities. Long-term debt is where you find the company's real leverage, and the notes to the financial statements break out its maturity schedule — how much comes due in 2027, 2028, and beyond. That maturity schedule is where refinancing risk lives, and it's a detail no summary dashboard surfaces.

Here's the reframe that changes how you read this section: a liability is not automatically a bad thing, and some are barely liabilities at all. **Deferred revenue** — cash a company has already collected for a product or service it hasn't yet delivered — sits in current liabilities ($9.54 billion for Apple), but it represents customers pre-paying, which is a sign of pricing power, not distress. Accounts payable works the other way too: a company that takes longer to pay suppliers is effectively borrowing from them interest-free. The businesses with the healthiest balance sheets often carry *more* of these "good" liabilities, not fewer. This is why [total debt](/metrics/calculated-values/total-debt) — the interest-bearing obligations specifically, **$84.34 Billion** for Apple — is a more meaningful leverage figure than the $275.75 billion in total liabilities, which lumps the operational and the financial together.

---

## Step 4: Understand Shareholders' Equity

Shareholders' equity is the residual — assets minus liabilities — but its internal composition tells you the company's whole financing history.

The main components are **common stock and additional paid-in capital** (what shareholders originally paid in when shares were issued), **retained earnings** (the cumulative profit the company has kept rather than paid out over its entire life), and **treasury stock** (shares the company has bought back, carried as a negative number that *reduces* equity). Retained earnings is the quiet headline here: a large, growing retained-earnings balance means decades of accumulated profitability that management chose to reinvest. A negative retained-earnings line — an accumulated deficit — means the company has lost more money over its life than it has made, or has returned more to shareholders than it earned.

Apple is the textbook case of the second possibility, and it's worth pausing on. Apple has earned **$128.93 Billion** in net income over the trailing twelve months alone — yet its retained earnings sits at just **$11.33 Billion** and total shareholders' equity at $107.52 billion. How does one of the most profitable companies in history carry so little accumulated equity? Because it has spent more than a decade returning nearly all of its profit to shareholders through buybacks and dividends. The repurchases pile up against equity and hold retained earnings down, even as the business throws off enormous cash. When you see thin equity like this, the question to ask isn't "is this company insolvent?" — it's "is this thin equity the result of losses, or the result of returning enormous amounts of capital to shareholders?" Those are opposite situations that look identical on the equity line alone. It's also why [return on equity](/metrics/returns-and-profitability/return-on-equity) can be misleading for heavy repurchasers — Apple's ROE runs above 148% precisely because that shrunken equity base is the denominator — and why [return on invested capital](/metrics/returns-and-profitability/return-on-invested-capital) (roughly 85% for Apple) is often the better read on how efficiently the business actually uses its capital.

---

## Step 5: Turn the Statement Into Ratios

A balance sheet on its own is a list. Its analytical power comes from a handful of ratios that measure the relationships between the line items — the timing questions Step 1 flagged, answered with numbers.

**Liquidity — whether it can pay the next twelve months.**

The [current ratio](/metrics/liquidity-ratios/current-ratio) divides current assets by current liabilities. Above 1.0 means more short-term assets than short-term bills; below 1.0 means the opposite. Apple's sits at almost exactly **1.00** ($149.82 billion against $149.33 billion) — but a below-1.0 or right-at-1.0 current ratio is not automatically a warning: capital-light businesses that collect from customers before paying suppliers routinely run near or below 1.0 as a sign of *efficiency*, not distress. The [quick ratio](/metrics/liquidity-ratios/quick-ratio) is the more conservative cut — it strips out inventory, which can be slow or impossible to convert to cash, and asks whether the most liquid assets alone cover current liabilities. Apple's quick ratio is 0.93.

**Leverage — how much of the company is financed by debt.**

The [debt-to-equity ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) compares total debt to shareholders' equity — how many dollars of borrowed money back each dollar of owner capital. Apple's is **2.56**, which looks high until you remember the denominator: that ratio is elevated largely because buybacks have shrunk equity, not because the company is over-borrowed. The [debt ratio](/metrics/leverage-and-debt-ratios/debt-ratio) compares total debt to total assets. Both answer the solvency question the current ratio doesn't: not "can it pay this year's bills?" but "how much of everything is owed to someone other than shareholders?" And because cash can be used to pay down debt, [net debt](/metrics/calculated-values/net-debt) — total debt minus cash — is often the truer leverage figure. Apple's $84.34 billion in total debt against $39.54 billion in cash leaves **$44.80 Billion** in net debt, a modest figure against $146.72 billion in trailing operating cash flow — the debt is real but trivially serviceable. The lesson generalizes in the other direction too: a company with more cash than debt shows *negative* net debt, a net cash position, and its gross debt figure alone would badly overstate its risk.

The reason to compute these from the as-filed balance sheet rather than a data provider's normalized version is that normalization changes the inputs. If an aggregator reclassifies an operating lease, folds a company-specific line into a standard bucket, or defines "total debt" differently than the filing does, every ratio built on top shifts. GeminIQ's [Calculated Metrics](/features#calculated-metrics) compute each of these ratios from the values Apple actually reported to the SEC, with every input traceable back to its XBRL tag in the filing.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-a-balance-sheet)**

---

## Reading the Balance Sheet Across Time

A single balance sheet is a photograph; the analysis happens when you line up several of them. One quarter's current ratio tells you little. Four years of current ratios tell you whether liquidity is improving or quietly deteriorating. A single goodwill balance is just a number; a goodwill balance that jumps after an acquisition and then gets written down two years later tells you a story about capital allocation.

The line items to track across time are the ones that reveal trend rather than state: is retained earnings growing (the business is compounding) or shrinking (it's losing money or returning capital faster than it earns)? Is [net debt](/metrics/calculated-values/net-debt) rising while cash falls (leverage building) or the reverse (deleveraging)? Is inventory growing faster than sales (a demand problem forming) — a signal the income statement won't show you but the balance sheet will? These are the questions that separate reading a balance sheet from merely looking at one.

This is where the balance sheet connects to the other two statements. It shares its bottom line — cash — with the top of the [cash flow statement](/blog/cash-flow-statement-explained), and its retained-earnings line absorbs the net income produced by the [income statement](/blog/how-to-read-an-income-statement). Read all three together and you have the complete financial picture; read one in isolation and you're guessing at the other two.

GeminIQ presents the balance sheet [exactly as the company filed it](/features#financial-statements) — every line item, every period, side by side — so you can watch these trends develop across years without copying a single number into a spreadsheet.

---

## Frequently Asked Questions

### What is the basic formula of a balance sheet?

Assets = Liabilities + Shareholders' Equity. The two sides always equal each other by construction, because every asset a company holds was financed either by a creditor (a liability) or by an owner (equity). Rearranged, the same equation defines equity as the residual: Equity = Assets − Liabilities.

### What's the difference between current and non-current items?

"Current" means within twelve months. Current assets (cash, receivables, inventory) are expected to convert to cash within a year; current liabilities (payables, short-term debt) are due within a year. Non-current items sit outside that window — long-term assets like property and goodwill, and long-term liabilities like bonds and long-term leases. The split is what liquidity and solvency analysis is built on.

### Is a higher total assets number always better?

No. Total assets is the least informative figure on the statement. A large asset base tells you nothing about how liquid those assets are, how much debt financed them, or how efficiently they generate returns. A company with mostly illiquid assets funded by near-term debt can be far weaker than a smaller company sitting on cash. The relationships between the line items — not their totals — carry the analysis.

### Can a company have negative shareholders' equity and still be healthy?

Yes, though it requires reading the cause. Negative equity from accumulated losses signals a struggling business. But negative or thin equity can also result from years of aggressive share buybacks, which pile up as negative treasury stock and reduce equity even while the business generates strong cash flow. The equity line alone can't distinguish the two — you have to check whether retained earnings is negative from losses or whether treasury stock is doing the work.

---

## Wall Street's data. Main Street's price.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. We built GeminIQ because we believe you deserve a better fundamental analysis tool—one that goes beyond basic price charts and processed numbers. We extract our data directly from SEC 10-K and 10-Q filings to ensure that when you look at a balance sheet or a cash flow statement, you are seeing the numbers exactly how the company reported them. Our goal is to give you the tools to verify the narrative for yourself using clean, traceable data. Start researching now at [GeminIQ.com](/).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-a-balance-sheet)**

All financial figures cited in this article reference Apple Inc.'s Q3 FY2026 10-Q (filed July 31, 2026, for the fiscal period ending June 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-Q).

---

## Blog: How to Read an Income Statement: A Line-by-Line Guide
source: https://www.geminiq.com/blog/how-to-read-an-income-statement

### How to Read an Income Statement: A Line-by-Line Guide
An income statement reads top to bottom as a series of subtractions from revenue, and understanding what gets subtracted at each stage — cost of goods sold, operating expenses, interest, and taxes — is what separates a headline earnings number from an informed read of how a company actually made its money.

Most people read an income statement backwards. They skip to the bottom line — net income, the number in the headline — and treat everything above it as supporting detail. But the bottom line is the least informative number on the statement, because by the time revenue has been reduced to net income it has passed through four separate subtractions, each of which can hide or distort what actually happened to the business. The story is in the order of those subtractions, not the final figure.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-an-income-statement)**

An income statement reads top to bottom as a fixed sequence: start with everything the company sold, then subtract costs in a set order until you reach what shareholders keep. Learning to read it means learning what leaves at each stage and why — because a company can grow its top line while every margin underneath quietly compresses, and only the full statement shows you that.

This guide walks through an income statement line by line, using **[Apple's](/stocks/AAPL) Q3 FY2026 10-Q** (filed July 31, 2026, for the period ending June 28, 2026) as the working example, and shows how [GeminIQ](/) pulls every line straight from the SEC filing with its XBRL tag intact — so the number you analyze is the number the company actually reported.

---

## Apple's Income Statement at a Glance (Trailing Twelve Months)

| Line item | Value | Margin |
|---|---|---|
| Revenue | **$466.82 Billion** | — |
| Cost of goods sold | $239.70 Billion | — |
| Gross profit | **$227.12 Billion** | 48.65% gross margin |
| Operating expenses (R&D + SG&A) | $72.26 Billion | — |
| Operating income | **$154.86 Billion** | 33.17% operating margin |
| Net income | **$128.93 Billion** | 27.62% net margin |

<sup>*Trailing-twelve-month figures as of Apple's Q3 FY2026 10-Q, period ending June 28, 2026.*</sup>

---

## Table of Contents

- [What Is an Income Statement?](#what-is-an-income-statement)
- [Step 1: Start With Revenue](#step-1-start-with-revenue)
- [Step 2: Subtract Cost of Goods Sold to Get Gross Profit](#step-2-subtract-cost-of-goods-sold-to-get-gross-profit)
- [Step 3: Subtract Operating Expenses to Get Operating Income](#step-3-subtract-operating-expenses-to-get-operating-income)
- [Step 4: Account for Interest and Other Non-Operating Items](#step-4-account-for-interest-and-other-non-operating-items)
- [Step 5: Subtract Taxes to Get Net Income](#step-5-subtract-taxes-to-get-net-income)
- [Reading Margins, Not Just Dollars](#reading-margins-not-just-dollars)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is an Income Statement?

An income statement — also called a profit and loss statement, or P&L — is the filing that answers one question: did the company make money, and where did it go as it moved from total sales down to what shareholders actually got to keep? Every public company files one every quarter in its 10-Q and every year in its 10-K, and structurally, every income statement follows the same pattern regardless of industry: start with revenue at the top, subtract a series of costs in a fixed order, and arrive at net income at the bottom.

Reading the statement well means understanding what gets subtracted at each stage and why the order matters, not just skipping to the last line. It's also one of the three core financial statements that only make full sense together — the net income calculated here flows onto the [balance sheet](/blog/how-to-read-a-balance-sheet) as retained earnings, and it's the starting line of the [cash flow statement](/blog/cash-flow-statement-explained), which reconciles this accounting profit back to actual cash.

---

## Step 1: Start With Revenue

Revenue — sometimes labeled "net sales" or "total revenues" — is the top line: the total dollar amount a company collected from selling its products or services during the period, before any costs are subtracted. Over the trailing twelve months through its Q3 FY2026 10-Q, **[Apple](/stocks/AAPL)** reported **$466.82 Billion** in revenue, up 14.2% year over year. Nothing about this figure alone tells you whether Apple made money — it's the starting point every other line on the statement subtracts from.

Revenue growth rate — how this period's revenue compares to the same period a year earlier — is usually the first thing worth checking before reading further down the statement, since a company can grow every dollar figure below the top line while actually losing ground on the metric that matters most: whether customers are buying more.

---

## Step 2: Subtract Cost of Goods Sold to Get Gross Profit

Cost of Goods Sold, often abbreviated COGS and sometimes labeled Cost of Revenue, is the direct cost of producing whatever the company sold — materials, direct labor, manufacturing overhead for a physical product, or hosting and delivery costs for a digital one. Subtracting COGS from revenue produces gross profit, and dividing gross profit by revenue produces [gross margin](/metrics/margin-metrics/gross-profit-margin), the first and most fundamental profitability ratio on the statement.

Apple's trailing twelve months show gross profit of **$227.12 Billion** on that $466.82 billion in revenue — a gross margin of **48.65%**, after $239.70 billion in COGS. Gross margin varies enormously by business model: a software company can run gross margins above 80% because there's almost no direct cost to deliver another copy of code, while a grocery retailer might run gross margins in the low twenties because it's reselling physical goods with thin markup. The number only means something in the context of what kind of business is reporting it.

---

## Step 3: Subtract Operating Expenses to Get Operating Income

Operating expenses cover everything the company spends running the business that isn't directly tied to producing what it sold — research and development, selling and marketing, and general administrative overhead. These typically appear as separate line items rather than one lump sum, which matters: a company investing heavily in R&D relative to its size is telling a different story than one spending the same percentage of revenue on G&A.

Apple's trailing twelve months carry **$42.90 Billion** in research and development expense and $29.36 billion in selling, general, and administrative expense — $72.26 billion in operating expenses combined. Subtracting them from gross profit produces operating income — **$154.86 Billion**, an [operating margin](/metrics/margin-metrics/operating-profit-margin) of **33.17%**. Operating income is arguably the single most useful line on the entire statement, because it measures profitability from the core business alone, before financing decisions or tax strategy enter the picture at all.

---

## Step 4: Account for Interest and Other Non-Operating Items

Below operating income, the statement typically adds or subtracts a handful of non-operating items — interest expense on debt, interest income on cash holdings, and sometimes one-time gains or losses that aren't part of the ongoing business. This section is where capital structure differences between companies start to show up: two businesses with identical operating income can report very different figures below this line if one carries substantially more debt than the other. In Apple's case the effect runs the other way — its pretax income of $155.91 billion sits slightly *above* its operating income of $154.86 billion, because the interest and investment income on its enormous cash pile more than offsets the interest on its debt.

This is also the section most prone to distortion in a [price-to-earnings](/metrics/valuation-metrics/price-to-earnings-ratio) comparison across companies, since a large one-time gain or loss here can swing net income in a single period without reflecting anything about the underlying operating business — a distinction worth checking before reading too much into a single quarter's bottom line.

---

## Step 5: Subtract Taxes to Get Net Income

The final subtraction is income tax expense, applied to pretax income to produce net income — the number most often quoted in headlines and used to calculate earnings per share. For Apple's trailing twelve months, $26.98 billion in income tax on $155.91 billion of pretax income — an [effective tax rate](/metrics/returns-and-profitability/effective-tax-rate) of **17.3%** — leaves **$128.93 Billion** in net income, a 27.62% [net margin](/metrics/margin-metrics/net-profit-margin) and diluted EPS of roughly $8.80. Net income is the true bottom line: what's left for shareholders after every cost, from direct production expense down to the government's share, has been subtracted.

A company's effective tax rate can shift meaningfully between periods due to one-time items like the release of a deferred tax valuation allowance, a tax credit, or a change in the geographic mix of where profits were earned. Reading net income without checking the tax line above it can make two otherwise-identical operating years look different purely because of a tax event that has nothing to do with how the business actually performed.

---

## Reading Margins, Not Just Dollars

The dollar figures on an income statement only become fully useful once they're converted into margins — gross margin, operating margin, and net margin — and tracked over multiple periods rather than read in isolation. Apple's TTM chain of 48.65% gross, 33.17% operating, 27.62% net is a compact profile of a business: nearly half of every sales dollar survives production, two-thirds of that survives the cost of running the company, and most of what remains survives interest and taxes. A company growing revenue while those margins compress at every stage is telling a different story than one growing revenue while margins hold steady or expand, even if the top-line growth rate looks identical in a headline.

The most reliable way to catch a margin story before it becomes an earnings surprise is to track the full statement — not just net income — across several consecutive quarters, checking each margin stage independently rather than assuming a healthy top line means a healthy bottom line follows automatically. GeminIQ presents the income statement [exactly as the company filed it](/features#financial-statements), across every period side by side, with each margin already calculated from the as-filed figures — so the multi-quarter trend is laid out rather than assembled by hand.

---

## Frequently Asked Questions

### What's the difference between gross profit, operating income, and net income?

Gross profit is revenue minus the direct cost of producing what was sold. Operating income is gross profit minus the operating expenses of running the business — R&D, sales and marketing, and administrative costs. Net income is operating income further adjusted for interest, other non-operating items, and taxes. Each one answers a narrower question than the one before it, and reading only the last line skips the story of how the company got there.

### Why do gross margins vary so much between industries?

Gross margin reflects the direct cost of producing whatever a company sells, and that cost structure differs fundamentally by business model. A software company's gross margin can exceed 80% because delivering an additional copy of a product costs almost nothing, while a retailer or manufacturer reselling or building physical goods typically runs a gross margin well under half that, since the direct cost of the product itself is a much larger share of the sale price.

### Why can net income differ from operating income by a large amount?

The gap between operating income and net income is made up of non-operating items — interest expense, interest income, one-time gains or losses, and income tax — none of which reflect the core operating business. A large one-time gain, a big tax benefit, or a heavy debt load can each move net income substantially in either direction without any change to the operating business itself, which is why operating income is often the more stable metric to compare across periods.

### Is a bigger income statement number always better?

Not necessarily. Revenue growth funded by heavy discounting can grow the top line while shrinking gross margin. Net income inflated by a one-time tax benefit or asset sale can look like an earnings beat without reflecting any change in the operating business. Reading the full statement — checking whether margin, not just the dollar figure, moved in the right direction at each stage — is a more reliable read than any single line taken alone.

---

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

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<sup>All financial figures cited in this article reference Apple Inc.'s Q3 FY2026 10-Q (filed July 31, 2026, for the fiscal period ending June 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-Q).</sup>

---

## Blog: How to Read SEC Form 4: Insider Buying and Selling Explained
source: https://www.geminiq.com/blog/how-to-read-sec-form-4

### How to Read SEC Form 4: Insider Buying and Selling Explained
Form 4 is filed within two business days of every insider transaction. Here's a field-by-field breakdown of exactly what the document contains — and how to read it.

SEC Form 4 is a two-page document. Most investors either ignore it entirely or glance at the headline number and move on. Both approaches miss most of what the filing actually contains. The real information in a Form 4 is not the share count — it is the transaction code, the ownership type, the price paid, the post-transaction total, and whatever the footnotes say. Together, those five elements tell you whether an insider made an economic decision or a mechanical one. This guide walks through every field in the document so you can read any Form 4 that hits EDGAR and know exactly what it means.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=how-to-read-sec-form-4)**

---

## Table of Contents

- [What Form 4 Is and Who Has to File It](#what-form-4-is-and-who-has-to-file-it)
- [Step 1: Read the Header for Reporting Person and Issuer](#step-1-read-the-header-for-reporting-person-and-issuer)
- [Step 2: Work Through Table I for Non-Derivative Securities](#step-2-work-through-table-i-for-non-derivative-securities)
- [Step 3: Decode the Transaction Code, the Most Important Column](#step-3-decode-the-transaction-code-the-most-important-column)
- [Step 4: Check Table II for Derivative Securities](#step-4-check-table-ii-for-derivative-securities)
- [Step 5: Read the Footnotes Where the Context Lives](#step-5-read-the-footnotes-where-the-context-lives)
- [Step 6: Confirm Direct vs. Indirect Ownership](#step-6-confirm-direct-vs-indirect-ownership)
- [The Two-Business-Day Rule and What It Means for Timing](#the-two-business-day-rule-and-what-it-means-for-timing)
- [How to Track Form 4 Filings Without Reading Each One Manually](#how-to-track-form-4-filings-without-reading-each-one-manually)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Form 4 Is and Who Has to File It

Form 4 is a Statement of Changes in Beneficial Ownership. The SEC requires it from anyone who qualifies as an "insider" under Section 16 of the Securities Exchange Act of 1934. The definition of insider is more precise than the word suggests. It covers three groups: corporate officers, directors, and any person or entity that beneficially owns more than **10%** of a class of the company's registered equity securities.

The officer definition goes further than most investors expect. Under SEC rules, an officer for Form 4 purposes includes the president, principal financial officer, principal accounting officer, any vice president in charge of a principal business unit or division, any other officer who performs a policy-making function, and any person who performs a similar policy-making function regardless of title. A regional sales manager with no policy-making authority does not trigger the filing requirement. A chief revenue officer who sits in on board strategy sessions almost certainly does.

Directors are straightforward — every member of the board of directors must file. The **10%** beneficial ownership threshold applies to large shareholders: hedge funds, activist investors, or any other entity that accumulates a stake above that level.

The filing requirement is triggered by any transaction that changes the insider's beneficial ownership: open-market purchases, open-market sales, option exercises, RSU vestings, tax-withholding dispositions, and gifts. Each transaction type generates a Form 4. Understanding which type you are looking at is the first step in reading the filing correctly.

---

## Step 1: Read the Header for Reporting Person and Issuer

The top section of Form 4 establishes who is filing and for which company. It looks administrative, but several fields here carry analytical weight.

**Line 1 (Name of Reporting Person)** identifies the insider filing the report. Note whether the reporting person is an officer, a director, or a **10%** beneficial owner — this is stated explicitly in the checkbox fields just below the name. A filing by a director carries different interpretive weight than a filing by the CFO. A filing by a **10%** holder carries different weight still, since that entity's motivations may be entirely separate from any view on the company's near-term fundamentals.

**Line 2 (IRS Identification)** can be an individual's Social Security number (typically redacted for individuals, appearing as the last four digits or a placeholder) or an entity's EIN for corporate filers. For individual insiders, this field rarely matters. For entity filers — a hedge fund, an LLC, a family trust — cross-referencing the EIN against other SEC filings can reveal whether multiple Form 4 filers share the same beneficial ownership structure.

**Line 4 (Relationship of Reporting Person to Issuer)** is where the checkboxes appear: Director, Officer (with title specified), **10%** Owner, and Other. This is the field to read before anything else on the form. The relationship determines how much weight the transaction carries. An open-market purchase by the CFO is a fundamentally different signal than an open-market purchase by a board member who holds no operational role.

**Line 5 (If Amendment)** tells you whether this is an original filing or an amendment. Amended Form 4s — filed as 4/A — exist to correct errors in prior filings, update ownership totals, or add footnote disclosures. Always check whether a filing you are reading is original or amended. If it is an amendment, find the original and compare.

---

## Step 2: Work Through Table I for Non-Derivative Securities

Table I is the primary table for the vast majority of Form 4 analysis. It covers transactions in non-derivative securities — common stock, preferred stock, restricted stock units that have vested into shares, and any other direct equity holding. If an insider buys or sells actual shares, it appears here.

The table has seven numbered columns plus a Column 2A. Reading them left to right:

**Column 1 (Title of Security)** names the class of shares involved. For most public companies this is simply "Common Stock." Where it says something else — Class A Common Stock, Class B, Series B Preferred — note the distinction. Different share classes carry different voting rights, and the column 1 entry tells you which class the insider is transacting in.

**Column 2 (Transaction Date)** is the date the transaction executed, not the date the Form 4 was filed. The gap between these two dates should be no more than two business days. A filing that shows a transaction date significantly earlier than the filing date may indicate a late-filed report — something the SEC tracks and penalizes. Late filings are worth noting because they suggest the insider may have less rigorous compliance practices, or in rare cases, that the transaction date was recorded incorrectly.

**Column 2A (Deemed Execution Date)** is used only when a transaction was executed on a different date than it was deemed effective — common in certain derivative exercises and plan-based transactions. For most standard open-market buys and sells, this column is blank.

**Column 3 (Transaction Code)** is the single most important column in the entire form. It is covered in full in the next section.

**Column 4 (Securities Acquired (A) or Disposed Of (D))** has three parts: the number of shares, whether they were acquired (A) or disposed of (D), and the price. This is the headline number most investors look at. Context matters far more than the raw share count — a sale of 10,000 shares by a CEO who owns 5 million shares is a very different event than a sale of 10,000 shares by a director whose total ownership was 12,000.

**The price field in Column 4** shows the price per share at which the transaction executed. For open-market purchases and sales, this is the actual market price paid or received. For RSU vestings and option awards, this is often left blank or entered as zero because no cash changed hands. When the price column is blank on a transaction that appears to be a purchase or sale, that is a signal to check the transaction code — the field in Column 3 that explains why.

**Column 5 (Amount of Securities Beneficially Owned Following Reported Transaction(s))** is the post-transaction ownership total. This is the number to track over time. The direction of this figure — rising, falling, or stable — across multiple Form 4 filings tells you more than any single transaction. An insider who has been filing steady RSU vesting events for three years, with a rising total ownership number because they are not selling the vested shares, is behaving differently than one whose total ownership number has been declining steadily despite routine RSU grants.

**Column 6 (Ownership Form: Direct or Indirect)** is addressed in detail later in this guide. The short version: D means the insider holds the shares personally; I means the shares are held through some other entity — a trust, an LLC, a spouse, a foundation. **Column 7 (Nature of Indirect Beneficial Ownership)** names that entity.

---

## Step 3: Decode the Transaction Code, the Most Important Column

Column 3 is where most investors stop reading carefully — and where most of the analytical signal lives. The transaction code is a single letter that categorizes every transaction on Form 4. The codes that matter most for fundamental research are the following.

**P — Open-Market Purchase.** The insider spent their own money to buy shares at the current market price. No compensation plan required this. No option exercise triggered it. No vesting schedule delivered it. The insider made an affirmative decision to allocate personal capital to the stock. This is the only transaction code that represents a completely voluntary, out-of-pocket equity investment by an insider. P transactions are the primary signal in insider transaction analysis.

**S — Open-Market Sale.** The insider sold shares at the current market price on the open market. Like P, this is a voluntary decision. Unlike P, it is far more common — executives accumulate large equity positions through RSU grants and option awards, and routine diversification selling is rational regardless of the insider's view of the stock. An S transaction requires significant additional context before it carries analytical weight. How large is the sale relative to total holdings? Is there a footnote indicating a 10b5-1 plan? Has the insider been filing S transactions at a consistent cadence, or is this unusual?

**A — Grant, Award, or Other Acquisition Pursuant to the Compensation Plan.** An RSU grant, a stock option award, or any other equity compensation delivered through the company's plan. The insider did not choose this. The compensation committee granted it. An A transaction increases the insider's share count but represents no economic decision. It should not be interpreted as bullish conviction. The vast majority of Form 4 filings with large share counts are A transactions — which is precisely why the transaction code must be read before the share count.

**D — Disposition to the Issuer.** Shares returned or surrendered to the company. This most commonly appears when an executive forfeits unvested RSUs upon departure or when shares are tendered back to the company as part of a specific plan provision. A D transaction reduces share count but typically reflects a structural employment event, not a market view.

**F — Payment of Exercise Price or Tax Liability.** This is the tax-withholding code. When an RSU vests, the insider owes ordinary income tax on the fair market value of the vested shares. Rather than writing a check, most executives instruct the company to withhold a portion of the vested shares to cover the tax obligation. Those withheld shares appear as an F transaction — a disposition, reducing the insider's share count. F transactions generate a significant amount of the "insider selling" that appears in financial news headlines. They represent no economic decision on the insider's part. The shares were never received in cash form; they were surrendered automatically to pay a tax bill.

**M — Exercise or Conversion of Derivative Security.** An insider exercising stock options or converting a derivative instrument into common shares. The exercise itself is mechanical — options are exercised when they are in-the-money and approaching expiration. What matters is what happens immediately after. If the M transaction is followed by an S transaction on the same day or the next business day, the insider sold the acquired shares immediately — an exercise-and-sell that produces cash but signals no equity conviction. If the M transaction appears without a corresponding S transaction, the insider retained the acquired shares — a more meaningful signal.

**G — Gift.** Shares transferred as a gift, typically to family members or charitable foundations. G transactions appear as dispositions on the insider's Form 4. They carry no investment signal — the insider received no cash and is not expressing a negative view of the company by giving shares away.

The remaining codes — J, K, L, U, W, X, Z — cover special transactions such as small acquisitions, equity swaps, tender offers, and inherited securities. These appear infrequently in normal corporate filing activity and require individual assessment when they do.

---

## Step 4: Check Table II for Derivative Securities

Table II covers derivative securities: stock options, warrants, convertible notes, performance share units, and any other instrument that gives the insider the right or obligation to acquire or dispose of the underlying equity at a future date or price.

The structure of Table II is more complex than Table I. Each row covers a specific derivative instrument, and the columns capture both the derivative transaction itself and the underlying equity it converts into.

**Column 1 (Title of Derivative Security)** names the instrument — "Employee Stock Option (Right to Buy)," "Restricted Stock Unit," "Performance Share Unit," or similar. The exact instrument name matters because different derivatives have different exercise mechanics, expiration terms, and vesting conditions.

**Column 2 (Conversion or Exercise Price)** shows the strike price for options and warrants — the price at which the insider can purchase the underlying shares. For RSUs and performance share units, this is typically left blank or entered as zero because these instruments convert to shares automatically upon vesting without any cash outlay. The spread between Column 2 and the current market price tells you whether an option is in-the-money or out-of-the-money.

**Column 3 (Transaction Date)** and **Column 4 (Transaction Code)** function identically to Table I's Column 2 and Column 3.

**Column 5 (Number of Derivative Securities Acquired or Disposed Of)** shows how many derivative units were granted, exercised, or sold.

**Column 6 (Date Exercisable and Expiration Date)** is the window during which the derivative can be exercised. For stock options, this tells you the earliest exercise date (often tied to a vesting schedule) and the final date before expiration. An option exercise occurring close to the expiration date is far less informative than one occurring well ahead of it — near-expiration exercises are often forced by the ticking clock rather than by the insider's view of the stock.

**Column 7 (Title and Amount of Securities Underlying Derivative)** identifies the underlying security and the number of shares the derivative converts into. This is the figure to compare against Table I ownership to understand total beneficial ownership on a fully-converted basis.

**Column 8 (Price of Derivative Security)** captures the price paid or received for the derivative instrument itself — relevant for secondary-market transactions in exchange-traded derivatives. For most employee compensation derivatives (options, RSUs), this is zero because the instrument was granted, not purchased.

**Column 9 (Amount of Derivative Securities Beneficially Owned Following Reported Transaction)** shows the post-transaction derivative position, parallel to Column 5 of Table I.

**Column 10 (Ownership Form)** again distinguishes direct from indirect ownership.

For most analytical purposes, Table II is secondary to Table I. The P and S transaction codes in Table I — voluntary open-market transactions — carry the primary signal. Table II matters most when an insider's total equity exposure needs to be assessed on a fully-diluted basis, or when an M transaction in Table I (an option exercise) needs to be traced back to the derivative instrument that generated it.

---

## Step 5: Read the Footnotes Where the Context Lives

Every Form 4 has a footnotes section at the bottom. Standard financial news coverage never mentions the footnotes. This is the single biggest gap between how most investors read Form 4 data and how it should be read.

The footnotes are where the following information typically appears: whether a transaction is executed pursuant to a pre-established Rule 10b5-1 trading plan, the adoption date of that plan if disclosed, whether shares are held in specific trust structures, whether a transaction is part of a planned divestiture program, whether the filing amends a prior report and what the correction is, and any other context the insider or their legal counsel believes is material to understanding the transaction.

The 10b5-1 footnote is the most important one to identify. Rule 10b5-1 allows insiders to establish pre-planned trading schedules — setting the price, volume, and timing of future transactions — when they are not in possession of material non-public information. Once a valid 10b5-1 plan is in place, transactions can proceed automatically even during otherwise restricted windows, such as the period immediately before an earnings release. A sale executed under such a plan will almost always carry a footnote disclosure: language such as "This sale was made pursuant to a Rule 10b5-1 plan adopted on [date]."

When that footnote is present, the transaction carries substantially less analytical weight than a discretionary sale. The decision to sell was made on the plan adoption date — possibly months earlier — under conditions that may no longer be relevant. The current sale is mechanical execution of a prior decision.

When a large S transaction has no 10b5-1 footnote and no other disclosed reason, it deserves more scrutiny. That is a discretionary sale: the insider chose, within the current trading window, to convert equity into cash at the current market price. It is not automatically bearish — diversification, tax planning, and liquidity needs are all legitimate motivations — but the absence of a plan disclosure means the analytical context is thinner and requires more investigation.

The SEC tightened the 10b5-1 rules in 2023. For officers and directors, trading under a new plan cannot begin until the later of 90 days after adoption or two business days after the company discloses results for the quarter in which the plan was adopted, with a maximum of 120 days. This reform reduced the ability to create plans immediately in advance of anticipated news events. A plan adopted under the post-2023 rules carries somewhat more credibility than plans established before the reform.

---

## Step 6: Confirm Direct vs. Indirect Ownership

Column 6 of Table I and Column 10 of Table II require the filer to indicate whether each position is held directly (D) or indirectly (I). The indirect category covers a wide range of structures: revocable trusts, irrevocable trusts, family limited partnerships, LLCs, and positions held by a spouse or other family member for whose securities the insider is deemed to have beneficial ownership.

Direct ownership — shares held personally by the insider — is the cleanest signal. A direct open-market purchase means the individual, personally, spent their own money on the stock. A direct open-market sale means the individual, personally, converted shares to cash.

Indirect ownership is murkier. A sale of shares held in a family trust might reflect estate planning, a trustee's decision, a beneficiary's liquidity need, or the insider's own portfolio management — any of these, or some combination. A purchase of shares through an LLC could reflect the insider's personal investment decision or a vehicle the LLC uses for reasons unrelated to the underlying stock. The existence of indirect ownership is not itself suspicious, but it reduces the precision of the signal. When a Form 4 shows both direct and indirect transactions, weigh the direct transactions more heavily.

Where indirect ownership gets interesting is the nature column — Column 7 of Table I (Column 11 of Table II), where filers describe the indirect holding. "By the John Smith Revocable Trust" tells you one thing. "By the John Smith 2019 Charitable Remainder Trust" tells you another. "By Clearwater Capital Partners LP" tells you a third. The structure of the vehicle can illuminate the purpose of the transaction in ways the transaction code alone cannot.

---

## The Two-Business-Day Rule and What It Means for Timing

Before the Sarbanes-Oxley Act of 2002, insiders had up to 40 days to report a transaction on Form 4. The 2002 reform compressed that window to two business days from the transaction date. This change fundamentally altered the usefulness of Form 4 data for investors.

With a two-business-day window, Form 4 filings are nearly real-time. When an insider transacts today, the filing is typically public by Thursday or Friday of the same week. This means the information reaches the public market while the context is still fresh — price levels, recent news, and company events that were current when the decision was made are all still visible.

What the two-day rule also means is that late filings are detectable. If the transaction date in Column 2 is, say, March 3, and the filing date on the Form 4 header is March 14, the filing is late. The SEC tracks late Section 16 filings and companies are required to disclose them in their annual [proxy statement](/blog/what-is-def-14a). A pattern of late filings from a particular insider or a particular company's officers is a governance signal worth noting — it suggests either lax compliance culture or, in rare cases, deliberate delay.

For research purposes, the gap between transaction date and filing date is visible in EDGAR's filing metadata. GeminIQ's [Insider Transactions](/features#insider-transactions) feature displays the Filed Date for every transaction in a sortable table alongside owner name, relationship, title, ownership type, purchase/sale classification, share count, and price per share — so the lag between execution and disclosure is immediately visible without manual EDGAR comparison.

---

## How to Track Form 4 Filings Without Reading Each One Manually

A company with ten officers and board members, all receiving regular RSU grants and participating in 10b5-1 plans, may file dozens of Form 4s per quarter. Reading each one individually — parsing the codes, checking footnotes, calculating net position changes — is impractical as a routine research process.

The analytical value of Form 4 data compounds over time. A single filing tells you a transaction occurred. Twelve months of filings tells you the baseline pattern. Five years of filings tells you the structural behavior — who buys, who never buys, who sells consistently versus who rarely sells, and when the pattern breaks. The pattern break is the signal. But identifying a pattern break requires the full history, and assembling that history from individual EDGAR downloads is a significant manual effort.

<center><sup>GeminIQ Insider Transactions feature showing the monthly purchase/sale bar chart (green = purchases, red = sales) and the eleven-column sortable transaction table sourced directly from raw SEC Form 4 filings.</sup></center>

GeminIQ's [Insider Transactions](/features#insider-transactions) feature pulls directly from the raw Form 4 feed and displays every transaction in two views: a bar chart that plots total purchase and sale dollar volume by month — green bars for purchases, red bars for sales — filtered by any custom date range, and a sortable transaction table below it. The table shows eleven columns for every row: Filed Date, Owner, Relationship, Title, Ownership type (Direct or Indirect), Purchase/Sale classification, number of shares, price per share, total transaction value in dollars, shares owned after the transaction, and Document Type. Every column is filterable, so you can isolate, for example, all direct open-market transactions by officers within a specific date window in seconds.

Because GeminIQ sources from the raw SEC filing rather than a third-party aggregator, the ownership type, relationship, and title fields are preserved exactly as filed. The distinction between a direct sale by the CFO and an indirect sale through a family trust — which changes the analytical weight of the transaction entirely — is visible in the table without cross-referencing the original EDGAR document. The Shares Owned column, updated after each transaction, lets you track the direction of an insider's total position across the full history without manually reconstructing it from individual filings. The pattern break — when an insider who has never purchased shares on the open market suddenly does — is immediately visible. That is the signal. For a deeper look at how to interpret what Form 4 patterns reveal over time, see [Insider Trading Tracker: How to Track Insider Buying and Selling](/blog/insider-trading-tracker).

---

## Frequently Asked Questions

### How can you tell if an insider actually bought stock or just received it?

Read the transaction code (Column 3 of Table I) before anything else on the form. Code **P** means an open-market or private purchase — the insider spent their own money, and nothing required them to. Code **A** means a grant or award delivered under a compensation plan, which the compensation committee decided, not the insider. Both increase the share count and both look identical in a headline that reports only "insider acquires 50,000 shares." Only one of them reflects a view on the stock.

### What is a 10b5-1 footnote and why does it matter?

Rule 10b5-1 lets insiders pre-establish a trading schedule — price, volume, and timing — while they are not holding material non-public information. When a footnote discloses that a transaction executed under such a plan, the decision to trade was made on the plan's adoption date, possibly months earlier, under conditions that no longer apply. That transaction carries substantially less analytical weight than a discretionary one. A large **S** sale with no 10b5-1 footnote and no other disclosed reason is the case that deserves scrutiny. Since the SEC tightened the rules in 2023, officer and director plans also carry a mandatory cooling-off period of 90 days or until the next open trading window, whichever is later, capped at 180 days.

### What is the difference between direct and indirect ownership on a Form 4?

Column 6 of Table I (Column 10 of Table II) marks each position as held directly (**D**) or indirectly (**I**). Direct means the shares are held personally by the insider, which is the cleanest signal — a direct purchase means that individual personally spent their own money. Indirect covers trusts, family partnerships, and similar structures, where a transaction may reflect estate planning, a trustee's decision, or a beneficiary's liquidity need rather than any view on the company. The nature-of-ownership footnote is what distinguishes them, so read it before weighing an indirect transaction.

### What is a Form 4/A?

A 4/A is an amended Form 4, flagged in Line 5 of the header. Amendments exist to correct errors in a prior filing, update ownership totals, or add footnote disclosure that was missing. Always check whether the filing you are reading is an original or an amendment — if it is an amendment, pull the original and compare the two, because what changed is often the informative part.

### How do you know if a Form 4 was filed late?

Compare the transaction date in Column 2 against the filing date in the header. Since the Sarbanes-Oxley Act of 2002 the deadline has been two business days, so a transaction dated March 3 and filed March 14 is late. The SEC tracks delinquent Section 16 filers, and companies must disclose them in the annual proxy statement. A pattern of late filings is itself worth noting — it suggests looser compliance practice around the insider's trading.

### Which fields on a Form 4 carry the most information?

Five, in roughly this order: the transaction code (Column 3 of Table I), the direct-versus-indirect ownership flag, the price paid, the shares-owned-following-transaction total, and the footnotes. The raw share count — the number most coverage leads with — is the least informative of the group on its own, because it says nothing about whether the transaction was a decision or a mechanism.

### Where can I find a company's Form 4 filings?

On SEC EDGAR, open the company's filing list and filter by form type 4. Filings by the company's insiders are listed there, and each insider also has an EDGAR page of their own listing every Form 4 they have filed across companies.

### Who is required to file a Form 4?

Officers, directors, and anyone who beneficially owns more than 10% of a class of the company's registered equity securities, the insiders covered by Section 16 of the Exchange Act. They must report most changes in their holdings within two business days.

---

## Related Reading

Form 4 is one filing in a broader information system. For the full picture of how SEC disclosures fit together:

- [SEC Form 4 Transaction Codes: Full List and What Each Code Means](/blog/form-4-transaction-code-list) — all 20 single-letter codes decoded, with the signal weight of each.
- [Form 4](/glossary/form-4) — the one-line definition and filing deadline, in the SEC filings glossary.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — covers 10-K, 10-Q, 8-K, DEF 14A, S-1, and Form 4 in a single reference.
- [How to Read a 10-K: A Value Investor's Guide](/blog/how-to-read-10-k) — the foundational annual filing that Form 4 data sits alongside.
- [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings) — how insider transaction patterns combine with balance sheet shifts and cash flow signals for a complete picture.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Insider Cluster Buying: What the Data Actually Shows
source: https://www.geminiq.com/blog/insider-cluster-buying-signal-data

### Insider Cluster Buying: What the Data Actually Shows
Insider cluster buying — simultaneous open-market purchases by multiple insiders at the same company — produces categorically stronger forward returns than any individual transaction. This post covers the academic evidence and a five-factor quality scoring framework.

**Insider buying is an open-market purchase of a company's stock by one of its officers, directors, or 10% owners, reported on SEC Form 4 with transaction code P.** It is the one insider transaction that means the person chose to spend their own money on the stock, which is why it carries more information than insider selling, and why several insiders buying at once, a cluster buy, carries more than any single purchase.

Financial media covers insider transactions as if every filing is equal signal. A CEO buys 10,000 shares — financial sites flag it. A director sells 5,000 — that generates a headline too. Both responses treat the individual transaction as the unit of analysis. The research record says they shouldn't.

Decades of empirical work on insider trading finds the same thing: individual insider purchases produce modest abnormal returns, inconsistently, with enough noise to make them unreliable as standalone research inputs. Cluster buying events — where multiple insiders at the same company purchase shares on the open market within a short window — produce returns that are categorically stronger and far rarer. The convergence of independent informed opinion is what creates the signal. And most investors never track it systematically because most platforms don't surface it cleanly.

This post covers the research evidence behind why the signal concentrates in clusters rather than individual transactions, what factors separate high-quality cluster events from low-quality ones, and what GeminIQ's raw Form 4 data reveals when you apply that framework to [GameStop's](/stocks/GME) 17-year insider transaction history.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=insider-cluster-buying-signal-data)**

---

## Why Individual Insider Buys Are A Weaker Signal Than You Think

The intuition behind insider buying as a signal is sound. An executive who purchases shares on the open market with personal capital is making a deliberate decision — a view on valuation, a bet on near-term catalysts, a statement of confidence in the business. That's categorically different from receiving RSUs through a compensation plan or exercising expiring options. They chose to buy at the current price with their own money.

But intuition and data don't always agree. The noise in any individual insider buy signal is substantial. Insiders purchase for reasons that carry no analytical content: stock ownership guideline compliance, portfolio optics ahead of an investor day, signaling stability during a CEO transition, tax-offset positioning. A director buying **2,000 shares** at **$20** to satisfy a minimum board ownership requirement generates a Form 4 filing that looks identical to a director buying **2,000 shares** at **$20** because they believe the company is trading at a significant discount to intrinsic value. The filing reports the code and the price. It doesn't report the motivation.

H. Nejat Seyhun's foundational research established that insider purchases were, in aggregate, predictive of positive future returns — but the predictive power was unevenly distributed. It didn't concentrate in the largest individual purchases. It concentrated when multiple insiders within the same firm were purchasing simultaneously. The firm-level signal consistently said more than any individual transaction.

Lakonishok and Lee's 2001 analysis in the Journal of Finance formalized this finding. Their central metric was the net purchase ratio — the fraction of a company's insider transactions within a given period that were purchases rather than sales. When that ratio was elevated — when more insiders were buying than selling at the same company in the same window — forward returns were meaningfully stronger. The predictive content lives in the convergence, not in any single filing.

Jeng, Metrick, and Zeckhauser's 2003 analysis in the Review of Economics and Statistics found that insider purchases in aggregate generate roughly **6%** annual abnormal returns — but this average masks wide variance between isolated low-conviction buys and genuine cluster events. Standard financial media reports the former with the same urgency as the latter. They are not the same event.

---

## What Makes a Cluster Event Different

The formal academic definition of a cluster buy typically requires two or more insiders purchasing shares at the same company within a defined window — often 30 days. That threshold is permissive enough to include events with minimal analytical weight, and applying it mechanically can cause investors to overweight low-quality cluster appearances.

What actually distinguishes a meaningful cluster event from a statistical coincidence is the convergence of several independent decisions. Each insider who buys on the open market is making their own assessment: do I want to allocate personal capital to this company at this price? When two insiders reach the same conclusion, there's a chance it's coincidental. When five insiders — spanning different roles, different departments, different information access levels — reach the same conclusion within a 9-day window, the coincidence interpretation collapses.

The amplification mechanism is informational diversity. Insiders at different levels of a company see different parts of the picture. A CFO has the clearest view of cash flow trajectory and near-term liquidity. An independent director sees the strategic governance picture from board presentations and committee work. An EVP running a business unit sees operational momentum in their segment. When all of them independently conclude that the current stock price undervalues what they can see, they're each drawing from different information sources to reach the same conclusion. That is the signal.

It is also worth noting what the research says about the other direction. Lakonishok and Lee's paper found that insider sales are largely uninformative as a standalone signal. The asymmetry is real and important. Cluster selling — simultaneous sales by multiple insiders — is far harder to interpret because the motivations for selling (diversification, estate planning, tax obligations, option expirations) are varied and unrelated to business conviction. The useful signal in Form 4 data is almost entirely on the purchase side.

---

## The Five Factors That Define Cluster Buy Quality

Not all cluster events are equal. A cluster buy by three independent directors who each purchased **$8,000** over the course of a quarter is technically a cluster. A cluster buy by the CEO, Chairman, and two independent directors who collectively purchased **$21.98 million** in a 3-day window — all discretionary, all direct — is a different category of event entirely. Using a single threshold to treat them equally produces false positives and underweights the events that matter most.

The following five factors capture most of the quality variance across real-world cluster events. Applying them takes minutes using GeminIQ's [Insider Transaction Timeline](/features#insider-transactions), which surfaces every Code P open-market purchase and Code S open-market sale directly from the raw Form 4 feed for any company in the database.

**Factor 1: Insider Role Hierarchy**

Not all Form 4 filers have equal access to the same information. A CEO, CFO, or COO has enterprise-wide visibility — financial performance, pipeline status, strategic options, near-term catalysts. An independent director sees a filtered version of the same picture through board presentations and committee materials. A senior VP or business unit head has deep operational visibility within their segment but limited exposure to the whole.

The strongest cluster events include C-suite insiders alongside board members. When the executive team and independent directors are making the same open-market purchase decision simultaneously, that is multi-tier convergence — they're each drawing on different information to reach the same conclusion about the stock price. A cluster composed exclusively of independent directors carries less weight than one anchored by C-suite participation. A cluster composed only of VP-level officers with no named C-suite or board representation is weaker still. Multi-tier representation amplifies the signal.

**Factor 2: Dollar Commitment Relative to Role**

The absolute dollar value of purchases matters — but commitment relative to each insider's compensation is the more informative measure. A CEO earning **$5 million** in total annual compensation who purchases **$50,000** of stock is making a modest gesture. A director earning **$200,000** in annual board fees who purchases **$150,000** of stock is making a much larger proportional bet.

The most informative cluster events are those where dollar commitment is large enough relative to each insider's financial position that the purchase represents a genuine financial decision rather than a routine ownership signal. When insiders are allocating amounts that would meaningfully affect their personal financial situation if the stock declined sharply, the conviction behind the transaction is quantifiably real.

**Factor 3: Time Compression**

The tighter the cluster, the stronger the signal. Five insiders purchasing within the same 3-day window is more informative than five insiders purchasing across the same quarter. Tight time compression suggests all participating insiders experienced the same triggering condition — a price dip, a post-earnings washout, a macro-driven sector selloff — and independently concluded it represented a buying opportunity.

Loose clustering across a full quarter may reflect nothing more than the opening of a quarterly trading window and five separate, unrelated decisions made at different moments for different reasons. That is technically a cluster, but the convergence is temporal coincidence rather than conviction alignment.

**Factor 4: Plan-Free Status**

Any purchase executed under a pre-arranged Rule 10b5-1 trading plan is categorically less informative than a discretionary purchase. A 10b5-1 plan was established months before execution — it reflects the insider's view at adoption, not their current assessment. For cluster events specifically, the ideal scenario is that none of the constituent purchases carry 10b5-1 footnote disclosures. When all participating insiders made discretionary open-market purchases outside of pre-planned schedules, the convergence reflects contemporaneous, independent conviction.

Checking plan status requires going directly to the Form 4 footnotes on EDGAR. GeminIQ's [Insider Transaction Timeline](/features#insider-transactions) identifies all Code P purchases and Code S sales cleanly from the raw filing data — footnote verification for plan status is the one step that requires pulling the underlying Form 4 document for each transaction in a cluster event.

**Factor 5: Price Context**

Cluster buying at a 52-week low, near book value, or following a period of significant price drawdown carries more information than cluster buying at elevated prices during a post-catalyst momentum run. The price context tells you whether insiders are expressing contrarian conviction — "this is cheap relative to what we know about the business" — or accumulating into a period when the stock already reflects positive expectations.

The strongest cluster signals in the empirical record have occurred when prices were under significant negative pressure and the consensus narrative was pessimistic. That is precisely when insiders have the least external incentive to buy, making their decision to do so most informative. Cluster buying into a depressed stock that is being downgraded by analysts and shorted by institutions represents a much cleaner signal than cluster buying into a stock that is outperforming its peers and generating favorable press.

---

## GameStop: Scoring Two Cluster Events Against the Framework

GeminIQ's raw Form 4 data for GameStop spans from November 2008 to January 2026 and covers every open-market purchase and sale in the company's full insider transaction history. The dataset contains multiple distinct cluster events — but two stand out for what they reveal about how the five-factor framework scores events at opposite ends of the quality spectrum.

**September 2019: Five Directors, One Inflection**

In a 9-day window between September 18 and September 27, 2019, five GameStop independent directors made simultaneous open-market purchases while the stock was trading near multi-year lows, between **$4.62** and **$5.38** per share.

The names and amounts from GeminIQ's raw Form 4 feed: Raul Fernandez purchased across two transactions — **5,250 shares** at **$4.62** and **4,900 shares** at **$5.07** — for approximately **$49,098** total. Carrie Teffner purchased **21,118 shares** at **$4.73** for **$99,888**. Gerald Szczepanski purchased **40,000 shares** at **$5.04** for **$201,600**. Kathy Vrabeck purchased **20,000 shares** at **$5.29** for **$105,800**. Lizabeth Dunn purchased **5,000 shares** at **$5.38** for **$26,900**. Five independent directors, six transactions, **96,268 shares**, **$483,286** combined, 9 calendar days. All direct ownership. No officer participation.

Against the five-factor framework: Role hierarchy scores moderate — all directors, no C-suite representation, no multi-tier convergence. Dollar commitment scores moderate to strong — several directors purchased amounts representing a meaningful fraction of typical independent director compensation, with Szczepanski's **$201,600** purchase being the standout. Time compression scores strongly at 9 days. Plan-free status appears clean based on the direct-ownership, open-market structures of the filings. Price context is the standout factor: purchases at **$4.62 to $5.38** represented the lowest prices GameStop had traded at in its public history up to that point.

The data was public in real time. Five directors making simultaneous purchases at a stock's all-time lows, captured cleanly by GeminIQ's Code P filter, was a visible signal. The subsequent company transformation — including Ryan Cohen's entry as an activist investor and eventual CEO — began roughly 14 months after this cluster.

**January 2026: Scoring the Highest-Quality Event in the Dataset**

The most recent and highest-scoring cluster event in GeminIQ's GameStop data occurred in a 3-day window between January 20 and January 23, 2026.

Ryan Cohen, serving as President, CEO, and Chairman, purchased **500,000 shares** on January 20 at **$21.12** for **$10,560,000**, then an additional **500,000 shares** on January 21 at **$21.60** for **$10,800,000** — **1,000,000 shares** and **$21,360,000** across two consecutive trading days, all direct ownership. Both transactions were filed under the same Form 4 accession on January 21, 2026; GeminIQ's transaction table surfaces the January 21 entry for this filing, with the full two-day purchase detail visible in the underlying Form 4 on EDGAR. Director Alain Attal purchased **12,000 shares** at **$20.90** on January 20 for **$250,800**, then **12,000 more** at **$21.63** on January 21 for **$259,560** — **$510,360** combined, direct ownership. Director Lawrence Cheng purchased **5,000 shares** on January 23 at **$22.87** for **$114,350**, through an indirect holding structure. Three insiders. **1,029,000 shares**. **$21,984,710**. Three calendar days.

Against the five-factor framework: Role hierarchy scores at maximum — the CEO and Chairman is the highest-tier insider available, joined by two independent directors, delivering the multi-tier convergence that single-tier clusters cannot provide. Dollar commitment is extraordinary — Cohen's **$21,360,000** represents one of the largest single-cluster CEO open-market commitments in recent public company data, and Attal's **$510,360** is substantial relative to typical independent director compensation. Time compression scores at maximum for a 3-insiders-over-3-days event. Plan-free status requires footnote verification on EDGAR, though the structure of Cohen's purchases — **500,000 shares** on each of two consecutive days at successively higher prices — is characteristic of discretionary accumulation rather than pre-scheduled plan execution. Price context scores moderate — the **$20.90 to $22.87** purchase range sits above the 2024 lows near **$10 to $11** but well below the post-meme peak ranges of 2021 to 2022.

<center><sup>GeminIQ Insider Transaction Timeline for GameStop (GME). Bar chart shows the January 2026 cluster as the largest purchase spike across the trailing 13-month view. Transaction table confirms the 3-day window: Ryan Cohen (President, CEO and Chairman) 500,000 shares at $21.60 on January 21 (Direct); Alain Attal (Director) 12,000 shares at $21.63 on January 21 and 12,000 at $20.90 on January 20 (Direct); Lawrence Cheng (Director) 5,000 shares at $22.87 on January 23 (Indirect). Cohen's full cluster total of 1,000,000 shares for $21,360,000 spans two dates within one Form 4 filing — the January 21 entry is surfaced in GeminIQ's table. Combined cluster value: $21,984,710. All data sourced from SEC Form 4 filings.</sup></center>

---

## When Cluster Buying Gets It Wrong

The framework improves signal quality — it does not guarantee an outcome. Cluster buying has a documented failure mode, and GameStop's own data illustrates it directly.

In a 3-day window between March 21 and March 24, 2022, the same cast of insiders executed another cluster of open-market purchases. Lawrence Cheng purchased **4,000 shares** at **$95.22** for **$380,880**, direct ownership. Ryan Cohen, filing through RC Ventures as a ten-percent owner and board member, purchased **100,000 shares** at **$102.45** for **$10,245,000**, indirect ownership through the entity. Alain Attal purchased **1,500 shares** at **$129.91** for **$194,865**, direct ownership. Three insiders, **$10,820,745** combined, 3 days.

Role hierarchy: strong. Dollar commitment: substantial. Time compression: tight. Plan-free status: consistent with discretionary structure.

But Factor 5 scored low. The purchases were made at prices ranging from **$95.22 to $129.91** — well above the normalized trading range the stock would occupy for the following two-plus years. GameStop traded predominantly in the **$10 to $25** range throughout most of 2023 and 2024. The 2022 cluster buyers paid elevated prices into residual post-meme premium rather than buying against a depressed narrative.

The lesson is not that cluster buying is unreliable. It's that price context is load-bearing in the framework. Insiders have better visibility into their own company's operations than any outside analyst. They do not have better visibility into the macro environment, interest rate dynamics, or market sentiment cycles that can compress valuations independent of business quality. A cluster that scores four factors well but fails on price context — purchasing into elevated prices rather than against negative pressure — carries substantially less signal than a cluster that scores all five.

The 2019 GameStop cluster at **$4.62 to $5.38** was buying against a catastrophic narrative. The 2022 cluster at **$95.22 to $129.91** was purchasing into a post-meme residual premium. The five-factor framework scores them very differently — and it should. Price context is the factor that separates conviction from coincidence.

---

## How to Track Cluster Events Without Downloading Filings

The practical barrier to systematic cluster buy analysis is volume. A company with ten active insiders filing through RSU vesting cycles can generate 40 to 60 Form 4 filings per year. Reading each one manually — parsing transaction codes, checking footnotes, calculating net share changes — is not a scalable research process.

GeminIQ's [Insider Transaction Timeline](/features#insider-transactions) pulls directly from the raw Form 4 feed and surfaces only the transactions that carry analytical content: Code P open-market purchases and Code S open-market sales. The RSU grants, tax withholding transactions, option exercises, and compensation-plan-driven filings that constitute the majority of Form 4 volume are filtered out before you ever see them. What remains is a clean record of when insiders chose to spend personal capital at the current market price — and when they chose to convert equity to cash.

With that filtered feed, identifying a cluster event becomes a pattern-recognition task. Multiple Code P transactions from different insiders appearing in the same short window are immediately visible. From there, the five-factor scoring process — role hierarchy, dollar commitment, time compression, plan-free status, price context — can be applied in minutes per company.

The fundamental data that provides the price context factor — where the stock is trading relative to book value, relative to cash flow, relative to the balance sheet — sits on the same company page in GeminIQ. Pre-calculated metrics including [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda), and [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) are derived directly from SEC filing data and available alongside the insider transaction timeline. The cross-reference between what insiders are doing and what the fundamentals show is immediate.

---

## Frequently Asked Questions

### Is insider buying a stronger signal than insider selling?

Generally, yes. Insiders sell for many reasons that have nothing to do with the stock: diversification, taxes, a house purchase, or a scheduled 10b5-1 plan. They buy for essentially one reason, which is that they expect the shares to be worth more. That asymmetry is why open-market purchases (code P) carry more information than sales, and why sales need context before they mean anything.

### What stocks are insiders buying right now?

That changes daily. Use an [insider trading tracker](/blog/insider-trading-tracker) filtered to open-market purchases (code P) over the last week or two, exclude trades made under 10b5-1 plans, and look for companies where several insiders bought within the same window.

### Does insider buying include stock awards and option exercises?

No. Grants and awards (code A) and option exercises (code M) add shares without the insider choosing to buy at the market price, so they are compensation, not insider buying. Only open-market or private purchases reported with code P count.
---

### Related Reading

- [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4) — how to read a single filing field by field before reading a cluster of them.
- [Insider Trading Tracker: How to Track Insider Buying and Selling](/blog/insider-trading-tracker) — free and paid ways to track insider trades, the transaction codes to filter for, and a five-step routine for any company's insider history.
- [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings) — how insider transaction patterns interact with cash flow signals, balance sheet shifts, and institutional ownership trends for a complete picture.
- [GameStop Stock Analysis (2026): The $4 Billion Debt Nobody Priced In](/blog/gamestop-10k-analysis-2026) — the fundamental picture behind the ticker where the cluster buying framework plays out in practice.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — how Form 4 fits into the broader EDGAR filing system alongside 10-K, 10-Q, 8-K, and 13F.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=insider-cluster-buying-signal-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All insider-transaction figures cited in this article are drawn from GameStop Corp.'s SEC Form 4 filings, publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001326380&type=4&dateb=&owner=include&count=40). Post-filing market reaction is measured from each filing's filed date.

---

## Blog: Insider Trading Tracker: How to Track Insider Buying and Selling
source: https://www.geminiq.com/blog/insider-trading-tracker

### Insider Trading Tracker: How to Track Insider Buying and Selling
An insider trading tracker turns SEC Form 4 filings into a searchable list of insider buys and sells. Here is where the data comes from, the free and paid ways to track it, and the filters that separate real conviction from compensation noise.

**An insider trading tracker collects the Form 4 filings that company officers, directors, and 10% owners must submit to the SEC within two business days of a trade, and turns them into a searchable list of who bought or sold, how many shares, and at what price.** The filings themselves are free on SEC EDGAR, so a tracker's value is in the filtering. The filter that matters most is the transaction code: only code P, an open-market purchase, is an insider choosing to spend their own money on the stock.

Most investors treat insider trading data as a headline feature. They see "CEO sells 50,000 shares" and reach for the sell button. They see "Director buys 10,000 shares" and start speculating about an acquisition. Both reactions miss the point. Reading a single transaction in isolation produces almost no analytical signal; the edge comes from knowing which transactions to keep and tracking the pattern across years.

This guide covers where insider trading data comes from, the three ways to track it, what to filter for, and a routine for turning a list of trades into a judgment about one company. For a field-by-field walkthrough of the form itself, see [How to Read SEC Form 4](/blog/how-to-read-sec-form-4).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=insider-trading-tracker)**

---

## Where Insider Trading Data Comes From

Every insider tracker reads the same source: Form 4, the Statement of Changes in Beneficial Ownership. Section 16 of the Securities Exchange Act requires officers, directors, and anyone owning more than **10%** of a class of a company's registered equity to report most changes in their holdings on Form 4 within two business days. Before the Sarbanes-Oxley Act of 2002, insiders had until the tenth day of the following month, which could mean a delay of up to 40 days. The two-day rule is what makes insider data close to real-time.

Each Form 4 reports the transaction date, the transaction code, the number of shares, the price, whether the shares are held directly or through a trust or other entity, and the insider's holdings afterward. [How to Read SEC Form 4](/blog/how-to-read-sec-form-4) walks through every column, and every tracker is a different way of sorting those same fields.

---

## Three Ways to Track Insider Trades

**1. SEC EDGAR, directly.** Free and authoritative. Open a company's filing list on EDGAR and filter by form type 4, or open an insider's own EDGAR page to see every Form 4 they have filed across companies. EDGAR's latest-filings view can also be filtered to Form 4 to watch filings as they arrive. The drawback is volume: you read one filing at a time, and the transaction code, 10b5-1 flag, and ownership totals have to be pulled out by hand.

**2. Free Form 4 screeners.** Sites such as OpenInsider, secform4.com, and Finviz's insider page parse every Form 4 into tables you can sort and filter by date, company, insider, transaction type, and size. They are the fastest way to scan the whole market for recent purchases or cluster buys. What they generally don't show is the company's fundamentals next to the trade.

**3. A research platform with insider data built in.** GeminIQ's [Insider Transaction Timeline](/features#insider-transactions) pulls directly from the raw Form 4 feed and shows every open-market purchase (code P) and open-market sale (code S) for each company, filtering out RSU grants, option exercises, and tax withholding before you see them. The same company page carries the financial statements and 90+ calculated metrics, including the [current ratio](/metrics/liquidity-ratios/current-ratio), net debt, and free cash flow, so an insider purchase can be read against the business it was made in.

---

## What to Filter For: The Transaction Codes That Matter

Most trackers list every Form 4 transaction, and most of those transactions are compensation mechanics, not decisions. Filter by transaction code first, ranked by how voluntary the trade is. The full list of twenty codes is in the [Form 4 transaction code reference](/blog/form-4-transaction-code-list).

**Open-market purchases (Code P) are the strongest signal available.** When an executive, director, or major shareholder purchases shares on the open market with their own money, they are making a deliberate decision to allocate personal capital to the stock at the prevailing price. They are not receiving compensation. They are not exercising an option that is expiring. They chose to buy. This is qualitatively different from every other transaction type, and it is the signal most worth tracking.

Open-market purchases are also rare. GeminIQ's [Insider Transaction Timeline](/features#insider-transactions) for [Apple](/stocks/AAPL) shows 435 total transactions across 17+ years of data — with only 4 open-market purchases ever recorded. All four were by board members. Not a single Apple executive has ever purchased shares on the open market in the entire dataset. At [GameStop](/stocks/GME), GeminIQ's raw Form 4 feed shows a radically different pattern: Ryan Cohen's open-market accumulation preceded his board seat and strategic restructuring. The data was public the entire time.

**Discretionary open-market sales (Code S, no 10b5-1 plan) are the second-most-meaningful signal.** These represent an insider deciding to convert equity into cash at the current price. They do not necessarily indicate a negative view — executives often have concentrated positions in a single company and diversification is rational portfolio management — but a sudden spike in discretionary selling volume, particularly from multiple insiders simultaneously, deserves investigation.

**Routine compensation-driven transactions (Codes A, F, D) carry almost no signal.** RSU grants (A), tax withholding on vesting (F), and shares returned to the company to cover tax obligations (D) are all mechanically generated by the compensation structure. They happen because the compensation plan requires them, not because the insider is expressing any view. A significant portion of the "insider selling" that generates alarming news headlines is actually RSU tax withholding — shares the insider never received in cash form, surrendered automatically to cover the tax bill on vesting.

**Option exercises (Code M) require context.** An executive exercising in-the-money stock options is not necessarily bullish or bearish — they may be exercising options approaching expiration regardless of their view. What matters is whether the exercise is followed immediately by an S transaction (a same-day or next-day sale of the acquired shares, often called an exercise-and-sell) or whether the insider retains the shares. An exercise followed by retention is far more bullish than an exercise followed by an immediate sale.

---

## 10b5-1 Plans: The Context That Changes Everything

Rule 10b5-1 allows corporate insiders to establish pre-planned trading schedules — specifying in advance the price, volume, and timing of future transactions — as a defense against insider trading allegations. The plan must be established when the insider is not aware of material non-public information. Once established, transactions under the plan can proceed even during otherwise restricted periods, such as the weeks before an earnings release.

For investors analyzing insider transactions, 10b5-1 plans are critical context. A sale executed under a pre-existing plan is not a decision the insider made today based on their current view of the company's prospects. It is a sale that was scheduled months ago under conditions that may no longer be relevant.

How do you identify 10b5-1 plan sales? Since April 2023, Forms 4 and 5 carry a checkbox for transactions made under a plan intended to satisfy Rule 10b5-1(c), and the filer gives the plan's adoption date in the explanation of responses. Older filings disclose a plan, if at all, in a footnote. Good trackers surface that flag; if yours doesn't, open the filing on EDGAR. If a sale has no such footnote and no other disclosed reason — particularly if the sale is large, discretionary, and by a named executive — it carries more analytical weight.

The SEC tightened its 10b5-1 rules in amendments effective February 2023, adding a mandatory cooling-off period between when a plan is adopted and when the first trade can execute. For directors and officers, trading cannot begin until the later of 90 days after adoption or two business days after the company discloses financial results for the quarter in which the plan was adopted, capped at 120 days. Other insiders wait 30 days. This reform reduced the ability to create "plans" immediately before anticipated news. A sale executed under a 2023-era plan carries more credibility than one established before the reform — but the analytical principle is the same: when you see a footnote disclosing a 10b5-1 plan, the decision to sell was made months ago, not today.

---

## The Patterns That Create Real Analytical Signal

A single Form 4 transaction, read in isolation, produces almost no reliable information. The analytical edge comes from patterns — across time, across individuals, and across context.

**Cluster buying** is the most powerful pattern in insider transaction analysis. When three or more insiders — particularly from different parts of the organization — purchase shares on the open market within a short window, the signal compounds. Each individual buyer might have a personal or tax-driven rationale. But simultaneous open-market purchases by a CFO, two independent directors, and an SVP within the same two-week window is not coincidental. It represents a convergence of informed opinion that is extremely rare in mature companies and worth investigating immediately.

**Long-term pattern disruption** is equally important. Establishing a multi-year baseline for any company's insider transaction history and then watching for deviations from that baseline is more valuable than reading individual filings. A company where executives have been routine sellers for a decade — using RSU vesting and plan-based sales — suddenly seeing its CFO make an open-market purchase at a price below book value is a meaningful break in pattern. The rarity of the event amplifies the signal.

**The absence of selling** is often underappreciated. In sectors where executive turnover is high and compensation in equity is heavy — technology, biotech, consumer discretionary — the default behavior is for insiders to sell regularly as RSUs vest and options come in-the-money. When a company's insider selling activity goes quiet — when an executive who typically sells quarterly stops filing any transactions — that can itself be a signal worth investigating. It may indicate a trading window restriction tied to an undisclosed material event.

**Volume acceleration or deceleration** matters more than direction in many cases. An executive who typically sells 5,000 shares per quarter suddenly selling 50,000 shares in a single transaction deserves investigation regardless of whether the transaction is plan-based. Conversely, a slowdown in routine selling activity — even without an explicit purchase — can signal internal optimism about near-term catalysts.

---

## What Insider Data Cannot Tell You

Form 4 data is powerful, but it has genuine limitations that are easy to forget in the excitement of a striking transaction.

Insider selling is almost always more common than buying. Executives receive substantial equity compensation and have naturally concentrated positions in a single company. Selling to diversify is rational regardless of the executive's view of the stock. The base rate of insider selling is so high that a single sale, or even a sustained period of selling, cannot be interpreted as a negative signal without significant additional context.

Insider buying is rare, but it can be wrong. Insiders have better information about their own company than outside investors — but they are not infallible forecasters of the stock price. An executive who bought aggressively before a competitor introduced a disruptive product may have had complete visibility into their own operations while being blind to external threats. Form 4 data is a window into what insiders know and believe about their business. It is not a guarantee of outcome.

Timing is imprecise. Even discretionary, non-plan purchases can precede significant stock declines if broader market conditions deteriorate independently of the company's fundamentals. Insider conviction about business quality does not protect against macro-driven selling pressure, sector rotation, or rate-driven multiple compression.

Reported ownership can be complex. Beneficial ownership rules mean that shares held by a spouse, a family foundation, or a revocable trust may all appear on the same Form 4 as if owned by the insider directly. Large changes in "indirect" holdings can reflect estate planning events rather than investment decisions.

---

## A Five-Step Routine for Using Any Insider Tracker

Whichever tracker you use, the same routine turns a list of trades into a judgment about one company.

The first step is to establish the baseline. Pull the full insider transaction history going back as far as the data allows — ideally three to five years minimum, ten or more for mature companies. Identify the dominant transaction types. Is the default behavior RSU-driven sales and tax withholding? Routine quarterly selling under plan? Nearly no activity at all? The baseline defines what "normal" looks like for this specific company.

The second step is to identify anomalies relative to that baseline. An open-market purchase in a company where the default behavior is pure RSU selling is immediately anomalous. A sudden spike in discretionary S transactions during a period of quiet is anomalous. These deviations, not the transactions themselves, are where the signal lives.

The third step is to cross-reference the anomaly with the fundamental data. An insider buying aggressively at a price that represents **0.8x book value** when the company has a historically strong [Return on Equity](/metrics/returns-and-profitability/return-on-equity) and a clean balance sheet is a different situation than an insider buying into a company with deteriorating margins and ballooning debt. GeminIQ's pre-calculated metrics — including [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), and [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) — sit on the same company page as the insider transaction data, making that comparison direct.

The fourth step is to assess the 10b5-1 context. Is the transaction plan-based or discretionary? For any sale that looks anomalous, check the filing's Rule 10b5-1 checkbox and the plan adoption date in the explanation of responses (or, for filings before April 2023, the footnotes). A plan adopted shortly before unusual company activity deserves a closer look than one adopted as part of routine compensation planning.

The fifth step is to check for cluster confirmation. Did any other insiders transact within the same window? Do their transaction types and directions agree? Conviction that spans multiple individuals at different levels of the organization is more compelling than any single filing, regardless of size.

---

## Frequently Asked Questions

### Is there a free insider trading tracker?

Yes. SEC EDGAR itself is free: every Form 4 is public, and a company's filing list can be filtered to show only Form 4s. Several free websites, including OpenInsider and secform4.com, parse those same filings into sortable tables. Paid platforms add alerts, history, and fundamentals alongside the trades.

### What is OpenInsider used for?

OpenInsider is a free website that parses SEC Form 4 filings into screenable tables. Investors use it to scan recent insider purchases and sales across the market, filter by transaction type and size, and spot cluster buying, where several insiders at one company buy within a short window.

### How quickly do insider trades show up in a tracker?

Form 4 is due within two business days of the transaction, and most trackers pick up filings from EDGAR shortly after they are accepted. A trade is therefore usually visible within two to three business days. Late filings do happen, and comparing the transaction date with the filing date shows when one was late.

### What stocks are insiders buying right now?

That changes daily, so no article can answer it. Filter any tracker to open-market purchases (code P) from the last week or two, exclude trades made under 10b5-1 plans, and look for companies where more than one insider bought. Purchases by several insiders at once, known as [cluster buying](/blog/insider-cluster-buying-signal-data), have historically been the stronger signal.

### Is it legal for insiders to trade their own company's stock?

Yes, provided they are not trading on material nonpublic information and they report the trade on time. The transactions a tracker shows are the legal, reported kind. Illegal insider trading is trading while aware of material nonpublic information, which a Rule 10b5-1 plan adopted in advance is designed to guard against.

---

## Related Reading

For deeper context on the filings that sit alongside Form 4 data in a complete fundamental research workflow, see the GeminIQ guides below:

- [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4) — the field-by-field walkthrough of the form itself, step by step through the header, both tables, and the footnotes.
- [SEC Form 4 Transaction Codes: Full List and What Each Code Means](/blog/form-4-transaction-code-list) — all 20 codes decoded, with the signal weight each one carries.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — covers 10-K, 10-Q, 8-K, DEF 14A, S-1, and Form 4 in one reference post.
- [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings) — how insider transaction patterns combine with balance sheet shifts and cash flow signals for a complete picture.
- [How to Read a 10-K: A Value Investor's Guide](/blog/how-to-read-10-k) — the foundational document that every Form 4 analysis should sit alongside.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=insider-trading-tracker)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Institutional Buying Before Big Runs: None Got Ahead of the Move
source: https://www.geminiq.com/blog/institutional-buying-before-stock-runs

### Institutional Buying Before Big Runs: None Got Ahead of the Move
GeminIQ's Form 13F data traces institutional ownership through the pre-run and run-era quarters of three celebrated multi-year stock moves — Tesla, NVIDIA, and Palantir — to test whether the 'smart money' actually got ahead of any of them.

**[NVIDIA](/stocks/NVDA)'s institutional ownership was at a multi-year low of 52.21% at the quarter ended December 2022 — the quarter before its AI-era climb began. Across Tesla, NVIDIA, and Palantir, none of the three runs shows institutions getting ahead of the move.**

[Tesla](/stocks/TSLA)'s stock rose more than sixfold in the nine months between March 2020 and December 2020. Over that same stretch, institutional ownership fell from **50.00%** to **45.77%**, dropping as low as **42.00%** at the sharpest point of the move. The people running the world's largest pools of capital did not buy Tesla's 2020 run. They watched their share of the company shrink while it happened.

That's the honest answer to a question investors like to assume works in the smart money's favor: did institutions front-run the biggest stock runs of the last several years, chase them once they were underway, or miss them outright? GeminIQ's Form 13F data can check this directly, quarter by quarter, against the actual price action — for [Tesla](/stocks/TSLA), [NVIDIA](/stocks/NVDA), and [Palantir](/stocks/PLTR), three of the most celebrated multi-year runs of the past decade. The answer is different for each, and only one of the three looks anything like institutions getting ahead of the move.

Every figure below is drawn from each company's own Form 13F institutional ownership data and [SEC filing history](/blog/sec-filings-guide) via GeminIQ, read in the order it was reported. GeminIQ's 13F coverage begins in Q1 2013 across the full universe — a hard floor confirmed while building this piece — so this study is restricted to runs whose pre-run and run-era quarters fall after that date.

| Company | The Run | Institutional Data Window | Outcome Metric |
|---|---|---|---|
| [Tesla (TSLA)](/stocks/TSLA) | 2020 — stock +6x in 9 months | Q2 2013–Q1 2026 | Institutional ownership: **50.00%** (Q1 2020) → **45.77%** (Q4 2020), with a low of **42.00%** (Q3 2020) |
| [NVIDIA (NVDA)](/stocks/NVDA) | 2023–2025 — the AI inflection | Q2 2013–Q1 2026 | Institutional ownership: **52.21%** (low, Dec 2022) → **60.66%** (Dec 2023) |
| [Palantir (PLTR)](/stocks/PLTR) | 2023–2025 — stock +20x | Q3 2020–Q1 2026 | Institutional ownership: **28.27%** → **50.93%** through the run |

## Tesla Institutional Ownership Fell From 50.00% to 45.77% Through the 2020 Run

<center><sup>GeminIQ data study: Tesla's closing price against institutional ownership, quarterly, 2013–2026. Built from as-filed 13F data via GeminIQ. n = 52 quarters.</sup></center>

By early 2020, [Tesla](/stocks/TSLA) was already a well-covered, well-owned stock — institutional ownership had run in the low-to-mid 50s for years. Then the stock did something few large-caps ever do.

**The Filing Data:** Tesla's price rose from **$34.93** (Q1 2020) to **$71.99** (Q2 2020) to **$143.00** (Q3 2020) to **$235.22** (Q4 2020) — more than a sixfold increase in nine months. Institutional ownership over those same four quarters: **50.00%** → **48.49%** → **42.00%** → **45.77%**. Ownership kept falling through 2021 as the stock climbed further, bottoming near **40.69%** even as the price peaked above **$359** in early 2022.

**The Signal:** This is about as clean a "missed it" result as this kind of data produces. Institutional ownership didn't just fail to rise ahead of the move — it fell fastest during the sharpest part of the rally, and it didn't meaningfully recover until 2024–2025, long after the run itself was over.

## NVIDIA Institutional Ownership Hit a 52.21% Low the Quarter Before the AI Run

<center><sup>GeminIQ data study: NVIDIA's closing price against institutional ownership, quarterly, 2013–2026. Built from as-filed 13F data via GeminIQ. n = 52 quarters.</sup></center>

Unlike Tesla, [NVIDIA](/stocks/NVDA) was a stock institutions had owned heavily for a decade. But their conviction wasn't steady — and it hit a low point at almost the worst possible time.

**The Filing Data:** Institutional ownership fell from a 2016 peak near **88%** down to **52.21%** by the quarter ended December 2022 — a multi-year low, though that comparison spans a period over which NVIDIA's share count and its index composition both changed materially, so the two endpoints are not measuring an identical shareholder base. The very next quarter, NVIDIA's price began its climb: **$27.69** (quarter ended April 2023) to **$46.64** (quarter ended July 2023), up **68%** in three months, then to **$132.55** by the quarter ended October 2024 and **$202.23** by the quarter ended October 2025. Institutional ownership recovered alongside the move — **56.57%** → **58.81%** → **59.14%** → **60.66%** by the end of 2023 — but as of the most recent filing it still hadn't reclaimed its 2016 highs, even with the stock up more than sevenfold from where the AI run began.

**The Signal:** NVIDIA's institutional base was at its thinnest right before the single biggest catalyst quarter in the company's history. What followed looks less like front-running and more like a gradual, partial catch-up.

## Palantir Institutional Ownership Rose From 28.27% to 50.93% During the Run

<center><sup>GeminIQ data study: Palantir's closing price against institutional ownership, quarterly, 2020–2026. Built from as-filed 13F data via GeminIQ. n = 23 quarters.</sup></center>

[Palantir](/stocks/PLTR) is the exception on this list — the only one of the three where institutional ownership moved in the same direction as the stock for almost the entire run, not against it or behind it.

**The Filing Data:** From the quarter ended March 2023 (**$8.45**) through the quarter ended September 2025 (**$182.42**), Palantir's stock rose more than twentyfold. Institutional ownership rose alongside it nearly every quarter: **28.27%** → **31.20%** → **34.29%** → **36.39%** → **36.03%** → **38.73%** → **46.15%** → **48.49%** → **47.48%** → **49.25%** → **50.93%**, up more than **80%** over the same stretch.

**The Signal:** This isn't a front-run — ownership was still climbing as the stock did, not ahead of it. But it's the closest thing on this list to institutions correctly reading a story as it developed and building into it consistently, rather than being caught flat-footed or bailing early.

## Did Institutional Ownership Predict Any of These Runs?

None of the three runs in this piece show institutions getting ahead of the move — the pattern that's supposed to justify calling 13F data "smart money." [Tesla](/stocks/TSLA)'s ownership share collapsed during the sharpest part of its 2020 rally. [NVIDIA](/stocks/NVDA)'s ownership bottomed the quarter before its AI-era climb began, then only partially rebuilt. Only [Palantir](/stocks/PLTR) shows anything like sustained conviction, and even there it's concurrent with the run, not predictive of it.

If there's a single honest takeaway across all three, it's that [13F filings](/blog/how-to-read-13f-filing) are a quarterly, lagged record of what institutions already did, not a forward indicator of what they're about to do. The same caveat applies to [insider Form 4 records](/blog/form-4-transaction-code-list): both describe a transaction that has already happened. That's worth remembering every time a headline calls a stock "institutionally favored" right before or right after it moves.

The most extreme institutional-ownership reading in GeminIQ's data isn't in this study at all: at one point [aggregated 13F filings reported more GameStop shares than GameStop had issued](/blog/gamestop-fundamentals-before-squeeze), which is what happens when lent shares are counted twice.

## Check Your Holdings

This same comparison works on anything you hold, and on anything you're [screening for](/screens). Pull up a position's price history alongside GeminIQ's [Institutional Ownership](/features#institutional-ownership) data and look at the relationship over time, not just the current ownership percentage. Rising ownership during a rally can mean conviction is building — or it can mean institutions are the ones paying up after the move, buying the same strength retail already bought. Falling ownership during a rally isn't automatically bearish either, as Tesla's 2020 quarter shows; sometimes it just means the move outran the institutional base entirely. The data is quarterly and lagged, always — treat every reading as a snapshot of last quarter's positioning, not a signal about next quarter's.

## Frequently Asked Questions

### Did institutions predict any of these three stock runs before they happened?

No. In none of the three cases did institutional ownership rise meaningfully in the quarters immediately before the run began. NVIDIA's ownership was at a multi-year low the quarter before its AI-era climb started; Tesla's was already declining before its 2020 run and kept falling through it.

### Did institutions buy NVIDIA before the AI run?

No. [NVIDIA's](/stocks/NVDA) institutional ownership fell from a 2016 peak near **88%** to **52.21%** by the quarter ended December 2022 — a multi-year low, and the quarter immediately before the price began climbing from **$27.69** (quarter ended April 2023) to **$46.64** (quarter ended July 2023), up **68%** in three months. Ownership then recovered alongside the move — **56.57%** → **58.81%** → **59.14%** → **60.66%** by the end of 2023 — and as of the most recent filing still hadn't reclaimed its 2016 highs. That is catch-up, not front-running. The 2016 comparison spans a period over which share count and index composition both changed materially.

### Did institutions buy Palantir before the run?

Not before it — alongside it. [Palantir's](/stocks/PLTR) institutional ownership was **28.27%** at the quarter ended March 2023, when the stock closed at **$8.45**, and rose nearly every quarter to **50.93%** by the quarter ended September 2025, when it closed at **$182.42**. Ownership rose more than **80%** while the stock rose more than twentyfold. That is the closest case on this list to institutions reading a story as it developed, but it is concurrent with the run, not ahead of it.

### Does institutional ownership predict stock returns?

Not in any of the three cases in this study. Tesla's ownership share fell through the sharpest part of its 2020 rally, NVIDIA's bottomed the quarter before its AI-era climb, and Palantir's rose only in step with the move. Form 13F is a quarterly filing disclosing positions as of quarter-end, typically 45 days later, so it is a record of what institutions already did rather than a forward indicator. Three named runs are not a base rate, and this study does not attempt to establish one.

### Is falling institutional ownership during a stock's rise always a bad sign?

No — Tesla's case is the clearest illustration of why it can mean the opposite. A falling ownership percentage during a sharp rally can simply mean the stock's price and shareholder base are growing faster than institutional positions are, not that institutions are selling in dollar terms.

### How current is GeminIQ's institutional ownership data?

Form 13F filings are quarterly by design and disclose positions as of each quarter's end, typically 45 days after the quarter closes. This data should never be treated as live or real-time positioning.

### Why doesn't this study include older, pre-2013 stock runs?

GeminIQ's 13F coverage begins in Q1 2013 across the full universe. A run whose pre-run and run-era quarters fall entirely before that date — a case confirmed and excluded while researching this piece — can't be told with this data.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=institutional-buying-before-stock-runs)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All institutional ownership and price figures in this article are drawn via GeminIQ from the SEC filing histories of [Tesla, Inc.](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001318605&type=10-K), [NVIDIA Corporation](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001045810&type=10-K), and [Palantir Technologies Inc.](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001321655&type=10-K), all publicly available on SEC EDGAR. Form 13F data reflects quarter-end positions reported with a standard filing lag and should not be read as live positioning.</sup>

---

## Blog: Institutional Ownership: What It Means and How to Track It
source: https://www.geminiq.com/blog/institutional-ownership-13f-filing-explained

### Institutional Ownership: What It Means and How to Track It
Institutional ownership, reported through SEC Form 13F filings, is one of the most widely cited and most poorly read signals in equity analysis. This guide explains the filing mechanics, what the ownership percentage actually measures, and where the real investment signal lives.

**Institutional ownership is the share of a company's stock held by investment managers such as mutual funds, pension funds, hedge funds, banks, and insurers, rather than by individual investors.** It is built from the Form 13F reports that managers with at least $100 million in qualifying securities file each quarter, so it is always a quarter-end snapshot published up to 45 days later.

Almost every financial data platform displays institutional ownership as a single percentage. Standard financial media treats a rising number as confirmation of smart-money interest and a falling number as a warning. But by the time any Form 13F hits EDGAR, the data it contains is already at minimum 46 days old — and may describe a position the filing manager has since materially changed. Beyond the lag, the percentage itself is structurally distorted: buybacks raise it without any institution purchasing a single share, index reconstitutions spike it without any valuation judgment, and ETF proliferation inflates the aggregate through double-counting. The signal investors believe they are reading from the institutional ownership line is not the signal the data actually carries. This guide explains what the 13F system discloses, where the genuine investment signal lives, and how to distinguish a real accumulation pattern from a mechanical one.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=institutional-ownership-13f-filing-explained)**

---

## Table of Contents

- [Where Institutional Ownership Data Comes From](#where-institutional-ownership-data-comes-from)
- [The 45-Day Reporting Lag](#the-45-day-reporting-lag)
- [The Four Position Types: Where the Signal Lives](#the-four-position-types-where-the-signal-lives)
- [Why the Ownership Percentage Is the Wrong Number](#why-the-ownership-percentage-is-the-wrong-number)
- [The Holder Count Signal](#the-holder-count-signal)
- [How to Track Institutional Ownership Changes in GeminIQ](#how-to-track-institutional-ownership-changes-in-geminiq)
- [When Institutional Ownership Signals Break](#when-institutional-ownership-signals-break)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Where Institutional Ownership Data Comes From

Institutional ownership figures are aggregated from Form 13F. Section 13(f) of the Securities Exchange Act requires any investment manager with at least **$100 million** in Section 13(f) securities (mostly exchange-listed stocks, plus certain options and convertibles) to report its long holdings each quarter, within **45 days** of quarter-end. That captures everyone from trillion-dollar index funds to boutique active managers, which is why the aggregate blends informed active investors with passive holders whose only input was a benchmark.

Three gaps in the source data carry straight through to every ownership figure built on it. Short positions are not reported, so a fund that is net short a stock can still appear as a holder. Cost basis and purchase dates are not reported, so a position opened last quarter looks the same as one held for a decade. And managers can request confidential treatment on Form 13F-CT to delay disclosing specific positions for up to a year, so reported ownership can understate active positioning. For a column-by-column walkthrough of the filing itself, see [How to Read 13F Filings](/blog/how-to-read-13f-filing).

---

## The 45-Day Reporting Lag

The lag is the single most important structural feature of 13F data, and the one most investors underestimate.

Consider the timeline for Q1. An institutional manager assembles its portfolio through January, February, and March. The quarter closes March 31. The manager has until May 15 to file. When that 13F hits EDGAR on May 15, it describes positions as of March 31 — **45 days earlier**. That is the best case, when a manager files on the last possible day. If a manager files promptly on April 15, investors reading that data on May 15 are still working from a March 31 snapshot. The freshness of the filing date is irrelevant to the staleness of the underlying data.

The consequence is direct: by the time a position becomes visible in a 13F, the manager has already had time to act on it. Depending on when in the quarter the position was established, that window runs anywhere from 46 to 136 days — enough time to add to the position, reduce it, or exit it entirely. A new position that appears in a Q3 13F may have been initiated in July, with the manager actively adding through October and November, before the filing confirms the original entry in mid-November. The 13F underrepresents how far along the conviction trade has already progressed.

On the exit side, a manager who began trimming late in Q2 and completed the exit in Q3 will show a full position in the Q2 filing. The Q3 filing then shows a complete liquidation, with no data showing the reduction unfolding across the transition. This is why using 13F data as a short-term trading signal — buying because a prominent manager just disclosed a position — is almost always acting on stale information as though it were current.

---

## The Four Position Types: Where the Signal Lives

The raw share count in any line item of a 13F is less informative than the change in that share count relative to the prior quarter's filing. Every position change across all 13F filers falls into one of four categories, and the interpretive weight assigned to each should differ accordingly.

### New Position

A stock appears in an institution's holdings table for the first time — no prior quarter's filing showed this holding. A new position is the clearest indication that a manager made a deliberate decision to allocate capital to this company at or near current price levels. It does not guarantee high conviction; new positions can be small exploratory entries. But it is the cleanest signal of fresh institutional interest. Tracking the number of unique managers opening new positions in a given stock across a single quarter is one of the most useful aggregates the 13F data set produces.

### Addition

An institution increases its share count beyond what was reported in the prior filing. An addition signals continued or growing conviction from an existing holder. A series of additions across multiple quarters in a row is a meaningful indicator of sustained institutional accumulation — the manager keeps adding at successive price levels, which implies a view that the stock remains undervalued relative to their target.

### Reduction

An institution decreases its share count from the prior quarter. A single reduction is inconclusive — it could be profit-taking, mechanical portfolio rebalancing, or the early stage of an exit. A series of reductions across multiple consecutive quarters carries more weight, particularly when the overall holder count in the stock is simultaneously declining. The combination of falling per-manager share counts and a shrinking holder count is a structurally bearish institutional signal.

### Liquidation

The stock no longer appears in the institution's holdings table. A liquidation can result from a complete sell-out, a fund closure, a portfolio restructuring, or a transition to a short position that eliminates the reported long. The most analytically significant signal comes not from any individual liquidation but from simultaneous liquidations across multiple managers in the same quarter — that convergence represents the strongest institutional exit signal the 13F system produces.

---

## Why the Ownership Percentage Is the Wrong Number

The headline institutional ownership percentage — the figure displayed prominently on virtually every financial platform — comes from a simple calculation: total shares reported by 13F filers divided by total shares outstanding. The math is correct. The problem is that the denominator changes for reasons entirely disconnected from institutional conviction, and using the resulting percentage as a signal produces systematic misreadings.

### The buyback distortion

When a company repurchases shares, total shares outstanding falls. If institutions hold their absolute share counts constant while the company shrinks the denominator, the ownership percentage rises — even though not a single institutional investor bought a share. The percentage increase is arithmetic, not analytical.

[Apple](/stocks/AAPL) provides the clearest illustration. Split-adjusted shares outstanding declined from approximately 23 billion in FY2014 to roughly 14.8 billion by FY2025 — a reduction of more than **36%** driven almost entirely by buybacks. Throughout that period, institutional ownership percentage held in a band between roughly **50%** and **60%**. Standard financial media treated this as evidence of sustained institutional conviction in Apple. But by tracking the absolute share counts in GeminIQ's [Institutional Ownership](/features#institutional-ownership) tracker, a different pattern emerges: institutions were trimming their absolute share holdings roughly in proportion to the buyback activity, maintaining proportional exposure while Apple shrank the total float. The percentage held steady. Absolute institutional share counts were declining. Those are opposite conclusions from the same data — and which one you reach depends entirely on whether you are reading the percentage or the underlying count.

### The index inclusion distortion

When a stock is added to the S&P 500 or any major index, every passive fund tracking that benchmark is mechanically required to purchase shares. Institutional ownership percentage can jump several points in the quarter of inclusion. That buying has no valuation content — it is structural, not analytical. Treating that spike as a bullish signal about the business mistakes a rule-following transaction for a deliberate investment decision.

### What to watch instead

Watch the absolute shares held by 13F filers, not the percentage — specifically the direction and magnitude of that figure quarter-over-quarter, controlled for changes in total shares outstanding and any major index events in the period. A flat percentage against a declining share count is not the same signal as a flat percentage against a stable share count. The raw share count is the number that reflects actual institutional behavior.

---

## The Holder Count Signal

The number of unique 13F filers reporting a position in a stock — the holder count — carries information that the ownership percentage discards entirely.

A rising holder count means more institutional managers are independently deciding to allocate capital to the same company. Each new position represents a separate analytical conclusion at a different firm, made by a different investment team, against a different risk framework. The convergence of independent decisions is analytically meaningful for the same reason an insider cluster event is meaningful. When multiple unrelated actors reach the same conclusion about the same stock in the same window, the aggregate signal carries more weight than any single position.

A falling holder count, even alongside a rising or stable ownership percentage, is a caution flag. It means fewer institutions hold a larger collective stake — concentration rather than broad accumulation. Concentration can indicate high-conviction active ownership, but it also amplifies downside volatility if the remaining large holders decide to reduce simultaneously.

The most constructive institutional ownership pattern is rising holder count combined with rising absolute share counts — the one that historically precedes sustained price appreciation. At least a meaningful fraction of the new entries should represent genuinely new positions, not existing holders simply adding at higher prices. New money entering at current price levels is a different statement than existing holders averaging up.

[Costco's](/stocks/COST) institutional ownership trajectory in GeminIQ's tracker illustrates this pattern. Total institutional ownership climbed from **57.39%** in December 2022 to **67.71%** by December 2025 — a sustained three-year trend across multiple quarters, not a single-quarter spike. Over the same window, total share count was essentially flat, confirming that this was genuine net buying at the aggregate level rather than a denominator effect from buybacks. That kind of multi-year, broad-based accumulation against a stable float is what confirmed institutional conviction looks like in the data.

<center><sup>GeminIQ 13F Institutional Holdings Tracker for Costco showing sustained ownership increase from 57.39% (December 2022) to 67.71% (December 2025) against a flat share count — a confirmed multi-year accumulation pattern sourced directly from SEC Form 13F filings.</sup></center>

---

## How to Track Institutional Ownership Changes in GeminIQ

Most financial platforms display institutional ownership as a single number — the most recent 13F aggregate as a percentage. That answers only the least useful question the data set can answer.

GeminIQ's [Institutional Ownership](/features#institutional-ownership) feature aggregates 13F filing data directly from SEC EDGAR and displays it as a time series, making the trajectory visible across multiple quarters rather than freezing the picture at the most recent filing date. The difference between a stock that has gone from **52%** to **67%** institutional ownership over six quarters and one that jumped from **52%** to **67%** in a single quarter is analytically enormous. The first pattern suggests sustained accumulation by a broadening base of institutional holders. The second may reflect an index inclusion, a large activist entering a position, or a one-quarter spike from passive flows. Those are entirely different setups that look identical as a single data point.

For any company you are analyzing, the workflow in GeminIQ is direct. Pull the institutional ownership time series to identify the direction and character of the trend. Is this a sustained multi-quarter accumulation or a one-quarter event? Has the holder count been rising alongside the percentage, or is the increase concentrated in a small number of large existing holders? Then cross-reference with the insider transaction timeline — available through GeminIQ's [Insider Transactions](/features#insider-transactions) module — to determine whether company management and institutional filers are moving in the same direction or diverging. A company where institutions are steadily accumulating while insiders are selling for routine compensation-related reasons is a structurally different analytical setup from one where both data streams are pointing toward an exit.

<center><sup>GeminIQ 13F Institutional Holdings Tracker for Apple showing the institutional ownership percentage over time, sourced directly from SEC Form 13F filings — including the dip to 49.38% in Q4 2022 and recovery to 57.52% by March 2025. The trajectory view reveals accumulation and distribution patterns that a single current-period data point cannot surface.</sup></center>

---

## When Institutional Ownership Signals Break

Not every movement in 13F data carries the signal it appears to. Four structural conditions produce ownership readings that look like conviction trades but reflect nothing analytical.

Index inclusion is the most common, and it follows the mechanism already covered above: passive funds are forced buyers regardless of valuation. Before assigning interpretive weight to a sudden spike in the institutional ownership trend, always verify whether a major index reconstitution event falls in the same period.

Window dressing is a Q4-specific distortion. Active managers sometimes purchase recent outperformers at year-end to ensure those holdings appear in annual portfolio disclosures — an optics-driven trade, not an analytical one. Holdings that appear as new positions in a Q4 13F and disappear from the same manager's Q1 filing the following year are frequently the product of window dressing rather than a genuine investment decision. The signal test is persistence: conviction positions survive into the following quarter; window-dressed positions often do not.

ETF proliferation creates a double-counting problem in aggregate ownership data. When multiple 13F filers hold shares of an ETF that itself holds a stock, the underlying shares can be counted once for the ETF and again for each fund manager holding the ETF. This inflates the raw aggregate figure and makes the headline percentage a poor proxy for any single manager's conviction.

Spin-off residuals create a related structural distortion. When a company distributes shares of a newly independent subsidiary to its existing shareholders, every institution holding the parent receives shares of the new entity automatically. Many of these holders have no specific analytical view on the spun-off business — they received the shares as a distribution and have not yet made a decision about the position. A high institutional ownership percentage for a newly public spin-off frequently reflects this automatic distribution from the parent's holder base, not deliberate capital allocation into the new entity. It typically takes two to four quarters before the 13F data for a spin-off reflects genuine conviction positions rather than residual inherited holdings.

A single percentage pulled from any aggregator strips out exactly this kind of structural context — the difference between a number that moved because of conviction and a number that moved on its own. Reading the trajectory correctly means knowing which of these four conditions sits behind every shift in the data. That is the difference between a real accumulation signal and statistical noise wearing the shape of one.

---

## Frequently Asked Questions

### What does institutional ownership mean?

It is the percentage of a company's shares held by institutions, such as mutual funds, index funds, pension funds, hedge funds, banks, and insurers, as reported on their quarterly Form 13F filings. An institutional ownership of 70% means filers reported holding shares equal to 70% of the company's shares outstanding at quarter-end.

### Is high institutional ownership good or bad?

Neither on its own. Most large US companies have high institutional ownership simply because index funds must own them. What carries information is the change: new positions, additions by active managers, and a rising count of holders. The level can also move for mechanical reasons, such as buybacks shrinking the share count or an index inclusion, with no investment decision behind it.

### Who are the largest institutional investors?

The largest 13F filers by reported holdings are the big index and asset managers, led by Vanguard and BlackRock. Their size is why institutional ownership of most large-cap stocks is high, and why a change in a passive holder's stake usually reflects fund flows rather than a view on the company.

### How often is institutional ownership updated?

Quarterly. Managers report holdings as of the last day of each calendar quarter and have 45 days to file, so the data is always at least 45 days old by the filing deadline, and up to about four and a half months old for a position opened early in the quarter.

---

## Related Reading

Institutional ownership is one layer of the ownership signal. The complete cross-reference framework spans both the institutional and insider data streams together:

- [How to Read a 13F Filing: Institutional Holdings Explained](/blog/how-to-read-13f-filing) — the column-by-column mechanics of the filing itself, if you need the document structure before the ownership trend.
- [Insider Cluster Buying Signals: What the Academic Research Actually Shows](/blog/insider-cluster-buying-signal-data) — the framework for reading multiple simultaneous insider purchases as a compound signal, and how to distinguish conviction buys from routine compensation transactions.
- [How to Read SEC Form 4: Insider Buying and Selling Explained](/blog/how-to-read-sec-form-4) — field-by-field breakdown of the Form 4 structure and the transaction codes that determine whether a reported transaction carries any analytical weight.
- [Hidden Information in SEC Filings: What Most Investors Overlook](/blog/what-investors-miss-in-sec-filings) — how institutional ownership trends, insider transactions, and balance sheet signals combine into a complete fundamental picture, with Apple and Costco as worked examples.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — where the 13F fits within the full EDGAR filing ecosystem alongside 10-K, 10-Q, 8-K, 13D, and Form 4.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=institutional-ownership-13f-filing-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Institutional ownership figures cited in this article are drawn from quarterly 13F filings (most recent readings through Q4 2025); Apple and Costco share-count and financial figures reference their most recent 10-K filings. All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193).<br>
All financial figures cited in this article reference Costco Wholesale Corporation's Q3 FY2026 10-Q (filed June 3, 2026, period ending May 10, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/909832/000090983226000051/cost-20260510.htm).</sup>

---

## Blog: Intel Stock Analysis 2026: What the Q1 10-Q Actually Shows
source: https://www.geminiq.com/blog/intel-stock-analysis-2026

### Intel Stock Analysis 2026: What the Q1 10-Q Actually Shows
Intel's stock rallied roughly 450% from its lows on AI promises and Computex headlines. The Q1 FY2026 10-Q filed April 24, 2026 tells a more complicated story — one involving $4.07 billion in restructuring charges, negative free cash flow, and a TTM ROIC of -3.4%.

**[Intel](/stocks/INTC) ($INTC) just filed its Q1 FY2026 10-Q (filed April 24, 2026, period ending March 31, 2026), and the financial media is not reading it. The narrative — AI comeback, Computex momentum, Foxconn partnership, 18A process node, full-stack reinvention — drove the stock from roughly $30 to a peak near $135, one of the most dramatic reversals of 2026. But the income statement, the cash flow statement, and GeminIQ's raw SEC data tell a different story. Revenue has fallen **33%** from its peak. Free cash flow is negative. The company took **$4.07 billion** in restructuring charges in a single quarter. And the trailing twelve-month [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) sits at **-3.4%**. Here is the fundamental, data-driven truth behind the ticker.**

| Field | Value |
|---|---|
| Ticker | $INTC |
| Filing | Q1 FY2026 10-Q |
| Filed | April 24, 2026 |
| Period End | March 31, 2026 |
| Free Cash Flow (TTM) | **-$3.12 Billion** |
| ROIC (TTM) | **-3.4%** |

## The Revenue Collapse the Rally Is Trying to Forget

The financial media covers [Intel](/stocks/INTC) as a comeback story. The raw income statement tells you how far there is still to go.

**The Data:** In FY2021, Intel generated **$79.024 Billion** in Total Revenues. By FY2022 that had fallen to **$63.054 Billion**. FY2023 brought **$54.228 Billion**. FY2024 came in at **$53.101 Billion**. FY2025 was **$52.853 Billion** — barely moved from the year before. Q1 FY2026 posted **$13.577 Billion** in quarterly revenue, which annualizes to approximately **$54.3 Billion**. Three years of restructuring and billions in capital investment have not reversed a **-33%** revenue decline from peak.

**The GeminIQ Edge:** Pulling [Intel's](/stocks/INTC) Total Revenues line directly from the raw [financial statements](/features#financial-statements) in GeminIQ makes the trajectory unmistakable. Standard aggregators often present trailing-twelve-month figures that smooth this decline. The period-by-period filing data does not.

<center><sup>GeminIQ Financial Statements showing Intel's Total Revenues from FY2021 ($79.024B) through Q1 FY2026 ($13.577B quarterly), documenting a 33% decline from peak. Source: SEC 10-K FY2021–FY2025, 10-Q Q1 FY2026.</sup></center>

## Gross Margin: The One Signal Worth Paying Attention To

Not everything in the filing is bad news. One metric has improved in a way worth noting, and it is worth separating from the noise.

**The Data:** [Intel's](/stocks/INTC) [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) (Gross Profit ÷ Total Revenues) collapsed from **55.4%** in FY2021 to **32.7%** in FY2024 as the company absorbed massive fab depreciation and underutilization costs. FY2025 showed a recovery to **34.8%**. Q1 FY2026 reached **39.4%**, its best quarterly gross margin since early 2024. Gross profit for the quarter was **$5.347 Billion** on **$13.577 Billion** in revenue, leaving **$934 million** in operating income before restructuring charges. The manufacturing cost story is, slowly, improving.

**The GeminIQ Edge:** GeminIQ's pre-calculated [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) surfaces this recovery in seconds. Viewing it alongside the [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) makes the remaining gap plain: gross margin is recovering, but operating losses persist — the spending has not caught up to the improvement.

<center><sup>GeminIQ Calculated Metrics showing Intel's Gross Profit Margin from FY2021 (55.4%) through Q1 FY2026 (39.4%), alongside Operating Profit Margin, which remains negative. Source: Gross Profit ÷ Total Revenues, 10-K FY2021–FY2025, 10-Q Q1 FY2026.</sup></center>

## The Restructuring That Never Ends

Here is the line item the Computex coverage ignores. [Intel](/stocks/INTC) has been taking impairment and restructuring charges at a scale that rivals its operating losses.

**The Data:** GeminIQ pulls the Restructuring, Settlement And Impairment Provisions line directly from each filing. In FY2024, Intel booked **$6.970 Billion** in restructuring and other charges — in a single year. FY2025 added **$2.191 Billion** more. Q1 FY2026 alone added **$4.070 Billion**. That is **$13.231 Billion** in write-offs and impairment charges across the last two fiscal years and the latest quarter, as the company continuously re-values assets from a capacity buildout that preceded the revenue collapse. The $4.07 billion figure in Q1 2026 is precisely what turned gross profit of **$5.347 Billion** into an operating loss of **-$3.136 Billion** (Operating Income (Loss)). Strip the restructuring charge and the business generated roughly **$934 million** in operating profit. Include it and the net loss was **-$3.728 Billion**.

**The GeminIQ Edge:** Standard financial media reported the Q1 2026 earnings miss and moved on. GeminIQ's raw filing data lets you track the cumulative impairment toll quarter-by-quarter — what has been written down, how often, and whether the charges are decelerating or accelerating. The Q1 2026 charge of $4.07 billion represents an acceleration, not a wind-down.

<center><sup>GeminIQ Financial Statements displaying Intel's Restructuring, Settlement And Impairment Provisions by filing period: FY2024 ($6.970B), FY2025 ($2.191B), Q1 FY2026 ($4.070B). Source: 10-K FY2024–FY2025, 10-Q Q1 FY2026.</sup></center>

## Free Cash Flow: The Number That Doesn't Match the Narrative

The stock surged **31.78%** in the month following the Q1 FY2026 filing date. The filing itself showed deeply negative free cash flow.

**The Data:** GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) for Q1 FY2026: operating cash flow of **$1.096 Billion** minus capital expenditures of **$3.636 Billion** equals **-$2.540 Billion**. On a trailing twelve-month basis through March 31, 2026, operating cash flow was **$9.980 Billion** against **$13.099 Billion** in capital expenditures — TTM free cash flow of **-$3.119 Billion**. This is an improvement from FY2024's **-$15.656 Billion** TTM FCF, but it remains negative. Intel is still spending more capital than its operations generate. The trailing twelve-month [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) is **-3.4%**. Every dollar of capital deployed across the business is generating a negative return.

**The GeminIQ Edge:** Pulling Intel's [Free Cash Flow](/metrics/calculated-values/free-cash-flow) and [ROIC](/blog/roic-return-on-invested-capital-explained) side-by-side in GeminIQ's calculated metrics makes the gap between narrative and reality visible at a glance. The capex is declining — **$23.944 Billion** TTM in FY2024, down to **$13.099 Billion** TTM through Q1 2026 — but Intel remains FCF-negative, and the stock is up over 30% in the month after the filing that showed it.

<center><sup>GeminIQ Calculated Metrics showing Intel's trailing twelve-month Free Cash Flow (Q1 FY2026: -$3.119B), capital expenditures ($13.099B), and operating cash flow ($9.980B). The gap remains negative despite capex cuts from FY2024 peaks. Source: 10-Q Q1 FY2026.</sup></center>

## The Balance Sheet: Carrying $45 Billion in Debt Through the Transition

[Intel's](/stocks/INTC) balance sheet reflects the true cost of funding a simultaneous revenue recovery and fab transformation at scale.

**The Data:** As of March 31, 2026, Intel's long-term debt stood at **$43.027 Billion**, with **$2.004 Billion** in short-term debt — a combined **$45.031 Billion** in total debt. Cash and equivalents were **$17.247 Billion**, leaving a net debt position of approximately **$27.8 Billion**. Trailing twelve-month EBITDA, calculated as operating income plus depreciation and amortization with each quarter's D&A figure properly isolated to a single quarter rather than summed from cumulative year-to-date filings, comes to approximately **$6.2 Billion**. The implied [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) ratio is approximately **4.5x**. For a company still generating negative free cash flow, this is a structural constraint. Total assets were **$205.332 Billion**, with total equity at **$124.989 Billion**.

**The GeminIQ Edge:** GeminIQ computes [Net Debt](/metrics/calculated-values/net-debt) directly from the as-filed balance sheet figures, without normalization. EBITDA specifically requires care here: Intel reports some quarters' depreciation and amortization as year-to-date cumulative figures rather than clean single-quarter amounts, and a naive sum across four quarters can more than double the true trailing figure if that isn't accounted for. The raw number, properly isolated to genuine quarterly amounts, is blunt regardless: Intel is carrying near-peak debt through a period of near-peak uncertainty in its transformation.

## What Are the People Running Intel Doing With Their Own Money?

Insider transactions filed under SEC Form 4 are one of the few signals that financial aggregators routinely obscure through rounding or filing lag. GeminIQ pulls the raw Form 4 data directly.

**The Data:** In late January 2026, CFO David Zinsner made an open-market purchase of **5,882 shares** at **$42.50** per share — approximately **$249,985** — a directional signal from the person responsible for the balance sheet described above. A week later, EVP and Chief Legal Officer Boise April Miller sold **20,000 shares** at **$49.05** per share, collecting approximately **$981,000** in proceeds. The CFO buying and the CLO selling within the same window was a mixed signal that a simple headline screener would miss entirely. The pattern has continued into the rally: Miller sold again on May 1, 2026, this time **40,256 shares** at **$99.53** — more than double her February exit price — and EVP Nagasubramaniyan Chandrasekaran sold **21,024 shares** at **$118.28** on May 29, 2026. No further open-market purchases by any executive appear in the record since Zinsner's January buy.

**The GeminIQ Edge:** GeminIQ's [Insider Transactions](/features#insider-transactions) feed surfaces these Form 4 filings alongside the share price at the time of each transaction. Tracking the pattern across the full rally, not just a single snapshot, shows two consecutive executive sales at successively higher prices as the stock climbed — a pattern more consistent with routine diversification into strength than any specific signal, but worth weighing against the CFO's earlier purchase made when the stock traded at a fraction of today's price.

<center><sup>GeminIQ Insider Transactions dashboard showing CFO David Zinsner purchasing 5,882 shares at $42.50 (January 26, 2026) and CLO Boise April Miller selling 20,000 shares at $49.05 (February 2, 2026), sourced from SEC Form 4 filings.</sup></center>

The market has already priced [Intel](/stocks/INTC) as an AI winner. The Q1 FY2026 10-Q shows a business still losing **$3.7 Billion** in a single quarter, writing down **$4 Billion** in assets, and spending more capital than it generates. The turnaround may prove real — but the income statement has not confirmed what the stock price has already assumed.

## Frequently Asked Questions

### How far has Intel's revenue fallen from its peak?

Intel's revenue has fallen approximately 33% from its FY2021 peak of $79.024 Billion, sitting at roughly $54.3 Billion on an annualized basis as of the Q1 FY2026 10-Q.

### Is Intel's free cash flow positive?

No. As of the Q1 FY2026 10-Q, trailing twelve-month Free Cash Flow is -$3.119 Billion, an improvement from FY2024's -$15.656 Billion but still negative.

### What is Intel's Net Debt-to-EBITDA ratio?

Approximately 4.5x, based on net debt of roughly $27.8 Billion against trailing twelve-month EBITDA of approximately $6.2 Billion, calculated with each quarter's depreciation and amortization isolated to a single quarter rather than summed from cumulative year-to-date filing figures.

### When did Intel last file its 10-Q, and what period does it cover?

Intel's most recent filing is a Form 10-Q filed April 24, 2026, covering the fiscal quarter ended March 31, 2026 (Q1 FY2026).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=intel-stock-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Intel Corporation's Q1 FY2026 10-Q (filed April 24, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/50863/000005086326000079/intc-20260328.htm).

---

## Blog: Interest Coverage Deterioration: Median Held Near 4x
source: https://www.geminiq.com/blog/interest-coverage-deterioration-screen

### Interest Coverage Deterioration: Median Held Near 4x
Interest coverage deterioration is widely assumed to be a broad casualty of the higher-rate cycle, but as-filed data shows the median company's coverage barely moved, while the sharpest individual declines trace to acquisition debt, not rate resets.

**[Synopsys, Inc.](/stocks/SNPS)**'s interest coverage ratio fell from **199.5x** to **0.96x** in two years — one of the sharpest declines in GeminIQ's entire filing universe. It looks like the higher-rate cycle's balance-sheet story in miniature: a company stretched thin by refinancing at higher cost, buckling under interest expense it could once absorb without noticing. The as-filed data tells a more specific story. Synopsys didn't get squeezed by rates — it took on acquisition debt to fund its roughly **$35 billion** purchase of Ansys. Its coverage ratio collapsed because a company that carried almost no debt suddenly carried a lot, not because its existing debt got more expensive.

This study reads GeminIQ's as-filed universe of trailing-twelve-month interest coverage — EBIT divided by interest expense — for companies with positive EBIT and at least **$5 million** in trailing interest expense, excluding financial companies. This study tracks the universe median by year from 2015 through the current filing snapshot, then ranks the sharpest three-year deteriorations among companies with over **$2 billion** in trailing revenue that were healthy (coverage above 3x) three years earlier.

## The Pattern

The assumption around the higher-rate cycle is broad balance-sheet stress: rates went up, interest expense went up, coverage ratios came down across the board. The as-filed data does not support that as a universe-wide story. The median interest coverage ratio for profitable, ex-financial companies sat at **4.18x** in 2015 and dipped modestly through the pandemic years. It actually *peaked* at **5.82x** in 2022 — the first full year of the hiking cycle — before settling back to **4.28x** in the current snapshot, essentially unchanged from a decade ago. Most companies termed out their debt at fixed rates before the hiking cycle began, and that decision shows up directly in the numbers: the median company's coverage never meaningfully cracked.

## The Data

| Year | Median Interest Coverage (Profitable, Ex-Financial) |
|---|---|
| 2015 | **4.18x** |
| 2018 | **4.19x** |
| 2020 | **3.61x** |
| 2021 | **4.77x** |
| 2022 | **5.82x** |
| 2023 | **4.54x** |
| 2024 | **3.87x** |
| 2025 | **3.87x** |
| 2026 | **4.28x** |

The median obscures real dispersion at the current snapshot. Among the **1,332 companies** meeting this study's criteria today, the 25th percentile sits at just **1.93x**, and **348 companies — 26.1% of the universe** — currently run coverage below 2x. A thin-coverage minority exists and is worth screening for individually; it simply isn't a new, rate-driven phenomenon showing up in the aggregate trend.

<center><sup>GeminIQ data study: median trailing-twelve-months interest coverage ratio by year, profitable ex-financial companies, as-filed. Built from as-filed 10-K/10-Q data via GeminIQ. n = 1,332 companies in the current snapshot; full series 2015–2026.</sup></center>

## The Extremes: M&A Debt, Not Rate Resets

**[Synopsys](/stocks/SNPS)**'s collapse from 199.5x to 0.96x and **[Accenture](/stocks/ACN)**'s drop from **213.2x** to **39.8x** share the same mechanism: both moved from a near-debt-free capital structure to a leveraged one inside a two-to-three-year window. In Synopsys's case, the timing lines up directly with its Ansys acquisition. Neither company's *existing* debt got more expensive — both added new debt on top of a base that previously had almost none, which mechanically crushes a coverage ratio regardless of the rate environment. That distinction matters for anyone screening on interest coverage trend alone: a sharp decline from an extremely high starting point is frequently an acquisition-financing story, not a distress signal. The two look identical on a bare ratio without checking the debt levels underneath.

**[Chevron](/stocks/CVX)** and **[ExxonMobil](/stocks/XOM)** also appear among the largest three-year drops, both falling from coverage ratios above 80x to still-comfortable levels in the 20x–52x range. Even a large percentage decline can land somewhere entirely healthy when the starting point was that extreme.

## The Method

Interest coverage is GeminIQ's trailing-twelve-months EBIT divided by trailing-twelve-months interest expense, drawn from as-filed data via GeminIQ's [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) metric. GeminIQ computes the yearly median across companies with positive EBIT and at least **$5 million** in trailing interest expense, excluding financial companies, for each calendar year 2015–2026. The deterioration ranking compares each company's most recent reading (within the last 15 months) against its own reading roughly three years earlier. It is restricted to companies with over **$2 billion** in trailing revenue that started from a coverage ratio above 3x. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any leveraged position's interest coverage trend on GeminIQ, and before assuming a decline reflects rate pressure, check whether total debt actually grew over the same window. A coverage ratio that fell because debt increased tells a very different story than one that fell because interest expense on the same debt load simply got more expensive. Every reader can run that same check directly against GeminIQ's as-filed data.

## Frequently Asked Questions

### Did the higher-rate environment broadly hurt interest coverage?

Not at the universe level, in GeminIQ's data. The median interest coverage ratio for profitable, ex-financial companies sat at 4.18x in 2015 and 4.28x in the current snapshot — essentially unchanged over a decade that included a full rate-hiking cycle. Most companies termed out debt at fixed rates before rates rose.

### What is causing the sharpest declines in interest coverage?

Acquisition-financed debt, more often than rate resets. Synopsys's coverage ratio fell from 199.5x to 0.96x in two years, timed to its roughly **$35 billion** Ansys acquisition — new debt added on top of a nearly debt-free base, not existing debt becoming more expensive.

### What counts as a low interest coverage ratio?

In GeminIQ's current snapshot, the 25th percentile among profitable, ex-financial companies with meaningful interest expense sits at 1.93x, and **26.1%** of that universe currently runs coverage below 2x.

### How is interest coverage calculated?

Interest coverage is trailing-twelve-months EBIT divided by trailing-twelve-months interest expense, available on GeminIQ as the [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) metric.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=interest-coverage-deterioration-screen)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). The yearly median and deterioration ranking are computed from GeminIQ's Interest Coverage Ratio metric across the described universe and snapshot window.

---

## Blog: Inventory Growing Faster Than Sales: The Warning, Scored
source: https://www.geminiq.com/blog/inventory-growing-faster-than-sales

### Inventory Growing Faster Than Sales: The Warning, Scored
GeminIQ's as-filed inventory and revenue data scores the classic 'warehouses outran the registers' warning across four verified cases — Carvana, VF Corp, Wayfair, and Under Armour — where inventory growth badly outpaced revenue growth ahead of steep declines, while the broader screened universe shows no reliable statistical edge from the spread alone.

[Carvana](/stocks/CVNA)'s Inventory Net hit **$3.1 Billion** by the end of fiscal 2021, up **204%** year-over-year against **129.4%** revenue growth. Three months after that filing, the stock was down **69.6%**. That's the largest inventory build in dollar terms in a screen built around one question: when a company's inventory grows meaningfully faster than its sales, does the filing data show it coming?

This ranking draws on GeminIQ's as-filed database: **8,574** quarterly filings across **171** companies in inventory-carrying retail and apparel sectors, filed between April 2011 and August 2026, ranked by the spread between year-over-year Inventory Growth and GeminIQ's pre-calculated Net Revenue TTM Growth 1Y, joined to each stock's return over the three months after the filing date.

What follows isn't a systematic signal. It's four specific, individually verified cases where the pattern showed up in the filings, presented in order of how far revenue growth was outrun.

| Rank | Company | Inventory Growth (1Y) | Revenue Growth (1Y) | Spread | 3-Month Return After |
|---|---|---|---|---|---|
| 1 | [Wayfair](/stocks/W) | **+63.6%** | **-14.8%** | **+78.4 pts** | **-47.2%** |
| 2 | [VF Corp](/stocks/VFC) | **+92.4%** | **+16.5%** | **+75.9 pts** | **-38.6%** |
| 3 | [Carvana](/stocks/CVNA) | **+204.0%** | **+129.4%** | **+74.6 pts** | **-69.6%** |
| 4 | [Under Armour](/stocks/UAA) | **+45.9%** | **+28.5%** | **+17.4 pts** | **-8.4%** |

## The Null Finding: The Spread Alone Is Not a Screen You Can Run

Screened broadly, this spread doesn't predict much. Across **8,574** quarterly filings from **171** companies in inventory-carrying retail and apparel sectors, quarters in the worst quartile of the inventory-to-revenue growth spread returned about the same as their sector's own base rate over the next three months — no meaningful outperformance and no meaningful underperformance. A study reporting that its own screen didn't work is a less satisfying result than a signal, and it is the honest one.

That is why the four companies below were individually selected and verified against public reporting rather than pulled off the top of the ranked screen. They are cases, not output.

## Wayfair (W): Building Into a Shrinking Top Line

[Wayfair](/stocks/W)'s case is arguably the starkest of the four, because revenue wasn't just decelerating — it was already shrinking. In the quarter ended June 2022, Inventory Growth (1Y) was **+63.6%** while Net Revenue TTM Growth 1Y was **-14.8%**, a company still building inventory into demand that had already turned negative. The post-pandemic furniture and home-goods boom had ended, and Wayfair kept stocking shelves for a customer base that wasn't showing up. The stock fell **47.2%** over the three months that followed.

## VF Corp (VFC): The Vans Problem, Visible in the Filings

[VF Corp](/stocks/VFC), the parent of Vans, The North Face, and Timberland, became one of retail's most public inventory reckonings by late 2022 — and the filings showed the imbalance well before the company's own guidance caught up. For the quarter ended June 2022, Inventory Growth (1Y) ran **+92.4%** against **16.5%** revenue growth. Over the following months, VF Corp cut its outlook three times, wrote down its Supreme acquisition, cut its dividend **41%**, and its longtime CEO retired. Three months after the filing that first showed the gap, the stock was down **38.6%**.

## Carvana (CVNA): The Used-Car Pile-Up

[Carvana](/stocks/CVNA) filed the widest inventory build in dollar terms on this list: Inventory Net reached **$3.1 Billion** for fiscal 2021, up **204%** year-over-year, against already-strong **129.4%** revenue growth. The company had stocked up on used cars at pandemic-peak prices. When interest rates rose and used-car values fell through 2022, that inventory became a liability, forcing steep write-downs and a cash crunch severe enough that analysts openly discussed bankruptcy risk. Three months after the fiscal 2021 filing, the stock was down **69.6%**. Twelve months out, it was down **94.9%**.

## Under Armour (UAA): The Slow Bleed

[Under Armour](/stocks/UAA) is the one entry here where the filings told a multi-year story rather than a single sharp break. For fiscal 2015, Inventory Growth (1Y) ran **+45.9%** against **28.5%** revenue growth — a real but comparatively modest gap next to the other three. The stock was down **8.4%** three months after that filing and **28.4%** a year out, as growth kept decelerating and inventory kept building through 2016 and 2017 before the company fully addressed it. It's the reminder that this pattern doesn't always resolve in a single quarter — sometimes the filings show the problem accumulating for years before the market fully catches up.

## The Method

Inventory Growth (1Y) has no pre-built GeminIQ metric. This post computes it directly from the raw `Inventory Net` balance sheet tag, comparing each filing's balance to the balance from approximately one year earlier — the same convention GeminIQ uses for [Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth). Revenue growth is GeminIQ's pre-calculated Net Revenue TTM Growth 1Y. The screen is restricted to retail, apparel, and other physical-goods sectors where a real inventory balance exists, with a **$1 Million** floor on the prior-year balance to exclude divide-by-near-zero artifacts. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

This is a spread you can check directly. Pull up any inventory-carrying position in GeminIQ's [Financial Statements](/features#financial-statements) view and find `Inventory Net` on the balance sheet, then compare it to the same line item from four quarters earlier to get its year-over-year change. Check that against the position's Net Revenue TTM Growth 1Y in [Calculated Metrics](/features#calculated-metrics). A gap where inventory is growing meaningfully faster than sales isn't a guaranteed warning sign — the four cases above show it can resolve in one bad quarter or unwind over several years — but it's a gap worth seeing in the filings before it shows up in a headline.

The same as-filed data supports a second check on the other side of the equation — what the market has already paid for the growth. That study is [priced for perfection, quantified](/blog/priced-for-perfection-explained).

## Frequently Asked Questions

### Why would a company's inventory grow faster than its sales?

Usually because the buying decision was made against demand that no longer exists by the time the goods arrive. Wayfair kept building stock into a top line that had already turned negative after the post-pandemic home-goods boom ended. Carvana bought used cars at pandemic-peak prices and was still holding them when rates rose and values fell. VF Corp's build showed up in the filings before its own guidance caught up. It is not always a mistake, either — semiconductor companies build ahead of demand as a matter of course, and in this screen those quarters showed no meaningfully worse forward return than the sector's base rate.

### How long after an inventory buildup did these stocks decline?

In three of the four cases here the move came quickly: Wayfair was down **47.2%**, VF Corp **38.6%**, and Carvana **69.6%** within three months of the filing that showed the gap. Under Armour is the counterexample — down only **8.4%** at three months and **28.4%** a year out, with inventory still building through 2016 and 2017. Carvana kept falling too, to **-94.9%** twelve months on. Across the full screened universe, though, the widest-spread quarters returned about the same as their sector's base rate, so no timing pattern generalizes from these four.

### Does inventory growing faster than sales always mean trouble ahead?

No. Screened across the full universe of retail and apparel filings in this study, quarters with the widest inventory-to-revenue growth spread performed about the same as their sector's own base rate over the next three months. The four cases in this post are specific, individually verified examples, not a statistical signal that generalizes.

### How is "Inventory Growth (1Y)" calculated if GeminIQ doesn't have a pre-built metric for it?

It's derived directly from the `Inventory Net` balance sheet tag: the current period's balance compared to the balance from approximately one year earlier, matched by filing date — the same convention GeminIQ uses for its pre-calculated Deferred Revenue Growth metric.

### Why isn't there a semiconductor company on this list?

Semiconductor companies build inventory ahead of demand as a matter of course, and in GeminIQ's screen, quarters with the widest inventory-outpacing-revenue spread in that sector showed no meaningfully worse forward return than the sector's own base rate. A build there reads more like confidence than risk, which is a different story than the one this post is telling.

### What counts as "inventory-carrying" for this screen?

Retail, apparel, and other physical-goods sectors by SIC code, with a **$1 Million** floor on the prior-year inventory balance to filter out small or newly-disclosed positions that can produce misleadingly large percentage swings.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=inventory-growing-faster-than-sales)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 171 companies in inventory-carrying retail and apparel sectors (by SIC code), drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 8,574 quarterly filings, filed April 2011 through August 2026, were screened for the spread between year-over-year Inventory Growth and GeminIQ's pre-calculated Net Revenue TTM Growth 1Y. Inventory Growth (1Y) is derived from the raw `Inventory Net` balance sheet tag and is not a GeminIQ platform metric. The screen applies a $1 Million floor on the prior-year inventory balance and bounded growth rates to exclude divide-by-near-zero and distressed-company artifacts. Across the full screened universe, the top quartile by spread showed no meaningful outperformance or underperformance versus the sector base rate over the following three months; the four companies named in this post were individually selected and verified against public reporting, not mechanically ranked by the raw screen. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Invested Capital Formula: A Worked Example From Apple's 10-Q
source: https://www.geminiq.com/blog/invested-capital-formula-step-by-step

### Invested Capital Formula: A Worked Example From Apple's 10-Q
A start-to-finish worked example of the invested capital formula, built by hand from Apple's Q2 FY2026 10-Q. Each of the three inputs — total equity, total debt, and excess cash — is located in the filing, traced to its XBRL tag, and combined into the figure that feeds ROIC.

Revenue is a single line on an income statement. Net income is a single line on the same statement. Invested capital is not a line anywhere. No filing reports it directly, which means every platform displaying a number labeled "invested capital" has already made three or four methodology decisions before that number reaches a screen. Which debt counts. Whether the current portion of long-term debt belongs in the total. How much cash is excess versus operationally necessary. Whether the figure comes from one period's balance sheet or an average of two. The only way to know whether you trust one of those numbers is to build it yourself once.

This guide does exactly that — one company, one filing, start to finish. It builds invested capital by hand from [Apple's](/stocks/AAPL) most recently filed 10-Q — Q2 FY2026 (filed May 1, 2026, period ending March 28, 2026) — locating each of the three inputs in the filing and tracing it back to the XBRL tag behind it.

For the plain-English definition, the formula on its own, and how the metric is calculated consistently across every company in the database, see the [Invested Capital metric page](/metrics/calculated-values/invested-capital) — the full definition and formula live there. This post assumes you have that and want to watch the arithmetic actually run.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=invested-capital-formula-step-by-step)**

---

## Table of Contents

- [The Invested Capital Formula](#the-invested-capital-formula)
- [Step 1: Find Total Equity](#step-1-find-total-equity)
- [Step 2: Find Total Debt — and Why the Current Portion Is Included](#step-2-find-total-debt-and-why-the-current-portion-is-included)
- [Step 3: Calculate Excess Cash](#step-3-calculate-excess-cash)
- [Step 4: Put It Together — Apple's Invested Capital, Start to Finish](#step-4-put-it-together-apples-invested-capital-start-to-finish)
- ["Invested Capital" vs. "Total Invested Capital" vs. "Average Invested Capital"](#invested-capital-vs-total-invested-capital-vs-average-invested-capital)
- [Invested Capital in Corporate Finance vs. Private Equity](#invested-capital-in-corporate-finance-vs-private-equity)
- [Why Invested Capital Differs So Much Across Platforms](#why-invested-capital-differs-so-much-across-platforms)
- [When Invested Capital Breaks](#when-invested-capital-breaks)
- [Where Invested Capital Shows Up: ROIC, Screens, and Beyond](#where-invested-capital-shows-up-roic-screens-and-beyond)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## The Invested Capital Formula

GeminIQ calculates invested capital using the financing approach — building the number from the funding side of the balance sheet:

**Invested Capital = Total Equity + Total Debt − Excess Cash**

Total Equity is Total Shareholders' Equity exactly as reported, carrying the Stockholders Equity tag. Total Debt is the interest-bearing borrowings defined in Step 2. Excess Cash is total cash less an Operating Cash Reserve, which GeminIQ estimates at **2%** of trailing-twelve-month revenue, caps at total cash, and floors at zero.

Three inputs, one subtraction. The formula is not the hard part. Two of the three inputs — Total Debt and Excess Cash — require a judgment call the raw filing never makes for you, and the next three steps show exactly how GeminIQ's [Calculated Metrics](/features#calculated-metrics) view makes that call, built from the same filing referenced above.

---

## Step 1: Find Total Equity

### What Is Total Equity in the Invested Capital Formula?

Total Equity is the simplest of the three inputs. It reports directly on the balance sheet as a single line, with no judgment calls required — the book value of everything shareholders own, net of treasury stock. Pulling it from GeminIQ's [Financial Statements](/features#financial-statements) view means it arrives with the XBRL tag attached, rather than folded into a normalized "equity" line that may or may not match what the company actually filed.

**The Data:** [Apple's](/stocks/AAPL) balance sheet as of March 28, 2026 reports Total Shareholders' Equity (the Stockholders Equity tag) of **$106.5 Billion**. A year earlier, the same line stood at **$66.8 Billion**. The **$39.7 Billion** swing reflects four consecutive quarters of net income compounding faster than buybacks and dividends returned it — and a Retained Earnings balance that flipped from an **-$15.6 Billion** accumulated deficit to a **$12.4 Billion** positive balance over the same year.

**When it breaks:** Total Equity can run negative for companies with aggressive buyback histories or large accumulated deficits — several large, profitable companies sit in exactly this position. Negative equity does not automatically signal distress; more often it signals a company returning more capital to shareholders than it retains. It does, however, mechanically depress invested capital, and in extreme cases can push the whole figure negative — at which point [ROIC](/blog/roic-return-on-invested-capital-explained) becomes undefined.

---

## Step 2: Find Total Debt — and Why the Current Portion Is Included

### What Counts as Total Debt for Invested Capital?

This is where invested capital calculations most commonly diverge, and GeminIQ's definition is broader than some investors expect. Total Debt for invested capital purposes includes every interest-bearing borrowing on the balance sheet — commercial paper and similar short-term instruments, the current portion of long-term debt, and the non-current portion of long-term debt. Nothing interest-bearing is left out: the current maturity of term debt is a real obligation the company must fund, so it belongs in the capital base just as the commercial paper and the long-dated notes do.

That is a narrower definition than the "Total Debt" used in a [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) calculation, which typically counts every interest-bearing obligation regardless of maturity. For invested capital, GeminIQ isolates the debt that represents ongoing, structural financing: non-current term debt that stays on the balance sheet for years, and revolving short-term instruments like commercial paper that companies continuously roll over rather than pay down. A maturity already scheduled for repayment out of existing cash within twelve months is a different economic animal from either one.

**The Data:** [Apple's](/stocks/AAPL) Q2 FY2026 balance sheet reports Commercial Paper of **$2.0 Billion**, Long Term Debt Current of **$8.3 Billion**, and Long Term Debt Noncurrent of **$74.4 Billion**. All three summed give **$84.7 Billion** in total interest-bearing debt, and the full **$84.7 Billion** counts toward invested capital — Commercial Paper, the **$8.3 Billion** current portion of term debt, and the non-current term debt alike.

<center><sup>GeminIQ Financial Statements showing Apple's Q2 FY2026 Balance Sheet: Total Shareholders' Equity (Stockholders Equity: $106.5 Billion), Commercial Paper (Commercial Paper: $2.0 Billion), Long-Term Debt, Current (Long Term Debt Current: $8.3 Billion), and Long-Term Debt, Noncurrent (Long Term Debt Noncurrent: $74.4 Billion). Source: 10-Q filed May 1, 2026.</sup></center>

**When it breaks:** A platform that excludes the current portion of long-term debt from invested capital shows a smaller capital base — and, mechanically, a higher ROIC — than one that includes it, the way GeminIQ does. Neither convention is wrong on its face, but the two are not comparable to each other, and an **$8 Billion**-or-larger current-debt balance can move the resulting ROIC by a full percentage point or more. When a by-hand calculation doesn't match a platform figure, this is the first place to check.

---

## Step 3: Calculate Excess Cash

### What Is Excess Cash?

Cash on the balance sheet above what a business needs for day-to-day operations is a financial asset, not deployed operating capital. Counting all of it toward invested capital understates ROIC for exactly the businesses where ROIC is most useful as a quality signal: capital-light, cash-rich ones. GeminIQ estimates the operating cash a business actually needs at **2%** of trailing-twelve-month revenue and treats everything above that threshold as excess.

**Operating Cash Reserve = min(Total Cash, 2% × Revenue TTM)**
**Excess Cash = Total Cash − Operating Cash Reserve** (floored at zero)

**The Data:** [Apple's](/stocks/AAPL) Cash And Cash Equivalents At Carrying Value stood at **$45.6 Billion** as of March 28, 2026, against Revenue TTM of **$451.4 Billion**. Two percent of that revenue figure is **$9.0 Billion** — the Operating Cash Reserve. Subtract it from total cash and Excess Cash comes to **$36.5 Billion**.

**When it breaks:** The **2%**-of-revenue rule is a standard corporate finance estimate, not a figure any company discloses. It holds up well as a consistent, comparable benchmark across the entire market, but a business with genuinely unusual working capital needs — heavy inventory financing, large customer deposits — may need meaningfully more or less operating cash in reality. Treat the excess cash figure as a reasonable estimate, not a number the company itself would sign off on.

---

## Step 4: Put It Together — Apple's Invested Capital, Start to Finish

With all three inputs built from the same filing, the arithmetic runs in one line:

**Invested Capital = Total Equity + Total Debt − Excess Cash**
**$106.5 Billion + $84.7 Billion − $36.5 Billion = $154.7 Billion**

**$154.7 Billion** is the capital base [Apple](/stocks/AAPL) must generate an operating return on, as of the Q2 FY2026 filing. It is not the **$371.1 Billion** in total assets. It is not the **$264.6 Billion** in total liabilities. Invested capital keeps the full interest-bearing debt load from Step 2 but strips out the cash Apple is not actually deploying into the business, and what is left is a more precise number than any headline balance sheet total.

<center><sup>GeminIQ Calculated Metrics showing Apple's Invested Capital at $154.7 Billion for Q2 FY2026 — matching the by-hand build above from Total Shareholders' Equity ($106.5 Billion), Total Debt for invested capital ($84.7 Billion), and Excess Cash ($36.5 Billion). Source: 10-Q filed May 1, 2026.</sup></center>

---

## "Invested Capital" vs. "Total Invested Capital" vs. "Average Invested Capital"

These three terms circulate almost interchangeably across financial media, and that interchangeability is exactly where the confusion starts. They are not three metrics. They are the same calculation, used two different ways.

**Invested Capital** and **Total Invested Capital** are the same figure: the point-in-time number built above, **$154.7 Billion** for [Apple](/stocks/AAPL) as of March 28, 2026. "Total" describes what the figure already is — a combination of debt and equity capital — rather than a separate methodology. If one source calls it "invested capital" and another calls it "total invested capital" for the same company and period, the two numbers should match, assuming both apply the same debt and excess cash conventions from Steps 2 and 3.

**Average Invested Capital** is genuinely different, and it is the figure that actually feeds [ROIC](/blog/roic-return-on-invested-capital-explained):

**Average Invested Capital = (Invested Capital, current period + Invested Capital, same period prior year) ÷ 2**

The averaging exists because ROIC measures a flow — NOPAT generated over a trailing twelve months — against a capital base, and a single point-in-time snapshot creates a timing mismatch with that flow. A company that raised a large amount of capital mid-year would have a period-end invested capital figure that includes months during which the new capital wasn't yet generating returns, artificially depressing ROIC. Averaging the current period against the same period one year earlier smooths that mismatch into a figure that better represents the capital base actually deployed across the trailing year.

**The Data:** [Apple's](/stocks/AAPL) invested capital one year earlier — Q2 FY2025, period ended March 29, 2025 — was **$144.8 Billion**, built from Total Equity of **$66.8 Billion**, Total Debt for invested capital of **$98.2 Billion**, and Excess Cash of **$20.2 Billion**. Average that against the current period's **$154.7 Billion** and Average Invested Capital comes to **$149.7 Billion** — exactly what feeds the ROIC calculation. Divide NOPAT TTM of **$122.3 Billion** by that **$149.7 Billion** and the result is **81.7%**, matching GeminIQ's displayed ROIC TTM. Every input traces cleanly back to two filings.

The practical distinction: a headline figure described simply as a company's "invested capital" is almost always the point-in-time figure. When a ROIC number is being reconstructed from its components, the denominator in play is the average. Dividing NOPAT by a single period's invested capital instead of the two-period average is one of the more common by-hand errors, and it produces a ROIC that won't reconcile with GeminIQ's pre-calculated figure even when every other input matches exactly.

---

## Invested Capital in Corporate Finance vs. Private Equity

One more thing worth clearing up before leaving the worked example, because it trips people up when they search the term: two entirely different concepts share this name, and search results return both without warning that they measure different things.

Everything above describes the corporate finance meaning — a balance sheet figure for an operating company, calculated from that company's own filings, used as the denominator in ROIC. It answers how much capital is deployed inside one business.

Private equity uses "invested capital" to mean something else: the portion of a fund's committed capital that has actually been called and deployed into portfolio companies, as distinct from capital that limited partners have promised but the fund has not yet drawn. A fund with **$1 Billion** in commitments that has deployed **$600 Million** has **$600 Million** of invested capital, regardless of what any portfolio company's balance sheet says. It is the denominator in fund-level return measures — multiple on invested capital, distributions to paid-in capital — and it describes the flow of money from investors into deals, not the capital structure of an operating business.

The distinction is not academic. The corporate figure is calculable from a 10-K or 10-Q by anyone. The private equity figure lives in fund reporting that limited partners receive and the public does not. When a search result for "invested capital" describes capital calls, dry powder, or vintage years, it is answering the fund question. The build above, and every invested capital figure on GeminIQ, answers the operating company question.

---

## Why Invested Capital Differs So Much Across Platforms

Pull the same company's invested capital from two different financial websites and a mismatch of **10%** or more is common. It is rarely a data error — it is four methodology decisions compounding on top of each other.

The debt definition is the largest source of divergence: whether the current portion of long-term debt is included, as shown in Step 2, whether operating lease liabilities are folded into debt, and whether preferred stock is treated as debt or equity all shift the total meaningfully. The excess cash assumption is the second: some platforms subtract all cash from invested capital, some subtract none, and GeminIQ's **2%**-of-revenue threshold sits between those extremes. The financing-versus-operating approach choice is the third — GeminIQ builds the figure from the funding side, and the [Invested Capital metric page](/metrics/calculated-values/invested-capital) explains why that approach is more robust than working from the asset side. Point-in-time versus average invested capital is the fourth — and the one that produces the most confusion, because a platform that shows a single "invested capital" figure without specifying whether it is a snapshot or a two-period average leaves the reader unable to reconcile it against a ROIC figure at all.

Operating lease treatment under ASC 842 deserves a specific callout. Since the standard took effect, most operating leases now appear on the balance sheet as both a lease liability and a right-of-use asset — line items that did not exist in this form before 2019. A platform that folds lease liabilities into debt while another's convention does not will produce a materially different invested capital figure for any company with a large real estate or equipment lease footprint. Restaurant chains, retailers, and airlines are the clearest examples, and this is not a minor edge case — it is a structural difference in how two platforms read the identical balance sheet.

GeminIQ's [pre-calculated Invested Capital](/metrics/calculated-values/invested-capital) applies one consistent convention — the financing approach, the debt definition in Step 2, and the **2%** excess cash rule — across every company in the database, sourced directly from XBRL-tagged filings rather than a normalized third-party feed. That number will not match every other platform. It will be internally consistent across the entire universe, which is the property that actually matters when comparing invested capital or ROIC across companies.

---

## When Invested Capital Breaks

Invested capital holds up as a denominator for most businesses across most periods. Three situations distort it enough to warrant a second look.

Large goodwill impairments shrink invested capital mechanically. A **$10 Billion** goodwill write-down reduces equity by roughly that amount net of any tax benefit, which shrinks invested capital in the same period — even though nothing about the business's actual operations changed. Any ROIC spike immediately following a large impairment deserves a check on whether the invested capital base still represents normal operating capital, not just a mathematically lower one.

Negative invested capital is the more severe failure mode. Companies with aggressive buyback histories or large accumulated deficits can push book equity negative enough that Total Equity plus Total Debt falls below Excess Cash, producing a negative figure. GeminIQ treats ROIC as null in these periods rather than displaying a number implying a meaningful "return" on a capital-deficient structure.

Businesses mid-cycle on a major capital investment — a new plant, an acquisition, a large capex ramp — show temporarily inflated invested capital before the new assets generate proportional operating returns. That is not a calculation error. It is a genuine, if temporary, mismatch between capital deployed and capital earning a return, and the trend across several years reads more reliably than any single period.

---

## Where Invested Capital Shows Up: ROIC, Screens, and Beyond

Invested capital is rarely the end goal of an analysis on its own. It is the foundation underneath several of the metrics and screens value investors rely on most, starting with [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained): NOPAT divided by average invested capital, and the single most important quality metric for evaluating whether a business creates or destroys economic value over time.

Its influence extends into screening as well. GeminIQ's [Quality Compounder screen](/screens/stock-screeners/quality-compounder) filters directly on ROIC at or above **20%**, which means every result depends on an invested capital figure calculated consistently across the entire company universe. Joel Greenblatt's [Magic Formula](/blog/magic-formula-investing-explained), replicable through GeminIQ's [screener](/screens/stock-screeners/magic-formula), ranks companies on ROIC and earnings yield together — invested capital is the hidden variable underneath the ROIC half of that ranking.

Any screen or ratio built on ROIC is only as reliable as the invested capital calculation underneath it. Knowing exactly how that number gets built — which debt counts, how excess cash is estimated, whether the figure is point-in-time or averaged — is what makes it possible to trust, or productively question, everything built on top of it.

---

## Frequently Asked Questions

### Is "total invested capital" a different metric from "invested capital"?
No. Both terms refer to the same point-in-time calculation — Total Equity plus Total Debt minus Excess Cash. "Total" describes the fact that the figure combines debt and equity capital; it is not a separate methodology. The term to actually watch for is "average invested capital," a distinct, two-period calculation used specifically as the ROIC denominator.

### What does invested capital mean in private equity?
Something different from the meaning used throughout this guide. In private equity, invested capital is the share of a fund's committed capital that has actually been called and deployed into portfolio companies, and it serves as the denominator in fund-level return measures like multiple on invested capital. The corporate finance figure built above measures capital deployed inside a single operating business and comes straight from that company's balance sheet. The two are unrelated calculations that happen to share a name.

### Is invested capital the same as enterprise value?
No, though the two share components. [Enterprise Value](/metrics/valuation-metrics/enterprise-value) uses market capitalization — the current stock price times shares outstanding — plus total debt, minus all cash. Invested capital uses book equity, the balance sheet figure rather than the market price, plus a narrower debt definition, minus only excess cash above an operating threshold. Enterprise value is a market-based acquisition-cost concept; invested capital is a book-based operating-capital concept, and the two produce very different numbers for the same company whenever the market price diverges meaningfully from book value.

### Can invested capital be negative?
Yes, though it is uncommon and usually signals an unusual capital structure rather than a calculation error. It occurs when Total Equity plus Total Debt falls below Excess Cash — most often for companies with large accumulated deficits or years of aggressive share buybacks that have pushed book equity toward or below zero. GeminIQ treats [ROIC](/blog/roic-return-on-invested-capital-explained) as null in these periods rather than computing a number from a capital-deficient base.

### Does invested capital include operating lease liabilities?
That depends on the platform and the approach. Under ASC 842, most operating leases now appear on the balance sheet as lease liabilities and right-of-use assets. Whether a given invested capital calculation folds those lease liabilities into "debt" is a specific methodology choice that varies by source, and for lease-heavy businesses — restaurant chains, retailers, airlines — it can shift the figure meaningfully. Always check what debt definition a platform uses before comparing invested capital across companies with different lease footprints.

### Why doesn't my by-hand invested capital calculation match GeminIQ's number?
Three causes account for most mismatches, in order of frequency: excluding the current portion of long-term debt from Total Debt, which Step 2 includes; using a different excess cash assumption than the **2%**-of-revenue rule; or comparing a point-in-time figure against what is actually the two-period average used in ROIC. Checking which of the three applies almost always resolves the discrepancy.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=invested-capital-formula-step-by-step)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s Q2 FY2026 10-Q (filed May 1, 2026, period ending March 28, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/320193/000032019326000013/aapl-20260328.htm).

---

## Blog: Jefferies (JEF) Q3 2026 Earnings: Revenue Up 11%, Tax Rate Down 9 Pts
source: https://www.geminiq.com/blog/jefferies-earnings-q3-2026

### Jefferies (JEF) Q3 2026 Earnings: Revenue Up 11%, Tax Rate Down 9 Pts
Jefferies reported Q3 2026 total revenues of $3.23 billion, up 11.1%, in the quarter ended August 31, 2026. The 10-Q cut the tax rate to 17.9% from the release's 24.8%, lifting net earnings $23.3 million above the release.

**[Jefferies](/stocks/JEF) (JEF) reported total revenues of $3.23 billion for the quarter ended August 31, 2026, up 11.1%, and diluted EPS of $1.08, up 6.9% from $1.01, in its September 28 release (Form 8-K). The 10-Q filed October 9 then added $23.3 million to net earnings attributable to common shareholders and cut the quarter's effective tax rate to 17.9% from the release's 24.8%, with pretax earnings unchanged at $351.0 million. Net earnings rose 18.9% on pretax growth of 5.8%, and the tax line supplied the difference.**

| Field | Value |
|---|---|
| Company | Jefferies ($JEF) |
| Quarter | Q3 FY2026, period ended August 31, 2026 |
| Earnings release | September 28, 2026 (Form 8-K) |
| 10-Q filed | October 9, 2026 |
| Revenue | **$3.23 Billion** (+11.1% YoY) |
| Diluted EPS | **$1.08** per the 8-K (+6.9% YoY from $1.01); the 10-Q adds $23.3M to common earnings after the release |
| Operating margin | 10.9% (-0.5 pts YoY) |
| Operating cash flow (TTM) | $4.42 Billion |
| Effective tax rate | **17.9% (24.8% in the 8-K; 26.9% a year earlier)** |

## Jefferies Q3 2026 Revenue, Net Earnings and Margins

[Jefferies](/stocks/JEF)' Q3 2026 total revenues were $3.23 billion, up 11.1% from $2.91 billion a year earlier and the highest of the last 16 quarters. Net revenues, after interest expense, rose a slower 8.5% to $2.22 billion, and two business lines carried them.

**The Data:** Advisory revenue was a record **$817.8 million**, up 24.7%, and Equities reached **$626.2 million**, up 28.7%. Fixed income fell 25.6% to $176.0 million, and Asset Management fell 51.6% to $85.6 million from $176.9 million. Operating margin was 10.9%, the second-highest of the last 16 quarters, yet 0.5 points below the 11.4% of a year earlier.

**Why:** Investment Banking and Equities added roughly $335.6 million of net revenue; Fixed income and Asset Management gave back roughly $151.9 million. Compensation rose 10.1% to $1.19 billion, outrunning the 8.5% revenue gain, so the compensation ratio edged to 53.7% from 52.9%. Pretax earnings grew 5.8%, slower than revenue. Record lines did not widen the margin.

<center><sup>GeminIQ Financial Statements shows `Revenues` of $3,230.8 million and `Net Income Loss` of $288.3 million for the quarter ended August 31, 2026, against $2,907.7 million and $242.5 million a year earlier. The highlighted cell marks the quarter's `Net Income Loss`, the highest of the last 16 quarters.</sup></center>

## What Jefferies' Q3 2026 10-Q Shows Beyond the Press Release

The 10-Q reports net earnings attributable to common shareholders of $283.9 million, $23.3 million above the $260.6 million in the September 28 release. Pretax earnings did not move: $351.0 million in both documents. Tax did.

**The Data:** Income tax expense in the 10-Q is **$62.8 million**, against $87.0 million in the release, an effective rate of **17.9%** against 24.8% and the 26.9% of Q3 2025. The nine-month rate is 20.6%, against 23.8% a year earlier. Net earnings were $288.3 million, up 18.9%, on pretax growth of 5.8%.

**Why:** The 10-Q's "Post-Closing Adjustments" section attributes the change to excess tax benefits on share-based awards, which raised the deferred tax asset by $24.2 million and lowered tax expense by the same amount. It credits the lower rate to those benefits, investment tax credits and lower state and local taxes. Had the rate held at last year's 26.9%, tax would have been about $94.4 million and net earnings about $256.6 million, up 5.8%, the same pace as pretax earnings. Roughly $31.6 million of the quarter's profit came from the tax line. The release did label its figures preliminary, so a revision was disclosed in advance; its size, 8.9% of common earnings, was not. The release's $1.08 of diluted EPS predates the adjustment.

<center><sup>GeminIQ Visualizations plots `Income Loss From Continuing Operations Before Income Taxes Extraordinary Items Noncontrolling Interest` as bars and `Income Tax Expense Benefit` as a line for nine quarters. The highlighted callout marks the August 31, 2026 tax expense of $62.8 million against pretax earnings of $351.0 million.</sup></center>

Readers who want the method can follow [how to read a 10-Q](/blog/how-to-read-10-q).

## Jefferies Q3 2026 Operating Cash Flow, Buybacks and Share Count

[Jefferies](/stocks/JEF)' Q3 2026 operating cash flow was $2.59 billion, against $184.2 million a year earlier, the highest of the last 16 quarters and of the 69 quarters since 2009. Net earnings of $288.3 million explain about a ninth of it.

**The Data:** Operating cash flow was $1.60 billion in Q2 and **$4.42 billion** over the trailing twelve months, against negative $1.75 billion a year earlier. Capital expenditure was only $49.3 million. Dividends paid were $91.9 million. The company repurchased 1.3 million shares for $70 million in the quarter, and 8.3 million for $441.2 million this year, of which 2.0 million shares and $108.2 million were net-share tax withholding. Shares outstanding were **229.7 million**, against 206.3 million at November 30, 2025, a rise of 11%. Long-term debt rose $2.56 billion to $18.46 billion.

**Why:** For a securities firm, operating cash flow absorbs changes in trading positions and customer balances, so the rest of the $2.59 billion came from non-cash items and operating assets and liabilities, not from earnings. GeminIQ's pre-calculated trailing-twelve-month [Free Cash Flow](/metrics/calculated-values/free-cash-flow) of $4.20 billion is therefore a balance-sheet swing, not a profit figure. On the share count, buybacks did not shrink it: SMBC's preferred shares converted into 27.6 million non-voting common shares on June 30, and SMBC held 19.6% on a fully diluted basis at quarter end. Conversion also cut preferred dividends to $7.1 million from $28.6 million, which is why common earnings rose 26.7% while the release's per-share figure rose 6.9%.

<center><sup>GeminIQ Financial Statements shows `Net Cash Provided By Used In Operating Activities` of $2.59 billion for the quarter ended August 31, 2026, against $184.2 million a year earlier, beside `Payments To Acquire Property Plant And Equipment`, `Share Based Compensation` and `Payments For Repurchase Of Common Stock`. The highlighted cell marks the operating cash flow figure.</sup></center>

## How JEF Stock Has Moved After Past Earnings Reports

Across [Jefferies](/stocks/JEF)' last 12 10-Q filings, filed October 6, 2023 to July 9, 2026, the one-month return afterward had a median of +1.1%, positive 7 times. The three-month median was +15.6%, positive 9 times.

**The Data:** One-month returns ran from **-13.5%** (filed January 28, 2025) to **+17.2%** (filed April 7, 2026). Three-month returns ran from -43.5% to +24.6%. After the last three Q3 filings, one-month returns were -10.8%, +1.0% and -0.3%, and three-month returns +13.4%, +24.6% and +21.4%. The new filing's window has not elapsed. GeminIQ's 13F institutional holdings show 64.94% ownership at June 30, 2026, up 0.47 points in a year and the fourth-highest of the last 16 quarters; the September 30 quarter has not been filed yet.

**Why:** The median is small next to the spread. A one-month median of +1.1% sits inside a range 30.7 points wide, so the typical filing was followed by little, and the extremes were large. These figures describe how [Jefferies](/stocks/JEF)' stock moved after its past filings; they are a historical association, not a forecast. The [Earnings Reaction Heat Map](/features#price-variance) lays out each window, and [GeminIQ's earnings-reaction study](/blog/stock-price-reaction-after-earnings) covers the pattern more broadly.

<center><sup>The GeminIQ Earnings Reaction Heat Map shows cumulative returns 1-3 months after each 10-Q filing, by fiscal year. The highlighted column marks the one-month return after Q3 filings. The Q3 2026 cells show "-" because the windows have not elapsed.</sup></center>

Past reactions describe how the stock moved; what the next filing's tax line does is a separate fact, and a release dated before the 10-Q can only preview it.

## Frequently Asked Questions

### When does Jefferies report earnings?

[Jefferies](/stocks/JEF) released Q3 2026 results on September 28, 2026 and filed its 10-Q on October 9, 2026. Last year it filed its fourth-quarter results on January 28, 2026, and the year before on January 28, 2025. That is a filing pattern, not a forecast of the next date.

### Does Jefferies pay a dividend?

Yes. Jefferies paid $91.9 million in dividends in the quarter ended August 31, 2026 and $370.0 million over the trailing twelve months, up 2.2% from $362.2 million. Per its 8-K, the board declared $0.40 per share, payable November 25, 2026 to holders of record on November 16.

### Is Jefferies profitable?

Yes. Jefferies earned $288.3 million in the quarter and $697.6 million in the first nine months of fiscal 2026. GeminIQ's pre-calculated [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) was 7.47% over the trailing twelve months, against 6.48% a year earlier, and trailing ROIC was 7.12%, against 5.43%.

### What was Jefferies' Q3 2026 revenue?

Jefferies' Q3 2026 total revenues were $3.23 billion, up 11.1%, and net revenues after interest expense were $2.22 billion, up 8.5%. Nine-month total revenues were $9.22 billion, against $7.87 billion a year earlier.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=jefferies-earnings-q3-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Jefferies Financial Group Inc.'s
Q3 2026 10-Q (filed October 9, 2026, period ending August 31, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed September 28, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/96223/000009622326000033/jef-20260831.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/96223/000009622326000028/jfgpressrelease8312026.htm).</sup>

---

## Blog: KB Home (KBH) Q3 2026 Earnings: EPS Down 35%, Cash Flow -$135M
source: https://www.geminiq.com/blog/kb-home-earnings-q3-2026

### KB Home (KBH) Q3 2026 Earnings: EPS Down 35%, Cash Flow -$135M
KB Home reported Q3 2026 revenue of $1.30 billion (-20% YoY) and diluted EPS of $1.05 (-35%). Operating cash flow was -$135.4 million while buybacks and dividends totaled $65.2 million.

**[KB Home](/stocks/KBH) (KBH) reported Q3 2026 revenue of $1.30 billion, down 20% year over year, and diluted EPS of $1.05, down 35%, for the quarter ended August 31, 2026; the earnings release came September 22 and the 10-Q was filed October 8. The 10-Q's cash flow statement carries what the release's tables do not: operating cash flow of -$135.4 million, the second-lowest of the last 16 quarters, in a quarter that reported $65.3 million of net income. Buybacks and dividends totaled $65.2 million anyway, with $415.0 million of credit-facility borrowings outstanding.**

| Field | Value |
|---|---|
| Company | KB Home ($KBH) |
| Quarter | Q3 FY2026, period ended August 31, 2026 |
| Earnings release | September 22, 2026 (Form 8-K) |
| 10-Q filed | October 8, 2026 |
| Revenue | **$1.30 Billion** (-20.0% YoY) |
| Diluted EPS | **$1.05** (-34.8% YoY) |
| Operating margin | 5.2% (-2.9 pts YoY) |
| Operating cash flow (TTM) | $74.96 Million |
| Operating cash flow (quarter) | **-$135.4 Million** |

## KB Home Q3 2026 Revenue, EPS and Margins

[KB Home](/stocks/KBH)'s Q3 2026 diluted EPS was $1.05, down 34.8% from $1.61 a year earlier and up from $0.43 in Q2, the third-lowest of the last 16 quarters. EPS fell less than the earnings behind it, and two items outside operations did the cushioning.

A reader who saw EPS fall 35% would expect net income to have fallen about as much. Instead it fell 40.6%.

**The Data:** Revenue was **$1.30 billion**, down 20.0% and the third-lowest of the last 16 quarters, on 2,732 homes delivered (down 19%) at an average selling price of $473,000 against $475,700. Pretax income fell 43% to $81.2 million, including a $3.5 million gain on the sale of an equity investment. Net income was $65.3 million, a net margin of 5.0%. Diluted shares were **61.76 million**, down 8.8% and the lowest of the last 16 quarters, and the effective tax rate was 19.6% against 23.3% (8-K). Housing gross margin was 16.5% against 18.2%; SG&A rose to 11.3% of housing revenues from 10.0%.

**Why:** Volume, not price, drove revenue. The 10-Q attributes the margin slide to pricing pressure, higher relative land costs and reduced operating leverage, and the 8-K attributes the lower tax rate to excess tax benefits from stock-based compensation. Had the tax rate held at 23.3%, net income would have been about $62.3 million and EPS about $1.01. The smaller share count supplied roughly six points of the gap between the 40.6% net income decline and the 34.8% EPS decline. The tax cushion is a one-quarter item: the company guided its Q4 rate to about 26%.

<center><sup>GeminIQ Financial Statements shows `Revenues`, `Net Income Loss` and `Earnings Per Share Diluted` for the five quarters through Q3 2026. The highlighted `Earnings Per Share Diluted` of $1.05 is the figure the tax and share-count effects flatter; net income was $65.3M.</sup></center>

## What KB Home's Q3 2026 10-Q Adds on Operating Cash Flow

[KB Home](/stocks/KBH)'s Q3 2026 operating cash flow was -$135.4 million, against +$197.7 million a year earlier, and free cash flow (operating cash flow less $9.6 million of capital expenditure) was -$145.0 million. The release led with revenue and EPS and carries no cash flow statement; the 10-Q shows the quarter's earnings went into land.

Negative operating cash flow is ordinary for a homebuilder buying lots: this quarter was the 13th-lowest of 65 quarters since August 2010, so twelve were lower.

**The Data:** Trailing-twelve-month operating cash flow was $75.0 million, down 81.0% from $394.5 million, and GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) fell to $28.7 million from $349.8 million. Investment in land and land development was **$722.3 million**, up 40% year over year, inside a nine-month total of $1.79 billion that is down 8%. Notes payable stood at $2.11 billion against $1.69 billion at November 30, 2025, and the debt-to-capital ratio was 35.7% against 30.3% (8-K). Against that, the company repurchased $50.0 million of stock and paid $15.2 million of dividends, **$65.2 million** in all.

**Why:** Net income is income recognized on 2,732 deliveries; the cash for replacement lots left in the same quarter, and the credit facility covered the gap. The $415.0 million drawn matches the roughly $416 million rise in notes payable. The benign reading is supported: ending backlog value rose 3% to $2.05 billion, the first year-over-year increase in four years, per the company. Repurchases already fell from $188.5 million in the year-earlier quarter, yet the share count kept shrinking on the strength of earlier buybacks. Payouts equaled the quarter's net income while free cash flow was negative.

<center><sup>GeminIQ Visualizations plots `Net Cash Provided By Used In Operating Activities` for 12 quarters. The highlighted Q3 2026 outflow of -$135.4M is the second-lowest of the last 16 quarters, against +$197.7M in Q3 2025.</sup></center>

<center><sup>GeminIQ Financial Statements shows `Net Cash Provided By Used In Operating Activities`, `Payments To Acquire Property Plant And Equipment`, `Share Based Compensation` and `Payments For Repurchase Of Common Stock` for five quarters. Capital expenditure was $9.6M against the $135.4M operating outflow, so land and inventory, not capex, absorbed the cash.</sup></center>

## KB Home's 2026 Guidance After Q3

[KB Home](/stocks/KBH)'s Q3 2026 housing revenues of $1.29 billion landed inside the $1.20 billion to $1.35 billion the company guided in its prior-quarter 8-K, and so did every other metric it guided. Deliveries of 2,732 sat inside 2,600 to 2,800, the 16.5% housing gross margin inside 16.0% to 16.6%, the 19.6% tax rate inside 19% to 21%, and 277 ending communities inside 270 to 280.

**The Data:** SG&A at 11.3% of housing revenues sat at the favorable edge of its 11.3% to 11.9% range, and all six metrics landed in the favorable half of their ranges. The 8-K says full-year deliveries, housing revenues and margins remain within the ranges last provided. The housing revenue range now runs **$4.90 billion to $5.10 billion**, from $4.90 billion to $5.30 billion, and the gross margin range is 16.0% to 16.2%, from 16.1% to 16.5%, a floor below the old one. For Q4, the company guided 3,000 to 3,500 deliveries and housing revenues of $1.45 billion to $1.65 billion.

**Why:** Q4 deliveries of 3,000 to 3,500 equal 68% to 80% of the 4,398 homes in ending Q3 backlog. Q3 delivered 60% of its beginning backlog, against 71% a year earlier, a decline the 10-Q ties to the shift toward Built to Order homes, which stay in backlog until delivered. The guidance therefore asks for faster backlog conversion than Q3 delivered, and at the top end more than a year ago.

## How KBH Stock Has Moved After Past Earnings Reports

After [KB Home](/stocks/KBH)'s last 12 10-Q filings with a completed one-month window (filed October 2023 to July 2026), the median one-month return was -0.9% and the return was positive after 5 of 12. The three-month median was +2.5%, positive after 6 of 12.

**The Data:** Three-month returns ran from -23.6% to +40.9%, a wider spread than the median suggests. After the last three Q3 filings, one-month returns were -2.5%, -2.3% and +8.4%, and three-month returns were +40.9%, -17.4% and -0.1%. This filing's window has not elapsed. Institutional ownership, from [SEC Form 13F](/features#institutional-ownership) filings, was **99.69%** at June 30, 2026 (61.60 million of 61.79 million shares), up from 90.88% a year earlier and the highest of the last 16 quarters.

**Why:** A soft first month has not been a guide to the third: in two of the three past Q3 filings the one-month and three-month signs differed. The history comes from the [Earnings Reaction Heat Map](/features#price-variance), and it is a historical association over past filings, not a forecast. At 99.69%, KBH's reported holder base has little room left to grow.

<center><sup>GeminIQ's Earnings Reaction Heat Map shows KBH returns 1-3 months after each 10-Q filing. The highlighted column is the first month after past Q3 filings (-2.5%, -2.3%, +8.4%); the Q3 2026 cells show "-" because their windows have not elapsed.</sup></center>

<center><sup>GeminIQ Institutional Ownership charts SEC Form 13F holdings through June 30, 2026, the latest quarter end available. The highlighted 99.69% is the highest of the last 16 quarters.</sup></center>

Any quarter where shareholder payouts track reported earnings while free cash flow is negative is being financed by the balance sheet, and the debt line in the next 10-Q shows how long that lasts.

## Frequently Asked Questions

### When does KB Home report earnings?

[KB Home](/stocks/KBH) released Q3 2026 results on September 22, 2026 and filed its 10-Q on October 8, 2026, 16 days later. Last year the company filed its fourth-quarter results on January 23, 2026, which is a filing-record pattern, not a forecast of the next date.

### Is KB Home doing well financially?

KB Home is profitable but earning less on each dollar of sales. GeminIQ's pre-calculated [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) was 4.39% on a trailing-twelve-month basis, down from 7.92% a year earlier. Per the 8-K, the debt-to-capital ratio was 35.7% and book value per share was $62.56, up 4% year over year.

### Does KB Home pay a dividend?

Yes. KB Home paid $15.2 million of dividends in Q3 2026, or $63.5 million over the trailing twelve months, down from $70.8 million a year earlier. Trailing free cash flow of $28.7 million covered about 45% of those dividends.

### Where can I verify KB Home's Q3 2026 figures?

The figures come from the [Q3 2026 10-Q](https://www.sec.gov/ix?doc=/Archives/edgar/data/795266/000079526626000071/kbh-20260831.htm) (accession 0000795266-26-000071) and the [September 22, 2026 earnings release](https://www.sec.gov/Archives/edgar/data/795266/000079526626000068/exh991kbh-earningsrelease0.htm) (accession 0000795266-26-000068), both on SEC EDGAR.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=kb-home-earnings-q3-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference KB HOME's
Q3 2026 10-Q (filed October 8, 2026, period ending August 31, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed September 22, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/795266/000079526626000071/kbh-20260831.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/795266/000079526626000068/exh991kbh-earningsrelease0.htm).</sup>

---

## Blog: Koyfin Alternative: When SEC Data Depth Matters
source: https://www.geminiq.com/blog/koyfin-alternative-sec-data

### Koyfin Alternative: When SEC Data Depth Matters
Compare Koyfin and GeminIQ by workflow: broad market dashboards versus direct SEC filing data built for XBRL traceability and source-level verification.

Koyfin is built for breadth: equities, ETFs, mutual funds, fixed income, FX, crypto, macroeconomic data, dashboards, portfolio tools, client reports, screeners, analyst data, filings, transcripts, and alerts. Koyfin says its global equity fundamentals, consensus estimates, and valuation data are sourced from S&P Capital IQ. It also says it buys data from more than a dozen vendors, with fund data from Morningstar and economic data from sources including FRED and Trading Economics.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=koyfin-alternative-sec-data)**

For the right user, that breadth is useful. If your workflow is market monitoring, multi-asset dashboarding, advisor reporting, ETF research, macro review, or portfolio presentation, Koyfin's breadth is the product.

But breadth has a tradeoff.

When the goal is not "show me everything," but "show me exactly what the company reported," the data source matters more than the dashboard. A broad market platform has to standardize many securities, asset classes, and data types into a usable interface. That standardization can be efficient, but it also pushes the analyst one step away from the filing.

GeminIQ is narrower by design. It focuses on US public company fundamentals and pulls 10-K and 10-Q data directly from SEC EDGAR. The goal is not to replace every market dashboard. The goal is to preserve the source detail investors need to verify the analysis.

That is the real comparison: Koyfin is broad market coverage. GeminIQ is filing-level depth.

## Not a Better-or-Worse Question

Koyfin is better if you want one platform for market dashboards, portfolio monitoring, ETF and mutual fund research, analyst estimates, macro data, transcripts, and client-facing reports. Those are real workflows. GeminIQ does not try to be that product.

GeminIQ is better if your edge comes from fundamental analysis built on traceable SEC data: raw GAAP line items, filing-level structure, historical 10-K and 10-Q data, and metrics you can audit back to the source.

The question is not which product has more features. The question is where your workflow breaks if the underlying financial data has been normalized before you see it.

If you are scanning the whole market, normalization may be acceptable. If you are building a model, auditing a balance sheet, calculating [invested capital](/metrics/calculated-values/invested-capital), or checking whether a platform's number matches the 10-K, normalization has tradeoffs.

## Koyfin's Strength Is Breadth

Koyfin is a mile wide by design.

Its official site positions the platform around market research, portfolio analysis, and client-ready reports. Its data coverage includes stocks, ETFs, mutual funds, government yields, indices, currencies, commodities, global economics, transcripts, cryptocurrencies, and news.

That is a compelling package for a macro-aware generalist investor or advisor. You can move from a yield curve to an ETF holding list to a watchlist to a portfolio report without changing systems.

But that same breadth creates a different data question. A platform covering that many asset types needs organized, standardized data. Standardized data is easier to compare, easier to chart, and easier to screen. It is also not the same thing as preserving a company's original SEC filing structure.

The number may help with broad comparison but lose filing-level context.

That is where GeminIQ draws a hard line.

## The Capital IQ Flag Matters

Koyfin discloses that its global equity fundamentals, consensus estimates, and valuation data are sourced from S&P Capital IQ. For most users, that is a positive. Capital IQ is a major institutional data provider, and normalized data can be useful for broad comparison, screening, and market monitoring.

But for precision-focused fundamental analysts, the question is different: what normalization decisions were made upstream?

When financial data flows through a third-party data provider, the provider has to map each company's filing into a standardized framework. Company-specific labels may be organized into broader categories. Distinct line items may be made more comparable. Historical values may be structured for consistency across companies.

That does not mean the data is bad. It means the data has been processed.

For many workflows, processed data is useful. For filing-level verification, it can be limiting.

Once the data has passed through an aggregator, the analyst has to ask:

- Did the platform preserve the filing's line item?
- Did it preserve the [XBRL tag](/features#financial-statements)?
- Did it merge economically different items into a cleaner category?
- Did it keep the same label after changing the number?
- Can I trace the displayed value back to the exact SEC filing data point?

On a broad market platform, the answer may not be visible. On GeminIQ, the product is built around making the answer visible.

GeminIQ removes that middle layer. It ingests filings directly from SEC EDGAR, preserves the company's reported structure, and keeps source-level detail available through [Financial Statements](/features#financial-statements). Every number is meant to remain traceable to the filing instead of being reduced to a black-box summary.

This is the difference between a platform that answers "what is the standardized number?" and a platform that answers "what did the company actually report?"

## The Risk Is Not That Koyfin Is Wrong

The risk is not that Koyfin is wrong.

The risk is that a broad market platform is optimized for a different job.

Koyfin is designed to help users research markets, analyze portfolios, build dashboards, and create reports across many asset classes. That requires breadth, speed, and standardization. GeminIQ is designed for fundamental analysts who want to work from the source filing data itself.

Those are different products.

A Koyfin user might reasonably care more about market context, asset allocation, macro data, ETF exposure, estimates, and presentation tools. A GeminIQ user cares more about whether a balance sheet line item can be tied back to the SEC filing.

The distinction matters because normalized data can be useful for quick scans and still be insufficient for source-level analysis.

If your workflow starts with a broad screen, Koyfin may be enough.

If your workflow starts with "show me the exact number the company filed," GeminIQ is built for that.

## Pricing Is Also a Data-Depth Question

Koyfin's pricing reinforces the breadth model.

As of May 25, 2026, Koyfin's official annual-billing pricing page lists Free at $0/month, Plus at $39/month, Premium at $79/month, Advisor Core at $209/month, and Advisor Pro at $299/month. The same plan comparison shows the Free tier with 2Y & 12Q of statement history and paid tiers with 10Y & 40Q.

That is not unusual. Broad platforms commonly gate historical depth, dashboards, formulas, portfolio tools, and reporting functionality by tier.

GeminIQ's counter-position is different: historical filing depth is core to the product. GeminIQ is built around 17+ years of quarterly and annual SEC filing history, with [Financial Statements](/features#financial-statements), [Calculated Metrics](/features#calculated-metrics), [Visualizations](/features#visualizations), and [Stock Screeners](/features#screener) derived from filing-level data. GeminIQ also starts at $0/month: the Free plan carries 3 years of history and 24 calculated metrics on the same as-filed pipeline as the paid product, with the full 17-plus-year archive, 90-plus metrics, and Stock Screener on the paid Annual ($29/month billed annually) or Monthly ($39/month) plan.

That matters because fundamental analysis is historical by nature.

One year tells you what just happened. Three years show a trend. Ten years show a cycle. Seventeen years show how the company behaved across different market regimes, capital allocation periods, margin structures, and balance sheet conditions.

A fundamental analyst does not only need more data. They need the original data.

## Who Koyfin Is Actually For

Koyfin is built for the investor who wants context across markets.

That user wants to know what the S&P 500 is doing, how rates are moving, what ETFs own a stock, how estimates changed, what the macro dashboard says, what analysts expect, and how a portfolio looks across asset classes.

That is a legitimate workflow.

The Koyfin user is often a generalist, advisor, portfolio monitor, or macro-aware investor who wants a fast, polished, broad interface. They are not necessarily trying to reconcile a line item to an individual 10-K or 10-Q.

GeminIQ is built for a different user.

The GeminIQ user wants to know whether the balance sheet line matches the filing. They want raw GAAP line items, not just standardized categories. They want [Calculated Metrics](/features#calculated-metrics) whose inputs can be checked. They want [Custom Tables](/features#custom-tables) built from specific reported items. They want [Visualizations](/features#visualizations) that chart the company's own reported structure over time. They want [Stock Screeners](/features#screener) backed by data they can verify.

That user is not asking for every asset class. They are asking for trust in the fundamentals.

## Why Filing-Level Data Changes the Workflow

The biggest difference between Koyfin and GeminIQ is not the interface. It is the audit trail.

When data is normalized, you can often compare companies faster. But when something looks wrong, you need to know where the number came from. Without source-level traceability, you are stuck reverse-engineering the platform's data pipeline.

GeminIQ starts from the opposite premise: preserve the filing first, then build the analysis layer on top.

That enables a different kind of workflow.
- Compare a reported line item to the SEC filing instead of trusting a standardized label.
- Build [Custom Tables](/features#custom-tables) using company-specific line items that might disappear in a normalized template.
- Use [Visualizations](/features#visualizations) to spot inflections in margins, working capital, debt structure, or cash flow using the company's own historical filings.
- Use [Calculated Metrics](/features#calculated-metrics) knowing the inputs come from source filing data.
- Use [Stock Screeners](/features#screener) to find companies, then drill into the source data rather than stopping at a platform summary.
- Use [Custom Watchlists](/features#custom-watchlists) to monitor companies where filing quality matters.
- Layer [Insider Transactions](/features#insider-transactions), [Institutional Ownership](/features#institutional-ownership), and [Price Variance / Earnings Reaction Heatmaps](/features#price-variance) on top of verified fundamentals.

This is not a broader workflow than Koyfin. It is a deeper one.

## The Best Koyfin Alternative Depends on the Job

If you want macro dashboards, ETF data, mutual fund data, analyst estimates, model portfolios, transcripts, advisor reports, and broad market monitoring, Koyfin is probably the more natural fit.

If your work starts with the SEC filing, GeminIQ is the better fit.

That is the honest comparison.

Koyfin helps you see more markets in one place. GeminIQ helps you trust the fundamental data underneath one company.

Koyfin is built for breadth. GeminIQ is built for source-level verification.

Koyfin uses licensed third-party data providers. GeminIQ pulls directly from SEC filings.

Koyfin is useful when speed and coverage matter. GeminIQ matters when precision and traceability matter.

The choice is not about which platform has the longer feature list. It is about which failure mode you are willing to accept.

For a broad market workflow, the failure mode is missing context outside the company. Koyfin solves that.

For a fundamental workflow, the failure mode is building analysis on a number you cannot trace back to the filing. GeminIQ solves that.

## Bottom Line

Koyfin is a strong broad market platform. That is its strength and its limitation.

Its value comes from pulling many market views into one place: charts, dashboards, estimates, portfolios, asset classes, and reports. For investors who want breadth, that is exactly the point.

But if your edge is in the fundamentals, breadth is not enough. You need to know what the company actually filed. You need to know whether the number on your screen can be traced back to the SEC filing. You need to know whether the metric you are using comes from source data or from a processed summary.

Normalization has tradeoffs. The number may help with broad comparison but lose filing-level context.

GeminIQ preserves the source detail investors need to verify the analysis.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=koyfin-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Largest Goodwill Impairment Charges in SEC Filings
source: https://www.geminiq.com/blog/largest-goodwill-impairment-charges-filings

### Largest Goodwill Impairment Charges in SEC Filings
The largest goodwill impairment charges in SEC filings history are directly traceable to the Goodwill Impairment Loss tag each company disclosed in its own 10-K, led by General Motors' $27.145 Billion write-down in 2012 and General Electric's $22.136 Billion write-down in 2018.

**[General Motors](/stocks/GM)** wrote down **$27.145 Billion** of goodwill in its fiscal 2012 10-K — the single largest goodwill impairment charge on record in GeminIQ's as-filed universe. It's a figure large enough that it is worth asking what it takes to make that list at all. A goodwill write-down is one of the few line items on a filing where a company is conceding, in its own regulatory disclosure, that money it already spent will not come back. Most goodwill impairments are small enough to pass without notice. The ones on this list were not.

<center><sup>GeminIQ Financial Statements for General Motors (GM): Goodwill falling from $29.019 Billion (FY2011) to $1.973 Billion (FY2012) alongside a $27.145 Billion Goodwill Impairment Loss — the largest confirmed goodwill impairment charge in GeminIQ's as-filed data.</sup></center>

This leaderboard reads GeminIQ's full as-filed financial-statement universe for every disclosed value under the **Goodwill Impairment Loss** and **Goodwill And Intangible Asset Impairment** tags, restricted to annual (10-K, full fiscal-year) figures, across **15,083** companies and GeminIQ's complete available filing history. **2,182** companies carry at least one confirmed goodwill impairment charge on record, spanning **4,084** distinct fiscal-year events. This ranks each company by its single largest confirmed annual write-down — it does not measure stock-price reaction, only the disclosed dollar figure itself.

## The Ranking

| Rank | Company | Ticker | Fiscal Year | Goodwill Impairment Charge |
|---|---|---|---|---|
| 1 | General Motors Co | GM | 2012 | **$27.145 Billion** |
| 2 | General Electric Co | GE | 2018 | **$22.136 Billion** |
| 3 | HP Inc | HPQ | 2012 | **$18.035 Billion** |
| 4 | Teva Pharmaceutical Industries Ltd | TEVA | 2017 | **$17.100 Billion** |
| 5 | Baker Hughes Co | BKR | 2020 | **$14.773 Billion** |
| 6 | Teladoc Health, Inc. | TDOC | 2022 | **$13.403 Billion** |
| 7 | Walgreens Boots Alliance, Inc. | WBA | 2024 | **$12.701 Billion** |
| 8 | Bank of America Corp | BAC | 2010 | **$12.400 Billion** |
| 9 | Lumen Technologies, Inc. | LUMN | 2023 | **$10.693 Billion** |
| 10 | Berkshire Hathaway Inc | BRK-A | 2020 | **$10.671 Billion** |
| 11 | Comcast Corp | CMCSA | 2022 | **$8.583 Billion** |
| 12 | Kraft Heinz Co | KHC | 2018 | **$7.008 Billion** |
| 13 | DXC Technology Co | DXC | 2020 | **$6.794 Billion** |
| 14 | Microsoft Corp | MSFT | 2012 | **$6.193 Billion** |
| 15 | CVS Health Corp | CVS | 2018 | **$6.149 Billion** |

## The Concentration

Most companies that impair goodwill do it quietly. Across the full 2,182-company universe carrying a confirmed impairment on record, the median company's single largest write-down is **$37.1 Million** — a rounding error against the fifteen names above. Those fifteen alone account for **$193.8 Billion** of the $718.2 Billion in combined single-largest write-downs across the entire confirmed universe, or **27.0%** of it. A handful of household names, almost all built on a single oversized acquisition, carry a quarter of all the goodwill destruction on record. The rest of the universe writes down small, forgettable amounts tied to smaller deals that simply didn't work out; the mega-write-downs are a different phenomenon entirely, and they cluster around a small, recognizable list of specific transactions.

<center><sup>GeminIQ Custom Tables charting Goodwill Impairment Loss from 10-K filings for the five largest confirmed charges in this leaderboard — GM, GE, HPQ, TEVA, and BKR ($ millions). HP Inc reported its charge under the combined Goodwill And Intangible Asset Impairment tag, so it has no line on this chart.</sup></center>

## General Motors: $27.145 Billion, Fiscal 2012

**[General Motors](/stocks/GM)** carries the single largest confirmed goodwill impairment charge in GeminIQ's data: $27.145 Billion, disclosed in the fiscal 2012 10-K under the `Goodwill Impairment Loss` tag. GM's own balance sheet shows the mechanism directly: `Goodwill` stood at **$29.019 Billion** at the end of fiscal 2011 and fell to **$1.973 Billion** by the end of fiscal 2012. That's a single-year collapse that wiped out roughly **93%** of the balance. That drop confirms the impairment charge as the driver, not a divestiture or reclassification.

## General Electric: $22.136 Billion, Fiscal 2018

**[General Electric](/stocks/GE)** disclosed a **$22.136 Billion** `Goodwill Impairment Loss` in its fiscal 2018 10-K, the second-largest confirmed charge in the data. The prior year's 10-K had already flagged a smaller **$2.550 Billion** impairment for fiscal 2017 under the same tag. GE's goodwill trouble was visible in the filings a full year before the far larger 2018 charge landed — not a single unexpected event.

## HP Inc: $18.035 Billion, Fiscal 2012

**[HP Inc](/stocks/HPQ)** reported an **$18.035 Billion** charge under the `Goodwill And Intangible Asset Impairment` tag for the fiscal year ended October 31, 2012 — one of the earliest and largest confirmed write-downs in the dataset. It is also disclosed under a combined goodwill-and-intangibles tag, rather than the goodwill-only tag most other companies on this list used. Because the tag bundles goodwill with other intangible assets, the confirmed figure is the combined impairment charge as HP itself reported it, not an isolated goodwill number.

## Teva Pharmaceutical: $17.100 Billion, Fiscal 2017

**[Teva Pharmaceutical Industries](/stocks/TEVA)** disclosed a **$17.100 Billion** `Goodwill Impairment Loss` for fiscal 2017, the fourth-largest confirmed charge on record and the only name in the top five headquartered outside the United States. It is also the only healthcare name in the top five, in a list otherwise dominated by industrial, technology, and financial companies.

## Baker Hughes: $14.773 Billion, Fiscal 2020

**[Baker Hughes](/stocks/BKR)** recorded a **$14.773 Billion** `Goodwill Impairment Loss` for fiscal 2020, rounding out the top five and standing as the largest confirmed charge among oilfield-services companies in the dataset. The prior fiscal year's 10-K shows no comparable charge under the same tag, meaning the full write-down landed within a single fiscal year rather than building gradually across several.

## The Method

GeminIQ reads every figure in this leaderboard directly from each company's own as-filed 10-K, under the `Goodwill Impairment Loss` or `Goodwill And Intangible Asset Impairment` XBRL tag. No figure is inferred from a change in the balance-sheet `Goodwill` line itself, since a balance decline can also come from a divestiture, a spinoff, or a foreign-currency translation adjustment rather than a genuine impairment charge. Each company's ranking reflects its single largest confirmed annual charge; a company that impaired goodwill in more than one fiscal year is ranked by its biggest year only.

## Check Your Holdings

Pull up any position's `Goodwill` balance by quarter on GeminIQ's [Financial Statements](/features#financial-statements) view and watch for a `Goodwill Impairment Loss` or `Goodwill And Intangible Asset Impairment` line appearing in the same period the balance drops. A falling goodwill balance with no matching impairment charge nearby is a divestiture or reclassification, not a write-down — checking both lines together, rather than trusting the balance-sheet delta alone, is the difference between a real finding and an artifact.

## Frequently Asked Questions

### How many companies in GeminIQ's data have disclosed a goodwill impairment?

**2,182** companies carry at least one confirmed goodwill impairment charge under a core goodwill-impairment tag across GeminIQ's full available filing history, spanning **4,084** distinct fiscal-year events in total.

### Does a falling goodwill balance always mean a company took an impairment?

No. Two of the largest goodwill-balance declines found while building this leaderboard — at companies with declines in the tens of billions of dollars — carried no matching value under any core goodwill-impairment tag for that fiscal year. Both were excluded from the ranking rather than credited with an unconfirmed impairment.

### What's the difference between "Goodwill Impairment Loss" and "Goodwill And Intangible Asset Impairment"?

`Goodwill Impairment Loss` is a goodwill-only figure. `Goodwill And Intangible Asset Impairment` is a combined tag some companies use to report a goodwill write-down together with impairments of other intangible assets in a single line. HP Inc's **$18.035 Billion** figure in this ranking is reported under the combined tag, as HP itself chose to disclose it.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=largest-goodwill-impairment-charges-filings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Impairment charges were identified and cross-checked directly against each company's own disclosed XBRL tag values, not inferred from balance-sheet changes; the ranking methodology is described above.

---

## Blog: Liquidity Ratios and Working Capital: Formulas Explained
source: https://www.geminiq.com/blog/liquidity-ratios-working-capital-explained

### Liquidity Ratios and Working Capital: Formulas Explained
Liquidity ratios measure whether a company can cover its short-term obligations, using progressively stricter definitions of what counts as available. This guide covers the current, quick, and cash ratios, the difference between working capital and net working capital, and why working capital to revenue carries more signal than any of the threshold ratios.

Every liquidity ratio arrives attached to the same rule: above **1.0** is healthy, below **1.0** is a warning. The rule is easy to teach, easy to screen on, and wrong often enough to be dangerous. Warehouse clubs, grocery chains, and large e-commerce retailers routinely operate below every one of these thresholds — not because they are fragile, but because they collect cash from customers before they owe it to suppliers, which is one of the most durable competitive advantages a business model can have. The ratio prints as a red flag. The economics underneath it are the opposite.

| | |
|---|---|
| **Current Ratio** | Current Assets ÷ Current Liabilities |
| **Quick Ratio** | (Current Assets − Inventory − Prepaid Expenses) ÷ Current Liabilities |
| **Cash Ratio** | Cash and Cash Equivalents ÷ Current Liabilities |
| **Working Capital** | Current Assets − Current Liabilities (a dollar amount, not a ratio) |
| **Net Working Capital** | (Current Assets − Cash) − (Current Liabilities − Short-Term Debt) |
| **Working Capital to Revenue** | Working Capital ÷ Revenue (TTM) |
| **Conventional threshold** | **1.0** on all three ratios — meaningful only against sector and trend |

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=liquidity-ratios-working-capital-explained)**

---

## Table of Contents

- [What Are Liquidity Ratios?](#what-are-liquidity-ratios)
- [What Is the Current Ratio?](#what-is-the-current-ratio)
- [What Is the Quick Ratio?](#what-is-the-quick-ratio)
- [What Is the Cash Ratio?](#what-is-the-cash-ratio)
- [Working Capital Is Not a Ratio](#working-capital-is-not-a-ratio)
- [What Is Net Working Capital?](#what-is-net-working-capital)
- [Working Capital to Revenue: The Ratio That Carries the Signal](#working-capital-to-revenue-the-ratio-that-carries-the-signal)
- [Why Negative Working Capital Can Signal Strength](#why-negative-working-capital-can-signal-strength)
- [When Liquidity Ratios Break](#when-liquidity-ratios-break)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Are Liquidity Ratios?

Liquidity ratios ask one question at three levels of strictness: can this company cover what it owes in the next twelve months with what it can convert to cash in the same window.

The three standard ratios share a denominator — current liabilities — and differ only in how generous they are about the numerator. The [Current Ratio](/metrics/liquidity-ratios/current-ratio) counts every current asset. The [Quick Ratio](/metrics/liquidity-ratios/quick-ratio) removes the assets that take time to convert. The [Cash Ratio](/metrics/liquidity-ratios/cash-ratio) counts only cash itself. Read together, the three of them describe not just whether a company can pay its bills but what it would have to sell to do it.

That progression is the useful part. A company whose three ratios cluster tightly holds current assets that are mostly liquid already. A company where the current ratio is comfortable and the quick ratio collapses is carrying its liquidity in inventory — and inventory stays liquid only until the moment everyone needs it to be.

---

## What Is the Current Ratio?

**Current Ratio = Current Assets ÷ Current Liabilities**

The current ratio is the broadest of the three and the most widely quoted. It answers a simple question: for every dollar owed in the next twelve months, how many dollars of short-term assets stand behind it. A ratio of **1.5** means a dollar fifty of current assets against every dollar of near-term obligation.

Above **1.0** is conventionally read as adequate short-term liquidity and below **1.0** as a liquidity risk. That reading holds for a manufacturer and fails for a grocer, because the ratio measures the stock of current assets and says nothing about the speed at which they turn. A retailer collecting cash at the register and paying suppliers on thirty-day terms can run below **1.0** indefinitely without ever being short of money.

**When it breaks:** The current ratio treats every current asset as equally available, which is the assumption that fails hardest under stress. Inventory may take months to move and receivables may never collect. It works as a screening starting point and as a trend line against a company's own history. It works poorly as a cross-sector comparison — a **1.5** that is strong for a retailer can be thin for a manufacturer carrying heavy inventory.

---

## What Is the Quick Ratio?

**Quick Ratio = (Current Assets − Inventory − Prepaid Expenses) ÷ Current Liabilities**

The quick ratio, also called the acid-test ratio, strips the numerator down to assets convertible to cash within roughly ninety days. Inventory comes out because a warehouse of raw materials cannot be liquidated on demand at anything close to carrying value. Prepaid expenses come out because a prepaid insurance policy cannot be converted to cash at all.

What remains is cash, cash equivalents, and receivables — the assets a company could actually deploy against a sudden obligation. A quick ratio above **1.0** means short-term liabilities are covered without selling a single unit of inventory.

The gap between the current ratio and the quick ratio is where this metric earns its place. In stable conditions the two tell similar stories. Under stress they diverge sharply, because inventory values fall exactly when a company most needs to convert them and receivables become hardest to collect exactly when customers are struggling too. The quick ratio is a stress-condition metric that happens to be reported in calm ones.

**When it breaks:** A quick ratio well below **1.0** is not automatically a warning. Businesses that turn inventory rapidly — grocery, quick-service restaurants, high-velocity retail — convert stock to cash faster than the ratio's ninety-day assumption models, and they operate comfortably at levels that would signal distress in a slower-moving business.

---

## What Is the Cash Ratio?

**Cash Ratio = Cash and Cash Equivalents ÷ Current Liabilities**

The cash ratio is the strictest liquidity test available. No receivables, no inventory, no other current assets — only cash on hand against everything owed within the year.

A cash ratio at or above **1.0** is uncommon outside technology companies and financial institutions, and for most businesses it would signal poor capital allocation rather than strength. Cash sufficient to cover every current liability is cash not invested in the business, not used to retire debt, and not returned to shareholders. The metric is not a target to maximize.

Where it earns its keep is stress testing and distress analysis. For a company already under financial pressure, the ability to meet obligations from cash on hand is the only liquidity measure that matters, because the receivables and inventory the other two ratios count on are precisely what stops being reliable.

---

## Working Capital Is Not a Ratio

**Working Capital = Current Assets − Current Liabilities**

[Working Capital](/metrics/liquidity-ratios/working-capital) is a subtraction, not a division, which makes it a dollar figure rather than a ratio. That distinction matters more than it sounds. A ratio is comparable across companies of different sizes on its face. A dollar amount is not — working capital of **$2 Billion** describes a completely different situation at a company with **$4 Billion** in revenue than at one with **$400 Billion**.

Working capital is most useful two ways: as a trend against a company's own history, and as a proportion of revenue. Declining quarter after quarter, it may indicate a business burning through liquidity. Growing steadily, it may indicate improving health — or inventory accumulating faster than it sells, which looks identical in the raw number and means the opposite.

---

## What Is Net Working Capital?

**Net Working Capital = (Current Assets − Cash) − (Current Liabilities − Short-Term Debt)**

[Net Working Capital](/metrics/liquidity-ratios/net-working-capital), sometimes called operating working capital, removes the items that are financing decisions rather than operating requirements. Cash comes out of current assets because a cash balance is a treasury choice, not something the operating cycle demands. Short-term debt comes out of current liabilities because borrowing is a financing obligation, unlike a trade payable that arises directly from running the business.

What survives is the capital tied up in the operating cycle: receivables, inventory, and prepaid assets on one side, trade payables and accrued expenses on the other. That is the figure that tells you how much money the business has locked inside its own operations at any moment.

The trend in net working capital relative to revenue is a leading indicator the income statement will not show for several quarters. Rising means more capital locked up — receivables collecting more slowly, inventory building faster than it moves, or supplier leverage eroding. Falling means either improving efficiency or a company stretching payables to conserve cash, and those two require the payables trend to tell apart.

---

## Working Capital to Revenue: The Ratio That Carries the Signal

**Working Capital to Revenue = Working Capital ÷ Revenue (TTM)**

[Working Capital to Revenue](/metrics/efficiency-and-turnover-ratios/working-capital-to-revenue) converts the dollar figure into something comparable, expressing working capital as a share of trailing twelve-month sales. It answers the question the threshold ratios cannot: how much capital does this business model require per dollar of sales.

A lower figure means the model runs on less locked-up capital, which translates directly into cash generation. A business needing five cents of working capital per revenue dollar can grow sales substantially without a proportional funding requirement. One needing twenty-five cents has to finance every dollar of growth, from operating cash flow or from borrowing, before that growth reaches shareholders.

This is where the liquidity ratios and the returns framework connect. Working capital forms part of the capital base that [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) measures returns against, and a business systematically reducing its working capital intensity raises its ROIC without changing a single thing about its margins. The threshold ratios describe whether a company can survive the next twelve months. This one describes how much capital its growth will consume.

---

## Why Negative Working Capital Can Signal Strength

Working capital below zero means current liabilities exceed current assets, and every conventional reading treats that as a warning. For a large group of profitable businesses, it is the opposite.

The mechanism is timing. A retailer that collects cash at the point of sale and pays suppliers on thirty- or sixty-day terms holds customer money for weeks before the corresponding payable comes due. The unpaid supplier balance sits in current liabilities. The cash it represents has already been spent or deployed. The result is a structurally negative working capital position reflecting genuine bargaining power — the company funds its operations with its suppliers' capital, interest-free, at scale.

But standard financial media doesn't read the footnotes, and a screener sorting for liquidity does not distinguish that business from one whose negative working capital comes from an inability to pay. The two look identical in the ratio and are separated entirely by what produced them. Negative working capital alongside strong operating cash flow and stable payables terms is a structural advantage. Negative working capital alongside deteriorating cash flow and lengthening payables is a company running out of room.

The [Cash Conversion Cycle](/blog/cash-conversion-cycle-formula-explained) separates them, because it measures the timing directly rather than inferring it from a balance sheet snapshot.

---

## When Liquidity Ratios Break

Three conditions distort every ratio in this post at once.

A single reporting date is not a year. Every liquidity ratio is computed from balance sheet figures captured on one day, and seasonal businesses look dramatically different depending on which day. A retailer reporting just after the holiday season shows collected cash and depleted inventory. The same retailer three months earlier shows the reverse. Neither snapshot describes the business, and comparing two companies with different fiscal calendars compares two different points in two different cycles.

Undrawn credit facilities are invisible. A company with a **$3 Billion** revolver it has not touched holds liquidity that appears nowhere in current assets, and its ratios understate its actual flexibility. The facility is disclosed in the filing footnotes rather than on the balance sheet face, which means a ratio computed from statement data alone cannot see it.

Classification shifts the numbers without changing anything. Whether an item lands in current or non-current is a reporting judgment, and a reclassification between periods moves both the numerator and the denominator without any underlying economic change. Pulling the components from GeminIQ's [Financial Statements](/features#financial-statements) view with the XBRL tags attached makes the shift visible — a ratio that moved because a line item was reclassified looks the same as one that moved because the business changed, until the underlying tags are compared.

---

## Frequently Asked Questions

### What is a good current ratio?

Conventionally above **1.0**, with **1.5** to **3.0** often cited as comfortable. Sector matters more than the threshold: retail and grocery businesses routinely operate below **1.0** because they collect from customers before paying suppliers, while a manufacturer at the same level would be carrying real risk. A company's own trend is more informative than any absolute number.

### What is the difference between the current ratio and the quick ratio?

The numerator. The current ratio counts all current assets; the quick ratio removes inventory and prepaid expenses, leaving cash, equivalents, and receivables. The quick ratio is the more conservative test, and the gap between the two shows how much of a company's short-term liquidity depends on selling inventory.

### Is negative working capital bad?

Not necessarily, and often the reverse. Businesses that collect cash before paying suppliers — warehouse clubs, grocery chains, high-velocity retail — run structurally negative working capital as a consequence of bargaining power. The distinguishing test is operating cash flow: negative working capital with strong cash generation is a business model advantage, while the same figure with deteriorating cash flow is a liquidity problem.

### What is the difference between working capital and net working capital?

Working capital is current assets minus current liabilities. Net working capital removes cash from the asset side and short-term debt from the liability side, isolating the capital tied up in operations rather than in treasury and financing decisions. Net working capital is the better measure of what the operating cycle actually requires.

### What is a good working capital to revenue ratio?

Lower is generally better, since it means less capital locked up per dollar of sales, but the level is set by the business model rather than by management skill. Software companies operate near zero or negative; distributors and manufacturers carrying inventory and extending trade credit require substantially more. Compare against sector peers and against the company's own trend rather than to a universal target.

### What are the main liquidity ratios?

The three core liquidity ratios are the current ratio (current assets ÷ current liabilities), the quick or acid-test ratio (which excludes inventory), and the cash ratio (cash and marketable securities ÷ current liabilities). Many analysts add the operating cash flow ratio, which divides cash from operations by current liabilities, and net working capital, a dollar figure rather than a ratio.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=liquidity-ratios-working-capital-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Lululemon Stock Analysis (2026): The Margin Compression Story
source: https://www.geminiq.com/blog/lululemon-stock-analysis-2026

### Lululemon Stock Analysis (2026): The Margin Compression Story
Lululemon's revenue is still growing, but the trailing twelve-month operating margin has fallen from 22.0% to 18.3% over the past two years, and Return on Invested Capital has dropped from 60.9% to 42.9% over the same period. Here's the full Q1 FY2026 10-Q breakdown.

**[lululemon](/stocks/LULU) ($LULU) just filed its Q1 FY2026 10-Q (filed June 4, 2026). Revenue is still growing, and on a headline basis that alone might suggest a business in good health. The trailing twelve-month numbers underneath tell a more complicated story: operating margin has fallen from 22.0% to 18.3% over the past two years, and Return on Invested Capital has dropped from 60.9% to 42.9% over the same period. Both peaked in between — operating margin at 23.7% and ROIC at 74.6% in the quarter ended January 2025 — which makes the decline from the peak steeper still. Growth alone doesn't tell you whether a business is becoming more or less efficient at converting that growth into profit — and here, it's become meaningfully less efficient.**

| Field                  | Value          |
| ---------------------- | -------------- |
| Ticker                 | $LULU          |
| Filing                 | Q1 FY2026 10-Q |
| Filed                  | June 4, 2026   |
| Period End             | May 3, 2026    |
| Operating Margin (TTM) | **18.3%**      |
| ROIC (TTM)             | **42.9%**      |

## The Margin Compression

This is the core of the story, and it's a sustained, multi-quarter trend rather than a single soft quarter.

**The Data:** [lululemon's](/stocks/LULU) TTM [Gross Margin](/metrics/margin-metrics/gross-profit-margin) has fallen from **58.3%** two years ago to **55.7%** as of this filing, after peaking at **59.3%** in the quarter ended April 2025. TTM Operating Margin has fallen from **22.0%** to **18.3%** over the same two years, off a **23.7%** peak in the quarter ended January 2025. TTM Net Income is **$1.46 Billion** on TTM Revenue of **$11.20 Billion**.

**The GeminIQ Edge:** Pulling [Calculated Metrics](/features#calculated-metrics) as a full multi-quarter trend, rather than comparing only the most recent quarter to a year-ago quarter, shows this compression has been gradual and consistent rather than a single cost shock. A steady, multi-period decline is a materially different signal than a one-quarter miss.

<center><sup>GeminIQ Calculated Metrics showing lululemon's TTM Gross Margin falling from 58.3% to 55.7%, and TTM Operating Margin falling from 22.0% to 18.3%, over the trailing two years.</sup></center>

## The ROIC Decline

Margin compression alone doesn't tell the full capital-efficiency story. [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) connects the profit side to the balance sheet.

**The Data:** [lululemon's](/stocks/LULU) TTM Return on Invested Capital has fallen from **60.9%** two years ago to **42.9%** as of this filing — still a strong figure in absolute terms, but a substantial decline, and steeper measured off the **74.6%** peak in the quarter ended January 2025. TTM Free Cash Flow is **$1.28 Billion**, on TTM Operating Cash Flow of **$1.94 Billion** against TTM CapEx of **$656 Million**.

**The GeminIQ Edge:** Pulling ROIC alongside the margin trend above, rather than in isolation, shows the two moving together: as margins compressed, the returns generated on invested capital compressed with them. CapEx has also grown as a share of operating cash flow, consistent with continued store investment amid slower same-store growth.

<center><sup>GeminIQ Calculated Metrics showing lululemon's TTM ROIC falling from 60.9% to 42.9% over the trailing two years, peaking at 74.6% in between, alongside TTM Free Cash Flow of $1.28 Billion.</sup></center>

## Growth Is Slowing, Not Stopping

[lululemon's](/stocks/LULU) headline revenue figure is still positive, and it's worth being precise about what's actually decelerating.

**The Data:** Annual revenue grew from **$4.40 Billion** in FY2020 to **$11.10 Billion** in FY2025 (fiscal year ended February 1, 2026) — a multi-year growth story that remains genuinely large in absolute terms. But the pace has slowed considerably: FY2025 revenue grew roughly **4.9%** over FY2024's **$10.59 Billion**, a fraction of the growth rates in earlier years of this trend.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) revenue data across the full multi-year history, rather than a single year-over-year comparison, makes the deceleration curve visible directly rather than needing to trust a summarized growth-rate headline.

<center><sup>GeminIQ Financial Statements showing lululemon's annual revenue growing from $4.40 Billion (FY2020) to $11.10 Billion (FY2025), with the year-over-year growth rate decelerating in the most recent year.</sup></center>

## Smart Money and the Insider Record

Two different signals around [lululemon](/stocks/LULU) worth checking on their own terms, alongside a valuation figure worth noting plainly.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has fallen from **79.9%** in March 2025 to **71.4%** as of the most recent 13F (March 2026, filed with the standard lag) — a meaningful decline, not a rounding difference. [Insider Transactions](/features#insider-transactions) show a heavily sale-weighted record: 248 sales against 14 purchases in the available history. The stock currently trades at approximately **10.9x** trailing earnings.

**The GeminIQ Edge:** An institutional ownership decline of this size, alongside a P/E multiple this low for a business still growing revenue, both point in the same direction: the market has already priced in a considerable amount of the margin and growth concerns described above, rather than waiting for further confirmation.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership falling from 79.9% (March 2025) to 71.4% (March 2026, most recent 13F).</sup></center>

## Frequently Asked Questions

### Why has lululemon's operating margin declined?

TTM Operating Margin has fallen from 22.0% to 18.3% over the trailing two years, driven by a parallel decline in gross margin from 58.3% to 55.7%, reflecting cost pressure that has outpaced revenue growth. Measured from the peaks reached in between — 23.7% operating margin and 59.3% gross margin — the compression is steeper still.

### Is lululemon's revenue still growing?

Yes, but at a decelerating rate. Annual revenue grew from $4.40 Billion (FY2020) to $11.10 Billion (FY2025), with the most recent year's growth rate (approximately 4.9%) well below the pace of earlier years in that trend.

### What is lululemon's current ROIC?

TTM Return on Invested Capital is 42.9%, down from 60.9% two years ago and from a 74.6% peak in the quarter ended January 2025 — still a strong absolute figure, but a substantial decline tracking the margin compression described above.

### When did lululemon last file its 10-Q, and what period does it cover?

lululemon's most recent filing is a Form 10-Q filed June 4, 2026, covering the fiscal quarter ended May 3, 2026 (Q1 FY2026).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=lululemon-stock-analysis-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference lululemon athletica inc.'s Q1 FY2026 10-Q (filed June 4, 2026, period ending May 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001397187/000139718726000078/lulu-20260503.htm).

---

## Blog: Magic Formula Investing: Greenblatt's Strategy Explained
source: https://www.geminiq.com/blog/magic-formula-investing-explained

### Magic Formula Investing: Greenblatt's Strategy Explained
Joel Greenblatt's Magic Formula ranks stocks by earnings yield and return on capital. Here's how the strategy works, what the evidence shows, and how to screen for it using clean SEC data.

Joel Greenblatt published *The Little Book That Beats the Market* in 2005 and made a provocative claim: a mechanical two-factor formula, applied consistently to a ranked universe of stocks, had beaten the S&P 500 by a significant margin over a 17-year period — without requiring a single discretionary judgment call. The formula is not complicated. It combines a measure of how cheaply you are buying the business with a measure of how good the underlying business actually is. Buy cheap, high-quality businesses. Hold them for a year. Rebalance. Repeat. The investment media has spent two decades either dismissing the approach as too simple or misapplying it because the underlying metrics are more sensitive to data quality than most investors realize. This guide covers what the formula actually measures, what the historical evidence shows, where the strategy fails, and how to run a credible version of the screen — anchored to the raw SEC filings where the inputs live.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=magic-formula-investing-explained)**

---

## Table of Contents

- [What Is the Magic Formula?](#what-is-the-magic-formula)
- [The Two Inputs: Earnings Yield and Return on Capital](#the-two-inputs-earnings-yield-and-return-on-capital)
- [How the Ranking System Works](#how-the-ranking-system-works)
- [The Historical Evidence](#the-historical-evidence)
- [Why Most Implementations Get It Wrong](#why-most-implementations-get-it-wrong)
- [The Real Reason It Works — and When It Doesn't](#the-real-reason-it-works-and-when-it-doesnt)
- [How to Run the Magic Formula Screen on GeminIQ](#how-to-run-the-magic-formula-screen-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is the Magic Formula?

The Magic Formula is a quantitative stock selection strategy developed by Joel Greenblatt, founder of Gotham Capital and adjunct professor at Columbia Business School. It appears in *The Little Book That Beats the Market* (2005) and the updated *The Little Book That Still Beats the Market* (2010). The core idea is rooted in value investing logic that predates Greenblatt by decades: great businesses bought at reasonable prices outperform mediocre businesses bought at any price, and mediocre businesses bought cheaply outperform great businesses bought at extravagant ones. The Magic Formula operationalizes this intuition into two specific metrics — earnings yield and return on capital — and combines them into a single composite rank across a defined universe of stocks.

What made the strategy influential was not originality. It was demonstration. Greenblatt published actual backtested returns covering the period from 1988 to 2004, showing the formula's ranked portfolio outperforming the S&P 500 by a substantial margin over that stretch. He then made it mechanical — anyone willing to follow the rules and ignore their emotions during underperformance periods could theoretically replicate the results. The appeal to retail investors was immediate, and the publication of the formula sparked an ongoing debate about whether quantitative value strategies can survive widespread adoption.

---

## The Two Inputs: Earnings Yield and Return on Capital

The formula has two components, and each one is doing a specific analytical job. Understanding what they measure — and how Greenblatt defines them — is essential before applying the strategy.

**Earnings Yield** is Greenblatt's valuation input. It is calculated as EBIT divided by [Enterprise Value](/metrics/valuation-metrics/enterprise-value) — the inverse of the EV/EBIT multiple, expressed as a percentage. The choice of EBIT over net earnings and Enterprise Value over market capitalization is deliberate and important. EBIT strips out the effects of leverage and tax rates, making it possible to compare businesses with radically different capital structures on equal footing. A company carrying significant debt will show lower net income than an identical unlevered business — but their EBIT figures will be similar, reflecting the same underlying operating economics. Enterprise Value replaces market capitalization in the denominator because it accounts for the debt that EBIT-paying investors have already taken on. Using market cap against EBIT would understate the true cost of acquiring the business's earnings stream. The result is a metric that answers the question: for the full price required to own this business — equity plus assumed debt, less cash — how much operating earnings am I getting per dollar paid?

**Return on Capital** is the quality input. Greenblatt defines it as EBIT divided by Net Fixed Assets plus Net Working Capital. This focuses on the tangible operating capital the business actually requires to run, and avoids the effective-tax-rate sensitivity of NOPAT-based approaches. A business with high return on capital earns significant operating profit relative to the fixed assets and working capital it has deployed. That efficiency tends to reflect a durable competitive advantage: pricing power, brand loyalty, switching costs, or an operating model that converts inputs into earnings far more effectively than competitors. Greenblatt's insight was that these businesses — the ones genuinely earning high returns on capital — tend to compound value through time in a way that consistently low-return-on-capital businesses never can, regardless of how cheaply the stock is priced.

The two metrics are complementary in a specific way. Earnings yield alone would lead you toward cheap businesses with no regard for quality — the value trap problem. Return on capital alone would lead you toward great businesses with no regard for price — the overpayment problem. The formula requires both, and the ranking system resolves the tradeoff mechanically.

---

## How the Ranking System Works

The implementation is straightforward. Start with a defined investment universe — Greenblatt typically uses US-listed companies with market capitalizations above a minimum threshold, excluding financial companies, utilities, and foreign-listed ADRs. Financial companies are excluded because their balance sheets are structured differently, making the working capital and fixed asset inputs meaningless for banks and insurers. Utilities are excluded because regulated capital structures produce artificially low return-on-capital figures that would skew the ranking.

Within the eligible universe, rank every company by earnings yield from highest to lowest — the cheapest business on an EV/EBIT basis receives rank 1. Then rank every company by return on capital from highest to lowest — the most efficient business receives rank 1. Add the two ranks together to produce a composite Magic Formula rank. The companies with the lowest composite scores — highest earnings yield combined with highest return on capital — are the buy candidates.

Greenblatt's original implementation called for selecting 20 to 30 stocks from the top of the combined ranking, holding each position for approximately one year, then rebalancing by selling the existing positions and replacing them with the new top-ranked candidates. The one-year holding period is not arbitrary: it aligns with the point at which short-term capital gains treatment rolls off for US taxpayers, making the annual rebalance tax-efficient for taxable accounts. The diversification across 20 to 30 names reduces single-stock concentration risk without diluting the strategy's exposure to the highest-ranked opportunities.

---

## The Historical Evidence

Greenblatt's original backtest covered the period from 1988 through 2004 and reported average annual returns of approximately **30.8%** for the top-ranked Magic Formula portfolio, compared to approximately **12.3%** for the S&P 500 over the same period. The universe in that test was US-listed stocks with market capitalizations above $50 million. Using a higher minimum market cap of $1 billion still produced outperformance, with average annual returns of approximately **22.9%** versus the index — a smaller edge, but still a substantial one over a 17-year span.

Several academic researchers subsequently tested the formula on out-of-sample data. A 2012 study by Persson and Selander applied the strategy to European markets from 2000 through 2010 and found outperformance in several countries, though with significant country-level variation. A 2014 study by Davydov, Tikkanen, and Äijö tested the formula on Nordic market data and found results consistent with the original US backtest. Gray and Carlisle, writing in *Quantitative Value* (2012), applied the formula to US data across a longer and more recent period and found that while the strategy outperformed over time, a simpler version — using earnings yield alone with a quality filter based on balance sheet strength rather than return on capital — produced similar or stronger results in some testing windows.

The evidence is not unanimous. Researchers testing the formula on data since its publication have found more mixed results, which is consistent with the academic literature on quantitative anomalies more broadly: strategies that attract attention often see their alpha compress as capital flows into the approach. The Magic Formula's empirical track record before 2005 is stronger than its documented performance after wide publication, which is the expected pattern for a published quantitative signal in an efficient market. The more important conclusion is this: the underlying logic — combining quality and value in a mechanical ranking — has a coherent theoretical basis and a credible long-term historical record. Whether the precise magnitude of the historical edge persists is a separate question from whether the approach is analytically sound.

---

## Why Most Implementations Get It Wrong

The formula is simple in concept and error-prone in execution. Three failure modes account for most of the gap between the theoretical strategy and what investors actually experience when they try to apply it.

The first is data quality. Both inputs — EBIT and Enterprise Value — are sensitive to how the underlying financial data is constructed. Enterprise Value requires current market capitalization, total debt, and total cash. If the debt figure used is stale or misclassified, Enterprise Value is wrong, and therefore earnings yield is wrong. EBIT is equally vulnerable: on many third-party financial platforms, operating income is normalized, restated, or merged with non-operating line items in ways that do not match the filed 10-K or 10-Q. A standard screener presenting Magic Formula rankings built on normalized data is presenting a result that diverges — sometimes significantly — from what the formula would produce if run on the raw SEC filings. The inputs look credible because they are labeled correctly. But the labels mask the fact that the underlying numbers have been processed through an intermediary before reaching the ranking model.

The second failure mode is universe definition. The formula's exclusions — financial companies, utilities, foreign-listed ADRs — are not optional. Including them produces distorted rankings because the metrics do not translate across those categories. An investor applying the formula to a universe that includes banks will find them frequently surfacing near the top of the earnings yield ranking, not because they are cheap in the same sense as an industrial company, but because the EBIT and working capital inputs are structurally incompatible with how banking businesses actually generate returns.

The third failure mode is behavioral. Greenblatt was explicit about this in both editions of the book: the strategy underperforms the market in roughly one out of every three to four years, and sometimes produces multi-year stretches of underperformance. Most investors do not hold through it. The moment the ranked portfolio lags the index for two consecutive years, the abandonment rate climbs sharply. The investors who abandoned in the year before a mean-reversion rally capture none of the excess return. The strategy requires a level of mechanical consistency that most investors — particularly those running discretionary portfolios alongside a quantitative screen — find difficult to maintain in practice.

---

## The Real Reason It Works — and When It Doesn't

The academic literature on value and quality factors suggests the Magic Formula's outperformance is not a free lunch — it is compensation for a specific kind of discomfort. The businesses that rank highly on combined earnings yield and return on capital are often doing so because something has gone wrong in the near term: an industry downturn, a cyclical earnings depression, a management transition, or a headline event that has driven the stock down relative to its long-run operating economics. These are exactly the situations where discretionary investors exit, pushing prices down further, and creating the cheap entry point that the earnings yield ranking surfaces. The return on capital filter then distinguishes businesses experiencing temporary distress from ones facing permanent structural deterioration.

The strategy breaks down in two distinct environments. The first is a momentum-driven market where high-quality businesses are already richly priced and the formula cannot find combinations of cheap valuation and strong returns simultaneously — in these conditions, the ranked portfolio tends to fill with businesses that are cheap for structural reasons rather than cyclical ones, and the quality filter does less useful work. The second is a prolonged low-interest-rate environment where investors systematically re-rate quality businesses upward, compressing earnings yields across the board and reducing the spread between the cheapest and most expensive valuations. Both conditions appeared in various stretches of the post-2010 market environment, which partly explains why post-publication performance has been more muted than the original backtest period. The formula does not fail in those environments — it simply has less raw material to work with.

---

## How to Run the Magic Formula Screen on GeminIQ

The credibility of any Magic Formula implementation depends entirely on the quality of the inputs, and the inputs live in the SEC filings. GeminIQ's [Stock Screener](/features#screener) builds every metric directly from XBRL-tagged 10-K and 10-Q data — not from a normalized third-party feed — which means the EBIT figure in the screener is the `OperatingIncomeLoss` tag from the filing, and the debt figures used in Enterprise Value are the balance sheet components as the company actually reported them.

The [Magic Formula screen](/screens/stock-screeners/magic-formula) applies six filters. Market Cap must exceed **$1 billion**, establishing the large-cap universe where liquidity is workable. GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) (ROIC TTM) must be at or above **25%** — the quality threshold that confirms the business earns strong returns on the capital it deploys. EV/EBIT TTM must be at or below **15** and at or above **1** — the valuation band that targets genuinely cheap businesses while excluding companies whose low multiples are a product of negative or near-zero operating earnings rather than value. Owner Org is set to exclude Finance and Crypto Assets — sectors where capital structure makes EBIT and ROIC comparisons unreliable. Results are sorted by EV/EBIT TTM ascending, so the companies offering the most operating earnings per dollar of enterprise value surface at the top. Running those six filters against the current US equity universe returns **107 companies** as of June 2026.

<center><sup>GeminIQ Stock Screener showing the Magic Formula filter set — Market Cap > $1B, ROIC TTM ≥ 25%, EV/EBIT TTM between 1 and 15, Finance and Crypto Assets excluded — sorted ascending by EV/EBIT TTM. 107 results as of June 2026. Top results include TRN at 3.49x EV/EBIT with 56.30% ROIC TTM, KLAC at 4.12x with 53.29% ROIC TTM, and ANF at 4.72x with 60.30% ROIC TTM. All inputs sourced from XBRL-tagged SEC filings via `Operating Income Loss` and as-filed balance sheet components.</sup></center>

This matters more than it sounds. A standard screener running the same filters on normalized data will produce a different list. Aggregators frequently adjust EBIT for restructuring charges, stock-based compensation, or acquired intangible amortization — a company carrying significant acquisition-related amortization will show a much higher adjusted EBIT on an aggregator than its as-filed figure. That gap moves the EV/EBIT multiple, which changes who ranks where. GeminIQ surfaces the as-filed EBIT, which is what Greenblatt's original formula uses. It is also explicit about what the screen does not do: it does not apply a composite dual-rank the way Greenblatt's original implementation described. It uses ROIC as a quality floor and EV/EBIT as the primary sort — a faithful practical approximation that avoids the data integrity problems that plague composite-rank implementations built on normalized inputs.

Once a company surfaces at the top of the screen, GeminIQ's [Calculated Metrics](/features#calculated-metrics) panel shows how ROIC TTM has trended across the prior 8 to 12 quarters. A business at **25% ROIC** after three years of consistent performance tells a different story than one that hit **25%** in a single quarter following an asset sale or a working capital release. The [Interactive Visualizations](/features#visualizations) make that trend visible in seconds. The Magic Formula is a starting point, not a conclusion. Greenblatt never argued the formula was a substitute for reading the filing — he argued it was a systematic way to identify the businesses worth reading. Pull the ranked candidates into GeminIQ's [Financial Statements](/features#financial-statements) view and ask the questions the formula cannot: Is the debt structure sustainable? Is working capital expanding or contracting? Does the EBIT figure reflect the ongoing business or a one-time event the ranking model cannot detect?

---

## Frequently Asked Questions

### What is the difference between Greenblatt's Return on Capital and standard ROIC?

Greenblatt's return on capital is EBIT divided by Net Fixed Assets plus Net Working Capital. Standard ROIC — including GeminIQ's pre-calculated version — uses NOPAT divided by total [invested capital](/metrics/calculated-values/invested-capital) including all debt and equity less excess cash. Greenblatt's version is simpler and avoids tax-rate sensitivity, but excludes the full debt load from the capital base, which can overstate returns for highly leveraged businesses. GeminIQ's screen uses ROIC TTM as its quality input — a more conservative and more methodology-transparent measure than Greenblatt's narrower definition, and one whose inputs are fully traceable to the XBRL-tagged filing data.

### Why are financial companies and utilities excluded?

Financial companies — banks, insurers, financial holding companies — have balance sheets where debt is part of the operating business model, not a financing decision layered on top of operations. Net working capital is a meaningless concept for a bank. Return on capital computed against a lending portfolio produces figures that are not comparable to an industrial or consumer company's capital efficiency. Utilities are excluded because regulated capital structures produce artificially low returns on capital — the regulatory framework sets the permitted return by design. Including either category distorts the ranking without adding analytical value.

### Does the strategy still work after publication?

The pre-publication backtest evidence is substantially stronger than the post-publication live record. This is consistent with the broader academic literature on published quantitative anomalies: once a factor is widely known, capital flows toward it and compresses the spread between cheap-and-quality and expensive-and-low-quality businesses. What remains is the underlying logic — buying good businesses cheaply is still better than the alternative — but the precise magnitude of the documented historical edge should be treated as a historical data point rather than a forward-looking guarantee. Greenblatt himself acknowledged in the updated edition that the strategy requires patience through underperformance periods and that behavioral consistency is as important as the formula itself.

### How many stocks should the portfolio include?

Greenblatt recommended 20 to 30 positions selected from the top of the combined ranking. Fewer than 20 concentrates too much risk in individual names; more than 30 dilutes the exposure to the highest-ranked candidates without meaningfully improving diversification. The portfolio is rebalanced annually, and Greenblatt suggested staggering purchases over the course of the first year — buying 5 to 7 positions per quarter — to avoid being fully deployed at a single market moment.

### What minimum market cap should be used?

Greenblatt's original backtest used $50 million as the floor. His large-cap version used $1 billion. Smaller market caps tend to produce higher-magnitude returns in backtests but introduce practical constraints: lower liquidity, wider bid-ask spreads, and data coverage that can be less complete. The GeminIQ Magic Formula screen defaults to the $1 billion floor, which the [Stock Screener](/features#screener) applies as a stackable filter that can be adjusted to match a specific portfolio's liquidity requirements.

---

### Related Reading

- [ROIC: Return on Invested Capital Explained — Formula, Benchmarks, and Real Filing Data](/blog/roic-return-on-invested-capital-explained)
- [Value Investing Glossary: Terms, Ratios, and Mental Models Defined](/blog/value-investing-glossary)
- [What Investors Miss in SEC Filings: Hidden Signals in 10-Ks and 10-Qs](/blog/what-investors-miss-in-sec-filings)

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Micron (MU) Q4 2026 Earnings: Revenue Up 379%, Deposits $12.75B
source: https://www.geminiq.com/blog/micron-earnings-q4-2026

### Micron (MU) Q4 2026 Earnings: Revenue Up 379%, Deposits $12.75B
Micron's Q4 FY2026 revenue was $54.23 billion, up 379% year over year, with diluted EPS of $32.87. The 10-K shows the strategic customer agreements behind its 'durability' claim carry $12.75 billion of customer deposits and about $33 billion of next-twelve-month obligations.

**[Micron](/stocks/MU) (MU) reported Q4 FY2026 revenue of $54.23 billion, up 379.3% year over year, and diluted EPS of $32.87, up about 1,062%, for the 14-week quarter ended September 3, 2026 (8-K released September 30; 10-K filed October 9, 2026). The release says its strategic customer agreements provide "added confidence in the durability of Micron's financial performance." The 10-K sizes that durability: $12.75 billion of customer deposits repayable from 2029 to 2031, and roughly $33 billion of obligations falling in the next twelve months, less than this one quarter's revenue.**

| Field | Value |
|---|---|
| Company | Micron ($MU) |
| Quarter | Q4 FY2026, period ended September 3, 2026 |
| Earnings release | September 30, 2026 (Form 8-K) |
| 10-K filed | October 9, 2026 |
| Revenue | **$54.23 Billion** (+379.3% YoY) |
| Diluted EPS | **$32.87** (+1,061.5% YoY) |
| Operating margin | 80.7% (+48.4 pts YoY) |
| Operating cash flow (TTM) | $89.67 Billion |
| Full-year revenue | **$133.19 Billion** (+256.3% YoY) |
| Customer deposits received (FY2026) | **$12.75 Billion** |

## Micron Q4 2026 Revenue, EPS and Margins

[Micron](/stocks/MU)'s Q4 2026 revenue was **$54.23 billion**, up 379.3% from $11.32 billion a year earlier and 30.8% from the prior quarter, and diluted EPS was **$32.87** against $2.83. Price built the quarter, and an extra week flatters the sequential comparison.

**The Data:** Gross margin reached 86.8% and operating margin 80.7%, each the highest of the last 16 quarters and of 65 since 2009. Operating income was $43.75 billion. For the full year, the 10-K reports DRAM sales up 252% on an approximate 180% rise in average selling prices and a mid-20% range rise in bit shipments.

**Why:** Revenue grew about 4.8-fold and operating margin about 2.5-fold, together a 12-fold gain against EPS's 11.6-fold; a higher share count and tax rate took a little back. Fiscal 2026 had 53 weeks, and the extra one sits here: the quarter ran from May 28 to September 3, 14 weeks against 13, so revenue per week rose about 21.5% sequentially, not 30.8%. Bit shipments grew about a quarter. The rest was price, and a margin built on price lasts as long as the price does.

<center><sup>GeminIQ Visualizations plots `Revenues` and `Operating Income Loss` for the last 12 quarters. Q4 FY2026 revenue of $54.2B, marked as the highest of 65 quarters since 2009, sits against $11.3B a year earlier; operating income reached $43.8B.</sup></center>

## What Micron's FY2026 10-K Shows Beyond the Press Release

[Micron](/stocks/MU)'s 10-K puts the transaction price allocated to remaining performance obligations at approximately $134 billion, with about one-fourth expected as revenue over the next twelve months. That is roughly $33 billion for the coming year, against $54.23 billion reported in Q4 alone.

**The Data:** A year earlier these obligations were "not material." Now **$134 billion** sits in take-or-pay agreements, of which $13 billion is already booked as contract liabilities, mostly customer deposits. [Micron](/stocks/MU) received **$12.75 billion** of deposits in 2026, nearly all scheduled for repayment between 2029 and 2031, and $7 billion of customer letters of credit stand behind them.

**Why:** The filing excludes agreements without fixed pricing or price bands and says the obligations are "not expected to be indicative of future revenue," so spot-priced sales sit outside the $134 billion. Management says gross margins at floor pricing should run "meaningfully above our peak quarterly margins in any past cycle"; the filing gives no figure to test that claim. Today the release's durability claim describes the contracts, and the revenue is mostly outside them.

## Micron Q4 2026 Operating Cash Flow, Debt and Customer Deposits

[Micron](/stocks/MU)'s Q4 2026 operating cash flow was $43.97 billion, up 667% from $5.73 billion a year earlier, and free cash flow (operating cash flow less capital expenditure) was $32.86 billion, the highest of the last 16 quarters.

**The Data:** Operating cash flow exceeded the quarter's $37.70 billion of net income by $6.27 billion. Capital expenditure reached $11.11 billion, also a 16-quarter high. Over the year, Micron repaid **$10.04 billion** of debt, cutting principal from $14.6 billion to $5.2 billion, while receiving $12.75 billion of customer deposits; net financing cash flow was +$630 million. Noncurrent customer contract liabilities rose from $142 million to $12.9 billion on the 8-K balance sheet. GeminIQ's pre-calculated [Net Debt to EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) is -0.31x on a trailing basis.

**Why:** Deposits are booked in financing, so they did not inflate operating cash flow. They did replace debt: repayment of one creditor funded by prepayment from customers, who get cash back in 2029 to 2031 only if they meet purchase minimums. Even adding the $12.9 billion to $5.2 billion of debt leaves far less than the $73.45 billion of cash and marketable investments, so liquidity is not the concern. A balance sheet that retires debt with customer prepayments has not become debt-free; it has changed creditors.

<center><sup>GeminIQ Financial Statements shows `Net Cash Provided By Used In Operating Activities` of $44.0B in Q4 FY2026, highlighted, against `Payments To Acquire Property Plant And Equipment` of $11.1B, with `Share Based Compensation` and `Payments For Repurchase Of Common Stock` beside them.</sup></center>

## Micron's Fiscal Q1 2027 Guidance After Q4

In its 8-K, Micron guided Q1 FY2027 revenue to $61.5 billion ± $1.5 billion and GAAP diluted EPS to $37.84 ± $1.00. The prior quarter's guide shows how the company's ranges have fared.

**The Data:** For Q4 the company guided revenue of $50.0 billion ± $1.0 billion and GAAP EPS of $30.73 ± $1.00. Actual revenue of **$54.23 billion** cleared the top of that range by $3.23 billion, and EPS of $32.87 cleared its $31.73 top. Operating expenses did not follow: GAAP $3.30 billion against about $1.86 billion guided, and non-GAAP $2.57 billion against $1.65 billion, even excluding the $500 million patent license charge the 8-K removes.

**Why:** The revenue overshoot of about $4.2 billion above the midpoint paid for an expense overshoot of about $1.4 billion. The new guide implies 13.4% more revenue than Q4, but if Q1 runs 13 weeks, revenue per week is about 22% higher. GAAP gross margin is guided to about 85.95%, below Q4's 86.8%, and EPS rises 15% because GAAP operating expenses are guided back to about $2.31 billion. The guide leans on price and volume, not margin.

## How MU Stock Has Moved After Past Earnings Reports

Across the last 12 [Micron](/stocks/MU) 10-Q filings with a completed one-month window (filed October 2023 to June 2026), the median one-month return was -4.4%, positive after 5 of 12, while the median three-month return was +17.0%, positive after 9 of 12.

**The Data:** The one-month range ran from **-30.0%** (FY2026 Q3, filed June 25, 2026) to +38.9% (FY2026 Q1). The three-month range ran from -30.9% to +94.6%. After the past three fourth-quarter filings, one-month returns were -6.2%, +5.7% and +16.6%. This filing's windows have not elapsed. In the 12 months of Form 4 data ending June 26, 2026, insiders filed 45 sales worth $215.8 million and two purchases worth $7.8 million, against 20 sales worth $17.8 million in the prior 12 months; CEO Sanjay Mehrotra accounted for $71.7 million, or 33%.

**Why:** The gap between a median one-month dip and a median three-month gain is the pattern in the GeminIQ [Earnings Reaction Heat Map](/features#price-variance); it is a historical association, not a forecast, and it describes how Micron's stock moved after its past filings. Insider sales ran 22 to 1 over purchases by count. The [Insider Transactions](/features#insider-transactions) data ends June 26, 2026, so it does not cover the weeks after the release. When a record quarter arrives, the number worth pricing is the share of it the customer has already signed for.

<center><sup>GeminIQ Earnings Reaction Heat Map shows returns 1-3 months after each 10-Q filing; the highlighted cell is the FY2026 Q3 one-month return of -30.0%, the weakest of the last 12 windows. The Q4 FY2026 window has not yet elapsed, so its cells show "-".</sup></center>

<center><sup>GeminIQ Insider Transactions summarizes SEC Form 4 purchases and sales per insider for filings dated June 27, 2025 to June 26, 2026; the highlighted row is Mehrotra, Sanjay at $71.7M of sales.</sup></center>

## Frequently Asked Questions

### When does Micron report earnings?

Micron released its Q4 FY2026 results on September 30, 2026 and filed its 10-K on October 9, 2026. Last year the company filed its first-quarter FY2026 results on December 18, 2025, a pattern from the filing record and not a forecast of the next date.

### Does Micron pay a dividend?

Yes. Micron declared a quarterly dividend of $0.15 per share on September 30, 2026, payable October 29, 2026 to holders of record on October 14. It paid $173 million in Q4 and $610 million in fiscal 2026, up from $522 million, after raising the rate from $0.115 to $0.15 in the third quarter.

### Is Micron doing well financially?

Micron's trailing net profit margin was 63.80% against 22.84% a year earlier, per GeminIQ's pre-calculated [Net Profit Margin](/metrics/margin-metrics/net-profit-margin). GeminIQ's [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) was 100.94% against 15.44%, and its [Current Ratio](/metrics/liquidity-ratios/current-ratio) was 3.31x. Cash and marketable investments totaled $73.45 billion at fiscal year-end.

### What was Micron's fiscal 2026 revenue?

Micron's fiscal 2026 revenue was $133.19 billion, up 256% from $37.38 billion, with net income of $84.97 billion and diluted EPS of $74.33. DRAM contributed $100.68 billion and NAND $31.79 billion.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=micron-earnings-q4-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Micron Technology, Inc.'s
fiscal 2026 10-K (filed October 9, 2026, period ending August 31, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed September 30, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/723125/000072312526000023/mu-20260903.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/723125/000072312526000018/a2026q4ex991-pressrelease.htm).</sup>

---

## Blog: Morningstar Alternative for SEC Filing Analysis
source: https://www.geminiq.com/blog/morningstar-alternative-sec-filing-data

### Morningstar Alternative for SEC Filing Analysis
A Morningstar alternative for filing-level analysis. Morningstar's star rating is built from an analyst's moat assessment and a proprietary fair value estimate; this post separates the ratings layer from what a company actually reported.

Morningstar occupies an unusual position in financial research: it is simultaneously a ratings agency, a research publisher, and a data vendor whose fundamentals show up inside competing products. Its equity methodology is published in detail, which is more than most rating systems offer, and the framework itself is coherent. Four components drive the star rating — the analyst's economic moat assessment, the analyst's fair value estimate, the uncertainty around that estimate, and the current market price.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=morningstar-alternative-sec-filing-data)**

Read that list again and notice what is missing. Three of the four inputs are judgments produced inside Morningstar. The fourth is the market price. Not one of them is a number a company reported.

That is not a flaw. It is what a rating is. But it means the star rating and the filing answer different questions, and an investor who treats the first as a summary of the second has skipped the step that mattered.

## Table of Contents

- [What the Star Rating Is Actually Measuring](#what-the-star-rating-is-actually-measuring)
- [The Moat Rating Depends on a Number No Filing Contains](#the-moat-rating-depends-on-a-number-no-filing-contains)
- [Coverage Is Narrower Than the Ticker Universe](#coverage-is-narrower-than-the-ticker-universe)
- [Morningstar Is Also the Data Under Other Platforms](#morningstar-is-also-the-data-under-other-platforms)
- [What a Filing-First Alternative Supplies](#what-a-filing-first-alternative-supplies)
- [Using the Rating Without Outsourcing the Analysis](#using-the-rating-without-outsourcing-the-analysis)
- [Frequently Asked Questions](#frequently-asked-questions)

## What the Star Rating Is Actually Measuring

The Morningstar Rating for stocks is a valuation signal, not a quality score, and the distinction gets lost constantly.

Morningstar's published methodology states the position plainly: five-star stocks sell at the biggest risk-adjusted discount to their fair value estimates, and one-star stocks trade at premiums to their estimated intrinsic worth. The fair value estimate comes from a proprietary [discounted cash flow](/blog/dcf-valuation-model-step-by-step) model, with valuation multiples used as supporting cross-checks rather than as the primary method.

So a five-star rating says the analyst's model produced a number well above the current price. It says nothing about whether the business is good, and it says nothing about what the company reported last quarter.

Fund star ratings work on entirely different logic — backward-looking, peer-relative, based on risk-adjusted past performance — which is why a single icon meaning two different things across two asset types generates so much confusion. Morningstar itself is consistent in warning that fund stars are not a buy signal.

An investor reading a stock's star rating is reading the output of somebody's forecast. Forecasts are legitimate inputs to a decision. They are not measurements.

## The Moat Rating Depends on a Number No Filing Contains

This is the part worth sitting with, because it exposes exactly where the ratings layer stops being derivable from filed data.

Morningstar's methodology defines an economic moat around excess profits, and it defines excess profits specifically as returns on invested capital above the firm's cost of capital — its estimate of WACC. A narrow moat means Morningstar believes the firm is more likely than not to sustain normalized excess returns for at least the next ten years. A wide moat extends that judgment further.

[Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) is calculable from filings. Operating income, taxes, debt, equity, cash, and the working capital that makes up [Invested Capital](/metrics/calculated-values/invested-capital) are all reported line items in a 10-K.

WACC is not. Two of its three core inputs — beta and the equity risk premium — are market assumptions rather than reported facts, which means the cost of capital in any moat framework is an estimate that no filing will ever confirm or contradict. The [WACC from a 10-K](/blog/how-to-calculate-wacc-from-10k) post walks through exactly which pieces come from the filing and which do not, and [ROIC vs. ROE vs. WACC](/blog/roic-vs-roe-vs-wacc) covers why the distinction changes what each number can be used for.

Change the assumed cost of capital by two percentage points and a company's excess returns can appear or vanish. The moat rating moves with it. The filings do not move at all.

That is not an argument against moat analysis, which is a useful framework and a real contribution to how investors think about durability. It is an argument for knowing which half of the calculation you can verify and which half you are accepting on trust.

## Coverage Is Narrower Than the Ticker Universe

The analyst-driven layer has a scope limit that is easy to miss.

Morningstar's equity research team covers roughly 1,500 companies globally with a staff of more than 100 analysts, all applying a single published methodology. That is deep coverage by any standard, and it is a fraction of the tradable universe. Thousands of US-listed companies have no analyst assigned to them, and where a figure is produced by a quantitative model rather than an analyst, Morningstar marks it — its stock report legend notes that a superscript Q indicates a price determined by a quantitative model.

The practical consequence is that the further you move from mega-cap coverage, the more the ratings layer thins out. Small caps, recent listings, and unloved industrials are exactly where a fundamental investor expects to find mispricing, and they are also where an analyst-assigned moat rating is least likely to exist.

Filings have no such gradient. Every registrant files the same forms on the same schedule, whether or not anyone is covering it.

## Morningstar Is Also the Data Under Other Platforms

There is a structural fact about Morningstar that changes how investors should read the wider landscape of tools.

Morningstar licenses fundamental data to other platforms. GuruFocus's own disclosures state that company fundamental data is provided by Morningstar and that analyst estimates draw on Morningstar alongside Refinitiv. Advisor platforms commonly source fund data from Morningstar as well.

That means an investor "cross-checking" a Morningstar figure against another platform may be checking the number against itself. Two screens agreeing feels like corroboration and often is not — it is one dataset displayed twice.

Independent verification requires a different source of truth, not a different interface onto the same one. The only source independent of every vendor is the document the company filed.

## What a Filing-First Alternative Supplies

GeminIQ produces no ratings, assigns no moats, and prints no fair value estimate. It supplies the layer those things are built on: 10-K and 10-Q data extracted directly from SEC EDGAR, with each company's reported line item structure preserved and the [XBRL tag](/blog/what-is-xbrl) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years. [Custom Tables](/features#custom-tables) build views from specific reported items. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Return on Equity](/metrics/returns-and-profitability/return-on-equity), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, so an investor can audit the metric against the numbers that produced it. Where a calculation requires a market assumption rather than a filed figure — cost of capital being the clearest case — the honest answer is that filings cannot supply it, and no platform claiming otherwise is reading a filing.

The split between what is filed and what is assumed is easy to see in one company's numbers. [Apple's](/stocks/AAPL) balance sheet as of March 28, 2026 reports Total Shareholders Equity of **$106.5 Billion**, against **$66.8 Billion** a year earlier — a **$39.7 Billion** swing, with Retained Earnings flipping from a **-$15.6 Billion** accumulated deficit to a **$12.4 Billion** positive balance over four quarters. Every one of those figures is filed, tagged, and checkable against the document.

The cost of capital those returns get measured against is none of those things. Move it two points and the same filed record produces a company earning excess returns or one destroying them. The filings settle the numerator and cannot settle the comparison — which is the honest boundary of what any moat framework can claim. [Invested capital, step by step](/blog/invested-capital-formula-step-by-step) covers the filed side of that calculation.

The tradeoff is stated rather than hidden. No ratings, no analyst reports, no funds, no international coverage. US public company fundamentals from EDGAR, and the ability to point at where every number came from.

## Using the Rating Without Outsourcing the Analysis

The productive way to use Morningstar is as a hypothesis, not a conclusion.

A five-star rating on a wide-moat company is a well-reasoned analyst telling you their model shows a discount. That is worth reading, and the written reports are frequently the best free explanation of a business available anywhere. Treat it as a starting question: what would have to be true for that fair value estimate to hold, and does the filed record support it?

Answering that question requires the filings, because it is the assumptions that differ between a rating and a thesis — and the assumptions are precisely what a star cannot show you.

Because Morningstar fundamentals also sit underneath other retail platforms, the [GuruFocus alternatives](/blog/gurufocus-alternative-sec-data) post covers the same data-layer question from the other direction.

The rating tells you what an analyst concluded about the future. Only the filing tells you what the company reported about the past, and one of those two things is checkable.

## Frequently Asked Questions

### What are the best Morningstar alternatives?

It depends on which layer you are replacing. For analyst research, ratings, and fund coverage, the substitutes are other research publishers, and none of them derive their conclusions purely from filings. For US equity fundamentals, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability, which supplies inputs rather than conclusions.

### What does the Morningstar star rating actually measure?

For stocks, it measures the relationship between the current market price and Morningstar's analyst-estimated fair value, adjusted for the uncertainty around that estimate. Five stars indicates the largest risk-adjusted discount to fair value. For funds, the star rating is a different system entirely — backward-looking and peer-relative, based on risk-adjusted past performance.

### Is the Morningstar economic moat rating based on SEC filings?

Partly. The moat framework defines excess profits as returns on invested capital above the firm's estimated cost of capital. Return on invested capital is calculable from filed data. Cost of capital is not — beta and the equity risk premium are market assumptions rather than reported figures, so the moat conclusion depends on an input that no filing contains.

### How many companies does Morningstar cover with analysts?

Morningstar's equity research team covers roughly 1,500 companies globally with more than 100 analysts applying one published methodology. That leaves most of the tradable universe without an analyst-assigned rating, with quantitative models filling some of the gap — Morningstar flags quantitatively determined figures in its reports.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=morningstar-alternative-sec-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Morningstar Equity Research Methodology (published PDF), for the four rating components, the DCF-based fair value approach, and the definition of economic moat as returns on invested capital above estimated cost of capital.
- Morningstar analyst coverage figures and the quantitative-model flag in stock analyst reports, from Morningstar published materials, reviewed August 2, 2026.
- GuruFocus published site disclosures naming Morningstar as its company fundamental data provider.

---

## Blog: Negative Cash Conversion Cycle: 76 Companies Run One
source: https://www.geminiq.com/blog/negative-cash-conversion-cycle-companies

### Negative Cash Conversion Cycle: 76 Companies Run One
A negative cash conversion cycle means a company collects cash from customers before it has to pay its own suppliers, and the as-filed data shows exactly which large companies structurally run one.

**[AT&T](/stocks/T)** runs a cash conversion cycle of **-442 days**. That means AT&T collects cash from its own customers well before it has to pay its suppliers, who are effectively financing over a year of the company's operations in the meantime. That's a structural advantage that has nothing to do with margin or growth, and everything to do with negotiating leverage and billing structure. It is not the most extreme case on this list, but it is one of the largest companies running the pattern, and the as-filed data shows exactly who else does it and why.

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period, restricted to **companies with at least $1 billion in trailing revenue** and a cost-of-revenue figure large enough to compute a reliable ratio. Cash Conversion Cycle is GeminIQ's [Cash Conversion Cycle](/metrics/efficiency-and-turnover-ratios/cash-conversion-cycle) metric — days sales outstanding plus days inventory outstanding, minus days payables outstanding — computed directly from as-filed receivables, inventory, payables, revenue, and cost of revenue. **76 companies** in that universe currently run a negative cycle within a plausible range; the table below ranks the twenty largest by magnitude.

## The Pattern

A negative cash conversion cycle is the mechanical opposite of how most businesses are taught to think about working capital. Instead of tying up cash in inventory and receivables while waiting to collect, the company is effectively using its suppliers' money to fund operations. Three distinct mechanisms produce it, and they show up as three distinct clusters in the ranking. Telecom and utility billing collects on a cycle shorter than supplier payment terms. Consumer-staples brands carry enough negotiating leverage to extend payables well past their own inventory turns, and marketplace or e-commerce models collect from the customer at the moment of sale while paying the supplier weeks later. None of the three is a signal of financial distress; all three are structural features of how the business is built.

## The Data

| Rank | Company | Ticker | Sector | Cash Conversion Cycle | Revenue (TTM) |
|---|---|---|---|---|---|
| 1 | AbbVie Inc. | ABBV | Manufacturing | **-476 days** | $64.4B |
| 2 | AT&T Inc. | T | Telecom | **-442 days** | $127.2B |
| 3 | Pitney Bowes Inc. | PBI | Manufacturing | **-375 days** | $1.9B |
| 4 | Coca-Cola Co | KO | Manufacturing | **-175 days** | $49.3B |
| 5 | Verizon Communications Inc. | VZ | Telecom | **-163 days** | $138.9B |
| 6 | Coty Inc. | COTY | Manufacturing | **-147 days** | $5.8B |
| 7 | BrightSpring Health Services | BTSG | Services | **-131 days** | $14.4B |
| 8 | Synopsys Inc. | SNPS | Services | **-121 days** | $8.7B |
| 9 | Phibro Animal Health Corp | PAHC | Manufacturing | **-119 days** | $1.5B |
| 10 | PepsiCo Inc. | PEP | Manufacturing | **-100 days** | $97.1B |
| 11 | Clorox Co | CLX | Manufacturing | **-75 days** | $6.8B |
| 12 | Ralph Lauren Corp | RL | Manufacturing | **-72 days** | $8.4B |
| 13 | Designer Brands Inc. | DBI | Retail Trade | **-72 days** | $2.9B |
| 14 | NXP Semiconductors N.V. | NXPI | Manufacturing | **-67 days** | $12.6B |
| 15 | American Electric Power Co | AEP | Utilities | **-63 days** | $22.4B |
| 16 | Air Products & Chemicals Inc. | APD | Manufacturing | **-59 days** | $12.6B |
| 17 | Coupang, Inc. | CPNG | Retail Trade | **-56 days** | $35.5B |
| 18 | Snap-on Inc | SNA | Manufacturing | **-52 days** | $5.3B |
| 19 | Apple Inc. | AAPL | Manufacturing | **-51 days** | $466.8B |
| 20 | O'Reilly Automotive Inc | ORLY | Retail Trade | **-50 days** | $18.6B |

<center><sup>GeminIQ Stock Screener sorted by Cash Conversion Cycle TTM, most negative first, before the plausible-range and $1B trailing revenue filters used in the ranking above. Net Revenue in this view is the latest quarter.</sup></center>

## AT&T and Verizon: Billing Ahead of Paying

Both telecoms bill customers on recurring cycles — often with prepaid or auto-pay components — while extending payment terms to equipment vendors and network contractors that run well past the collection window. **[AT&T](/stocks/T)**'s **-442 days** and Verizon's **-163 days** sit in the same family, and the size of the gap between the two is itself informative. AT&T's more negative figure reflects a heavier mix of prepaid and equipment-financed billing relative to Verizon's, even though both are running the same underlying mechanism at nine-figure revenue scale.

<center><sup>GeminIQ Calculated Metrics: AT&T's Cash Conversion Cycle TTM by quarter, March 2022 through June 2026, negative in every period.</sup></center>

## Coca-Cola, PepsiCo, and Clorox: Supplier Leverage, Not Distress

**[Coca-Cola](/stocks/KO)** and PepsiCo are the cleanest illustration of the second mechanism. Neither company is short on cash or slow to collect from bottlers and retailers. The negative cycle comes entirely from the payables side, where decades of brand leverage let both companies negotiate supplier payment terms far longer than their own inventory and receivable turns require. A **-175 day** or **-100 day** cash conversion cycle at this kind of scale is a direct, filed measure of negotiating power that a margin figure alone would never show.

## Amazon and the Marketplace Mechanism

**[Amazon](/stocks/AMZN)** narrowly missed the top twenty at **-45 days**, but it is the textbook case for the third mechanism: a retailer that collects from the customer at checkout and pays the supplier on standard trade terms weeks later. That timing gap finances a meaningful share of its own inventory float with other people's money. **[O'Reilly Automotive](/stocks/ORLY)**, at **-50 days**, runs the same marketplace-adjacent logic inside physical auto parts retail — fast-turning inventory paired with extended supplier terms.

**[Apple](/stocks/AAPL)**, at **-51 days**, is the case most investors already associate with negative working capital, and the filings show it holds at nearly half a trillion dollars in revenue — proof the mechanism scales without breaking.

## The Method

Every figure above is GeminIQ's Cash Conversion Cycle metric — trailing-twelve-months days sales outstanding plus days inventory outstanding, minus days payables outstanding. GeminIQ computes it from as-filed revenue, cost of revenue, receivables, inventory, and payables for each company's most recent filing period within the last fifteen months. The ranking excludes companies whose cost-of-revenue figure is too small relative to revenue to produce a reliable ratio, since a near-zero denominator can distort the underlying turnover math without reflecting a real operating pattern. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's Cash Conversion Cycle on GeminIQ and check the sign. A negative number is not automatically bullish, and a positive one is not automatically bearish. The question worth asking is which of the three mechanisms above is producing it, and whether that mechanism is a durable structural feature of the business or a temporary artifact of one unusual quarter. Every reader can run that check directly against GeminIQ's as-filed data for their own holdings.

## Frequently Asked Questions

### What does a negative cash conversion cycle mean?

It means a company collects cash from its customers before it has to pay its own suppliers, so suppliers effectively finance part of its operations. GeminIQ computes it as days sales outstanding plus days inventory outstanding, minus days payables outstanding.

### Is a negative cash conversion cycle good or bad?

Not automatically either. Telecom and utility billing, consumer-staples supplier leverage, and marketplace models all produce one, and none of those is a signal of distress. The useful question is which mechanism is behind the number and whether it is a durable feature of the business.

### Which companies have a negative cash conversion cycle?

**76 companies** with at least $1 billion in trailing revenue currently run one within a plausible range. The largest by magnitude are AbbVie at **-476 days**, AT&T at **-442 days**, and Pitney Bowes at **-375 days**; Coca-Cola, Verizon, PepsiCo, and Apple also appear in the top twenty.

### How many days negative is the largest company on the list?

AbbVie leads the ranking at **-476 days**. Among the largest companies by revenue, AT&T runs **-442 days** on **$127.2 billion** in trailing revenue and Apple runs **-51 days** on **$466.8 billion**.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=negative-cash-conversion-cycle-companies)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Rankings are computed from GeminIQ's Cash Conversion Cycle metric across the described universe and snapshot window.

---

## Blog: Net-Net Stocks: Graham's Liquidation Formula in 2026
source: https://www.geminiq.com/blog/net-net-stocks-graham-strategy

### Net-Net Stocks: Graham's Liquidation Formula in 2026
Net-net stocks trade below NCAV — current assets minus all liabilities — giving investors margin of safety even if fixed assets and future earnings are worth nothing. This post covers the formula, historical evidence, and how to screen for true net-nets in 2026.

The financial media's verdict on Benjamin Graham's net-net strategy is swift and confident: the approach died with the Great Depression, the modern market is too efficient for liquidation-value investing, and anyone still hunting for net-nets is chasing ghosts. That verdict is wrong — but it is wrong in a specific, important way that most coverage misses entirely. The academic record documents meaningful excess returns from net-net portfolios well into the 21st century. What has changed is not whether the strategy works but where the opportunities appear, how many names are in the universe at any given time, and — critically — whether the investor has access to the accurate balance sheet data the formula demands. A net-net calculation is only as reliable as the current assets number underneath it, and that number is where most screening tools break down before the analysis even begins.

This post covers everything you need to run Graham's net-net strategy in 2026: the formula, the historical evidence, the data quality traps mainstream screeners ignore, and how to use GeminIQ's [Stock Screener](/features#screener) to surface candidates the way Graham himself would have — from primary source data.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=net-net-stocks-graham-strategy)**

---

## Table of Contents

- [What Is a Net-Net Stock?](#what-is-a-net-net-stock)
- [Why Graham's Net-Nets Worked: The Historical Context](#why-grahams-net-nets-worked-the-historical-context)
- [The Academic Record: Does Net-Net Still Generate Returns?](#the-academic-record-does-net-net-still-generate-returns)
- [The NNWC Formula in Practice](#the-nnwc-formula-in-practice)
- [The One-Third Rule: Net-Net Risk in Plain English](#the-one-third-rule-net-net-risk-in-plain-english)
- [The Data Quality Problem](#the-data-quality-problem)
- [How to Find Net-Net Stocks in GeminIQ](#how-to-find-net-net-stocks-in-geminiq)
- [Net-Net and the Broader Value Toolkit](#net-net-and-the-broader-value-toolkit)

---

## What Is a Net-Net Stock?

A net-net stock is a company whose market capitalization falls below its net current asset value (NCAV) — the dollar amount that would remain if you took all of the company's current assets, subtracted every liability it carries (current and long-term), and sold nothing else. No factory equipment. No real estate. No brand value. No going-concern premium. Just the liquid pile, measured against the total claims on the business.

Graham formalized this in both Security Analysis (1934) and _The Intelligent Investor_ (1949), calling the figure Net-Net Working Capital (NNWC). The formula is:

**NNWC = Current Assets − Total Liabilities**

When a company's market capitalization falls below its NNWC, the market is valuing all of its fixed assets, long-term investments, and future earnings at zero — or less. Graham's argument was that this represented a structural irrationality: no rational liquidator would pay less for a business than the net proceeds of selling just its cash, receivables, and inventory. If you can buy a dollar of liquid assets for **67 cents**, the margin of safety exists even if the underlying business never earns another dollar of profit.

This is meaningfully more extreme than a standard price-to-book screen. A company trading at **P/B 0.6×** might have the bulk of its book value locked in property, plant, and equipment — assets with uncertain liquidation value and real depreciation risk. A true net-net has a market cap below the sum of its current assets alone *after subtracting all liabilities*. The distinction is what gives the strategy its unique risk-reward profile. For a deeper look at how Graham used P/B and tangible book value as screening tools, see our [Value Investing Glossary](/blog/value-investing-glossary).

---

## Why Graham's Net-Nets Worked: The Historical Context

Graham developed the net-net framework after the 1929 crash, when the U.S. equity market had collapsed far enough that dozens of solvent, operating businesses were genuinely trading at sub-liquidation prices. His own investment partnership ran concentrated net-net positions throughout the 1930s and into the 1940s. This was not a theoretical exercise — it was the primary approach generating returns for serious value investors for nearly two decades.

The conditions that made Depression-era net-nets plentiful were not subtle. Companies with sound current asset bases were being sold at prices that implied their entire fixed asset base, future earnings, and franchise value were worthless. A panicked and illiquid market was pricing the cost of selling an ownership stake far below the proceeds of simply shutting the business and collecting the receivables. For a patient, solvent investor with a long time horizon, the asymmetry was not difficult to see.

As the post-war economy recovered and institutional investing grew, the population of large-cap U.S. net-nets evaporated. By the time Graham published the final edition of _The Intelligent Investor_ in 1973, he acknowledged that the strategy's easiest application had passed. But he did not call it dead — he described it as harder to execute and requiring greater diversification than it had in the 1930s. That distinction carries directly into 2026, and it is what the media consistently misses when it declares the strategy obsolete.

---

## The Academic Record: Does Net-Net Still Generate Returns?

The academic record is considerably more favorable to net-net investing than mainstream dismissals suggest.

Henry Oppenheimer's 1986 study, "Ben Graham's Net Current Asset Values: A Performance Update," is the foundational piece of documented evidence. Studying U.S. stocks meeting the NCAV criterion from 1970 to 1983, Oppenheimer documented average annual returns of approximately **29%**, versus roughly **11%** for the broader market benchmark over the same period. The excess return — approximately **18 percentage points per year**, sustained over thirteen years on a clearly defined mechanical strategy — is not a marginal edge. The companies in that universe were not glamorous: micro-cap industrial companies, small retailers, obscure manufacturers. They were cheap precisely because no one wanted to own them. That structural unpopularity is what preserved the premium.

Subsequent academic work confirmed that the net-net effect had not fully disappeared, though excess returns compressed as the strategy became more widely known and the domestic universe shrank. International markets produced the clearest modern evidence. Japan had a large and persistent population of net-net stocks throughout the 2000s and 2010s, driven by corporate governance norms that prioritized balance sheet accumulation over shareholder returns. Several well-documented value investors generated substantial excess returns operating in that environment.

In the U.S. today, true net-nets are rare among any company of meaningful size. Most appear in micro-cap and nano-cap names — often in declining industries, with genuine operational problems that explain why the market is assigning a sub-liquidation price. But standard financial media doesn't read the footnotes. It sees a small, unappealing company and dismisses both the stock and the strategy. The data says the dismissal is premature.

---

## The NNWC Formula in Practice

Calculating NNWC is straightforward in principle and tricky in practice, for exactly the reason that makes this strategy worth pursuing: the inputs are less reliable than they look.

## Step 1: Pull current assets from the balance sheet

This is the sum of cash and cash equivalents, short-term investments, accounts receivable (net of allowances), inventory, and prepaid expenses. GeminIQ's [Financial Statements](/features#financial-statements) view surfaces these line items exactly as reported in the SEC filing, without the normalization that collapses sub-components into aggregated figures.

## Step 2: Subtract total liabilities — not just current liabilities

This is the single most common error in net-net analysis. Long-term debt, deferred tax liabilities, operating lease obligations, pension liabilities, everything. A company can show attractive net current assets while carrying substantial long-term debt that would wipe out the position in a liquidation scenario. The correct formula uses total liabilities, full stop.

## Step 3: Compare to market capitalization

If NNWC exceeds market cap, the company is a candidate. The ratio of NNWC ÷ Market Cap is the key figure. Graham's own practice targeted stocks where NNWC represented at least **150%** of market capitalization — a margin of safety on top of the margin of safety.

Graham did not stop at the gross current assets figure, and neither should you. His private calculations applied conservative haircuts to each component of current assets: receivables were discounted to approximately **75 cents on the dollar** to account for collectability risk, inventory was carried at roughly **50 cents on the dollar** to account for impairment typical in forced liquidations, and other current assets were written down further still. Cash and short-term equivalents were taken at face value. Applying these haircuts produces a more conservative NNWC figure that Graham considered more reflective of what an investor would actually recover. GeminIQ's pre-calculated [Current Ratio](/metrics/liquidity-ratios/current-ratio) and [Quick Ratio](/metrics/liquidity-ratios/quick-ratio) serve as initial liquidity filters, but the haircut-adjusted NNWC requires pulling the underlying component data from the as-filed balance sheet — a task GeminIQ's [Financial Statements](/features#financial-statements) view makes tractable.

---

## The One-Third Rule: Net-Net Risk in Plain English

Graham was clear-eyed about the strategy's limitations in a way that most modern summaries omit. His documented observation — drawn from his own extensive experience running net-net portfolios — was that within a diversified basket, roughly one-third of companies would recover to fair value and generate substantial gains, roughly one-third would remain cheap indefinitely without recovering (a slow grind near zero excess return), and roughly one-third would continue to deteriorate, consuming capital.

That distribution is not a problem for the strategy — it is the strategy. Net-net investing has never been about picking the individual winners within the universe. It is a portfolio approach built on the actuarial logic that the average outcome across a sufficiently diversified basket of deeply discounted companies is positive, even when individual names are genuinely troubled businesses. Graham recommended holding 20 to 30 positions simultaneously, not three or five. Concentrated bets on individual net-nets are a fundamentally different — and considerably riskier — approach that Graham himself did not endorse.

The practical implication: an investor who buys a single net-net because the NNWC ratio is attractive has not replicated Graham's strategy. They have made a concentrated bet on a troubled company with unknown catalysts. The position-sizing discipline and diversification requirement are integral to how the excess returns documented in the academic literature were generated.

GeminIQ's pre-calculated [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) is a useful first-pass solvency check to layer on net-net candidates. Graham's framework assumed the company is solvent and has not drawn down cash to crisis levels — candidates with Altman Z-Scores below **1.8** (the distress zone) represent a different kind of risk than a merely unfashionable company trading below liquid asset value. They are not automatically excluded: some genuine recovery situations exist at low Z-Scores. But they require a separate, explicit solvency assessment before sizing any position.

---

## The Data Quality Problem

Net-net screening is more sensitive to balance sheet accuracy than almost any other quantitative strategy because the entire thesis rests on the liquidation value of current assets. A **10% error in the current assets figure** can move a company from a true net-net with **1.3× NNWC coverage** to a company that does not qualify at all. That is not a rounding issue — it is the difference between a margin of safety and a false signal.

Three specific failure modes affect standard screening data when applied to this strategy.

**Receivables quality.** Standard financial data aggregators report total receivables as a single net line item. But as-filed XBRL data from SEC filings frequently includes separate disclosures for trade receivables, related-party receivables, and the allowance for doubtful accounts as distinct line items. A company that has quietly increased its allowance for doubtful accounts — a common early indicator of credit deterioration — has a lower true receivables value than the headline net figure suggests. When an aggregator collapses these into a single number, the increase in the allowance is invisible. GeminIQ preserves the as-filed line item structure, letting the analyst see the receivables sub-components exactly as the company reported them to the SEC.

**Inventory valuation.** Graham's **50 cents on the dollar** haircut for inventory was not arbitrary — it reflected the real discount typically required to liquidate inventory in a distressed scenario, where finished goods may be perishable, work-in-process has limited resale value, and raw materials must be sold in bulk. Getting the haircut right requires seeing the inventory breakdown in the filing: finished goods versus work-in-process versus raw materials, LIFO reserve disclosures, write-down history. Most aggregator screeners apply book value inventory without any sub-component visibility. GeminIQ's [Financial Statements](/features#financial-statements) view links back to the underlying XBRL source for each balance sheet line, preserving the filing's original inventory classification.

**Post-ASC 842 lease liabilities.** Since the adoption of ASC 842 in 2019, operating lease obligations appear on the balance sheet as right-of-use assets and corresponding liabilities. The current portion of those operating lease liabilities is a real claim on the company's near-term cash — it functions, in practice, as a current liability. But the classification of these as current versus non-current varies meaningfully across filers, and an aggregator applying a normalized balance sheet template can misclassify or omit them, understating the liability side of the NNWC equation. GeminIQ extracts lease liabilities as filed, without normalization. The metric tells the story — but only when the metric is sourced from the right place.

A standard screener will flag a micro-cap trading at **P/B 0.4×** and surface it as a net-net candidate. By pulling the raw balance sheet via GeminIQ's [Financial Statements](/features#financial-statements) view, you can verify whether the receivables allowance has been growing, whether the inventory is finished goods or work-in-process, and whether lease liabilities are fully captured on the liability side. That verification is the work. For a full breakdown of why this matters across strategies, see our post on [verifying financial data against the SEC filing](/blog/verify-financial-data-against-sec-filing).

---

## How to Find Net-Net Stocks in GeminIQ

GeminIQ's [Stock Screener](/features#screener) surfaces net-net candidates using filters built from as-filed SEC data. Because every metric is sourced directly from the raw EDGAR filing rather than a third-party aggregator, the [Current Ratio](/metrics/liquidity-ratios/current-ratio), [Price-to-Book Ratio](/metrics/valuation-metrics/price-to-book-ratio), and [Debt Ratio](/metrics/leverage-and-debt-ratios/debt-ratio) values you are filtering on reflect the actual balance sheet — not a normalized version of it.

The [GeminIQ Net-Net Stocks Screener](/screens/stock-screeners/net-net-stocks) uses three filters to identify the candidate pool: [Current Ratio](/metrics/liquidity-ratios/current-ratio) ≥ **2.0** (strong current asset coverage), [Price-to-Book Ratio](/metrics/valuation-metrics/price-to-book-ratio) ≤ **0.75** (trading well below book value), and [Debt Ratio](/metrics/leverage-and-debt-ratios/debt-ratio) ≤ **0.5** (manageable total liabilities relative to assets). Set the sort to Price-to-Book ascending to surface the deepest discounts first.

<center><sup>GeminIQ Stock Screener returning 194 net-net candidates with filters applied: Current Ratio ≥ 2.0, P/B ≤ 0.75, Debt Ratio ≤ 50%, sorted by P/B ascending. All figures sourced from each company's most recently filed 10-Q as reported to the SEC.</sup></center>

For each candidate returned, the confirmation step requires opening the company's [Financial Statements](/features#financial-statements) view and manually computing: (Current Assets − Total Liabilities) ÷ Market Cap. Any company where this ratio exceeds **1.0×** is a true Graham net-net. Any company where it exceeds **1.5×** — the margin of safety on top of the margin of safety — warrants the closest attention.

After confirming net-net status, GeminIQ's [Visualizations](/features#visualizations) tab allows you to chart total assets, total liabilities, and market cap side by side across reporting periods. A company where liabilities are growing faster than assets quarter over quarter is a deteriorating candidate. One where the asset base is stable or expanding while market cap remains compressed is a more durable position. Trend matters as much as the current ratio.

The final quality check: pull GeminIQ's pre-calculated [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) for each name. Remove candidates scoring below **1.8** from the initial list or flag them for a separate, explicit solvency analysis before assigning any position size.

---

## Net-Net and the Broader Value Toolkit

Net-net investing sits at the most extreme end of the asset-value spectrum in quantitative value investing. Understanding how it relates to adjacent strategies clarifies when to use it and how to construct a diversified value portfolio around it.

Joel Greenblatt's Magic Formula, which GeminIQ's [Stock Screener](/features#screener) supports directly, ranks companies on [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and earnings yield — two measures of operational quality and earnings-based cheapness. A Magic Formula company might trade at **P/B 4×** or **6×** and still appear on the screen because its returns on capital are exceptional. Net-net companies will almost never appear in that list. Their ROIC is often negligible or negative, which is precisely why they are trading below liquid asset value. The two strategies do not compete — they occupy completely different parts of the valuation universe. See our [Magic Formula investing guide](/blog/magic-formula-investing-explained) for how that strategy complements net-net in a diversified value approach.

The Piotroski F-Score is more naturally paired with net-net analysis. Piotroski's original research applied his nine-signal scoring framework specifically within the universe of low price-to-book stocks — the same starting population where net-nets are found. A high Piotroski score on a net-net candidate means the company's fundamentals are stabilizing or improving rather than deteriorating, which shifts it toward the one-third that recovers rather than the one-third that continues to decline. Running both filters simultaneously is one of the more disciplined modern implementations of Graham's approach. See our post on the [Piotroski F-Score as a value trap detector](/blog/piotroski-f-score-value-trap) for a full breakdown of how the scoring framework works within a value screen.

The consistent thread across all of these strategies is that data quality determines whether the signal is real. Net-net investing, more than any other quantitative approach, requires current asset and liability figures that match the actual filing — not a normalized template that smooths over the sub-components where the real information lives. That is not a technical footnote. It is the edge.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=net-net-stocks-graham-strategy)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: NOVAGOLD (NG) Q3 2026 Earnings: EPS -$0.08, Equity Loss Up 222%
source: https://www.geminiq.com/blog/novagold-earnings-q3-2026

### NOVAGOLD (NG) Q3 2026 Earnings: EPS -$0.08, Equity Loss Up 222%
NOVAGOLD's Q3 FY2026 10-Q shows no revenue and a diluted loss of $0.08 per share, against $0.04 a year earlier. Donlin Gold's equity loss rose 222% to $24.0 million, while operating cash flow was only -$3.3 million.

**[NOVAGOLD](/stocks/NG) (NG) reported no revenue for Q3 FY2026, the quarter ended August 31, 2026, and a diluted loss of $0.08 per share against $0.04 a year earlier, in an 8-K release and 10-Q both filed October 8, 2026. The $36.0 million net loss looks like a cash drain, yet operating cash flow was an outflow of only $3.3 million, because the Donlin Gold funding that pays for the loss runs through investing activities. Donlin's equity loss rose 222% to $24.0 million, and the company raised its 2026 spending guidance by $11.5 million to about $110.0 million, all of it in corporate costs.**

| Field | Value |
|---|---|
| Company | NOVAGOLD ($NG) |
| Quarter | Q3 FY2026, period ended August 31, 2026 |
| Earnings release | October 8, 2026 (Form 8-K) |
| 10-Q filed | October 8, 2026 |
| Revenue | **None** reported (development-stage company) |
| Diluted EPS | **-$0.08** (loss per share doubled from -$0.04) |
| Operating margin | n/a (no revenue) |
| Operating cash flow (TTM) | $-20.96 Million |
| Donlin Gold equity loss | **$23.97 Million (+222% YoY)** |

## NOVAGOLD Q3 2026 Net Loss, EPS and Operating Loss

[NOVAGOLD](/stocks/NG)'s Q3 2026 net loss was $36.0 million, up 130% from $15.6 million a year earlier, and its operating loss was the largest of the last 16 quarters. A company with no revenue and one asset would seem to have a loss that tracks head-office costs. At NOVAGOLD it tracks a partner's engineering budget.

**The Data:** Operating loss was **$36.0 million** against $13.7 million in Q3 2025 and $25.8 million in Q2. Of the $22.3 million increase, $16.5 million came from the equity loss on Donlin Gold (**$24.0 million** against $7.5 million) and $5.8 million from general and administrative expense ($12.0 million against $6.3 million). Interest income of $3.8 million, up from $1.2 million, offset part of it. Weighted shares rose 7.9% to 438.8 million, so the loss per share doubled while the net loss grew 130%.

**Why:** The equity loss is [NOVAGOLD](/stocks/NG)'s 60% share of Donlin Gold's mineral property expenditures, $23.8 million this quarter per Note 5, as the Bankable Feasibility Study (BFS) work accelerates. The release attributes the higher G&A to professional fees on the pending Donlin Gold transaction with Paulson. Had the share count stayed at last year's 406.5 million, the loss per share would have been about $0.09 instead of $0.08. The net loss was the second-largest of the last 16 quarters, so the overhead is not what moved it.

<center><sup>GeminIQ Financial Statements show `Operating Income Loss` and `Net Income Loss` of -$36.0 million each in the quarter ended August 31, 2026, against -$13.7 million and -$15.6 million a year earlier. The purple box marks the Q3 2026 net loss.</sup></center>

<center><sup>GeminIQ Visualizations plot `Income Loss From Equity Method Investments` as bars and `General And Administrative Expense` as a line across nine quarters. The callout marks the Q3 2026 equity loss of about $24.0 million, the line that drove the increase.</sup></center>

## What NOVAGOLD's Q3 2026 10-Q Shows Beyond the Press Release

[NOVAGOLD](/stocks/NG)'s Q3 2026 operating cash flow was an outflow of $3.3 million, against $0.9 million a year earlier. The release led with the $36.0 million loss and $343.4 million of cash and term deposits; the cash flow statement shows where the money left.

A reader who saw the $36.0 million loss would expect operating cash outflow of similar size. Instead the filing puts most of the cash in a different section.

**The Data:** Operating cash flow of **-$3.3 million** was the eighth-lowest of the last 16 quarters, an unremarkable rank beside the second-largest loss. Funding of Donlin Gold, $24.8 million, sits in investing activities. Over nine months the filing shows operating cash outflow of $14.9 million and **$56.7 million** of Donlin funding. The release itself puts net operational cash expenditures at $28.1 million, the $24.8 million plus $3.3 million of corporate costs. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) was -$21.0 million over the trailing twelve months, a figure smaller than nine months of Donlin funding alone.

**Why:** Under the equity method described in Note 5, cash funding raises the carrying value of the Donlin investment, now $222.9 million, and Donlin's spending is then written off as the equity loss. The same dollars reach net loss and investing cash flow but never operating cash flow: Q3's equity loss was $24.0 million against $24.8 million of funding. That placement is standard for an equity-method holder, so the metric is not wrong; it measures only the corporate side of a company whose spending is mostly project-side.

<center><sup>GeminIQ Financial Statements show `Net Cash Provided By Used In Operating Activities` of -$3.3 million for the quarter ended August 31, 2026, and `Share Based Compensation` of $2.3 million, a non-cash item inside the loss. The purple box marks operating cash flow, which excludes the $24.8 million of Donlin funding.</sup></center>

## NOVAGOLD 2026 Guidance, Cash and Barrick Note After Q3

In the 8-K, [NOVAGOLD](/stocks/NG) raised fiscal 2026 operating expenditure guidance by $11.5 million to approximately $110.0 million, from the $98.5 million it guided after Q2. Readers would take a raise during a BFS ramp as project spending creeping up. The raise sits elsewhere.

**The Data:** Guided Donlin Gold funding is unchanged at $78.8 million, while corporate G&A excluding share-based compensation rose to about $31.2 million from $19.7 million. The company says $7.7 million of the increase was incurred through Q3 and $3.8 million is expected in Q4, all tied to the Paulson transactions. Nine-month Donlin funding of **$56.7 million** is 72% of the $78.8 million with one quarter left. The balance sheet held $146.4 million of cash and $197.0 million of term deposits, and GeminIQ's [Current Ratio](/metrics/liquidity-ratios/current-ratio) was 44.51x against 26.91x a year earlier.

**Why:** The company attributes the raise to legal and professional fees and says it expects them to stay elevated into early fiscal 2027. It also says a portion of 2026 funding will relate to Donlin's 2027 budget, because December 2026 activities are pre-funded in November. The Barrick promissory note carried $177.5 million on August 31, against an option to prepay it in full for $100.0 million on or before December 3, 2026; management says it is fully funded to do so and to finish the BFS. Management also says it expects to raise additional capital later to support detailed engineering.

## How NG Stock Has Moved After Past Earnings Reports

Across [NOVAGOLD](/stocks/NG)'s last 12 10-Q filings with completed windows (filed October 3, 2023 to June 24, 2026), the median one-month return after filing was -3.9%, and it was positive after 5 of 12. These figures describe how NOVAGOLD's stock moved after its past filings; they are a historical association, not a forecast.

**The Data:** The one-month range ran from -25.2% to +49.0%, and the three-month median was +0.3% with 6 of 12 positive. Past Q3 filings were followed by one-month returns of +4.3% (FY2023), -14.3% (FY2024) and -15.7% (FY2025). This filing's window has not elapsed. The [Earnings Reaction Heat Map](/features#price-variance) shows each cell. On ownership, GeminIQ's 13F data put institutions at 74.86% on June 30, 2026, up 6.71 points from a year earlier and the second-highest of the last 16 quarters; the September 30 filings have not landed.

**Why:** A spread that wide around a near-zero median says the post-filing move depends little on the direction of the loss, which has been negative throughout. Form 4 filings dated February 6, 2025 to February 6, 2026 show five purchases totaling $50.3 million and one $115 sale, after a prior twelve months with neither. A buy-heavy record runs against the roughly 3:1 sell-to-buy base rate, though later filings are not yet in the data.

<center><sup>The GeminIQ Earnings Reaction Heat Map shows returns 1-3 months after each 10-Q filing. The outlined column marks the one-month return after each filing, and the Q3 FY2026 cells show "-" because their windows have not elapsed.</sup></center>

<center><sup>GeminIQ Insider Transactions summarize SEC Form 4 purchases and sales per insider for filings dated February 6, 2025 to February 6, 2026, the latest filing date in the data. Purchases dominate the total.</sup></center>

For a company that equity-accounts its only asset, the investing section holds the burn rate that the operating line leaves out.

## Frequently Asked Questions

### When does NOVAGOLD report earnings?

NOVAGOLD reported its Q3 FY2026 results on October 8, 2026, and filed the 10-Q the same day. Last year it filed its fourth-quarter results on January 22, 2026, and the year before on January 23, 2025. That is a filing pattern, not a forecast of the next date.

### Does NOVAGOLD pay a dividend?

NOVAGOLD paid no dividend in the quarter ended August 31, 2026, and none over the trailing twelve months. The company has no revenue and funds its Donlin Gold share from cash raised through share offerings.

### Is NOVAGOLD profitable?

NOVAGOLD is not profitable. It lost $36.0 million in Q3 FY2026 and $77.0 million over nine months, and GeminIQ's [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) was -25.97% on a trailing basis. Its balance sheet is liquid, with $349.8 million of current assets against $7.9 million of current liabilities.

### What was NOVAGOLD's free cash flow in Q3 2026?

NOVAGOLD's Q3 FY2026 free cash flow was -$3.3 million, with no capital expenditure, and -$21.0 million over the trailing twelve months. Both figures exclude the $24.8 million the company funded to Donlin Gold, which the filing records in investing activities.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=novagold-earnings-q3-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference NOVAGOLD RESOURCES INC.'s
Q3 2026 10-Q (filed October 8, 2026, period ending August 31, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed October 8, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/1173420/000117184326006530/ng20260831_10q.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1173420/000117184326006528/exh_991.htm).</sup>

---

## Blog: NVIDIA Q1 FY2027 10-Q: 99% ROIC, Slowing Inventory Turns
source: https://www.geminiq.com/blog/nvidia-10q-analysis-q1-fy2027

### NVIDIA Q1 FY2027 10-Q: 99% ROIC, Slowing Inventory Turns
NVIDIA's Q1 FY2027 10-Q shows TTM Return on Invested Capital at 99.1%, down from 112.3% a year ago as the invested capital base grew faster than after-tax profit. A less-discussed metric has moved the other way: inventory turnover has fallen from 5.16x to 3.53x over the same period.

**[NVIDIA](/stocks/NVDA) ($NVDA) just filed its Q1 FY2027 10-Q (filed May 20, 2026). Most coverage of this stock stays fixated on the quarterly revenue print. The more interesting story is what's happening beneath it: trailing twelve-month Return on Invested Capital sits at 99.1%, down from 112.3% a year ago. But a less-discussed operational metric has moved in the opposite direction — inventory turnover has slowed meaningfully over the same period, and that nuance is worth understanding alongside the headline number.**

| Field                    | Value          |
| ------------------------ | -------------- |
| Ticker                   | $NVDA          |
| Filing                   | Q1 FY2027 10-Q |
| Filed                    | May 20, 2026   |
| Period End               | April 26, 2026 |
| ROIC (TTM)               | **99.1%**      |
| Inventory Turnover (TTM) | **3.53x**      |

## The ROIC Story: 112.3% to 99.1%

A [ROIC](/blog/roic-return-on-invested-capital-explained) near 100% sounds almost implausible. What the trend shows is a business easing off an even more implausible peak.

**The Data:** [NVIDIA's](/stocks/NVDA) TTM Net Operating Profit After Tax is **$136.73 Billion**, against Average [Invested Capital](/metrics/calculated-values/invested-capital) of **$137.91 Billion** — a ROIC of **99.1%**, down from **112.31%** a year ago. The path is not a straight line: **112.31%** in Q1 FY2026, then **103.07%**, **100.41%**, a **91.74%** trough in the January 2026 quarter, and back up to **99.15%** on this filing. TTM Net Income sits at **$159.61 Billion**, on TTM Revenue of **$253.49 Billion**, with a TTM Operating Margin of **64.0%** and a TTM [Gross Margin](/metrics/margin-metrics/gross-profit-margin) of **74.1%**.

**The GeminIQ Edge:** Pulling [Calculated Metrics](/features#calculated-metrics) alongside the raw Income Statement shows this isn't a one-quarter spike. ROIC has compressed across the past year as the invested capital base grew faster than after-tax profit, then turned back up in the most recent quarter. A business converting nearly a dollar of after-tax operating profit for every dollar of capital deployed is an exceptionally rare structural position, not a screener artifact.

<center><sup>GeminIQ Calculated Metrics showing NVIDIA's ROIC TTM easing from 112.31% (Q1 FY2026) to 99.15% (Q1 FY2027) with a 91.74% trough in the January 2026 quarter, alongside Gross Profit Margin TTM of 74.15% and Operating Profit Margin TTM of 64.02%.</sup></center>

## The Buyback Engine Continues

Unlike many large technology companies where stock-based compensation quietly offsets buybacks, [NVIDIA's](/stocks/NVDA) share count keeps shrinking.

**The Data:** Basic shares outstanding have fallen from **24.578 Billion** in mid-2024 to **24.286 Billion** as of this filing — a steady, continued decline rather than a one-time reduction. TTM Free Cash Flow stands at **$119.08 Billion**, providing ample capacity to continue funding repurchases alongside R&D and capacity investment.

**The GeminIQ Edge:** Tracking [Financial Statements](/features#financial-statements) share count data across multiple periods, rather than a single snapshot, confirms the reduction is sustained rather than a single buyback announcement inflating one quarter's optics.

<center><sup>GeminIQ Financial Statements showing NVIDIA's basic shares outstanding declining from 24.578 Billion (mid-2024) to 24.286 Billion (Q1 FY2027), alongside TTM Free Cash Flow of $119.08 Billion.</sup></center>

## Inventory Turnover Is Actually Slowing

This doesn't fit the purely bullish version of this story, and burying it wouldn't be honest.

**The Data:** [NVIDIA's](/stocks/NVDA) TTM Inventory Turnover has fallen from **5.16x** a year ago to **3.53x** as of this filing — a meaningful, multi-quarter decline, not a single noisy print. This is a lower figure than the "elite, moving product four times a year" framing that circulated based on an earlier filing period.

**The GeminIQ Edge:** Pulling [Calculated Metrics](/features#calculated-metrics) across a full multi-quarter trend, rather than a single period in isolation, is the only way to catch a directional shift like this. A declining turnover ratio can reflect deliberate inventory build ahead of anticipated demand just as easily as slowing sell-through, and the filing data alone doesn't resolve which explanation is correct — but the trend itself is real and worth tracking going forward, not something to ignore because the ROIC headline is more flattering.

<center><sup>GeminIQ Calculated Metrics showing NVIDIA's TTM Inventory Turnover declining from 5.16x to 3.53x over the trailing year.</sup></center>

## Smart Money and the Insider Record

Two different signals around [NVIDIA](/stocks/NVDA) worth checking on their own terms.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has moved in a fairly narrow band, ranging from **59.8%** to **63.3%** over the trailing year and sitting at **61.5%** as of the most recent 13F (March 2026, filed with the standard lag) — stable, not a dramatic shift either direction. [Insider Transactions](/features#insider-transactions) show a heavily sale-weighted record: 723 sales against 23 purchases in the available history.

**The GeminIQ Edge:** Neither figure is dramatic on its own, and that's the honest read rather than a manufactured one. A stable institutional base and a sale-heavy insider pattern are standard for a company whose stock has appreciated this dramatically over the trailing several years, not a signal worth over-reading in either direction.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership holding a 59.8%-63.3% band over the trailing year, ending at 61.5% as of March 2026.</sup></center>

## Frequently Asked Questions

### What is NVIDIA's current ROIC?

NVIDIA's TTM Return on Invested Capital is 99.1%, down from 112.3% a year ago, driven by NOPAT of $136.73 Billion against Average Invested Capital of $137.91 Billion.

### Is NVIDIA's inventory turnover improving or declining?

Declining. TTM Inventory Turnover has fallen from 5.16x a year ago to 3.53x as of the Q1 FY2027 10-Q, a meaningful multi-quarter trend rather than a single-period anomaly.

### Is NVIDIA still buying back stock?

Yes. Basic shares outstanding have fallen from 24.578 Billion in mid-2024 to 24.286 Billion as of this filing, a sustained decline funded by TTM Free Cash Flow of $119.08 Billion.

### When did NVIDIA last file its 10-Q, and what period does it cover?

NVIDIA's most recent filing is a Form 10-Q filed May 20, 2026, covering the fiscal quarter ended April 26, 2026 (Q1 FY2027).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=nvidia-10q-analysis-q1-fy2027)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference NVIDIA Corporation's Q1 FY2027 10-Q (filed May 20, 2026, period ending April 26, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001045810/000104581026000052/nvda-20260426.htm).

---

## Blog: Operating Leases vs. Debt: The ASC 842 Problem
source: https://www.geminiq.com/blog/operating-leases-vs-debt-asc-842

### Operating Leases vs. Debt: The ASC 842 Problem
Most sources report Lululemon's total debt at $2.14 billion. Its actual interest-bearing debt is $0 — both are true, because $2.14 billion is entirely operating lease liabilities under ASC 842, an accounting standard that moved leases onto the balance sheet in 2019 without changing how their cost is treated on the income statement. This guide covers exactly what ASC 842 changed and didn't change, the full Lululemon case where this distinction produces a genuinely misleading debt figure, and how to separate real interest-bearing debt from lease liabilities on any company's balance sheet.

Most sources report [Lululemon's](/stocks/LULU) total debt at **$2.14 billion**. Lululemon's actual interest-bearing debt is **$0**. Both statements are true, depending entirely on whether "debt" includes operating lease liabilities. The fact that a company can carry zero borrowings while showing up on a debt screen as leveraged is not a data error. It's the direct, foreseeable consequence of an accounting standard that changed where lease obligations live on the balance sheet without changing what kind of obligation they actually are.

This guide covers exactly what ASC 842 changed in 2019, what it deliberately left unchanged, the full Lululemon case where this distinction produces a genuinely misleading debt figure, and how to tell a real interest-bearing liability from an operating lease liability on any company's balance sheet before a screener's "total debt" field does the conflating for you. Lululemon appears here strictly as the illustration — the subject is the accounting standard, not the company. The business itself, its growth trajectory, and its valuation are covered separately in our [Lululemon stock analysis](/blog/lululemon-stock-analysis-2026).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=operating-leases-vs-debt-asc-842)**

---

## Table of Contents

- [What ASC 842 Actually Changed](#what-asc-842-actually-changed)
- [What ASC 842 Didn't Change](#what-asc-842-didnt-change)
- [The Lululemon Example: $2.14 Billion That Isn't Debt](#the-lululemon-example-214-billion-that-isnt-debt)
- [Why Aggregators Get This Wrong](#why-aggregators-get-this-wrong)
- [How to Tell Lease Liabilities From Real Debt on Any Balance Sheet](#how-to-tell-lease-liabilities-from-real-debt-on-any-balance-sheet)
- [Which Industries This Affects Most](#which-industries-this-affects-most)
- [The Metrics That Break Under ASC 842, and the Ones That Still Work](#the-metrics-that-break-under-asc-842-and-the-ones-that-still-work)
- [Reading Lease Liabilities Correctly on GeminIQ](#reading-lease-liabilities-correctly-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What ASC 842 Actually Changed

Before ASC 842 took effect for public companies in fiscal years beginning after December 15, 2018, operating leases lived entirely off the balance sheet. A retailer's store leases, an airline's aircraft leases, a manufacturer's equipment leases — all of it sat in the footnotes as disclosed "future minimum lease payments," a schedule of obligations with no corresponding liability on the face of the balance sheet at all. A company could run its entire physical footprint on leased real estate and show none of that commitment as a liability anywhere an investor would naturally look.

ASC 842 moved that obligation onto the balance sheet, for the first time, as two matched entries: a right-of-use asset representing the value of the leased space or equipment, and a corresponding operating lease liability representing the obligation to make future payments. For companies with hundreds of long-term retail, restaurant, or aircraft leases, this was not a cosmetic change. Total liabilities on the balance sheet grew by a real, often multi-billion-dollar amount overnight, for a company that hadn't taken on a single dollar of new borrowing.

---

## What ASC 842 Didn't Change

The part of the standard that creates the actual analytical trap is what it left alone. Operating lease cost continues to be recognized as a single, straight-line operating expense on the income statement, sitting above operating income — exactly where it sat before 2019. No portion of it gets reclassified as interest expense the way a loan payment splits into principal and interest. The balance sheet now shows a lease liability that looks, structurally, like debt. The income statement shows an expense that behaves, structurally, like rent — because that's exactly what it still is.

That mismatch is the entire problem. Any screening tool, ratio, or platform that pulls "total liabilities" or a blanket "debt" tag off the balance sheet without separating operating lease liabilities from actual borrowings inherits a number that looks like leverage but generates none of the financial characteristics leverage normally carries — no interest expense, no maturity default risk in the conventional sense, no covenant package tied to a lender.

---

## The Lululemon Example: $2.14 Billion That Isn't Debt

Lululemon's Q1 FY2026 10-Q reports total debt that most third-party sources put at **$2.14 billion**. Broken down on the actual balance sheet, that figure is **$357.2 million** in current operating lease liabilities and **$1.78 billion** in non-current operating lease liabilities — and nothing else. Lululemon's interest-bearing debt, the kind that generates an interest expense line and a maturity schedule tied to a lender, is **$0**.

The distortion cascades through every ratio built on that "debt" figure. [Net Debt](/metrics/calculated-values/net-debt), calculated correctly as interest-bearing debt minus cash, is actually **negative $1.51 billion** — a net cash position, not a net debt position. [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) reads **-0.59x**. [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) breaks entirely, since reported interest expense TTM is **$0** and any EBIT divided by zero returns an undefined or meaningless result. [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), which correctly measures total liabilities against equity rather than debt specifically, reads **0.77x** — a real number, but one that reflects total liabilities including the lease obligations, not a borrowing-based leverage figure at all. A company with genuinely zero debt and over a billion and a half dollars in net cash appears, across a naive reading of several of the most common leverage screens, to be carrying real financial risk it does not actually carry.

---

## Why Aggregators Get This Wrong

The error is almost always structural rather than deliberate. A data pipeline built around a single, blanket "total debt" or "long-term liabilities" tag — or one that sums every liability-side line item without checking which specific tag each one carries — pulls operating lease liabilities into the same bucket as notes payable, term loans, and bonds, because both categories sit in the same general region of the balance sheet and both increase total liabilities in the same direction. Nothing about the raw dollar figure signals the difference. Only the specific XBRL tag attached to each line does.

That's exactly the distinction a platform built on as-filed tag preservation can maintain and a platform built on a normalized "total debt" bucket cannot. `OperatingLeaseLiabilityCurrent` and `OperatingLeaseLiabilityNoncurrent` are different tags from `LongTermDebtNoncurrent` or `ShortTermBorrowings`, filed separately, for a reason — collapsing them into one number for convenience is where the misclassification actually happens. Whether a given platform serves you the as-filed line or a processed, pre-summed version of it is the single variable that determines which debt figure you see, which is why it's the first thing worth checking about any data source — the comparison we run against [S&P Capital IQ](/competitor-comparison/sp-capital-iq) starts from exactly that question.

---

## How to Tell Lease Liabilities From Real Debt on Any Balance Sheet

The check generalizes past any single company. Two tests, applied together, catch this on nearly every filing. First: does the company report a non-trivial interest expense line on the income statement? A company with billions in balance sheet "debt" and interest expense near zero is very likely carrying lease liabilities rather than borrowings, since actual debt almost always generates a corresponding interest charge. Second: does the balance sheet itself label the liability lines separately? Under ASC 842, operating lease liabilities are required to be presented as their own line items, distinct from long-term debt, which means the separation is available directly in the filing without any calculation — it just requires reading the actual line items rather than trusting a single pre-summed total.

A company whose reported "debt" disappears almost entirely once operating lease liabilities are excluded, while its interest expense stays near zero throughout, is a company with real estate or equipment commitments — not a leveraged balance sheet.

---

## Which Industries This Affects Most

Retail chains, restaurant companies, and airlines carry the largest share of this distortion, because all three run substantial physical footprints on leased real estate or leased aircraft rather than owned assets. A national retailer with hundreds of store leases, or an airline with a fleet held mostly under lease rather than purchased outright, can show balance sheet lease liabilities running into the billions with genuinely modest or zero conventional borrowing behind it. The pattern isn't limited to these sectors, but it concentrates there because leasing rather than owning physical infrastructure is a structural feature of how those business models operate, not an unusual financing choice any single company made.

---

## The Metrics That Break Under ASC 842, and the Ones That Still Work

Laid side by side, the Lululemon figures above sort the common leverage checks into two groups — the ones that survive a balance sheet full of lease liabilities and the ones that don't:

| Metric | Under ASC 842 | Why | Lululemon reading |
| --- | --- | --- | --- |
| Screener "total debt" | Breaks | A blanket debt tag pulls `OperatingLeaseLiability` lines in alongside borrowings | $2.14B reported vs. $0 interest-bearing |
| [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) | Breaks | Reported interest expense TTM is $0; EBIT divided by zero returns nothing usable | Undefined |
| [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) | Misleading, not broken | Correctly measures total liabilities against equity, so lease obligations are inside it by design | 0.77x |
| [Net Debt](/metrics/calculated-values/net-debt) | Works | Built from interest-bearing debt minus cash, so lease liabilities never enter it | Negative $1.51B (net cash) |
| [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) | Works | Inherits the same interest-bearing-only debt figure | -0.59x |
| [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda) | Works | Built from the same interest-bearing-only debt figure, so lease liabilities never enter it either | **0.00x** — total debt of $0 against $2.57B of TTM EBITDA |
| [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) | Least distorted | Composite: working capital, retained earnings, and market value of equity dilute any single debt input | 5.70, clear of the 2.99 safe-zone threshold |

Not every leverage metric breaks the same way. [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), when calculated using a total debt figure that deliberately includes operating lease liabilities as their own explicit component — rather than either excluding them entirely or conflating them silently with conventional debt — remains a genuinely useful measure of total financial obligation, lease and loan alike, relative to the earnings available to service both. The failure mode isn't using a metric that accounts for lease liabilities; it's using one that either hides them entirely or mislabels them as something they're not.

[Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score) is the composite check least distorted by this specific issue, since it draws on working capital, retained earnings, and market value of equity alongside leverage rather than isolating a single debt figure. Lululemon's Z-Score of **5.70**, well clear of the **2.99** safe-zone threshold, tells a consistent story with the zero-interest-bearing-debt balance sheet in a way that a naive debt-to-equity read does not.

One boundary is worth stating plainly, because this guide is deliberately narrow: what follows is how ASC 842 distorts each of these ratios, not how the ratios themselves are constructed or interpreted. The formulas, the thresholds, and the full read on each are covered where they belong — [Interest Coverage Ratio Explained](/blog/interest-coverage-ratio-explained), [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda), and [Gross Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained). The only thing ASC 842 adds to any of them is the question of which liabilities went into the numerator in the first place.

---

## Reading Lease Liabilities Correctly on GeminIQ

GeminIQ's [Financial Statements](/features#financial-statements) view carries operating lease liabilities as their own distinct line items — current and non-current — exactly as the company filed them, alongside conventional debt lines that carry their own separate tags. Neither gets silently folded into the other. [Net Debt](/metrics/calculated-values/net-debt) and [Interest Coverage Ratio](/metrics/leverage-and-debt-ratios/interest-coverage-ratio) both draw specifically from interest-bearing debt, which is why they correctly show Lululemon's actual position — a net cash balance sheet — rather than the misleading leveraged read a blanket total-liabilities figure would produce.

A more complete walkthrough of this exact Lululemon balance sheet, alongside six other checks run against the same filing, is covered in [Financial Metrics for Value Investors](/blog/financial-metrics-value-investors).

---

## Frequently Asked Questions

### Does ASC 842 mean operating leases are debt now?

Not in the conventional sense. ASC 842 requires operating lease obligations to appear on the balance sheet as a liability, but it did not reclassify the associated expense as interest, and it did not turn a lease into a loan. The obligation is real, but it doesn't carry the same interest-expense signature or default characteristics conventional debt does.

### Why does Lululemon show $2.14 billion in "debt" with zero interest expense?

Because that $2.14 billion is entirely operating lease liabilities under ASC 842, not interest-bearing borrowings. Lululemon's actual debt is $0, and it holds a net cash position once its cash balance is compared against that zero, rather than against the lease liability figure most sources report as debt.

### How can I tell if a company's reported "debt" includes operating leases?

Check the balance sheet's actual line items — ASC 842 requires operating lease liabilities to be presented separately from long-term debt. If interest expense on the income statement is near zero relative to the reported debt figure, that's a strong signal the "debt" is substantially lease liabilities rather than borrowings.

### Which industries are most affected by this issue?

Retail chains, restaurant companies, and airlines, because all three typically run large physical footprints on leased real estate or leased aircraft rather than owned assets, producing substantial balance sheet lease liabilities that have nothing to do with conventional borrowing.

The $2.14 billion was never hidden. It's sitting on Lululemon's own balance sheet, correctly labeled, exactly as ASC 842 requires. The only thing standing between that label and a misleading debt figure is whether whoever's reading it — or whatever platform is summarizing it — actually reads the line.

---

## Related Reading

- [Financial Metrics for Value Investors: A Lululemon Case Study](/blog/financial-metrics-value-investors) — the full seven-check workflow this example is drawn from.
- [Interest Coverage Ratio Explained](/blog/interest-coverage-ratio-explained) — how this same ASC 842 issue breaks the interest coverage ratio specifically.
- [Gross Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained) — the leverage metric that handles lease liabilities correctly when built with them as an explicit component.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=operating-leases-vs-debt-asc-842)**

## Research Faster. Invest Smarter.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. We built GeminIQ because we believe you deserve a better fundamental analysis tool—one that goes beyond basic price charts and processed numbers. We extract our data directly from SEC 10-K and 10-Q filings to ensure that when you look at a balance sheet or a cash flow statement, you are seeing the numbers exactly how the company reported them. Our goal is to give you the tools to verify the narrative for yourself using clean, traceable data. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference lululemon athletica inc.'s Q1 FY2026 10-Q (filed June 4, 2026, period ending May 3, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001397187/000139718726000078/lulu-20260503.htm).

---

## Blog: Palantir Q1 2026 10-Q: Margin Story, Ongoing Dilution
source: https://www.geminiq.com/blog/palantir-10q-analysis-q1-2026

### Palantir Q1 2026 10-Q: Margin Story, Ongoing Dilution
Palantir's Q1 FY2026 10-Q shows TTM operating margin has climbed to 38.1%, up from 10.8% at the end of FY2024, a sustained improvement. Alongside it, basic shares outstanding have grown more than 7% over the same period.

**[Palantir](/stocks/PLTR) ($PLTR) just filed its Q1 FY2026 10-Q (filed May 5, 2026). The operating leverage story here is real: trailing twelve-month operating margin has climbed to 38.1%, up from 10.8% at the end of FY2024. That's a genuine, dramatic improvement worth taking seriously. Alongside it, basic shares outstanding have grown more than 7% over roughly the same stretch. Both things are true at once, and neither should be ignored in favor of the other.**

| Field                     | Value          |
| ------------------------- | -------------- |
| Ticker                    | $PLTR          |
| Filing                    | Q1 FY2026 10-Q |
| Filed                     | May 5, 2026    |
| Period End                | March 31, 2026 |
| Operating Margin (TTM)    | **38.1%**      |
| Basic Shares Growth (2yr) | **+7.3%**      |

## The Margin Expansion Story

The operating leverage narrative around this stock is not hype. The trend is sustained and the numbers back it up.

**The Data:** [Palantir's](/stocks/PLTR) TTM Operating Margin has climbed from **10.8%** at the end of FY2024 to **38.1%** as of this filing, a steady, multi-quarter climb rather than a single strong quarter. TTM [Gross Margin](/metrics/margin-metrics/gross-profit-margin) sits at **84.1%**. TTM Net Income is **$2.28 Billion** on TTM Revenue of **$5.22 Billion**. TTM [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) has climbed alongside it, from **7.8%** to **36.8%** over the same period.

**The GeminIQ Edge:** Pulling [Calculated Metrics](/features#calculated-metrics) as a full trend, rather than a single snapshot, confirms this margin expansion has compounded quarter over quarter rather than arriving in one jump. That distinction matters — a steady multi-quarter trend is a far stronger signal than a single beat.

<center><sup>GeminIQ Calculated Metrics showing Palantir's TTM Operating Margin climbing from 10.8% to 38.1% and TTM ROIC from 7.8% to 36.8%, alongside TTM Gross Margin rising from 80.3% to 84.1%, across the six quarters from the end of FY2024 to Q1 FY2026.</sup></center>

## The Share Count Keeps Climbing

Margin expansion tells you how efficiently [Palantir](/stocks/PLTR) runs. Share count tells you how much of that efficiency actually accrues to a given shareholder over time.

**The Data:** Basic shares outstanding have grown from approximately **2.232 Billion** in mid-2024 to **2.394 Billion** as of this filing, an increase of roughly **7.3%** over two years. Diluted shares stand at **2.571 Billion**. This is a continued, gradual increase rather than a flat or shrinking share count.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) share count data across a full multi-year trend, rather than a single period in isolation, shows the direction clearly: management's margin gains are real, but they're being spread across a growing share base rather than a fixed or shrinking one.

<center><sup>GeminIQ Financial Statements showing Palantir's basic shares outstanding growing from approximately 2.232 Billion (mid-2024) to 2.394 Billion (Q1 FY2026), a roughly 7.3% increase.</sup></center>

## The Free Cash Flow Machine

Alongside the margin expansion, the cash conversion story remains genuinely strong.

**The Data:** [Palantir's](/stocks/PLTR) TTM Operating Cash Flow is **$2.72 Billion** against TTM CapEx of just **$35.1 Million**, for TTM Free Cash Flow of **$2.69 Billion** — a capital-light model converting the vast majority of operating cash flow directly into free cash flow.

**The GeminIQ Edge:** Pulling [Financial Statements](/features#financial-statements) cash flow data directly shows just how little capital this business needs to reinvest in itself relative to the cash it generates, a structural characteristic of a software-driven model rather than a one-time efficiency gain.

<center><sup>GeminIQ Financial Statements showing Palantir's TTM Operating Cash Flow of $2.72 Billion against TTM CapEx of just $35.1 Million, for TTM Free Cash Flow of $2.69 Billion.</sup></center>

## Smart Money and the Insider Record

Two different signals around [Palantir](/stocks/PLTR) worth checking on their own terms.

**The Data:** [Institutional Ownership](/features#institutional-ownership) has climbed from **48.5%** in December 2024 to **52.0%** as of the most recent 13F (March 2026, filed with the standard lag). [Insider Transactions](/features#insider-transactions) show an overwhelmingly sale-weighted record: 625 sales against a single purchase in the available history.

**The GeminIQ Edge:** The institutional climb is a modest, steady positive. The insider record is the more striking of the two — a 625-to-1 sale-to-purchase ratio is a considerably more lopsided pattern than typical for a mature large-cap, and it's worth weighing against the stock's valuation (currently trading at roughly 153x trailing earnings) rather than dismissing as routine equity-comp-driven selling.

<center><sup>GeminIQ Institutional Ownership tracker showing ownership climbing from 48.5% (December 2024) to 52.0% (March 2026, most recent 13F).</sup></center>

## Frequently Asked Questions

### What is Palantir's current operating margin?

Palantir's TTM Operating Margin is 38.1%, up from 10.8% at the end of FY2024, a sustained multi-quarter expansion rather than a single-quarter improvement.

### Is Palantir still diluting shareholders?

Yes. Basic shares outstanding have grown from approximately 2.232 Billion in mid-2024 to 2.394 Billion as of the Q1 FY2026 10-Q, an increase of roughly 7.3% over two years.

### How strong is Palantir's free cash flow?

TTM Free Cash Flow is approximately $2.69 Billion, on TTM Operating Cash Flow of $2.72 Billion against TTM CapEx of just $35.1 Million, reflecting a highly capital-light business model.

### When did Palantir last file its 10-Q, and what period does it cover?

Palantir's most recent filing is a Form 10-Q filed May 5, 2026, covering the fiscal quarter ended March 31, 2026 (Q1 FY2026).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=palantir-10q-analysis-q1-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Palantir Technologies Inc.'s Q1 FY2026 10-Q (filed May 5, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000028/pltr-20260331.htm).

---

## Blog: Pay Versus Performance: Reading Executive Comp in the Proxy
source: https://www.geminiq.com/blog/pay-versus-performance-table-explained

### Pay Versus Performance: Reading Executive Comp in the Proxy
The Pay Versus Performance table shows what executives were actually paid once equity awards are marked to the stock price that mattered — a figure the Summary Compensation Table does not provide. This guide covers Item 402(v) compensation actually paid, the CEO pay ratio, the Rule 10D-1 clawback policy, the say-on-frequency vote, and the equity award detail tables sitting behind the headline totals.

A say-on-pay vote result gets reported as a single approval percentage, and the story usually ends there. What actually determines whether that percentage will hold up over multiple years sits three disclosures deeper in the same proxy: the table that shows what executives were actually paid once equity awards are marked to the stock price that mattered, the ratio between CEO pay and the median employee, and the policy governing whether a company can claw back compensation after a restatement.

[Our DEF 14A guide](/blog/what-is-def-14a) covers the proxy statement itself — the CD&A, the Summary Compensation Table, the say-on-pay vote and the approval bands that tell you whether shareholders are satisfied. This guide goes further, into the specific quantitative disclosures — some only a few years old — that determine whether that satisfaction is actually earned: the Pay Versus Performance table's "compensation actually paid" figure, the CEO pay ratio, the compensation clawback policy every listed company has been required to adopt since 2023, and the say-on-frequency vote that decides how often shareholders get to weigh in at all.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pay-versus-performance-table-explained)**

---

## Table of Contents

- [What the DEF 14A Guide Already Covers](#what-the-def-14a-guide-already-covers)
- [The Pay Versus Performance Table: Compensation Actually Paid](#the-pay-versus-performance-table-compensation-actually-paid)
- [The CEO Pay Ratio](#the-ceo-pay-ratio)
- [The Compensation Clawback Policy](#the-compensation-clawback-policy)
- [The Say-on-Frequency Vote: How Often Shareholders Get a Say](#the-say-on-frequency-vote-how-often-shareholders-get-a-say)
- [Beyond the Summary Compensation Table: The Equity Award Detail Tables](#beyond-the-summary-compensation-table-the-equity-award-detail-tables)
- [Reading Compensation Data Against What GeminIQ Already Tracks](#reading-compensation-data-against-what-geminiq-already-tracks)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What the DEF 14A Guide Already Covers

The Compensation Discussion and Analysis and Summary Compensation Table are the foundation: the CD&A explains the compensation philosophy and peer group methodology behind executive pay, and the Summary Compensation Table reports the standardized dollar total for each named executive officer. The say-on-pay vote itself — the non-binding shareholder approval of that pay package, and the approval percentages that separate a routine result from a governance problem — is covered in depth in [our proxy statement guide](/blog/what-is-def-14a), along with the rest of the document. What follows is the next layer down: the quantitative disclosures that were added specifically because the Summary Compensation Table's single total wasn't giving shareholders the full picture.

| Disclosure | Rule | What it requires | When it applies |
|---|---|---|---|
| Pay Versus Performance table | Item 402(v) of Regulation S-K | Compensation Actually Paid alongside the Summary Compensation Table total, plus net income, total shareholder return, and a company-selected performance measure | Fiscal years ending on or after December 16, 2022; five years of history, three for smaller reporting companies |
| CEO pay ratio | Item 402(u) of Regulation S-K | The ratio of CEO total compensation to the median employee's, with the identification methodology disclosed | Since 2018; smaller reporting companies, emerging growth companies, and foreign private issuers exempt |
| Compensation clawback policy | SEC Rule 10D-1, via NYSE and Nasdaq listing standards | A written no-fault policy recovering erroneously awarded incentive pay for the three fiscal years preceding a restatement determination | Listing standards effective October 2, 2023 |
| Say-on-frequency vote | Section 14A of the Exchange Act | A separate shareholder vote on how often say-on-pay occurs — every one, two, or three years, or abstain | At least once every six years |

---

## The Pay Versus Performance Table: Compensation Actually Paid

A reader scanning a CEO's total in the Summary Compensation Table reasonably takes that figure as the final word on what the executive was paid for the year. It isn't always: that total values equity awards at their grant-date price, months or years before the market has any say in what those awards end up worth. Every proxy statement for a fiscal year ending on or after December 16, 2022 must include a Pay Versus Performance table under Item 402(v) of Regulation S-K precisely to close that gap. The table covers the company's five most recently completed fiscal years (three for smaller reporting companies) and shows, alongside the familiar Summary Compensation Table total, a separate figure the SEC calls "Compensation Actually Paid," or CAP.

CAP starts from the Summary Compensation Table total and then adjusts the equity award components to reflect their value at fiscal year-end or vesting, rather than their value on the original grant date. An executive granted options when the stock was falling sees a materially lower CAP figure than the grant-date value implied. An executive granted options right before a rally sees a materially higher one. That single adjustment is why a company's own CD&A can describe a "conservative" compensation year while its Pay Versus Performance table shows CAP swinging by tens of millions of dollars — the CD&A describes the committee's original decision, and the CAP figure describes what the market did to that decision afterward.

The table also requires the company to disclose net income and total shareholder return alongside CAP for the same five years, plus a company-selected performance measure the compensation committee considers most important, and a required narrative explaining the relationship between the two. Reading that relationship description tells you directly whether the company's own required disclosure supports the CD&A's story that pay tracks performance, or whether the two diverge in ways the CD&A doesn't address.

---

## The CEO Pay Ratio

Since 2018, every proxy statement requiring Item 402 executive compensation disclosure — other than filings from smaller reporting companies, emerging growth companies, and foreign private issuers, all of which are exempt — must disclose the ratio between CEO total compensation and the median employee's total compensation, under Item 402(u) of Regulation S-K. The company identifies its median employee once every three years using any reasonable methodology it discloses, then recalculates that specific employee's total compensation annually using the same definition applied to named executive officers.

A ratio invites the reader to rank companies against each other the moment two of them report one — a low ratio at one company and a high ratio at another read like they're measuring the same thing. In practice they aren't: the ratio varies enormously by industry and workforce composition, which makes single-company trend, not cross-company comparison, the more reliable way to read it. [National Health Investors](/stocks/NHI) disclosed a CEO-to-median-employee ratio of roughly **10 to 1** for fiscal year 2024 — a healthcare REIT with a small, relatively uniform corporate workforce. A retailer or restaurant chain with a large hourly workforce will show a structurally higher ratio than that, independent of whether either company's CEO pay is reasonable. What's worth tracking is the ratio's direction at a single company over several years: a ratio climbing steadily while median employee compensation stays flat in nominal terms is a different story than one where both figures are rising together.

---

## The Compensation Clawback Policy

A clawback reads like a penalty, and the natural assumption is that one only fires after a company has proven an executive did something wrong. SEC Rule 10D-1 doesn't require that proof: every NYSE- and Nasdaq-listed company has been required to maintain a written compensation clawback policy since the exchanges' listing standards took effect on **October 2, 2023**, and the policy requires the company to recover erroneously awarded incentive-based compensation from current and former executive officers whenever an accounting restatement is required — covering compensation received during the three fiscal years preceding the restatement determination, regardless of whether any executive officer was personally at fault. A company that fails to adopt a compliant policy, fails to disclose it, or fails to actually enforce a recovery it triggers risks delisting.

The policy itself is filed as an exhibit to the annual report, and the proxy discloses whether a clawback was actually triggered during the year and, if so, the amount recovered. This is the direct link back to amended SEC filings: a [10-K/A that restates prior financial statements](/blog/amended-sec-filings-10-k-a-explained) is precisely the event that can trigger a mandatory, no-fault recovery of incentive pay under this policy — which means an investor who spots a restatement has a specific, disclosed follow-up question: did the company's clawback policy actually claw anything back?

---

## The Say-on-Frequency Vote: How Often Shareholders Get a Say

Separate from the say-on-pay vote itself, Section 14A of the Exchange Act requires companies to hold a distinct say-on-frequency vote at least once every six years — a single decision that can set the cadence for as many as six annual say-on-pay ballots before shareholders revisit it — asking shareholders how often they want future say-on-pay votes to occur. The ballot presents exactly four choices: every one year, every two years, every three years, or abstain. The board can recommend an option but cannot limit the vote to a yes/no on that recommendation.

The overwhelming majority of large-cap companies land on annual votes, which is why say-on-pay shows up on most proxy ballots every year without a reader ever noticing the underlying frequency decision. A company running a three-year cycle instead is disclosing something worth registering: shareholders get roughly a third as many formal opportunities to register dissent through this specific channel, which raises the bar for what "the last vote was fine" actually tells you about the current year's pay practices.

---

## Beyond the Summary Compensation Table: The Equity Award Detail Tables

Four additional standardized tables under Item 402 sit behind the Summary Compensation Table's headline totals, and together they show the mechanics the total column compresses into one number. The Grants of Plan-Based Awards table discloses the specific equity and non-equity incentive awards granted during the year. It includes the threshold, target, and maximum payout levels for performance-based awards — the range the Summary Compensation Table's single reported figure was drawn from. The Outstanding Equity Awards at Fiscal Year-End table shows every unvested option and stock award an executive is currently holding, the closest thing the proxy offers to a real-time snapshot of unrealized executive wealth tied up in the stock. The Option Exercises and Stock Vested table reports what an executive actually received in cash or shares during the year from exercising options or vesting awards — the closest thing to "compensation actually pocketed" that exists outside the Pay Versus Performance table's CAP calculation. Pension Benefits and Nonqualified Deferred Compensation round out the set for companies that still offer those structures, increasingly rare outside older, larger organizations.

Read together with the Summary Compensation Table, these four tables answer a question the total column alone cannot: not just what an executive was paid on paper this year, but what they're actually sitting on, and what they've actually converted to cash.

| Table | What it shows | The question it answers |
|---|---|---|
| Summary Compensation Table | The standardized dollar total for each named executive officer | What was the executive paid on paper this year? |
| Pay Versus Performance | Compensation Actually Paid — equity revalued at fiscal year-end or vesting | What was that pay decision worth once the market repriced it? |
| Grants of Plan-Based Awards | Equity and non-equity incentive awards granted during the year, with threshold, target, and maximum payout levels | Where did the Summary Compensation Table's single figure come from? |
| Outstanding Equity Awards at Fiscal Year-End | Every unvested option and stock award the executive is currently holding | How much unrealized wealth is tied up in the stock? |
| Option Exercises and Stock Vested | What the executive actually received in cash or shares from exercises and vesting during the year | What has actually been converted to cash? |
| Pension Benefits and Nonqualified Deferred Compensation | Deferred and pension arrangements, at the companies that still offer them | What is owed beyond current-year pay? |

One caveat applies to every row of that table. None of these disclosures sit inside the audited financial statements — they are Item 402 proxy disclosures, prepared by the company and overseen by the compensation committee, and the auditor's opinion on the 10-K does not extend to them. Our guide to [which SEC filings are audited](/blog/which-sec-filings-are-audited) covers where that line falls across the rest of the filing set.

---

## Reading Compensation Data Against What GeminIQ Already Tracks

None of the tables covered here are XBRL-tagged financial statement data, and GeminIQ doesn't extract them directly — they're proxy disclosures governed by Item 402 of Regulation S-K, not the 10-K and 10-Q filings GeminIQ's [Financial Statements](/features#financial-statements) feature is built on. What GeminIQ does carry is the financial-statement consequence of everything the proxy discloses: the aggregate stock-based compensation expense the Summary Compensation Table's individual figures roll up into, and the share dilution that equity awards eventually produce.

GeminIQ's pre-calculated [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) metric is the company-wide total that the proxy's individual NEO figures represent a small, named slice of, and [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) puts that aggregate cost in proportion to the business. The [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) metric measures the share-count side of the same story, calculated from the filed financial statements rather than from the proxy: it divides the weighted average diluted share count by the weighted average basic count, both taken as filed, so the gap between them is the effect of every option, warrant, convertible and unvested RSU still outstanding. Awards the proxy discloses at the individual level land in that number twice — first widening the basic-to-diluted gap while they sit outstanding and unexercised, then moving into the basic count itself once they are exercised or vest. Most mature companies run a ratio between **1.00** and **1.03**; companies leaning heavily on stock compensation run **1.03** to **1.10**, and persistent dilution above **3%** to **5%** is the level worth explaining. The proxy tells you who received the awards. The share count tells you what they cost every other holder. Which filings a platform actually extracts from is worth confirming before assuming a figure is there — our [comparison with TIKR](/competitor-comparison/tikr) sets out what GeminIQ pulls and where it draws the line.

---

## Frequently Asked Questions

### What is "compensation actually paid" in the Pay Versus Performance table?

Compensation Actually Paid, or CAP, starts from the Summary Compensation Table total and replaces the grant-date value of equity awards with their value at fiscal year-end or vesting. It's required under Item 402(v) of Regulation S-K and can differ substantially from the Summary Compensation Table figure in years when the stock price moved sharply after grants were made.

### Which companies are exempt from CEO pay ratio disclosure?

Smaller reporting companies, emerging growth companies, and foreign private issuers are all exempt from Item 402(u)'s pay ratio requirement. Every other company subject to Item 402 executive compensation disclosure must include it.

### Does a compensation clawback require executive wrongdoing?

No. Rule 10D-1's listing-standard requirement is a no-fault recovery: if an accounting restatement is required, the company must recover erroneously awarded incentive-based compensation from current and former executive officers regardless of whether any of them were personally responsible for the error.

### How often do shareholders vote on say-on-pay frequency?

At least once every six years, under Section 14A of the Exchange Act. Shareholders choose among annual, biennial, or triennial say-on-pay votes, or may abstain; most large-cap companies land on an annual cycle.

Every one of these disclosures exists because the Summary Compensation Table's single total wasn't enough on its own — and together, they're the difference between reading a pay package and verifying one.

---

## Related Reading

- [DEF 14A Proxy Statement: What Investors Look For](/blog/what-is-def-14a) — the full guide to the CD&A, board composition, and the say-on-pay vote bands.
- [Amended SEC Filings: What a 10-K/A Actually Means](/blog/amended-sec-filings-10-k-a-explained) — the restatement that can trigger a mandatory clawback.
- [Complete Guide to SEC Filing Types for Investors](/blog/sec-filings-guide) — where the DEF 14A fits alongside the 10-K, 10-Q, 8-K, and S-1.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pay-versus-performance-table-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Peloton Stock Collapse: The Warnings Were in the Filings
source: https://www.geminiq.com/blog/peloton-stock-collapse-warning-signs

### Peloton Stock Collapse: The Warnings Were in the Filings
Peloton's stock collapse was visible in its own SEC filings months before the company ousted its CEO and cut thousands of jobs. This forensic study reads Peloton's full 10-K and 10-Q history, from its 2019 IPO through 2026, to pinpoint exactly where the inventory bloat, growth deceleration, and insider selling would have shown up first.

**[Peloton Interactive](/stocks/PTON) ($PTON) closed out 2020 at an all-time high of $151.72 a share. By the end of its March 2026 quarter, that same share changed hands for $4.29 — a decline of 97.2%. The story everyone tells is that a pandemic-era fad met an inevitable reckoning, and that nobody could have called the turn until the stock was already in freefall. But standard financial media doesn't read the footnotes. Read Peloton's own 10-Qs in the order they were filed, and the warning signs were already stacked three deep a full quarter before Peloton's board pushed out its founder-CEO in February 2022 — while the warehouse was still filling with unsold hardware and the people running the company had already banked more than a billion dollars selling their own shares.**

Every figure in this study is drawn from Peloton Interactive's own 10-K and 10-Q filings, filed between November 2019 and May 2026, covering fiscal periods from its September 2019 IPO quarter through its March 2026 quarter — 27 consecutive quarterly filings read in the order the company filed them, joined to how the stock actually traded in the one to three months after each filing hit SEC EDGAR.

## The Growth Years, 2019–2021

The market's belief during this stretch wasn't complicated: Peloton was the future of fitness, and the pandemic had handed it a permanent tailwind. The revenue numbers backed that story up, quarter after quarter, in a way that made the eventual reversal look unthinkable.

**The Filing Data:** [Peloton's](/stocks/PTON) `Revenues` grew from **$228.0 Million** in its first quarter as a public company (September 2019) to **$757.9 Million** by September 2020 — a **232.4%** year-over-year jump. The acceleration didn't stop there. By December 2020, the same quarter the stock closed at its $151.72 all-time high, quarterly `Revenues` reached **$1,064.8 Million**, up **128.4%** year-over-year; by March 2021 they reached **$1,262.3 Million**, up **140.6%**. On paper, growth was still accelerating.

**The Signal:** Underneath the headline growth, [Peloton](/stocks/PTON) was building manufacturing and warehouse capacity — including its own U.S.-based Peloton Output Park facility — sized for a demand curve that assumed the pandemic buying pattern was permanent rather than pulled-forward. The filings don't show a company managing a temporary surge; they show a company committing capital as if **200%-plus** growth was the new baseline. That assumption is exactly what the next four quarters would break.

<center><sup>GeminIQ Financial Statements showing Peloton's `Revenues` by quarter from its September 2019 IPO period through its March 2021 quarter, alongside year-over-year growth. Growth peaked at 232.4% (Sept 2020) before the deceleration below.</sup></center>

## The Warehouse That Outran the Register

By mid-2021, the media narrative was still "growth stock normalizing" rather than "growth story ending." The stock had already pulled back from its December 2020 high, but a pullback after a 400%-plus pandemic run reads as healthy, not terminal. It wasn't being read against the balance sheet.

**The Filing Data:** In the June 2021 quarter, [Peloton's](/stocks/PTON) `Revenues` grew just **54.3%** year-over-year — a sharp deceleration from the **140.6%** posted the quarter before — while `Inventory Net` climbed to **$937.1 Million**, an all-time high at the time. By the September 2021 quarter, revenue growth had collapsed further to **6.2%** year-over-year, and `Inventory Net` had grown to a new record of **$1,269.2 Million**. Days Inventory Outstanding, GeminIQ's calculated measure of how long inventory sits before it sells, rose from 66.9 days in March 2021 to 84.0 days in June 2021 to 111.2 days in September 2021. By the December 2021 quarter — the same quarter Peloton's board would announce a leadership change — `Inventory Net` peaked at **$1,541.3 Million** with Days Inventory Outstanding at 130.2 days. Year-over-year revenue growth, in that same filing, had fallen to just **6.5%**.

**The Signal:** A retailer holding inventory for 130 days while its own sales growth has crashed to single digits is not managing seasonal stocking — it's sitting on unsold product it can't move. GeminIQ's [Days Inventory Outstanding](https://www.geminiq.com/metrics/efficiency-and-turnover-ratios/days-inventory-outstanding) metric turned the disconnect into a single trackable number nearly a full year before it showed up as a headline. The eventual reckoning arrived in the June 2022 quarter. `Cost Of Goods Sold` of **$708.5 Million** exceeded `Revenues` of **$678.7 Million** outright, and `Gross Profit` went negative, at **-$29.8 Million**, as accumulated inventory finally hit the income statement through markdowns and write-downs. The inventory sat on the balance sheet in plain view the entire time — as did what Peloton's own executives were doing with their own shares.

<center><sup>GeminIQ data study: Peloton's Inventory Net against year-over-year Revenues growth, quarter by quarter. Built from as-filed 10-K/10-Q data via GeminIQ. n = 27 filings, Q1 FY2020–Q3 FY2026.</sup></center>

## What Insiders Did With Their Own Shares

The bull case through 2020 and 2021 leaned heavily on conviction — the idea that the people who built Peloton believed in the growth story as much as the market did. GeminIQ's raw Form 4 feed tells a different story about where that conviction actually went.

**The Filing Data:** Between November 2020 and August 2021, founder and then-CEO John Foley sold 100,000 shares in nearly every single month, at prices ranging from **$93.44** to **$161.86** a share, for a combined **$119.3 Million**. He was far from alone: over 2020 and 2021 combined, [Peloton's](/stocks/PTON) officers and directors sold **$1,042.2 Million** worth of stock — **94.4%** of every dollar of insider selling in the company's entire history through the most recent quarter in this study. Over that same two-year window, GeminIQ's 13F institutional ownership tracker shows institutional ownership of Peloton shares actually rose, from **69.2%** in March 2021 to **81.4%** by December 2021.

**The Signal:** The people with the earliest read on the inventory and growth numbers above were net sellers, consistently, at prices between **$87** and **$162**, while outside institutional capital was still net buying into the decline. Institutional and insider Form 4/13F data on GeminIQ is quarterly, not real-time, so this isn't a live signal — it's a pattern visible only in hindsight, across the filings, exactly like the inventory buildup above. But the direction of that pattern — one founder, eleven monthly sales, zero purchases — is not something a single earnings call or press release would have surfaced.

<center><sup>GeminIQ Insider Transactions showing Peloton officer and director Sale filings, 2020–2021. John Foley alone sold $119.3 Million across eleven separate transactions in this window.</sup></center>

## The Dilution Ratio That Read 1.00 While the Share Count Kept Climbing

A screener glancing at [Peloton's](/stocks/PTON) Dilution Ratio during its collapse would have seen almost nothing wrong. That's the trap.

**The Filing Data:** GeminIQ's [Dilution Ratio](https://www.geminiq.com/metrics/returns-and-profitability/dilution-ratio) — diluted shares divided by basic shares — read a flat 1.00 for nearly every quarter from mid-2021 through 2025. Over that same stretch, `Weighted Average Number Of Shares Outstanding Basic` grew from 269,177,048 at Peloton's September 2019 IPO quarter to 428,911,447 by March 2026, a **59.3%** increase, while `Share Based Compensation` climbed from **$18.7 Million** in the September 2019 quarter to a peak of **$182.1 Million** in a single quarter by September 2022. GeminIQ's [Stock-Based Compensation to Revenue](https://www.geminiq.com/metrics/margin-metrics/stock-based-compensation-to-revenue) metric rose from **3.83%** of trailing revenue in March 2021 to **15.31%** by December 2022 — more than fifteen cents of every revenue dollar going to equity compensation at the peak.

**The Signal:** A Dilution Ratio of exactly 1.00 means GAAP's treasury-stock method found no dilutive securities worth counting — which happens automatically once a company is posting a net loss, because options and converts become anti-dilutive by rule. The dilution didn't stop; it just moved out of the ratio and into the raw share count and the SBC expense line, where the erosion still shows up. The tell is in what happened once Peloton edged back toward profitability: by September 2025, with a rare positive quarterly `Net Income Loss` of **$13.9 Million**, the Dilution Ratio finally moved off 1.00, to 1.04, and by March 2026 — another profitable quarter — it read 1.19, with `Weighted Average Number Of Diluted Shares Outstanding` of 512,261,196 against a basic count of 428,911,447. The metric worked exactly as designed the moment there was income for dilution to apply against. It just had nothing to measure against for four straight years of losses.

<center><sup>GeminIQ Calculated Metrics showing Peloton's Dilution Ratio and Stock-Based Compensation to Revenue against Weighted Average Number Of Shares Outstanding Basic, 2019–2026.</sup></center>

## The Balance Sheet Cracks

The final signal isn't a single quarter — it's the trajectory of the balance sheet itself, and GeminIQ's [Altman Z-Score](https://www.geminiq.com/metrics/leverage-and-debt-ratios/altman-z-score) turns that trajectory into a single number with documented distress thresholds.

**The Filing Data:** [Peloton's](/stocks/PTON) [Altman Z-Score](/blog/altman-z-score-financial-distress) stood at 14.57 in December 2020 — deep in the "safe zone" above the 2.99 threshold. By September 2021 it had fallen to 5.81. By December 2021, the same quarter the board announced its leadership change, it had been cut more than in half again, to 2.28 — already below the 2.99 safe-zone line and into the "gray zone." By March 2022, it read 1.14, below the 1.81 distress-zone threshold. By June 2022 it was negative, at -1.67. Total Shareholders' Equity, which stood at **$2,368.9 Million** in December 2021, fell to **$592.9 Million** by June 2022 and turned negative for the first time in March 2023, at **-$127.0 Million**. By then, the accumulated `Retained Earnings Accumulated Deficit` had reached **$4,690.0 Million**. Unlike companies where negative equity reflects an aggressive buyback program against strong cash flow, Peloton's `Payments For Repurchase Of Equity` shows no meaningful buyback activity across this entire window — the negative equity here is accumulated losses, full stop.

**The Signal:** Each of the four post-filing return windows tracked in this study lines up with the deterioration above. The FY2021 annual report, filed August 27, 2021, was followed by a cumulative three-month return of **-52.83%**; the next 10-Q, filed November 5, 2021, was followed by **-51.37%**. Then came February 8, 2022 — the same day Peloton announced John Foley's departure as CEO and roughly 2,800 job cuts — when that quarter's 10-Q was followed by a cumulative three-month return of **-52.88%**. The final 10-Q in this window, filed May 10, 2022 and the first to report a negative `Gross Profit`, was followed by **-26.43%**. None of these figures predict what any stock does next; they describe, in this single company's own history, what happened after each filing landed.

<center><sup>GeminIQ Calculated Metrics showing Peloton's Altman Z-Score falling from 14.57 (Dec 2020) through the 2.99 and 1.81 distress thresholds to -1.67 by June 2022, alongside Total Shareholders' Equity from Financial Statements.</sup></center>

## What the Filings Said Before the Market Knew

Stack the signals against the calendar, and the September 30, 2021 10-Q — filed November 5, 2021 — is the point where three of them were already sitting in the same filing at once. `Inventory Net` had just hit a then-all-time high of **$1,269.2 Million** with Days Inventory Outstanding at 111.2 days, up from 66.9 days two quarters earlier. Year-over-year revenue growth had crashed to **6.2%**, down from **140.6%** two quarters before that. And John Foley had, by that point, sold 100,000 shares in ten of the previous eleven months, with no offsetting open-market purchases from company insiders anywhere in the record. The Altman Z-Score in that same filing had been cut nearly in half in a single quarter, from 8.91 to 5.81.

The stock closed that September quarter at **$87.05** — down **43%** from its all-time high, but still more than nineteen times higher than where it would eventually trade. The market had priced in a pullback. The filings, read together rather than one line at a time, were already describing something closer to a structural break. The CEO change and the goodwill impairment that "confirmed" the story to headlines wouldn't arrive for another four and five months, respectively — and by then the stock had already fallen another **60%**.

## Check Your Holdings

This isn't a Peloton-specific pattern — it's a repeatable check anyone can run against their own portfolio inside GeminIQ. Pull up [Calculated Metrics](/features#calculated-metrics) for any company you hold and look at Days Inventory Outstanding next to trailing revenue growth: rising Days Inventory Outstanding alongside decelerating revenue growth for two consecutive quarters is the exact combination that showed up in Peloton's filings a year before the headlines caught up. Then open [Insider Transactions](/features#insider-transactions) and check whether officer and director activity is one-directional — persistent selling with zero open-market buying, especially from founders, is worth weighing against whatever management says on the earnings call. Finally, track the Altman Z-Score over four or five consecutive quarters rather than as a single snapshot; a score that's fallen out of the 2.99 safe zone into the 1.81–2.99 range is GeminIQ's raw-filing equivalent of a distress flag most aggregator-based screeners won't surface until it's already a headline.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=peloton-stock-collapse-warning-signs)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures in this article are drawn from Peloton Interactive, Inc.'s 10-K and 10-Q filings, filed 2019–2026 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001639825&type=10-K).

---

## Blog: PepsiCo (PEP) Q3 2026 Earnings: EPS Up 17%, Core EPS Up 2%
source: https://www.geminiq.com/blog/pepsico-earnings-q3-2026

### PepsiCo (PEP) Q3 2026 Earnings: EPS Up 17%, Core EPS Up 2%
PepsiCo reported Q3 FY2026 revenue of $25.27 billion (+5.6%) and diluted EPS of $2.23 (+17.4%). The 10-Q shows excluded items drove about four-fifths of the operating profit gain, and the 8-K cut core EPS guidance.

**[PepsiCo](/stocks/PEP) (PEP) reported Q3 FY2026 revenue of $25.27 billion, up 5.6%, and diluted EPS of $2.23, up 17.4%, for the 12 weeks ended September 5, 2026; the company released results and filed its 10-Q on October 8, 2026. The 17% did not come from the core business: the 8-K puts core EPS growth at 2% and credits tariff refunds with 4 points of a core operating profit gain that was 3% in total. Items PepsiCo excludes from core account for about four-fifths of the reported operating profit gain. The same release cut full-year core EPS growth guidance to +2.5% to +3.5%, from the low end of +5% to +7%.**

| Field | Value |
|---|---|
| Company | PepsiCo ($PEP) |
| Quarter | Q3 FY2026, 12 weeks ended September 5, 2026 |
| Earnings release | October 8, 2026 (Form 8-K) |
| 10-Q filed | October 8, 2026 |
| Revenue | **$25.27 Billion** (+5.6% YoY) |
| Diluted EPS | **$2.23** (+17.4% YoY) |
| Operating margin | 16.9% (+1.9 pts YoY) |
| Operating cash flow (TTM) | $10.27 Billion |
| Diluted EPS growth vs core EPS growth (8-K) | **+17.4% vs +2%** |

## PepsiCo Q3 FY2026 Revenue, EPS and Operating Margin

[PepsiCo](/stocks/PEP)'s Q3 FY2026 diluted EPS was **$2.23**, up 17.4% from $1.90, on revenue of $25.27 billion, up 5.6% from $23.94 billion. Nearly all of the EPS gain traces to one line, because everything below it barely moved.

**The Data:** Operating income rose to **$4.26 billion** from $3.57 billion, up 19.4%, the highest of the last 16 quarters. The tax rate was 21.4% in both quarters, diluted shares fell 0.4% to 1,367 million, and net interest expense fell $22 million. Gross margin of 54.4% was the seventh-lowest of the last 16 quarters, so the margin gain did not start at gross profit.

**Why:** Share count contributed about 0.4 points of the 17.4% and tax none, which leaves operating profit. SG&A grew 4.1% against revenue growth of 5.6%, and a $133 million impairment, primarily the Rockstar brand, in the prior-year quarter did not recur, per the 8-K. GeminIQ's pre-calculated [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) (TTM) rose 5.64 points to 16.67%, more than three times the quarter's 1.9-point gain, because the year-ago trailing period carried the 2025 impairments. An operating margin at its third-highest level in the last 16 quarters is partly a comparison against a charge-laden base.

<center><sup>GeminIQ Financial Statements shows `Revenues`, `Operating Income Loss`, `Net Income Loss` and `Earnings Per Share Diluted` from the 10-Q. The highlighted `Operating Income Loss` of $4.26 billion for the quarter ended 2026-08-31 is the line that carried the EPS gain.</sup></center>

## What PepsiCo's Q3 FY2026 10-Q Shows Beyond the Press Release

[PepsiCo](/stocks/PEP)'s 10-Q filed October 8, 2026 reports operating profit up 19%, while the 8-K's reconciliation shows core operating profit up 3%, to $4.28 billion from $4.14 billion. A reader who saw EPS up 17% would expect operating profit to have grown on operations. Instead items the company excludes from core swung by $551 million, about 80% of the $691 million reported gain.

**The Data:** Excluded items added back $568 million in the prior-year quarter and $17 million this year, derived from the 8-K reconciliation. Core operating margin fell 35 basis points to 16.9% while reported margin rose 195. The 8-K attributes **4 points** of core operating profit growth to tariff refunds, which leaves core operating profit down roughly 1% without them (derived).

**Why:** The 10-Q lists productivity savings and pricing among the drivers, and the reconciliation shows those are the 3%, not the 19%. The refunds are cash [PepsiCo](/stocks/PEP) says it has substantially received after the Supreme Court ruled many IEEPA tariffs invalid, so they are real, but they recover past payments rather than set a run rate.

<center><sup>GeminIQ Visualizations plots `Operating Income Loss` from the 10-Q for the last 16 quarters. The highlighted $4.26 billion for the quarter ended 2026-08-31 is the highest of the span, against $3.57 billion a year earlier.</sup></center>

## PepsiCo Q3 FY2026 Free Cash Flow, Dividends and Debt

[PepsiCo](/stocks/PEP)'s Q3 FY2026 operating cash flow was $5.58 billion, up 24.9% from $4.47 billion, and free cash flow (operating cash flow less capital expenditure) was $4.67 billion, the second-highest of the last 16 quarters. The trailing year tells a different story.

**The Data:** Operating cash flow was **$2.32 billion** in the prior quarter, so Q3 was 140% higher sequentially. Trailing-twelve-month operating cash flow fell 12.6% to $10.27 billion, while GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) rose 7.1% to $7.27 billion. Dividends paid over the same twelve months were **$7.88 billion**, 108% of that free cash flow, although Q3's $2.02 billion dividend was 43% of the quarter's. Net debt to EBITDA improved to 2.17x from 3.15x per GeminIQ's [Net Debt to EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda).

**Why:** Free cash flow rose while operating cash flow fell because the gap between them, mostly capital spending, shrank from about $5.0 billion to $3.0 billion (derived). Capex of $916 million was the eighth-lowest of the last 16 quarters. Buybacks were $739 million in 36 weeks against $247 million of share-based compensation, and diluted shares reached their lowest in 16 quarters, so the repurchases did more than offset dilution. PepsiCo's dividend is covered by one strong quarter, not yet by the year.

<center><sup>GeminIQ Financial Statements shows `Net Cash Provided By Used In Operating Activities`, `Share Based Compensation`, `Payments For Repurchase Of Common Stock` and `Payments Of Dividends` from the 10-Q. The highlighted operating cash flow of $5.58 billion for the quarter ended 2026-08-31 is the figure the section argues from.</sup></center>

## PepsiCo's 2026 Guidance After Q3

In its October 8, 2026 8-K, PepsiCo guided fiscal 2026 core EPS growth of **+2.5% to +3.5%**, down from the low end of +5% to +7% in July, while raising net revenue growth to approximately +6% from +4% to +6%. Revenue guidance went up and profit guidance came down.

**The Data:** Core constant currency EPS growth is now +1% to +2%, from the low end of +4% to +6%. The core tax rate guide fell to approximately 21% from 22%. Organic revenue growth is approximately +3%, inside the previous +2% to +4%; the foreign exchange tailwind and net acquisitions each rose to 1.5 points from 1. Core EPS grew 5% over the first 36 weeks.

**Why:** The revenue raise came from currency and acquisitions, one point combined, with none from organic growth. EPS guidance fell despite a one-point lower tax rate, which means the company lowered its operating profit expectations. A 5% year-to-date gain against a full-year range of 2.5% to 3.5% implies core EPS declines in the fourth quarter. The 8-K says additional structural cost reduction actions are being identified to mitigate "rising input cost inflation."

## How PEP Stock Has Moved After Past Earnings Reports

Across the last 12 PepsiCo 10-Q filings with a completed one-month window, filed 2023-10-10 to 2026-07-09, the median one-month return was +1.1%, positive after 7 of 12, and the median three-month return was -1.7%, positive after 5 of 12. These figures describe how [PepsiCo](/stocks/PEP)'s stock moved after its past filings; they are a historical association, not a forecast.

**The Data:** One-month returns ranged from **-2.8%** (FY2024 Q3) to **+8.6%** (FY2024 Q2). Past Q3 filings were followed by one- and three-month returns of +1.5% and +4.1% (FY2023), -2.8% and -9.5% (FY2024), and +0.9% and +0.3% (FY2025). The Q3 FY2026 row has no returns yet because its window has not elapsed.

**Why:** The best and worst one-month windows came three months apart in the same fiscal year, so a filing date alone separated little. The GeminIQ [Earnings Reaction Heat Map](/features#price-variance) shows each window against the company's own distribution.

<center><sup>GeminIQ Earnings Reaction Heat Map shows PepsiCo's returns 1-3 months after each 10-Q filing from 2022 through the October 8, 2026 filing. The current quarter's cells show "-" because its windows have not elapsed.</sup></center>

Institutions held 79.04% of PepsiCo shares at the June 30, 2026 SEC Form 13F quarter end, the highest of the last 16 quarters and up from 71.90% a year earlier. SEC Form 4 data through March 4, 2026 shows two sales totaling $5.3 million in the prior 12 months, against 10 sales totaling $22.7 million the year before, and no purchases since February 27, 2013.

<center><sup>GeminIQ Institutional Ownership charts SEC Form 13F holdings by quarter end through June 30, 2026, highlighting 79.04%, the highest of the last 16 quarters.</sup></center>

A quarter whose reported profit growth runs several times ahead of the company's own core measure has already counted the items that flattered it.

## Frequently Asked Questions

### Is PepsiCo doing well financially?

PepsiCo's trailing-twelve-month net profit margin was 12.19% as of Q3 FY2026, up from 7.85% a year earlier. GeminIQ's pre-calculated [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) was 19.03%, up 5.72 points. Both comparisons lap the 2025 impairment charges, so they overstate the underlying improvement.

### When does PepsiCo report earnings?

PepsiCo reported Q3 FY2026 results on October 8, 2026. Last year it filed its fourth-quarter results on February 3, 2026, and its Q3 FY2025 filing came on October 9, 2025. That is a pattern from the filing record, not a forecast of the next date.

### Does PepsiCo pay a dividend?

Yes. PepsiCo paid $2.02 billion of dividends in Q3 FY2026, the highest of the last 16 quarters, and $7.88 billion over the trailing twelve months, up 4.4%. The 8-K guides 2026 dividends of $7.9 billion within $8.9 billion of total cash returns.

### What is PepsiCo's current revenue?

PepsiCo's Q3 FY2026 net revenue was $25.27 billion, and 36-week revenue was $68.90 billion, up 6.7%. The 8-K puts 36-week organic revenue growth at 2.7%.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pepsico-earnings-q3-2026)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference PepsiCo, Inc.'s
Q3 2026 10-Q (filed October 8, 2026, period ending August 31, 2026), with
guidance and management commentary drawn from the company's Form 8-K earnings
release (filed October 8, 2026). All SEC filings are publicly available at
[SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/77476/000007747626000048/pep-20260905.htm) and
[SEC EDGAR](https://www.sec.gov/Archives/edgar/data/77476/000007747626000050/q320268-kxexhibit991.htm).</sup>

---

## Blog: Piotroski F-Score: How to Spot a Value Trap Before It Snaps Shut
source: https://www.geminiq.com/blog/piotroski-f-score-value-trap

### Piotroski F-Score: How to Spot a Value Trap Before It Snaps Shut
Piotroski F-Score is a nine-signal scoring system that distinguishes cheap stocks on a recovery trajectory from those in fundamental decline. Built from raw SEC filing data, it was designed to eliminate value traps within a low price-to-book universe.

A stock trading below its book value sounds like a deal. The company's assets are worth more than the market says, the argument goes. Buy the gap. That logic has worked in enough historical studies — Benjamin Graham ran it for decades — that serious investors still use low price-to-book screens as a starting point for value research.

The problem is structural. A low P/B screen ranks companies by how cheap their market price is relative to net assets. It says nothing about what those assets are doing over time. The company with **$10 per share** in book value that earned **15% ROA** last year and the company with **$10 per share** in book value that earned **2% ROA** and is losing ground look identical in the screen. The first might genuinely be cheap. The second is probably priced correctly for its trajectory — and buying it means walking straight into a value trap.

In 2000, Joseph Piotroski, then a professor at the University of Chicago, published research designed to solve precisely this problem. Using nothing but publicly available financial statement data — no management interviews, no qualitative judgment, no price momentum — he constructed a nine-signal scoring system that distinguishes companies on a recovery trajectory from those still in decline. His results showed approximately **7.5% annual outperformance** separating the highest-scoring stocks from the lowest-scoring ones within a low-P/B universe, from 1976 to 1996. That scoring system is the Piotroski F-Score, and understanding it changes how you read a cheap stock.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=piotroski-f-score-value-trap)**

---

## Table of Contents

- [What Is a Value Trap?](#what-is-a-value-trap)
- [How Piotroski Built the Score](#how-piotroski-built-the-score)
- [Signal Group 1: Profitability](#signal-group-1-profitability)
- [Signal Group 2: Financial Strength](#signal-group-2-financial-strength)
- [Signal Group 3: Operating Efficiency](#signal-group-3-operating-efficiency)
- [How to Interpret Your Score](#how-to-interpret-your-score)
- [Why the Data Source Determines the Score's Reliability](#why-the-data-source-determines-the-scores-reliability)
- [How to Run the Piotroski Screen in GeminIQ](#how-to-run-the-piotroski-screen-in-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is a Value Trap?

A value trap is a stock that appears cheap by conventional valuation metrics — typically price-to-book, P/E, or price-to-sales — but continues declining in price because the underlying business is genuinely deteriorating, not temporarily mispriced. The "trap" metaphor is precise: the position looks like an opportunity until you own it, at which point the mechanism that made it look cheap — the declining earnings, the eroding book value, the weakening competitive position — becomes visible in every subsequent quarterly filing.

The trap does not announce itself. A manufacturing company at **0.7× book value** looks cheap relative to its replacement value. What the P/B ratio does not show is that the gross margin has contracted for three consecutive years, the current ratio has been falling, and the asset base has been shrinking faster than management can rationalize it. Those facts are in the SEC filings — in the income statement, balance sheet, and cash flow statement — but a raw valuation screen does not read them. It just sees the multiple.

The F-Score is a systematized way of reading them before you act on the price.

---

## How Piotroski Built the Score

In "Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers," Piotroski studied every low price-to-book stock on major U.S. exchanges from 1976 to 1996. The central question was simple: can accounting-based signals, applied mechanically and without judgment, identify which cheap stocks will subsequently outperform within that universe?

The answer was yes. Piotroski identified nine financial statement signals — binary tests, each scoring a 1 if positive and a 0 if not — that collectively predicted subsequent stock performance. Portfolios of stocks scoring **8 or 9** outperformed portfolios scoring **0 or 1** by approximately **7.5% annually** over the study period. Buying the high-F-Score stocks and shorting the low-F-Score stocks within the low-P/B universe generated substantial excess returns with no information beyond publicly available filings.

The critical framing is what the F-Score does not do. It does not identify great businesses. It does not predict growth or forecast what a stock will do next quarter. It identifies whether the fundamentals of a cheap company are stabilizing and improving — or whether the cheapness is a leading indicator of continued deterioration. The alpha in Piotroski's research came as much from systematically avoiding the worst traps as from concentrating in the best recoveries.

Subsequent academic research has broadly confirmed the score's effectiveness as a negative filter, though the alpha has compressed somewhat as the approach has become widely known. The signal is most powerful where Piotroski found it: within the low price-to-book universe, where the stakes of distinguishing a genuine recovery from a terminal decline are highest.

---

## Signal Group 1: Profitability

The four profitability signals establish a foundational threshold — is this business actually earning money, and is the trend improving or worsening?

**Signal 1: ROA is positive.** Return on assets — net income divided by average total assets — must be greater than zero. A company with negative ROA is consuming its asset base rather than generating returns on it. In a low P/B screen, negative ROA is not uncommon: cyclical businesses at trough earnings, companies in active restructuring, and businesses in structural decline all land here. The signal is not demanding — it asks only that the company earns something, not that it earns well. But it eliminates the cohort where the fundamental math of the business is currently pointed in the wrong direction.

**Signal 2: Operating cash flow is positive.** This signal steps behind the income statement to test whether earnings have cash substance. A company can report positive net income while generating negative operating cash flow — when revenue is recognized before cash is received, when inventory is building faster than it is sold, or when accrued expenses are deferred into future periods. Positive operating cash flow means the business is generating real cash from its operations, regardless of what the income statement reports. It is the most basic test of whether earnings are grounded in economic reality.

**Signal 3: ROA improved year-over-year.** Direction matters as much as level. A company with a positive but declining ROA is on a trajectory toward the danger zone. A company with a positive and improving ROA is demonstrating that the business is getting better, not worse. This signal distinguishes businesses in early recovery — where the trend is the informative data point — from businesses that appear stable on a single-period snapshot but are quietly deteriorating quarter over quarter.

**Signal 4: Accruals.** The most sophisticated of the nine signals and, for many analysts, the most powerful. The accruals signal compares operating cash flow to reported net income. If operating cash flow exceeds net income, [earnings quality](/blog/earnings-quality-accruals-analysis) is high — the business is generating more cash than it is reporting in profit, which is the conservative and favorable direction. If reported net income significantly exceeds operating cash flow, the gap is filled with accounting accruals: estimates and deferrals that have benefited the income statement without producing cash. In a troubled company, a large and growing accrual balance is a warning sign that reported earnings are running ahead of the cash reality. The income statement looks better than the cash flow statement, which is rarely a sign that things are actually improving.

GeminIQ's [Calculated Metrics](/features#calculated-metrics) surface [Return on Assets TTM](/metrics/returns-and-profitability/return-on-assets) and [Operating Profit Margin TTM](/metrics/margin-metrics/operating-profit-margin) directly from XBRL-tagged SEC filing data — the same inputs the profitability signals require. GeminIQ's [Financial Statements](/features#financial-statements) view lets you compare operating cash flow against net income for any candidate, making the accrual signal directly readable without additional calculation.

---

## Signal Group 2: Financial Strength

If the profitability signals ask whether the business is earning money, the financial strength signals ask whether the balance sheet is getting stronger or weaker while it does. A company can be nominally profitable while accumulating debt, tightening its liquidity buffer, and diluting shareholders to stay afloat. That combination does not represent stabilization — it represents a business shifting from an earnings problem to a balance sheet problem.

**Signal 5: Long-term debt ratio decreased year-over-year.** Total long-term debt divided by average total assets, compared to the same ratio in the prior year. A declining ratio means the company is de-levering — paying down debt, growing its asset base organically, or both. A rising ratio means the company is becoming more financially fragile even if earnings appear stable. In a classic value trap, rising leverage is often the triggering mechanism: the company borrows to sustain operations while the core business deteriorates, until the debt load itself creates the crisis that finally destroys equity value. This signal catches that pattern before the crisis.

**Signal 6: Current ratio improved year-over-year.** Current assets divided by current liabilities, year-over-year directional change. A rising current ratio means near-term liquidity is improving — the company is building its buffer against short-term obligations. A falling current ratio means liquidity is tightening. For a company that already looks cheap, tightening liquidity raises the probability that the next operational shortfall forces a dilutive equity raise or a distressed debt refinancing — both events that transfer value away from existing shareholders at exactly the wrong time.

**Signal 7: No new equity issuance in the past year.** A company issuing common shares to fund operations — rather than to finance a clearly value-accretive acquisition — is typically doing so because internal cash generation cannot cover the gap between what it spends and what it earns. For investors in low P/B stocks, equity issuance at a depressed price is particularly destructive: the new shares are priced near trough valuation, directly reducing book value per share for existing holders and confirming that management lacks confidence in a near-term recovery. A company that has not issued equity in the past year is demonstrating that it can sustain operations without diluting shareholders to do it.

GeminIQ's pre-calculated [Debt Ratio](/metrics/leverage-and-debt-ratios/debt-ratio) and [Current Ratio](/metrics/liquidity-ratios/current-ratio) are filterable directly in the [Stock Screener](/features#screener), allowing the leverage and liquidity conditions to be applied at scale before reviewing individual companies.

---

## Signal Group 3: Operating Efficiency

The two efficiency signals ask the most forward-looking question in the F-Score: is the business becoming more productive over time, or less?

**Signal 8: Gross margin improved year-over-year.** Gross margin — revenue minus cost of goods sold, divided by revenue — measures the unit economics of the core business before overhead. An improving gross margin means the company is holding pricing power, reducing input costs, or shifting mix toward higher-margin products. A declining gross margin is the earliest warning sign that competitive pressure, cost inflation, or volume losses are compressing the fundamental economics of the business. It frequently appears in gross margin before it appears in operating income or net income, because SG&A cuts and one-time adjustments can temporarily mask gross margin deterioration at the operating line. When a company's gross margin is contracting across consecutive filings, the income statement is typically being managed, not improving.

**Signal 9: Asset turnover improved year-over-year.** Revenue divided by average total assets, compared to the prior year. Asset turnover measures how efficiently the company generates revenue from its asset base. Improving asset turnover means the company is doing more with what it has — a sign of genuine operational improvement. Deteriorating asset turnover in a capital-intensive business means the asset base is either growing faster than the revenue it generates or that revenue is declining faster than the company can right-size its asset structure. Either dynamic is a negative indicator within a value screen, where the core question is whether the business is stabilizing or still in decline.

GeminIQ's [Gross Profit Margin TTM](/metrics/margin-metrics/gross-profit-margin) and [Asset Turnover TTM](/metrics/efficiency-and-turnover-ratios/asset-turnover) are pre-calculated from as-filed SEC data and available as direct threshold filters in the [Stock Screener](/features#screener).

---

## How to Interpret Your Score

With nine binary signals, F-Scores range from 0 to 9. The zones Piotroski identified are not rigid cutoffs — they are probability thresholds based on historical frequencies of subsequent outperformance and underperformance within the low-P/B universe.

A score of **8 or 9** identifies a company passing nearly every test simultaneously: improving profitability, a strengthening balance sheet, and gaining operational efficiency. This combination — cheap and fundamentally improving across all three dimensions — is the highest-probability recovery profile in Piotroski's framework. The business is cheap and the data says it is getting better, not worse. This is the combination that drove the return separation in the original research.

A score of **3 to 7** is the middle ground where most companies land. The business is passing some signals and failing others. At this range the score narrows the analytical field but does not make the decision. Which signals are failing matters: a company scoring poorly on the financial strength signals but well on profitability and efficiency may be on a genuine recovery path that simply requires balance sheet cleanup. A company failing the efficiency signals while maintaining nominal profitability may be managing its income statement while the underlying economics continue to erode. The score prompts the right questions; reading the actual filing answers them.

A score of **0, 1, or 2** is the value trap warning zone. A company failing seven, eight, or nine of these signals simultaneously in a low-P/B screen is the profile Piotroski found most predictive of continued underperformance. The low price is not a margin of safety — it is the market's assessment of a business in ongoing fundamental decline, and the financial statements confirm it. Standard screeners surface these companies as potential value opportunities. The F-Score provides the counter-argument, directly from the filings. The most productive use of time is eliminating this cohort before spending further analytical energy on individual positions.

The most reliable application of the F-Score is as a **negative filter**. It does not guarantee that an 8 or 9 outperforms. It documents, systematically, that a 0, 1, or 2 is failing multiple independent tests of financial health simultaneously — and that the historical probability of recovery from that profile, within a low-P/B universe, is low.

---

## Why the Data Source Determines the Score's Reliability

The F-Score is built entirely on year-over-year changes in accounting ratios. That makes it more data-source-sensitive than almost any other quantitative metric, because the signal lives in the change — and the change depends entirely on whether the prior-year and current-year figures are derived consistently from the same filing structure.

Standard third-party financial data aggregators normalize financial statements to fit standardized templates. When a company reclassifies a cost item — moving it from cost of goods sold to operating expenses, or vice versa — an aggregator applying a normalized template may restate the prior year to match the new presentation. That restatement makes the apparent gross margin look identical across periods, which eliminates what should have been a meaningful gross margin signal. The aggregator shows no change. The as-filed data shows exactly what the company reported in each period — including the reclassification discontinuity that a careful analyst would want to investigate.

The accrual signal faces a parallel problem: comparing operating cash flow to net income across periods requires that both figures are sourced from the same filing structure, without normalization adjustments that introduce artificial consistency. Lease accounting changes under ASC 842 affect the current ratio signal. Acquisition-related asset growth affects the asset turnover signal in ways that may have nothing to do with operational efficiency. A reliable F-Score requires financial data that preserves the as-reported structure — not standardized data that smooths those differences away. For a detailed walkthrough of how aggregator normalization distorts calculated metrics across specific line items, the guide to [verifying financial data against SEC filings](/blog/verify-financial-data-against-sec-filing) covers the mechanics directly.

GeminIQ sources all financial statement inputs from XBRL-tagged SEC filings and does not apply aggregator normalization to as-reported line items. A gross margin reclassification shows up as a period discontinuity in the historical series — which is what it is, and what an F-Score calculation built on year-over-year comparisons needs to see.

---

## How to Run the Piotroski Screen in GeminIQ

GeminIQ's [Stock Screener](/features#screener) applies the most tractable Piotroski conditions as direct metric filters. Because computing a precise year-over-year delta for all nine signals requires accessing multiple historical filing periods simultaneously, the screener approximates the F-Score by filtering for the threshold levels that correspond to positive signals — profitability above zero, reasonable leverage, and improving efficiency — to surface companies that would score well on the F-Score framework.

The filters map directly to the three signal groups. For profitability: [Return on Assets TTM](/metrics/returns-and-profitability/return-on-assets) ≥ 5 and [Operating Profit Margin TTM](/metrics/margin-metrics/operating-profit-margin) ≥ 5. For financial strength: [Debt Ratio](/metrics/leverage-and-debt-ratios/debt-ratio) ≤ 45 and [Current Ratio](/metrics/liquidity-ratios/current-ratio) ≥ 1.5. For operating efficiency: [Gross Profit Margin TTM](/metrics/margin-metrics/gross-profit-margin) ≥ 20 and [Asset Turnover TTM](/metrics/efficiency-and-turnover-ratios/asset-turnover) ≥ 0.4. Set Sort By to Return on Assets TTM descending to surface the most profitable companies passing the full filter stack at the top of the list.

For the most faithful application of Piotroski's original research — where the strongest alpha was documented — add a [Price-to-Book Ratio](/metrics/valuation-metrics/price-to-book-ratio) filter of P/B ≤ 2.0. This restricts results to the low-P/B universe where the F-Score was designed to operate as a value trap filter. Without the value overlay, the screen surfaces financially healthy companies broadly, which is useful in its own right, but removes the specific context where the score's trap-detection function is most powerful.

The full pre-configured screener is available at GeminIQ's [Piotroski F-Score Screener](/screens/stock-screeners/piotroski-f-score). For a complementary approach that combines cheapness and quality from a different angle, the [Magic Formula investing post](/blog/magic-formula-investing-explained) covers how earnings yield and return on invested capital combine in Greenblatt's screener — a methodology that targets a similar class of undervalued businesses but ranks by quality and value simultaneously rather than filtering on financial health signals. And for a deeper look at why the quality of underlying financial data matters for any metric calculated from it, the [ROIC explainer](/blog/roic-return-on-invested-capital-explained) covers how methodology differences move calculated figures by ten percentage points or more for the same company in the same period.

---

## Frequently Asked Questions

### Does the F-Score work outside the low price-to-book universe?

The score functions as a financial health indicator in any context, but the documented alpha — approximately **7.5% annual return separation** — came specifically from the low-P/B universe. Applied universally, the score retains value as a negative filter: avoiding the 0–2 cohort is still useful regardless of valuation context. But the magnitude of the return separation in Piotroski's research was a low-P/B phenomenon. Most academic follow-up work confirms the score is more powerful as a quality tiebreaker within a value screen than as a standalone signal applied to the full market.

### What is the difference between the F-Score and the Altman Z-Score?

They measure related but distinct things. The [Altman Z-Score](/blog/altman-z-score-financial-distress) is a bankruptcy prediction model — it estimates the probability of financial distress within two years using a weighted formula of five balance sheet and income statement ratios. The F-Score is a financial health improvement score — it measures whether a company's fundamentals are getting better or worse across nine binary signals. A company can carry a safe Altman Z-Score (low near-term bankruptcy risk) and a low F-Score (fundamentals deteriorating gradually). For value investors, both are useful in combination: the Z-Score screens out existential risk, and the F-Score screens out ongoing fundamental deterioration before it reaches a crisis.

### Can I apply the F-Score to technology companies?

With modification. Asset turnover is naturally lower for capital-light software businesses, and the gross margin signal may require threshold adjustment for SaaS companies where cost-of-revenue structure differs fundamentally from manufacturing or retail. The profitability signals — positive ROA, positive operating cash flow, improving ROA, strong accruals — transfer directly and are arguably most informative for capital-light businesses where cash flow quality is the critical variable. The accrual signal is particularly worth examining for technology companies: a software business where reported earnings consistently run far ahead of operating cash flow is a qualitatively different situation than one where cash generation matches or exceeds reported income.

### How frequently should the F-Score be re-evaluated?

Quarterly, aligned with 10-Q filing cadence. Because the signals are based on year-over-year comparisons, each new filing updates the trailing inputs. A company that scored a 3 in Q1 because of a temporarily weak current ratio and declining asset turnover may score a 6 by Q3 if the balance sheet has strengthened and efficiency trends have reversed. The score is a dynamic indicator, not a permanent classification. Treating a single score as static misses the directional information that makes the tool most useful — the trend of the score is often as informative as the level.

### Why might F-Score calculations differ across financial platforms?

Because the underlying financial statement inputs differ. Gross margin reclassifications that an aggregator has normalized away will produce a different gross margin improvement signal than the as-filed data. Lease capitalization under ASC 842 affects both the current ratio and asset turnover calculations, and platforms handle the current portion of operating lease obligations differently. The ROA calculation depends on how average total assets are derived across periods, and whether any restated figures have been applied to prior periods. The most reliable calculation uses as-filed XBRL data directly, without normalization that introduces artificial consistency across periods. Two platforms running the same company through the same nine signals can produce scores that differ by two or three points for this reason alone.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=piotroski-f-score-value-trap)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Priced for Perfection, Quantified: When Great Earnings Aren't Enough
source: https://www.geminiq.com/blog/priced-for-perfection-explained

### Priced for Perfection, Quantified: When Great Earnings Aren't Enough
GeminIQ's cross-universe filing data quantifies the 'priced for perfection' pattern: quarters combining strong revenue growth with an above-sector Price-to-Sales Ratio were followed by the weakest three-month returns of any bucket in this study, while cheap, weak quarters delivered the strongest.

**"Priced for perfection" describes a stock whose price already assumes the good quarter it is about to report — so a strong result changes nothing and anything less breaks the story. Measured across 111,782 as-filed quarterly filings, quarters that were both strong (positive revenue growth) and expensive (a [Price-to-Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) above the company's own sector median) returned a mean +1.00% over the following three months, against a universe base rate of +2.74% — the weakest of the four buckets in this study.**

In July 2011, [Netflix](/stocks/NFLX) beat earnings estimates by more than **13%**, grew revenue **51.7%** year-over-year, and had already run up **63.5%** for the year heading into the print. Three months later the stock was down more than half. The quarter itself was good. The price had already priced in a better one.

That pattern has a name investors reach for constantly — "priced for perfection" — and until now it has mostly lived as a vibe, not a number. GeminIQ's as-filed data can quantify it directly: every quarter where trailing revenue grew year-over-year, crossed with whether the stock traded above or below its own sector's valuation, joined to what happened over the next three months.

This study reads **111,782** quarterly filings — 10-Qs and 10-Ks, excluding financial-sector issuers — from **3,283** companies in GeminIQ's as-filed database, filed between February 2011 and May 2026, joined to each stock's cumulative return over the three months following the filing date.

## Strong Quarters at Expensive Prices Returned the Least

Split every filing two ways: did trailing revenue grow year-over-year, and did the stock trade above or below the median Price-to-Sales Ratio (P/S) of every other company filing under the same four-digit SIC code that quarter. Four buckets fall out, and valuation — not the quarter itself — does almost all the work.

Quarters that were both **strong** (positive revenue growth) and **expensive** (P/S above the sector median) were followed by the weakest returns of any bucket over the next three months. Quarters that were **weak** (revenue growth at or below zero) and **cheap** (P/S at or below the sector median) were followed by the strongest. Whether the quarter itself was good barely moved the outcome once valuation is held constant. The expensive column underperformed the cheap column in both rows, by a wider margin than the strong column outperformed the weak column in either.

## Three-Month Returns by Quarter Strength and Sector-Relative Valuation

<center><sup>GeminIQ data study: mean 3-month post-filing return by quarter strength and sector-relative valuation. Built from as-filed 10-K/10-Q data via GeminIQ, joined to post-filing market reaction. n = 111,782 filings, February 2011–May 2026.</sup></center>

| Quarter | Valuation | N | Mean 3-Month Return | Median 3-Month Return |
|---|---|---|---|---|
| Weak (revenue growth ≤0%) | Cheap (≤ sector median P/S) | 22,250 | **+5.33%** | +2.18% |
| Weak (revenue growth ≤0%) | Expensive (> sector median P/S) | 19,127 | **+1.49%** | 0.00% |
| Strong (revenue growth >0%) | Cheap (≤ sector median P/S) | 33,725 | **+3.65%** | +1.48% |
| Strong (revenue growth >0%) | Expensive (> sector median P/S) | 36,680 | **+1.00%** | 0.00% |

Across the full eligible sample, the universe base rate over the same three-month window is **+2.74%** mean, **+0.73%** median. Every bucket above is measured against that base rate, not against zero — three months after any random filing in this window, the average stock was already up, because the sample sits inside a long bull market. The strong-and-expensive bucket returned roughly a third of the base rate. The weak-and-cheap bucket returned nearly double it.

This is a historical association across GeminIQ's filing sample, not a forecast for any individual stock. Every figure above is winsorized at the top and bottom 1% of returns so a handful of extreme quarters can't carry the result, and every bucket clears the 200-filing floor this series requires before drawing a conclusion by a wide margin.

## Netflix, Etsy, Peloton, and Snap: Four Priced-for-Perfection Quarters

Four names carry this pattern in ways that are hard to forget — and not all for the same reason.

| Company | Quarter | Revenue Growth | P/S | Sector Median P/S | 3-Month Return |
|---|---|---|---|---|---|
| [Netflix](/stocks/NFLX) | July 2011 | **+51.7%** | — | — | **-56.9%** |
| [Etsy](/stocks/ETSY) | November 2021 | **+61.7%** | **11.81** | **2.80** | **-45.1%** |
| [Peloton](/stocks/PTON) | November 2021 | **+72.7%** | **6.44** | **0.82** | **-51.4%** |
| [Snap](/stocks/SNAP) | April 2022 | **+38%** | **13.21** | **4.17** | **-49.7%** |

[Netflix](/stocks/NFLX) already opened this piece. Its **July 2011** quarter is close to a textbook case: earnings beat consensus by more than **13%**, revenue grew **51.7%** year-over-year, and the stock had already run up **63.5%** year-to-date heading into the print. Three months later it was down **56.9%**, as a controversial price hike and, weeks later, the short-lived "Qwikster" split turned an expensive, growing stock into a cautionary tale.

[Etsy](/stocks/ETSY)'s **November 2021** quarter beat on both revenue and earnings, and the stock popped more than **13%** the next day. GeminIQ's data shows trailing revenue growth of **61.7%** against a Price-to-Sales Ratio of **11.81** — more than four times the **2.80** sector median that quarter. None of that was wrong three months later, when the position was down **45.1%**. What changed wasn't Etsy's business; it was every expensive growth stock getting repriced at once as the market rotated out of 2021's pandemic winners.

[Peloton](/stocks/PTON)'s **November 2021** quarter is the honest exception on this list — it missed Wall Street's revenue and EPS estimates and came with a guidance cut, and the stock fell **36%** in a single after-hours session. What still puts it in this bucket is trailing revenue growth of **72.7%** against a Price-to-Sales Ratio of **6.44**, nearly eight times its sector's **0.82** median — the business was still growing fast by GeminIQ's own filed numbers even as the deceleration became impossible to ignore. Three months out, the position was down **51.4%**.

[Snap](/stocks/SNAP)'s **April 2022** quarter looked fine on its face — revenue grew **38%**, daily users beat guidance — but its own forward guidance came in below what the Street wanted, at a Price-to-Sales Ratio of **13.21** against a **4.17** sector median. The real break came a month later: a rare mid-quarter warning that even the lowered guidance wouldn't hold sent the stock down **43%** in a single session, its worst day ever, and dragged the rest of digital advertising down with it. The position was down **49.7%** three months after the April filing.

## How Sector-Relative Valuation Was Measured

Revenue strength comes from GeminIQ's pre-calculated Net Revenue TTM Growth 1Y; valuation comes from Price-to-Sales Ratio (P/S), compared against the median P/S of every other filing under the same four-digit SIC code that quarter rather than the market as a whole, so an expensive software name isn't judged against a cheap grocery chain. Financial-sector issuers (SIC 6000–6799) are excluded, since P/S is a poor fit for banks and insurers. Full methodology — including how the winsorizing, the base-rate comparison, and the 200-filing floor are applied — is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## How to Check If a Holding Is Priced for Perfection

This isn't a screen that requires a study to run. Pull up any position in GeminIQ's [Calculated Metrics](/features#calculated-metrics) view and check its Net Revenue TTM Growth 1Y and Price-to-Sales Ratio (P/S), then check GeminIQ's [Earnings Market Reaction Heat Map](/features#price-variance) to see how the position has already traded since its last filing. Open the [Stock Screener](/features#screener), filter to the same four-digit SIC code, and sort by P/S TTM to see where the position actually sits against its own peers, not the market as a whole. A holding with strong revenue growth trading above its sector's median P/S is sitting in the bucket that returned the least in this study — worth knowing before the next print, not after it.

## Frequently Asked Questions

### What does "priced for perfection" mean?

It describes a stock trading at a price that already assumes the best plausible version of its next quarter. Because the good result is already in the price, a strong quarter gives the stock nothing new to react to, and anything short of the assumption removes something. In this study the phrase is given a measurable definition: a filing where trailing revenue grew year-over-year *and* the stock's Price-to-Sales Ratio sat above the median of every other company filing under the same four-digit SIC code that quarter. Those quarters returned a mean **+1.00%** over the next three months against a **+2.74%** base rate — the weakest of the four buckets.

### Is a high Price-to-Sales Ratio always a warning sign?

No. This study never uses a fixed multiple, because what counts as high depends entirely on the sector: Etsy's **11.81** sat against a **2.80** sector median, while Peloton's lower **6.44** sat against a **0.82** median and was the more extreme reading of the two relative to its peers. The finding is also an association across a large sample, not a verdict on a position — the expensive-and-strong bucket still returned a positive **+1.00%** mean over three months, just less than the universe did.

### What counts as an "expensive" quarter in this study?

A filing where the stock's trailing Price-to-Sales Ratio (P/S) sat above the median P/S of every other company filing under the same four-digit SIC code that quarter — a sector-relative threshold, not a fixed multiple.

### How many filings does the strong-and-expensive bucket cover?

**36,680** quarterly filings across the sample window, well above the roughly 200-filing floor this series requires before drawing a conclusion from a bucket.

### Does a strong, expensive quarter mean a stock will fall?

No. The study reports what quarters carrying these two traits were historically followed by across a large sample — a historical association over the sample window, not a forecast for any specific position.

### Why does valuation seem to matter more than whether the quarter itself was good?

Across all four buckets, the expensive column underperformed the cheap column by a wider margin than the strong column outperformed the weak column — suggesting the starting price does more work than the quarter's headline growth number, once both are measured against the same sample.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=priced-for-perfection-explained)**

## Research Faster. Invest Smarter.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. We built GeminIQ because we believe you deserve a better fundamental analysis tool—one that goes beyond basic price charts and processed numbers. We extract our data directly from SEC 10-K and 10-Q filings to ensure that when you look at a balance sheet or a cash flow statement, you are seeing the numbers exactly how the company reported them. Our goal is to give you the tools to verify the narrative for yourself using clean, traceable data. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 3,283 companies outside the financial sector (SIC 6000–6799 excluded), drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 111,782 quarterly filings, filed February 2011 through May 2026, make up the eligible sample (non-null Net Revenue TTM Growth 1Y, Price-to-Sales Ratio, sector code, and three-month forward return). Post-filing returns are cumulative from each filing's filed date, winsorized at the top and bottom 1%, and never compounded. "Expensive" and "cheap" are determined against each filing's own four-digit SIC code median Price-to-Sales Ratio for that quarter, not a fixed threshold. The universe base rate (+2.74% mean / +0.73% median three-month return) is computed from the same eligible sample. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: How to Pull SEC Financial Data With Python
source: https://www.geminiq.com/blog/pull-sec-financial-data-python

### How to Pull SEC Financial Data With Python
The SEC publishes almost every number in almost every 10-K and 10-Q through three free XBRL endpoints that need no key and no signup, which makes writing your own data pipeline look like a weekend job. This guide builds that pipeline properly — all three endpoints, the frames period syntax that silently 404s, the rate limit, CIK padding, duplicate rows, and fiscal-period alignment — and then shows the two problems that remain after the script is finished, because they are properties of the filings rather than bugs in the code.

The case against paying for fundamental data is always the same, and it is a fair one: the SEC gives this away. Three public XBRL endpoints, no key, no signup, no cost, every number in almost every 10-K and 10-Q sitting behind a URL. A hundred lines of Python and the problem is solved.

The script part of that is true. A Python script against SEC EDGAR's API will run cleanly, return a 200 status code, parse into valid JSON, and still be wrong — because a script that only handles the happy path silently mishandles the situations EDGAR's own data structure creates: a filing history too long for one response, a rate limit that throttles without warning, a period parameter that 404s if it is off by one character, a fiscal quarter that appears twice, and a fiscal calendar that doesn't line up with the calendar year the script assumes.

This guide builds the whole thing from the ground up, calling out each trap at the exact point in the code where it has to be handled. Then it does the more useful thing: it shows what is still broken after the script is finished and correct, because those last two problems live in the filings, not in the code.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pull-sec-financial-data-python)**

---

## Table of Contents

- [The Endpoints You Are Working With](#the-endpoints-you-are-working-with)
- [Step 1: Set Up Request Headers](#step-1-set-up-request-headers)
- [Step 2: Handle Submissions Pagination](#step-2-handle-submissions-pagination)
- [Step 3: Respect the Rate Limit](#step-3-respect-the-rate-limit)
- [Step 4: Pull One Company's Concept History](#step-4-pull-one-companys-concept-history)
- [Step 5: Query Every Company at Once With Frames](#step-5-query-every-company-at-once-with-frames)
- [Step 6: Deduplicate Repeated Rows in a Response](#step-6-deduplicate-repeated-rows-in-a-response)
- [Step 7: Align Fiscal Periods Correctly](#step-7-align-fiscal-periods-correctly)
- [Step 8: Put It Together](#step-8-put-it-together)
- [What This Script Doesn't Solve](#what-this-script-doesnt-solve)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## The Endpoints You Are Working With

The SEC's XBRL data lives behind a small number of RESTful endpoints at `data.sec.gov`, all free, all returning JSON, none requiring an API key. Three of them serve XBRL facts and one serves filing metadata, and choosing the wrong one is the difference between a single fast call and downloading a company's entire reporting history to read one line off it.

| Endpoint | URL pattern | What it returns | Call it when |
|---|---|---|---|
| `submissions` | `/submissions/CIK{10-digit}.json` | A company's filing history — form types, dates, accession numbers | You need the list of filings, not the numbers inside them |
| `companyfacts` | `/api/xbrl/companyfacts/CIK{10-digit}.json` | Every XBRL fact one company has ever reported, across every concept and filing | You are building a full model across many line items for one company |
| `companyconcept` | `/api/xbrl/companyconcept/CIK{10-digit}/{taxonomy}/{tag}.json` | One concept for one company across its whole filing history | You already know the tag and want a single trend line |
| `frames` | `/api/xbrl/frames/{taxonomy}/{tag}/{unit}/{period}.json` | One concept across every company that reported it for one period | You want a cross-sectional comparison rather than one company |

`companyfacts` pulls back everything a company has ever tagged — often several hundred distinct concepts across `us-gaap`, plus a much thinner `dei` (Document and Entity Information) taxonomy carrying entity-level facts like shares outstanding. Requesting a full facts file for a single metric like revenue means downloading and discarding almost everything in the response. `frames` inverts the whole model: instead of one company across many concepts, one concept across every company. It is the only cross-sectional endpoint the SEC offers.

One formatting rule applies to every URL above: the CIK — the Central Index Key, the permanent numeric identifier the SEC assigns to each filer — must be zero-padded to exactly 10 digits, with the literal string `CIK` prefixed onto it. [Apple's](/stocks/AAPL) CIK is 320193, but the URL requires `CIK0000320193`. Passing the unpadded number returns a 404 rather than resolving gracefully, and it is the single most common first mistake. The full padding rules, including where EDGAR is more forgiving than this, are in [EDGAR Accession Numbers and Filing URL Structure](/blog/edgar-accession-number-url-structure).

---

## Step 1: Set Up Request Headers

Every request to `data.sec.gov` needs a descriptive `User-Agent` header identifying the caller and a contact method — a request without one gets a 403, not a graceful fallback, and it is the second most common first mistake after CIK padding.

```python
import requests
import time

HEADERS = {"User-Agent": "YourApp your-email@example.com"}
BASE = "https://data.sec.gov"
```

Replace the placeholder with a real app name and a real contact email. The SEC doesn't validate the string beyond checking that a `User-Agent` header is present at all, but an accurately descriptive one is what the fair-access policy actually asks for.

---

## Step 2: Handle Submissions Pagination

The `submissions` endpoint returns a company's filing history — but not all of it in one response. The `filings.recent` block covers at least one year of filings or the 1,000 most recent, whichever is larger. Anything older lives in separate JSON files, referenced under `filings.files`, each with the same columnar structure as `recent`. A script that reads only `filings.recent` silently truncates the filing history of any company with more than a year or two of activity — which is most established companies.

```python
def sec_get(url, headers=HEADERS, max_retries=3):
    for attempt in range(max_retries):
        resp = requests.get(url, headers=headers, timeout=20)
        if resp.status_code == 200:
            time.sleep(0.12)  # stay comfortably under 10 requests/second
            return resp.json()
        if resp.status_code == 403:
            raise RuntimeError("403 — check that your User-Agent header is set and descriptive.")
        if resp.status_code == 429:
            time.sleep(10)
            continue
        resp.raise_for_status()
    raise RuntimeError(f"Failed after {max_retries} retries: {url}")

def get_full_submissions(cik):
    cik_padded = str(cik).zfill(10)
    data = sec_get(f"{BASE}/submissions/CIK{cik_padded}.json")
    recent = dict(data["filings"]["recent"])  # copy so we don't mutate the response

    for older_file in data["filings"].get("files", []):
        older = sec_get(f"{BASE}/submissions/{older_file['name']}")
        for key in recent:
            if key in older:
                recent[key] = older[key] + recent[key]

    return data, recent
```

Each entry in `filings.files` carries its own `name` — the exact filename to request next — so the code never has to guess a URL pattern for the older archives. It just follows the pointer the SEC's own response gives it.

---

## Step 3: Respect the Rate Limit

`data.sec.gov` caps requests at **10 per second per IP address**, enforced regardless of how many machines are making the calls. Exceeding it triggers a temporary block — typically around **10 minutes** — that gets extended if requests keep arriving during the timeout, rather than a clean error on each request after the limit.

The `sec_get` function above already sleeps 0.12 seconds after every successful call, which keeps a sequential script comfortably under the ceiling without a more elaborate rate limiter. For anything pulling data across more than a handful of companies, that per-request delay adds up in wall-clock time faster than it looks on paper. A job touching a few hundred companies is a run measured in minutes, not seconds — and that's by design, not a bug in the script. For jobs at that scale, the SEC's own bulk `companyfacts.zip` archive — republished nightly around **3:00 a.m. ET**, containing the same data the `companyfacts` and `frames` APIs serve — is faster than looping through individual calls.

---

## Step 4: Pull One Company's Concept History

With headers and pagination handled, pulling an actual number looks like the easy part. It is the part where most scripts quietly break, and the break shows up as a 404.

```python
REVENUE_TAG_CANDIDATES = [
    "RevenueFromContractWithCustomerExcludingAssessedTax",
    "Revenues",
]

def get_concept_series(cik, tag, taxonomy="us-gaap"):
    """
    Return the units dict for one concept, or None if this company has never
    reported under that element. A 404 here is data, not a failure.
    """
    cik_padded = str(cik).zfill(10)
    url = f"{BASE}/api/xbrl/companyconcept/CIK{cik_padded}/{taxonomy}/{tag}.json"
    try:
        return sec_get(url)["units"]
    except requests.HTTPError as err:
        if err.response is not None and err.response.status_code == 404:
            return None
        raise

def get_revenue_series(cik, candidates=REVENUE_TAG_CANDIDATES):
    for tag in candidates:
        units = get_concept_series(cik, tag)
        if units and "USD" in units:
            return tag, units["USD"]
    raise RuntimeError(
        f"None of {candidates} returned data for CIK {cik}. "
        "Check the company's own filed tags before assuming the element exists."
    )
```

A 404 on a `companyconcept` request does not mean the endpoint is broken or the CIK is wrong. Most often it means exactly what it says: this company has never reported anything under that element. Hard-coding `us-gaap/Revenues` and treating a 404 as an outage is the single most common way a working script produces an empty dataset for a real company.

The reason there is more than one candidate to try is a taxonomy change, not a quirk of the API. The element that carried service revenue on income statements for years was deprecated in the 2018 taxonomy alongside ASC 606 and superseded by `RevenueFromContractWithCustomerExcludingAssessedTax`, and a large share of filers moved to the newer element while others kept the older, simpler one. Which element a given company uses depends on the filer and the period, so the only safe pattern is to try each candidate and let the 404 tell you. [The taxonomy post](/blog/xbrl-financial-data-providers-compared) covers why the vocabulary moves at all.

The response for a resolved concept is one time series and nothing else:

```json
{
  "cik": 320193,
  "entityName": "Apple Inc.",
  "units": {
    "USD": [
      {
        "end": "2024-09-28",
        "val": 391035000000,
        "accn": "0000320193-24-000123",
        "fy": 2024,
        "fp": "FY",
        "form": "10-K",
        "filed": "2024-11-01"
      },
      {
        "end": "2023-09-30",
        "val": 383285000000,
        "accn": "0000320193-23-000106",
        "fy": 2023,
        "fp": "FY",
        "form": "10-K",
        "filed": "2023-11-03"
      }
    ]
  }
}
```

Each entry in the `units.USD` array is one reported value: the period end date, the value itself (in whole dollars, never thousands or millions), the accession number of the filing it came from, the fiscal year and period, the form type, and the date it was filed. That `accn` field is the reason any figure derived from this endpoint stays checkable — it resolves to one exact filing, and nothing else.

---

## Step 5: Query Every Company at Once With Frames

`frames` answers a different question: not "what has this company reported," but "what did every company report." A single call to:

```
GET https://data.sec.gov/api/xbrl/frames/us-gaap/AccountsPayableCurrent/USD/CY2024Q1I.json
```

returns one JSON object with a `data` array containing one entry per company that reported Accounts Payable, Current as of that period — thousands of rows from a single request, in place of thousands of individual `companyconcept` calls:

```json
{
  "taxonomy": "us-gaap",
  "tag": "AccountsPayableCurrent",
  "ccp": "CY2024Q1I",
  "uom": "USD",
  "label": "Accounts Payable, Current",
  "description": "Carrying value as of the balance sheet date...",
  "pts": 3440,
  "data": [
    {
      "accn": "0001104659-24-037408",
      "cik": 1750,
      "entityName": "AAR CORP",
      "loc": "US-IL",
      "end": "2024-02-29",
      "val": 230300000
    }
  ]
}
```

The `pts` field states the row count up front — always equal to the length of `data` — which is worth checking before assuming the response includes every company you expected. A materially lower `pts` count than expected usually means the tag itself isn't the one most companies in your universe actually use.

### Building the Period Parameter

The single most common `frames` failure is a malformed period parameter, and getting it right requires knowing whether the concept you are requesting is a duration fact or an instant fact.

| Period format | Shape | Concept type | Example | Use for |
|---|---|---|---|---|
| `CY####` | Full calendar year (a duration of roughly 365 days) | Duration | `CY2024` | Annual income statement and cash flow concepts |
| `CY####Q#` | Calendar quarter (a duration of roughly 91 days) | Duration | `CY2024Q1` | Quarterly income statement and cash flow concepts |
| `CY####Q#I` | Point in time, as of a specific date (`I` for instantaneous) | Instant | `CY2024Q1I` | Balance sheet concepts |

Balance sheet concepts — `Assets`, `Liabilities`, `StockholdersEquity`, `AccountsPayableCurrent` — are instant facts and require the `I` suffix. Income statement and cash flow concepts — `Revenues`, `NetIncomeLoss`, `OperatingIncomeLoss` — are duration facts and use the plain form. Appending `I` to a duration concept, or omitting it from an instant one, doesn't return a helpful error. It returns a 404, which looks identical to a typo in the tag name and sends most people debugging the wrong part of the URL.

This isn't something a filer decides fact by fact, which is why the table above is reliable rather than a rule of thumb. Every concept in the US-GAAP taxonomy carries its own declared period type — instant or duration — set once, centrally, when the concept was defined. `us-gaap:Assets` is declared instant, because a balance sheet reports what a company owns as of a date. `us-gaap:Revenues` is declared duration, because revenue only means something over a span of time. A filer cannot legally attach a duration context to `us-gaap:Assets`, or an instant context to `us-gaap:Revenues` — validation software rejects the mismatch before the filing is ever accepted.

One convention to know before doing date arithmetic on what comes back. XBRL interprets a `startDate` as the very beginning of that calendar day and an `endDate` as the very end of that calendar day. A period written in a filing as "April 1, 2023 to March 31, 2024" is encoded with a start of `2023-04-01` and an end of `2024-03-31`, but the underlying instant those two dates actually bound runs from midnight opening April 1 to midnight closing March 31. XBRL's own published guidance describes the resulting confusion plainly: the same calendar date means a different literal instant depending on whether it appears in a `startDate`, an `endDate`, or an `instant` element, and that asymmetry has caused, in the specification's own words, "a lot of confusion and a lot of tagging errors." A pipeline computing period length from those two dates has to know the convention to get the day count right.

---

## Step 6: Deduplicate Repeated Rows in a Response

The same fiscal period can appear more than once in a `companyconcept` response. When a company reports a prior period again — as a comparative figure in a later filing, or as a corrected number after a restatement — both entries stay in the historical record, tied to different accession numbers and `filed` dates. A script that takes the first match for a period, or averages the two, gets a number nobody actually reported.

```python
def dedupe_latest_filed(facts):
    """
    Keep only the most recently filed value for each (fy, fp, end) period.
    """
    latest = {}
    for fact in facts:
        key = (fact["fy"], fact["fp"], fact["end"])
        if key not in latest or fact["filed"] > latest[key]["filed"]:
            latest[key] = fact
    return sorted(latest.values(), key=lambda f: f["end"])
```

Keying on `(fy, fp, end)` rather than `end` alone matters too — the same period-end date can occasionally carry more than one `fp` designation across filing types, and treating those as one key would silently merge two different things.

Worth being precise about scope: this handles duplicate rows in an API response, which is a data-shape problem. It is not a way to detect that a restatement happened, what changed, or whether it matters — that is a research question, and it is covered in [How to Find Restatements in Filings](/blog/how-to-find-restatements-in-filings). All this function does is pick one row per period.

The `frames` endpoint doesn't need this. Its own documentation states it aggregates one fact for each reporting entity that is "last filed" for the requested period, meaning the SEC already performs this selection server-side. `companyconcept` and `companyfacts` make no such guarantee, and the SEC's own field descriptions don't warn you to add the step.

---

## Step 7: Align Fiscal Periods Correctly

A company's `end` date doesn't tell a script which calendar quarter it covers — only the `fp` field does. Apple's fiscal Q1 ends in December; [Microsoft's](/stocks/MSFT) fiscal Q1 ends in September. A script that buckets facts into calendar quarters by inspecting the month of `end` gets Apple and Microsoft's fiscal years misaligned relative to each other, even though both companies' own data is internally correct.

```python
def interim_periods_only(facts):
    """
    Use fp (Q1/Q2/Q3/FY) — the company's own fiscal-period label — never
    infer the period from the calendar month of 'end'.
    """
    return [f for f in facts if f["fp"] in ("Q1", "Q2", "Q3")]
```

This also matters for annual figures: a 10-K's `fp` value is `FY`, and filtering it out here (or including it, for an annual series) has to be deliberate rather than inferred from the reporting date.

The second half of getting periods right is knowing what an interim figure actually contains. A 10-Q reports flow concepts like revenue as year-to-date figures, not quarter-only. A `companyconcept` response for a Q3 filing shows nine months of revenue, not three. Deriving the standalone third-quarter number requires subtracting the prior quarter's year-to-date figure from the current one — a calculation the API never performs for you, and one this script deliberately does not perform either, so that everything it prints is exactly what the filing said.

---

## Step 8: Put It Together

```python
if __name__ == "__main__":
    cik = 320193  # Apple

    submissions, recent = get_full_submissions(cik)
    print(f"{submissions['name']}: {len(recent['accessionNumber'])} total filings retrieved")

    tag, revenue = get_revenue_series(cik)
    print(f"Revenue element resolved to: us-gaap:{tag}")

    clean = dedupe_latest_filed(revenue)
    interim = interim_periods_only(clean)

    for f in interim[-8:]:
        print(f"{f['end']}  {f['fp']} {f['fy']}  ${f['val']:,}  "
              f"(as filed — year-to-date, not a standalone quarter)  accn {f['accn']}")
```

Run end to end, this pulls Apple's complete filing history — not just the most recent year — resolves which revenue element the company actually reports under rather than assuming one, and prints the last eight deduplicated, correctly fiscal-labelled interim revenue figures, each with the accession number of the filing it came from.

Read that output label carefully, because it is the difference between a correct script and a wrong dataset. Those are not eight quarters of revenue. They are eight year-to-date figures, exactly as the filings report them. Turning them into standalone quarters is a subtraction the script above leaves to you on purpose, and a script that skips that step while calling its output "quarterly revenue" is producing wrong numbers with a straight face.

---

## What This Script Doesn't Solve

Everything above is real work, and none of it is wasted: the script is correct, the endpoints are free, and the data is authoritative. That is the honest version of the "just script it" argument. Here is the other half.

Two problems survive every line of the code above, because they aren't bugs in the request logic — they are properties of the underlying filings.

The first is a tag that is present and wrong. If a company's `Revenues` element captured one component of revenue rather than the total in a particular year, no amount of correct pagination, deduplication, or fiscal alignment recovers the right number. The script returns exactly what was filed, which is the whole point, and exactly what was filed is misleading. That is [a tag-drift problem](/blog/xbrl-tag-changes-between-filing-years), and the only defense is checking the tag against the filing.

The second is a tag that isn't there at all. If a company reported a line item under a custom extension tag it defined itself, rather than the standard `us-gaap` element this script queries, the value is invisible to the query — no error, no warning, no row. The candidate-list pattern in Step 4 handles standard-element aliases, not company-invented ones, and nothing generic can, because a custom tag has no meaning outside that one filer's own taxonomy. [The taxonomy post](/blog/xbrl-financial-data-providers-compared) covers when a filer is permitted to create one and what every platform downstream has to guess as a result.

Both require reading the actual `tag` value a company used, not just querying the concept a script assumes it used. That is a research step, not a code fix, and it is the step the pipeline never finishes. This is also the honest way to think about the build-versus-buy question: the script is a weekend. Keeping it correct across tag aliases, taxonomy revisions, custom extensions, and restated periods, for every company you care about, is not. Platforms that attach a source citation to an extracted figure — [Finbox](/competitor-comparison/finbox) among them — remove part of that maintenance burden while still handing back a modeled number. GeminIQ's [Financial Statements](/features#financial-statements) go the other way: every value keeps the tag and the accession number it was filed under, so the check the script above can't perform is one you can run on any figure in seconds. If what you want is the number the company actually reported, with the tag still attached, that is what the [paid and free plans](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pull-sec-financial-data-python) are for.

---

## Frequently Asked Questions

### Why does my SEC EDGAR script get a 403 error?

Almost always a missing or generic `User-Agent` header. `data.sec.gov` requires a descriptive header identifying the requester and a contact method on every request, including the first one.

### Why does a companyconcept or frames request return a 404?

Three common causes, in order. An unpadded CIK — the API requires exactly 10 digits with a `CIK` prefix. A mismatched frames period suffix — an instant concept like `Assets` requested without the trailing `I`, or a duration concept like `Revenues` requested with it. Or the company simply never reported under the element you asked for, which is data rather than an error and should be handled as a fallback rather than a crash.

### What's the difference between companyfacts, companyconcept, and frames?

`companyfacts` returns every concept for one company. `companyconcept` returns one concept for one company across all periods. `frames` returns one concept across every company for a single period. The choice depends on whether you're building a dataset for one company or one metric across the market.

### How do I know if a tag should be instant or duration?

The taxonomy declares it. Every concept in the US-GAAP taxonomy has a fixed period type set when the concept was defined — balance sheet items like `Assets` are instant, income statement and cash flow items like `Revenues` are duration — and a filer cannot legally attach the wrong type of context to a concept.

### Why is my filing history missing older filings?

The `submissions` endpoint's `filings.recent` block only covers roughly the last year or 1,000 filings, whichever is larger. Older filings are referenced separately under `filings.files` and need to be fetched and merged in.

### Why do I get two values for the same fiscal quarter?

A period reported again in a later filing — as a comparative figure or a corrected number — stays in the record alongside the original, tied to a different accession number. Deduplicate by keeping the entry with the most recent `filed` date for each `(fy, fp, end)` combination.

### Can I use the `end` date to figure out which fiscal quarter a filing covers?

No, not reliably. Companies with non-calendar fiscal years — Apple, Microsoft, and many others — have an `end` date that doesn't align with calendar quarters. Use the `fp` field (`Q1`, `Q2`, `Q3`, `FY`) instead.

### Do I need an API key for the SEC EDGAR XBRL API?

No. None of the endpoints require registration or a key. They do require a descriptive `User-Agent` header with contact information, and requests are capped at 10 per second per IP address.

A script that runs without errors and a script that returns correct data are two different bars to clear. Everything in this guide is aimed at the second one — and at being clear about where the second one still isn't enough.

---

## Related Reading

- [When XBRL Tags Change Between Filing Years](/blog/xbrl-tag-changes-between-filing-years) — a failure mode no amount of correct pagination or deduplication can fix.
- [SEC XBRL Taxonomy Explained for Investors](/blog/xbrl-financial-data-providers-compared) — why the elements this script queries change between filing years, and when a filer can invent its own.
- [EDGAR Accession Numbers and Filing URL Structure](/blog/edgar-accession-number-url-structure) — the CIK and accession-number formatting rules behind every URL above.
- [XBRL Tags: A Fundamental Investor's Guide](/blog/xbrl-tags-fundamental-investors-guide) — how to read the tags themselves once you have the data.
- [Financial Data Normalization Explained](/blog/financial-data-normalization-explained) — what happens to this same tag-resolution problem on the aggregator side.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=pull-sec-financial-data-python)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Endpoint URL patterns, response fields, the 10-requests-per-second rate limit, the User-Agent requirement, the frames "last filed" aggregation rule, and the nightly bulk `companyfacts.zip` archive are all as documented at data.sec.gov and sec.gov/os/accessing-edgar-data.
- The `startDate` / `endDate` boundary convention and the quoted language on tagging errors are from XBRL's own published guidance on period contexts.
- `RevenueFromContractWithCustomerExcludingAssessedTax` and the 2018 taxonomy / ASC 606 transition referenced from the FASB US GAAP Financial Reporting Taxonomy release notes.
- Sample JSON responses are illustrative of each endpoint's structure; values shown reference Apple Inc. and AAR Corp filings via SEC EDGAR.

---

## Blog: Quality Compounder Investing: Philosophy, Criteria, and Screener
source: https://www.geminiq.com/blog/quality-compounder-investing-explained

### Quality Compounder Investing: Philosophy, Criteria, and Screener
Quality compounder investing identifies businesses that earn high returns on invested capital, can reinvest those earnings at similar rates, and sustain both for decades. This guide covers the five measurable criteria, the compounding math, and how to screen for them using as-filed SEC data.

Two businesses can show identical ROIC today. One earned **45% ROIC** three years ago; the other earned **18% ROIC** three years ago. The first is in competitive decline. The second is building a moat. A standard screener cannot tell them apart. That is the central problem with finding genuine quality compounders — not the definition of the category, which is straightforward, but the data behind any attempt to screen for it systematically. Quality compounder investing identifies businesses that earn high returns on invested capital, can reinvest those earnings at similarly high rates, and sustain both for extended periods. The compounding math is powerful: a business earning **25% ROIC** and reinvesting all its earnings at that rate doubles its intrinsic value roughly every three years, growing it by approximately **30×** over fifteen years. The problem is that businesses meeting this definition are rare, the market recognizes them, they almost never trade at cheap valuations, and most screeners used to find them run on normalized, aggregator-adjusted data rather than the as-filed numbers that reveal whether the economics are genuine. This guide covers what quality compounders are, the five measurable criteria that define them, why they are harder to identify than most platforms suggest, and how to screen for them using financial data sourced directly from SEC EDGAR filings.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quality-compounder-investing-explained)**

---

## Table of Contents

- [What Is a Quality Compounder?](#what-is-a-quality-compounder)
- [The Compounding Math: Why ROIC and Reinvestment Rate Are Inseparable](#the-compounding-math-why-roic-and-reinvestment-rate-are-inseparable)
- [The Five Criteria That Define a Quality Compounder](#the-five-criteria-that-define-a-quality-compounder)
- [Why Quality Compounders Almost Never Trade Cheap](#why-quality-compounders-almost-never-trade-cheap)
- [What Standard Screeners Get Wrong](#what-standard-screeners-get-wrong)
- [How to Run the Quality Compounder Screen in GeminIQ](#how-to-run-the-quality-compounder-screen-in-geminiq)
- [Reading Your Results: What to Verify Beyond the Filters](#reading-your-results-what-to-verify-beyond-the-filters)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What Is a Quality Compounder?

A quality compounder is a business that earns returns on invested capital well above its cost of capital, can redeploy meaningful amounts of those earnings at similarly high rates, and sustains both for long periods — ten years, twenty years, or more. The phrase is widely used but imprecisely applied. It is not a synonym for "high-quality business" or "blue-chip stock." It describes a specific economic structure: a flywheel that generates a high rate of return on every dollar put into the business and has a large enough reinvestment opportunity to keep the flywheel spinning at that rate.

The framework has roots in several decades of practitioner writing. Terry Smith built the Fundsmith Equity strategy around three principles: buy good companies, don't overpay, and do nothing. Nick Sleep and Qais Zakaria ran the Nomad Investment Partnership on the conviction that scale economies shared with customers create the most durable compounding businesses. Thomas Russo's long-duration philosophy pushed the same idea further — hold exceptional businesses through short-term earnings disappointments and let the underlying compounding play out over years, not quarters. Michael Mauboussin and Alfred Rappaport then formalized the academic version through their work on competitive advantage period, defining it as the duration over which a business can sustain above-cost returns on new investments before competitors erode them away. Common to all of these frameworks is a single conviction: most of the value in an exceptional business sits in terminal value — what the business will be worth in year ten or year twenty — rather than in near-term earnings. That conviction makes patience the most important variable in the strategy, not entry timing or quarterly execution.

The practical definition narrows to five measurable criteria: high gross margins, high return on invested capital, consistent revenue growth, low debt, and strong net profitability. Each captures a different dimension of the compounding engine. Together, they filter for businesses with the structural characteristics that make long-duration compounding possible. No single criterion is sufficient. All five together describe a category of company that is genuinely rare in the public markets.

---

## The Compounding Math: Why ROIC and Reinvestment Rate Are Inseparable

ROIC is the rate at which a business creates value. The reinvestment rate — the fraction of earnings the business can pour back into the engine at that ROIC — is the throttle that determines how fast intrinsic value actually grows. Both variables together govern the compounding trajectory, and most quality screens built around ROIC alone capture only half the picture.

Consider two businesses, each earning **20% ROIC**. The first reinvests **80%** of earnings back into the business at that rate. The second can only reinvest **20%** — the remainder goes out as dividends or buybacks because no high-return deployment opportunity remains. Using the reinvestment rate identity, earnings growth equals ROIC multiplied by reinvestment rate: the first business grows earnings at **16%** annually, the second at **4%**. Over fifteen years, the first business compounds its earnings base by roughly **9×**. The second compounds by roughly **1.8×**. Identical ROIC. Vastly different outcomes.

This is why a high-ROIC business that pays a large dividend or repurchases stock aggressively can be a perfectly good investment without being a great compounder. The quality compounder framework targets something more specific: businesses where the reinvestment opportunity is large enough to absorb most of what the business earns at the same high rate, keeping the flywheel spinning at full speed. For a full explanation of how ROIC is calculated from SEC filings and where third-party platforms introduce divergence, see [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained). The revenue growth filter in the quality compounder screen is the reinvestment capacity test — a business showing **20% ROIC** with no revenue growth has a capped compounding runway, while one showing **20% ROIC** with **15%** consistent revenue growth is expanding the capital base on which it compounds, multiplying the effect year over year. Both halves of the equation must be present simultaneously: ROIC measures the engine's power; revenue growth confirms it is expanding. One without the other is a good business. Not the compounding vehicle this framework targets.

---

## The Five Criteria That Define a Quality Compounder

The quality compounder framework translates the philosophical definition into five measurable filters — each drawn from data available directly in SEC filings, each targeting a distinct dimension of the compounding engine.

### What Is Gross Profit Margin in the Context of Quality Compounders?

GeminIQ's pre-calculated [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) screen filters for companies at **40%** or above. This is a structural signal, not an arbitrary threshold.

A business with gross margins below **40%** is typically competing on volume or price in a market where the product or service is not sufficiently differentiated to command premium economics. Commodity manufacturers, most retailers, and undifferentiated industrials rarely clear this level. Technology platforms, consumer brands with durable pricing power, specialty healthcare businesses, and industrial niche leaders — the sectors where quality compounders concentrate — typically run gross margins of **50%**, **60%**, or higher. A gross margin consistently above **40%** demonstrates that the unit economics at the product level are sound: the business captures meaningful value per unit sold, which creates the financial headroom to invest in R&D, distribution, and operations without sacrificing profitability elsewhere. More importantly, sustained high gross margins across multiple years signal competitive insulation. Businesses facing genuine price pressure at the product level lose gross margin over time; businesses that maintain it across business cycles have demonstrated that the pricing power is structural rather than cyclical. For a deeper analysis of how gross margin structure differs across business models, see [Gross Profit Margin: What It Reveals About Business Model Quality](/blog/gross-profit-margin-business-model-analysis).

### What Is the ROIC Threshold for Quality Compounders?

[Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) is the central metric in the quality compounder framework. GeminIQ's screen requires **ROIC TTM ≥ 20%** and sorts results by ROIC descending, placing the highest capital-efficiency businesses at the top of the list.

The S&P 500 median ROIC across a full business cycle is approximately **10–12%**. Most US businesses carry a cost of capital in the **8–10%** range. At **20% ROIC**, the spread above cost of capital is large and clearly positive — the business earns roughly twice what it costs to fund. At **30% ROIC** and above, the returns could only be sustained by a durable competitive advantage: a structural reason why competitors cannot enter and replicate the economics at scale. The **20%** threshold is the entry floor, not the ideal target. The quality compounder's ROIC typically runs well above it; the filter eliminates the large population of businesses that never achieve it. But standard financial media doesn't read the footnotes — and the footnote that matters most here is the ROIC trend. The screener captures the current figure; what actually distinguishes a genuine compounder from a business in competitive decline is whether that figure is stable or falling.

### What Is Revenue Growth in the Context of Quality Compounders?

GeminIQ's [Revenue Growth](/metrics/growth-metrics/revenue-growth) filter requires **Net Revenue TTM Growth 3Y ≥ 10%** — a three-year trailing average, not a one-year figure. The three-year window is deliberate. A single year of elevated revenue growth can reflect a product cycle, an acquisition, or a commodity price spike. Three consecutive years of double-digit growth reflect a business consistently expanding the capital base at which it compounds.

Revenue growth is the reinvestment capacity test applied at scale. A business earning **25% ROIC** with flat revenue has exhausted or chosen not to pursue reinvestment opportunities at that rate — it is returning capital rather than deploying it. Revenue growth at or above **10%** indicates that the business is actively finding high-return deployment outlets within its own operations, expanding the surface area on which it earns exceptional returns. For investors building long-duration positions, that distinction is not marginal. It is the mechanism. GeminIQ also offers an advanced filter — **Net Revenue TTM Growth 5Y ≥ 8%** — which confirms that growth has persisted across a longer horizon, separating sustained compounders from cyclical businesses that ran hot for three years and have since begun to decelerate.

### What Is the Debt-to-Equity Threshold for Quality Compounders?

GeminIQ's screen sets [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) at **≤ 0.5**. This filter is among the most diagnostic in the screen because of what it reveals about the origin of the business's returns.

A genuine quality compounder does not need leverage to earn high returns on capital. The unit economics are strong enough at the product level and the operating level that debt adds no structural benefit to the return profile. When a business shows **20%+ ROIC** alongside significant debt, it raises a specific question: are those returns business-quality-dependent, or capital-structure-dependent? Leverage amplifies headline ROIC but amplifies downside risk proportionally. Mauboussin's competitive advantage period framework makes this distinction concrete: a business with a long CAP earns high returns through structural advantages that persist through cycles. A business requiring leverage to achieve the same headline return is doing something fundamentally different. Beyond the diagnostic function, low debt confers strategic optionality. Quality compounders with minimal leverage can accelerate reinvestment when competitors are cutting back, acquire assets at distressed prices when credit conditions tighten, and sustain high capital deployment rates through cycles that force their leveraged counterparts to pull back. That asymmetry compounds over time.

### What Is the Net Profit Margin Threshold for Quality Compounders?

[Net Profit Margin](/metrics/margin-metrics/net-profit-margin) at **≥ 10%** is the full-stack quality test. High gross margins can be eroded at the operating level. A business with **60%** gross margins can convert poorly to net income if it runs heavy research and development spending, a large sales force, or a complex administrative structure that absorbs the gross profit before it reaches the bottom line.

A **10%** net margin requirement confirms that pricing power and efficiency at the gross level translate through the entire income statement to actual earnings. It also establishes a floor on the quality of those earnings — businesses earning **10%** net margins or above have demonstrated that their operating cost structure is sustainable relative to revenue. The combination of **40%** gross margins and **10%** net profit margins means the business surrenders no more than **30 percentage points** of revenue between gross profit and net income — to operating expenses, interest, and taxes combined. That remaining room is the foundation for the reinvestment capacity the framework depends on, and it is the financial expression of what "durable competitive advantage" actually looks like in a filed income statement.

---

## Why Quality Compounders Almost Never Trade Cheap

The market recognizes exceptional businesses. This is the market working correctly, not failing. A business earning **30% ROIC** consistently, growing revenue at **15%** annually, with minimal debt and strong net margins, is worth far more than any multiple of current earnings can capture — because the terminal value of the compounding engine, extended over a decade or two, is enormous. The market prices this in. Quality compounders therefore trade at **30×**, **40×**, or **50×** earnings. Sometimes higher.

This creates a specific trap for value-oriented investors applying quality compounder criteria. The search for a quality compounder at a deep discount — a **12×** P/E or a significant discount to a DCF-derived intrinsic value estimate — will almost always fail in one of two ways. Either the business is not as good as the screen suggests — the data is normalized, the ROIC is overstated, the revenue growth is acquired rather than organic — or the market has temporarily mispriced it for a reason that requires careful investigation, and that reason is usually alarming. The experienced practitioners who formalized this framework converged on the same conclusion through different routes: the right response to identifying a genuine quality compounder is to pay a fair price and hold for a long time, not to wait for a cheap entry that rarely materializes. At a ten-year or twenty-year holding period, the difference between buying at **30×** and **40×** earnings is far smaller than the difference between buying and not buying. The compounding does the work. Entry price matters, but holding period and the durability of the compounding engine matter more.

---

## What Standard Screeners Get Wrong

Quality compounder screens are among the most aggregator-sensitive in fundamental analysis because all five core criteria — gross margin, ROIC, revenue growth, leverage, and net profit margin — involve normalization choices that differ significantly across platforms. Three problems arise with particular frequency.

The first is gross margin reclassification. The boundary between cost of goods sold and operating expenses is a management reporting decision, not a GAAP-mandated definition. Software businesses, in particular, classify cloud hosting costs, customer support expenses, and professional services delivery differently across companies and across time. A platform applying a normalized cost template reclassifies some of these items into COGS, producing a different gross margin figure than the company itself reported. GeminIQ preserves the company's own cost classification, and its pre-calculated [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) reflects the as-filed figure rather than an external approximation. A standard screener running on normalized data may show a materially different result for the same company in the same period — sometimes higher than filed, sometimes lower — depending on how the aggregator reclassified hosting and support costs. But by pulling the raw income statement directly via GeminIQ, you can see exactly which cost classifications management applies and whether the gross margin in your screener result actually reflects the business being analyzed. For a detailed look at how normalization works across platforms, see [Financial Data Normalization Explained](/blog/financial-data-normalization-explained).

The second problem is stock-based compensation and its effect on [quality of earnings](/blog/earnings-quality-accruals-analysis). High-ROIC technology businesses frequently pay a significant fraction of economic value to employees in equity rather than cash. SBC is a non-cash expense but represents real economic dilution: new shares issued reduce per-share ownership for existing shareholders in a way that does not appear in the operating income line. Two businesses can show identical gross margins, identical ROIC, and identical net profit margins on an as-reported basis while one pays its employees **15%** of revenue in equity and the other pays **2%**. GeminIQ's pre-calculated [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric surfaces this figure directly from the filing's cash flow statement. Running it as an overlay on quality compounder screener output changes which companies deserve serious follow-up and which are generating headline profitability partly by shifting compensation off the income statement.

The third problem is acquired revenue growth versus organic revenue growth. Revenue growing at **15%** annually through acquisitions and revenue growing at **15%** organically look identical in any aggregator-generated summary figure. The underlying economics are not the same. An acquisition-driven grower has deployed additional capital — which should hit the [invested capital](/metrics/calculated-values/invested-capital) denominator and reduce ROIC — while the acquired revenue comes with integration risk, goodwill exposure, and uncertain durability. GeminIQ's as-filed financial statements preserve the company's own segment disclosures and acquisition footnotes. The distinction that determines whether a **15%** revenue growth figure represents a genuine reinvestment compounder or a serial acquirer cannot be surfaced by the screener filter alone. It requires looking at the actual filing — which is precisely what GeminIQ makes accessible.

---

## How to Run the Quality Compounder Screen in GeminIQ

The GeminIQ [Quality Compounder Screener](/screens/stock-screeners/quality-compounder) applies all five filters against as-filed SEC EDGAR data with no third-party normalization. Open the GeminIQ [Stock Screeners](/features#screener) and add the following filters:

| Filter | Operator | Value |
|---|---|---|
| [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) TTM | ≥ | 40 |
| [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) TTM | ≥ | 20 |
| [Net Revenue TTM Growth 3Y](/metrics/growth-metrics/revenue-growth) | ≥ | 10 |
| [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) | ≤ | 0.5 |
| [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) TTM | ≥ | 10 |

Set **Sort By** to [Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) TTM, direction **Descending** — highest capital efficiency first.

For the highest-conviction subset, add a second revenue filter:

| Filter | Operator | Value |
|---|---|---|
| [Net Revenue TTM Growth 5Y](/metrics/growth-metrics/revenue-growth) | ≥ | 8 |

The five-year filter separates businesses with sustained long-term growth from those that passed the three-year threshold during a cyclically favorable period. The result count shrinks, but the remaining companies have demonstrated compounding capacity across a longer horizon — which is the whole point of the framework.

The screener will return a small number of companies. That is by design. Genuine quality compounders are rare. Technology platforms, consumer brands with durable pricing power, specialty healthcare businesses, and industrial niche leaders account for most results because the combination of high gross margins, high ROIC, consistent growth, and minimal debt describes a narrow slice of the public markets. Capital-intensive industrials, commodity producers, banks, and insurance companies are structurally unlikely to appear because their economics make the five-filter combination difficult to pass simultaneously. The small result count is a feature — it reflects the genuine scarcity of the category, not a limitation of the screen.

---

## Reading Your Results: What to Verify Beyond the Filters

The screener returns a filtered starting universe. The real work begins after the filters run.

The first verification is ROIC stability. Pull GeminIQ's [Calculated Metrics](/features#calculated-metrics) trend view for each result and check ROIC across twelve or more quarters. A business showing **25% ROIC** today that showed **20%** five years ago is gaining competitive advantage — the moat is widening and the compounding engine is accelerating. A business showing **25% ROIC** today that showed **42%** five years ago has passed the filter but is in structural competitive decline. The screener captures the current figure. The trend reveals whether it is stable, improving, or mean-reverting. For this particular framework, the trend is the more important signal.

The second verification is stock-based compensation intensity. Pull GeminIQ's [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) for each result, particularly for any technology company in the output. A business with **25% ROIC** and **12% SBC to revenue** has a materially different economic picture than one with **25% ROIC** and **1.5% SBC to revenue**, even though their income statements look nearly identical. The equity dilution that does not appear in operating income shows up in the share count — and the share count trend across eight quarters in GeminIQ's [Financial Statements](/features#financial-statements) view confirms whether dilution is accelerating, stable, or declining.

The third verification is revenue composition. Look at the company's segment disclosures and the investing activities section of the cash flow statement. When cash paid for acquisitions appears alongside double-digit revenue growth, the story is fundamentally different from the same growth rate generated entirely from existing products and geographies. The screener cannot separate these cases. The as-filed financial statements can. GeminIQ's [Financial Statements](/features#financial-statements) view surfaces both in the same interface, across multiple consecutive periods.

The fourth verification is reinvestment trajectory. Examine capital expenditure trends, research and development spending relative to revenue, and retained earnings growth across eight or more filing periods. A genuine quality compounder increases its reinvestment over time as the opportunity set expands. A business that passes the five filters but shows flat or declining reinvestment relative to revenue is signaling something important about the durability of its growth runway. The compounding story holds only for as long as the reinvestment opportunity remains. Identifying when that opportunity begins to exhaust is the qualitative judgment no screener can make. GeminIQ's multi-period filing view — twelve or more consecutive quarters of reinvestment data in a single interface — is where that investigation starts.

---

## Frequently Asked Questions

### What is a quality compounder?

A quality compounder is a business that earns returns on invested capital substantially above its cost of capital — typically **20%** or higher — can reinvest meaningful fractions of those earnings at similar rates, and sustains both for extended periods. The defining characteristic is not a single high-ROIC year but a pattern of stable or improving returns on an expanding capital base, combined with consistent revenue growth that demonstrates ongoing reinvestment capacity. The math is powerful: a business sustaining **25% ROIC** with high reinvestment rates roughly doubles intrinsic value every three years.

### What ROIC qualifies as a quality compounder?

The GeminIQ quality compounder screen requires **Return on Invested Capital (ROIC) TTM ≥ 20%**. A ROIC consistently above **25%** typically indicates a durable competitive advantage. The S&P 500 median across a full business cycle is approximately **10–12%**, so **20%** already represents a substantial premium to the average public company. More important than the absolute level is the trend: a **22% ROIC** that was **18%** five years ago is a more compelling signal than a **28% ROIC** that was **40%** five years ago.

### How is a quality compounder different from a GARP stock?

[GARP investing](/blog/garp-investing-peter-lynch-explained) — Growth at a Reasonable Price — uses the PEG ratio to find companies with strong earnings growth trading at moderate P/E multiples. It is a valuation-first framework that uses growth as the quality input. Quality compounders are identified by capital efficiency and return durability first, with valuation as a secondary consideration — and in practice, quality compounders rarely offer PEG ratios anywhere near Lynch's preferred range because their P/E multiples are structurally elevated. A genuine quality compounder would typically fail a GARP screen for being too expensive. A typical GARP candidate would often fail a quality compounder screen for insufficient ROIC. The strategies target different opportunity types.

### Why do quality compounders often have low dividend yields?

Genuine quality compounders tend to retain most earnings because the reinvestment opportunity — deploying capital back into the business at **20%+** ROIC — creates more value per dollar than distributing it as cash. A business earning **25% ROIC** on retained earnings compounds shareholder wealth at a rate that most investors cannot replicate through alternative investments at equivalent risk. A large dividend yield frequently signals that a business has exhausted its high-return reinvestment opportunities, which, for a quality compounder, is a warning sign about the durability of the compounding engine rather than an attractive income feature.

### Does GeminIQ's quality compounder screener use adjusted or as-filed data?

GeminIQ builds its [Stock Screeners](/features#screener) database from raw SEC EDGAR XBRL filings with no third-party normalization. Gross margins, ROIC inputs, revenue figures, and net profit margins all reflect the company's own as-filed cost classifications and reporting structure — not an aggregator's normalized interpretation. This matters specifically for quality compounder screening because gross margin reclassification, stock-based compensation treatment, and revenue composition are all common divergence points between as-filed and normalized data, and all three affect which companies appear in screener results.

---

## Related Reading

- [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained) — the single most important metric in the quality compounder framework, with a full explanation of the NOPAT formula, invested capital calculation, and why third-party figures frequently diverge from as-filed SEC data.
- [Gross Profit Margin: What It Reveals About Business Model Quality](/blog/gross-profit-margin-business-model-analysis) — how gross margin structure differs across industries and what a consistent **40%+** margin signals about competitive positioning and pricing power durability.
- [Buffett Stock Criteria: Buying a Quality Business at a Fair Price](/blog/buffett-stock-criteria-quality-business) — Buffett's qualitative framework for evaluating business quality overlaps significantly with quality compounder criteria, particularly on durable competitive advantage and earnings power consistency.
- [GARP Investing: Peter Lynch's PEG Ratio Strategy Explained](/blog/garp-investing-peter-lynch-explained) — the growth-at-a-reasonable-price framework is conceptually adjacent to quality compounder investing but uses different filters and selects for different types of businesses and entry conditions.
- [Magic Formula Investing Explained](/blog/magic-formula-investing-explained) — Greenblatt's strategy combines earnings yield and ROIC in a composite ranking. The ROIC component overlaps with quality compounder criteria; the requirement for cheap valuation does not, making it a complementary rather than identical approach.
- [Free Cash Flow Yield Explained](/blog/free-cash-flow-yield-explained) — FCF yield is a useful overlay metric for quality compounder results, confirming that high ROIC and strong margins are translating into actual cash generation rather than accrual-based earnings.
- [Financial Data Normalization Explained](/blog/financial-data-normalization-explained) — how third-party platforms adjust financial data before it reaches screeners, and why gross margin and ROIC figures frequently differ from as-filed SEC reporting for the types of businesses quality compounder screens target.
- [90+ Financial Metrics Value Investors Use](/blog/financial-metrics-value-investors) — the anchor reference post covering ROIC, gross margin, revenue growth, and net profit margin with definitions and context.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Quartr Alternative: Filings, Not Just Transcripts
source: https://www.geminiq.com/blog/quartr-alternative-sec-filing-data

### Quartr Alternative: Filings, Not Just Transcripts
A Quartr alternative for the numbers behind the call. Quartr delivers live earnings calls, transcripts, and IR material across 15,000+ companies; this post explains why first-party material and as-filed statements are not the same record.

Quartr does one job and does it better than anyone. Live earnings calls with real-time transcripts across more than 15,000 public companies in 65 markets, slide decks, press releases, and IR material assembled into a searchable library running past 50 million first-party documents, with a free mobile app that removed the last excuse for not listening to a call. Its AI layer works only across that first-party corpus, with outputs traceable to the source, which is a deliberately narrow design and a defensible one.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quartr-alternative-sec-filing-data)**

Quartr is also candid about not being a screener, a portfolio tracker, or a valuation platform. It is an access layer for what companies say about themselves.

That phrasing is the entire point of this post, and it is not a criticism. "First-party" and "as-filed" both describe material that came from the company, and investors routinely treat them as the same tier of evidence. They are not.

## Table of Contents

- [First-Party Is Not the Same as Filed](#first-party-is-not-the-same-as-filed)
- [The Slide Deck and the Statement Disagree by Design](#the-slide-deck-and-the-statement-disagree-by-design)
- [What the Call Cannot Settle](#what-the-call-cannot-settle)
- [Where Transcripts Are Irreplaceable](#where-transcripts-are-irreplaceable)
- [The Record Underneath the Narrative](#the-record-underneath-the-narrative)
- [Running Both in Sequence](#running-both-in-sequence)
- [Frequently Asked Questions](#frequently-asked-questions)

## First-Party Is Not the Same as Filed

Both descriptions are accurate and they mark different levels of accountability.

An earnings presentation is prepared by management, formatted by investor relations, and published on the company's own site. A press release is written to be quoted. A call is scripted for the opening remarks and improvised in the Q&A. All of it is first-party — it comes from the company, unmediated by any aggregator, which is exactly what makes Quartr's corpus valuable.

A 10-K is a different instrument. It is a statutory filing submitted to the SEC on a prescribed schedule, containing financial statements prepared under GAAP and audited by an independent registered public accounting firm, with officer certifications attached and legal liability behind the signatures. Its figures are tagged in XBRL so machines can read them, and it is the document a company is held to.

The gap shows up in what each one is free to do. A deck can choose which metric to lead with. A filing has to present the statements in full.

## The Slide Deck and the Statement Disagree by Design

This is where the practical risk lives, and it is not a matter of anyone being dishonest.

Companies present adjusted figures in earnings materials because they believe those figures better describe the operating business — stripping out restructuring, acquisition costs, stock-based compensation, impairments, or other items management considers non-recurring. That is a legitimate argument, disclosed and reconciled. It is also a number the company defined, and the definition can change.

The GAAP figure in the filed statement cannot be redefined. Whatever the deck leads with, the statement reports the full picture.

An investor working from transcripts and slides is working from management's framing of results. That framing is informative — how a company chooses to present itself tells you something — but it answers a different question than the statement does. And the transcript makes the two hard to separate, because a number spoken on a call carries no label indicating whether it is GAAP or adjusted, and nothing in the audio distinguishes them.

Guidance compounds the issue. Forward numbers discussed on a call are forecasts. They are not filed, not audited, and not binding, and by the time the period they describe closes, the only durable record of what happened is a financial statement.

## What the Call Cannot Settle

There is a category of question that transcripts structurally cannot answer, and it maps closely to where analysis actually gets decided.

Anything requiring a time series is out of reach — how a margin behaved across twelve quarters, whether working capital has been quietly absorbing cash, how share count moved against buyback spending. Calls describe the quarter just ended; they do not carry a decade of comparable figures.

Anything requiring cross-company comparison is out of reach for the same reason. Fifteen thousand companies talking about themselves does not produce a comparable dataset, because each one is describing itself in its own terms.

And anything living in the footnotes stays there. Lease composition, debt maturity schedules, segment reconciliations, tax positions, contingencies, the detail behind an aggregated caption — management does not read footnotes on a call, and no amount of search across transcripts surfaces a disclosure that was never spoken aloud. [What investors miss in SEC filings](/blog/what-investors-miss-in-sec-filings) covers where that material sits.

## Where Transcripts Are Irreplaceable

The case for Quartr's corpus is strong and dismissing it would be a mistake.

Filings do not explain strategy. They do not tell you why a company is entering a market, how management thinks about a competitive threat, what a capital allocation priority is for the next three years, or which part of the business the CEO is most defensive about. Tone in the Q&A frequently carries more information than the prepared remarks, and an analyst pressing a question that management declines to answer directly has produced a data point that appears in no document.

Tracking language over time is its own discipline. A phrase that appears in four consecutive calls and vanishes in the fifth is a signal. A KPI that management stops mentioning after emphasizing it for two years is a signal. That kind of change is only visible if you have the whole transcript history, which is exactly what Quartr assembled.

Those are questions about intent and narrative. They are worth asking, and they resolve against a different record.

## The Record Underneath the Narrative

GeminIQ covers the other half. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value, so a figure quoted on a call can be checked against what the company filed for the same period.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, which is where a GAAP figure and an adjusted figure stop being confusable. [Visualizations](/features#visualizations) chart the reported structure over time, turning a claim about a trend into something you can look at. [Custom Tables](/features#custom-tables) assemble the specific reported items a thesis depends on. [Calculated Metrics](/features#calculated-metrics) including [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Net Debt](/metrics/calculated-values/net-debt), and [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) are computed from as-filed inputs rather than from a presentation's definition. For orientation on what each form contains, [how to read a 10-K](/blog/how-to-read-10-k) and [how to read a 10-Q](/blog/how-to-read-10-q) cover the structure.

There is no audio, no transcript search, and no live coverage. The scope is the filed record.

## Running Both in Sequence

These products do not compete, and the sequence between them is where the discipline is.

Listen to the call for the questions. Management's framing tells you what they want emphasized, the Q&A tells you what analysts are worried about, and the language drift across quarters tells you what changed. Every one of those produces a specific, checkable claim — a margin that is supposed to be expanding, a segment that is supposed to be inflecting, a leverage position that is supposed to be improving.

Where extracted KPIs from those same presentations feed a model, the [Daloopa alternatives](/blog/daloopa-alternative-sec-data) post covers what that dataset mixes together.

Then open the filing, because a claim made on a call is an assertion and a figure in a 10-K is a filed one. The call tells you the story management is telling. The statements tell you whether the numbers behind it hold — and only one of those two records was signed.

## Frequently Asked Questions

### What are the best Quartr alternatives?

It depends on the need. For live earnings calls, transcripts, slides, and IR material, the substitutes are other transcript and event-coverage platforms. For the financial statements those calls discuss, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability, which is a complement rather than a replacement.

### Are earnings call transcripts the same as SEC filings?

No. A transcript records what management said on a call, which is first-party but unaudited, frequently built around adjusted figures, and often forward-looking. A 10-K or 10-Q is a statutory filing containing GAAP financial statements audited by an independent firm, with officer certifications and legal liability attached.

### Why do figures on an earnings call differ from the 10-K?

Usually because the call is discussing adjusted or non-GAAP measures, which exclude items management considers non-recurring, while the filing reports the full GAAP figures. Both are disclosed and reconciled, but the adjusted figure is defined by the company and can be redefined, while the GAAP line item cannot.

### Can I find footnote detail in an earnings call?

Rarely. Lease composition, debt maturity schedules, segment reconciliations, tax positions, and the detail behind aggregated captions live in the filing's notes and are not read aloud. Searching transcript archives cannot surface a disclosure that was never spoken.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quartr-alternative-sec-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Quartr coverage figures, event types, live transcript capability, document library scale, product tiers, and stated product scope reviewed August 2, 2026 from Quartr's own site, product pages, and app listing, plus third-party tool listings.

---

## Blog: The QuickFS Alternative That Actually Pulls From the Filings
source: https://www.geminiq.com/blog/quickfs-alternative-sec-data

### The QuickFS Alternative That Actually Pulls From the Filings
QuickFS shut down in February 2026 after disclosing that its data was GuruFocus data, not figures parsed from filings. GeminIQ parses every US 10-K and 10-Q itself, keeps line items as filed, links each period to its source filing, and exports to Excel.

QuickFS told users its data came straight from company filings. GeminIQ's does. We parse every US 10-K and 10-Q ourselves, keep every line item as filed, link each period to its source filing, and export the whole history to Excel in one click.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quickfs-alternative-sec-data)** or [see Apple's full history free](/stocks/AAPL).

Direct from SEC EDGAR, no data vendors · 17+ years of history · Every period linked to its filing · $29/mo billed annually

## Table of Contents

- [What Happened to QuickFS](#what-happened-to-quickfs)
- [Why "From the Filings" Matters: One Apple Number](#why-from-the-filings-matters-one-apple-number)
- [Coming From QuickFS? Here Is What Maps to What](#coming-from-quickfs-here-is-what-maps-to-what)
- [Do Not Trust Us. Check Any Number in Three Clicks.](#do-not-trust-us-check-any-number-in-three-clicks)
- [How the Main QuickFS Alternatives Compare](#how-the-main-quickfs-alternatives-compare)
- [What GeminIQ Does Not Do (Yet)](#what-geminiq-does-not-do-yet)
- [One Plan, Priced for Individual Investors](#one-plan-priced-for-individual-investors)
- [Built by Two Founders Who Wanted the Real Numbers](#built-by-two-founders-who-wanted-the-real-numbers)
- [Frequently Asked Questions](#frequently-asked-questions)

## What Happened to QuickFS

On February 3, 2026, QuickFS announced it was shutting down. A day later, its founder disclosed that the data customers believed came directly from company filings had in fact been GuruFocus data, redistributed without permission. The original notices are no longer online; [QuickFS's site](https://quickfs.net/) now shows a farewell note from its founder, and [Shibui Finance](https://shibui.finance/quickfs-alternatives) summarizes both notices.

If you relied on QuickFS, you lost two things at once: your favorite tool and your confidence in where the numbers came from. Many users built years of spreadsheets on it.

We are not here to pile on. We built GeminIQ because we had the same problem from the other side: the numbers on the big data sites did not match the 10-K, and we wanted to know why.

## Why "From the Filings" Matters: One Apple Number

In its fiscal 2025 10-K, Apple reports two separate figures in its cash flow statement:

| Line item as filed (Apple FY2025 10-K) | Amount |
| --- | --- |
| [Repurchases of common stock](https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm) | $90,711M |
| [Payments for taxes related to net share settlement of equity awards](https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm) | $5,960M |
| What a standardized data feed shows as "Repurchase of Common Stock" | $96,671M |

That **$5,960M** is not a buyback. It is cash Apple paid to tax authorities on behalf of employees when their stock awards vested. A standardized template that has one buyback row combines the two into a single "repurchases" line, so a shareholder-yield calculation built on that number overstates real buybacks by about **6.6%**.

At [Broadcom](/stocks/AVGO) the gap is bigger. In fiscal 2025, shares repurchased for tax withholdings on vesting of equity awards came to **$3,860M**, more than the **$2,450M** the company spent on repurchases under its buyback program.

GeminIQ keeps every row the way the company filed it, labeled with the [XBRL](/blog/what-is-xbrl) element the company tagged it with. Apple's two figures stay on two rows, Payments For Repurchase Of Common Stock and Payments Related To Tax Withholding For Share Based Compensation, across all 17 fiscal years from 2009 to 2025. The [hidden problems with third-party financial data](/blog/third-party-financial-data-problems) post covers more ways a standardized template regroups what a company reported.

**[See Apple's cash flow as filed →](/stocks/AAPL)**

## Coming From QuickFS? Here Is What Maps to What

| What you used in QuickFS | In GeminIQ |
| --- | --- |
| About 20 years of financial statements | 17+ years on paid plans (from 2009 for large filers, 2011 for smaller ones), annual and quarterly |
| Excel add-in that pulled data live with `=QFS()` formulas, plus an API | One-click .xlsx export on paid plans: statements, 90+ metrics, insider trades, institutional ownership, earnings reaction; real numeric values; per-dataset date ranges |
| Standardized line items (GuruFocus data, per its founder's notice) | Line items exactly as filed, keyed by XBRL tag so each row stays consistent over time |
| Ratios and metrics | 90+ calculated metrics: ROIC, FCF yield, Altman Z, EV/EBITDA, cash conversion cycle, 3- and 5-year growth |
| US, Canadian, Australian and European stocks | US SEC filers only |
| Also in GeminIQ | Every period linked to its source filing; screener with 100+ metrics, up to 10 stacked filters and 18 prebuilt value strategies; watchlists with thesis, price targets and alerts for new 10-K/10-Q filings; insider Form 4 tracker; 13F ownership trend; post-filing price reaction heat map; peer comps with implied valuation range |

> **Rebuilding your QuickFS spreadsheets?** Export a company from GeminIQ and open the statements sheet next to your old file. Each row is one reported value with its XBRL tag, period end, and form, so a SUMIFS or a pivot on tag and period rebuilds any line your old formulas pointed at, and the same tag lines up year after year.

## Do Not Trust Us. Check Any Number in Three Clicks.

1. Open any company page, for example [/stocks/AAPL](/stocks/AAPL), and pick a statement: Balance Sheet, Cash Flow, or Income Statement.
2. In the Recent filings list beside the statement, click the 10-K or 10-Q for the period you want.
3. The source filing opens on SEC EDGAR. Find the line, compare the number.

If a number does not match, email [feedback@geminiq.com](mailto:feedback@geminiq.com). We correct filer errors where we can.

## How the Main QuickFS Alternatives Compare

Prices and features as published on each company's site, checked October 10, 2026. Tell us if anything here is out of date and we'll fix it.

|  | GeminIQ | GuruFocus | TIKR | ROIC.ai | StockAnalysis |
| --- | --- | --- | --- | --- | --- |
| Price | $348/yr or $39/mo | US Premium $549/yr | Plus about $215/yr ($24.95/mo monthly) | $29 or $89/mo | Pro $79/yr |
| Paid history | 17+ yrs | Up to 30 yrs | 10 yrs (Plus, Pro); 30 yrs (Ultimate) | 5 yrs (Individual); all available (Professional) | 10 to 40 yrs |
| Data approach | Parsed in-house from SEC XBRL, as filed | Licensed fundamentals (Morningstar) | S&P Capital IQ, standardized | Normalized template | Standardized default; As Reported view available |
| Excel export | Yes, one click | Excel and Google Sheets add-ins | Yes | Yes, paid tiers | Yes (Pro: 1 download/day) |
| Coverage | US only | Global | Global | Global (paid tiers) | Global (130,000+ stocks and funds) |

Where a competitor is stronger, it says so above: every one of them covers more of the world than we do, and most go further back. For feature-by-feature detail, see [GeminIQ vs. GuruFocus](/competitor-comparison/gurufocus), [GeminIQ vs. TIKR](/competitor-comparison/tikr), and [GeminIQ vs. ROIC.ai](/competitor-comparison/roic-ai). If what you miss most is pulling numbers live into a spreadsheet with a formula, the [Wisesheets alternative](/blog/wisesheets-alternative-sec-data) post covers that category honestly.

## What GeminIQ Does Not Do (Yet)

- **US companies only.** If you need international coverage, GeminIQ is not your tool.
- **No live spreadsheet add-in or API.** You export to Excel; you don't pull live with a formula.
- **Banks, insurers and REITs** are covered, but their XBRL filings are messier, so expect more gaps.
- **History starts with XBRL**, in 2009 for the largest filers and 2011 for smaller ones.

## One Plan, Priced for Individual Investors

- **$29/mo billed annually ($348/yr)** or **$39/mo** monthly
- 7-day trial
- Free tier with no account: 3 years of history on every company page, plus a free screener with 18 prebuilt strategies

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quickfs-alternative-sec-data)**

## Built by Two Founders Who Wanted the Real Numbers

We are [Chad Hartman](/about/chad-hartman) and [Brett Hartman](/about/brett-hartman). Brett is a software engineer; Chad's background is quantitative analysis and data. We started GeminIQ after the numbers on the big data sites kept disagreeing with the 10-Ks we were reading. So we wrote our own parser for SEC XBRL, with no data vendors in between. We still answer every support email ourselves.

## Frequently Asked Questions

### Can I import my old QuickFS spreadsheets?

Not automatically. Export the company from GeminIQ to .xlsx, place it beside your old file, and repoint your formulas. Rows are labeled by XBRL tag, so they stay consistent year to year.

### Where does GeminIQ's data come from?

Directly from SEC EDGAR XBRL filings, parsed by our own software. We do not license data from any vendor.

### How far back does the data go?

To 2009 for the largest filers and 2011 for smaller ones, which is when XBRL filing began. That is 17+ years on paid plans; the free tier shows 3 years.

### How fast do new filings show up?

Filings are processed overnight, so a 10-K filed today is usually on the site tomorrow.

### Do you cover international stocks?

No. GeminIQ covers US SEC filers only.

### Why do your numbers sometimes differ from other sites?

Most sites show standardized data, which regroups line items into a fixed template. We show what the company filed. Open the filing from the Recent filings list on any company page to check the source.

### What happens if a company files an error?

We correct filer errors where we can identify them.

### Is there a free trial?

Yes, 7 days. There is also a free tier with no account needed.

---

## Rebuild Your Research on Numbers You Can Check

Every US company, 17+ years, exactly as filed, one click to Excel.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=quickfs-alternative-sec-data)**

Or [browse any company free](/stocks), no account needed.

## Data Used / Sources

- Apple Inc. Form 10-K for the fiscal year ended September 27, 2025 (filed October 31, 2025, accession 0000320193-25-000079), consolidated statement of cash flows: Repurchases of common stock $90,711M; Payments for taxes related to net share settlement of equity awards $5,960M.
- Broadcom Inc. Form 10-K for the fiscal year ended November 2, 2025 (filed December 18, 2025, accession 0001730168-25-000121), consolidated statement of cash flows: Repurchases of common stock - repurchase program $2,450M; Shares repurchased for tax withholdings on vesting of equity awards $3,860M.
- Both sets of figures cross-checked against the SEC's XBRL company facts (PaymentsForRepurchaseOfCommonStock, PaymentsRelatedToTaxWithholdingForShareBasedCompensation).
- QuickFS shutdown and data-source notices (February 2026): summarized by [Shibui Finance](https://shibui.finance/quickfs-alternatives); QuickFS's current farewell note is at [quickfs.net](https://quickfs.net/).
- Competitor prices and features taken from each company's public website.
- Standardized "Repurchase of Common Stock" of -$96,671M for Apple FY2025 as shown on StockAnalysis's default (standardized) cash flow view, checked October 10, 2026.

<sup>QuickFS, GuruFocus, TIKR, ROIC.ai and StockAnalysis are trademarks of their respective owners. GeminIQ is not affiliated with them. Comparison information was taken from each company's public website.</sup>

---

## Blog: Receivables Growing Faster Than Revenue: Weaker Returns Followed
source: https://www.geminiq.com/blog/receivables-growing-faster-than-revenue

### Receivables Growing Faster Than Revenue: Weaker Returns Followed
Receivables growing faster than revenue is a filing-level fact anyone can check quarter over quarter, and in GeminIQ's data the widest gaps between receivables growth and revenue growth were followed by weaker forward returns than the broader filing universe, with the gap widening the further out the window runs.

**[SolarEdge Technologies](/stocks/SEDG)** reported accounts receivable growth of **21.2%** against revenue growth of negative 4.3% in the 10-K covering fiscal 2023 — a 25.5-point gap. That's the difference between how fast money owed to the company was growing and how fast the company was actually selling. The twelve months that followed produced a cumulative return of **-78.12%**. Receivables growing faster than revenue is one of the oldest checks in fundamental analysis, and it is also one of the easiest to verify directly: both figures sit on the filing itself, quarter over quarter, with no estimation required.

This study reads GeminIQ's as-filed universe of quarterly and annual filings, computing the year-over-year growth rate of each filer's trailing-twelve-month receivables figure against GeminIQ's pre-calculated [Revenue Growth](/metrics/growth-metrics/revenue-growth) (1-Year) for each filing, joined to GeminIQ's post-filing market reaction data. **146,882** filing-periods across **5,679** companies have both growth figures computed; **98,668** of those filings also have post-filing return data available, drawn from GeminIQ's partial price-history coverage. The comparison window runs from each filing's own filed date out to twelve months, and every figure below is measured against the broader universe base rate, not against zero. This is a historical association measured over the sample window, not a forecast for any individual company.

## The Pattern

Accounts receivable growing faster than revenue means a company is collecting cash more slowly relative to what it reports selling. That gap can open up because credit terms loosened to pull sales forward, because revenue was recognized before cash actually changed hands, or because a small number of customers are paying later than usual. None of that is visible in a headline revenue growth figure. It is visible immediately in the relationship between two lines that already sit on every 10-K and 10-Q: the receivables balance on the balance sheet and revenue on the income statement.

## The Data

Filings were sorted into deciles by the spread between year-over-year receivables growth and revenue growth. The top decile — filings where receivables outpaced revenue by the widest margin — is compared against the rest of the universe at four post-filing checkpoints.

| Checkpoint | Top-Decile Gap Cohort (median) | Rest of Universe (median) |
|---|---|---|
| 1 month | **0.00%** | 0.61% |
| 3 months | **1.33%** | 1.84% |
| 6 months | **0.61%** | 2.56% |
| 12 months | **1.90%** | 6.02% |

<center><sup>GeminIQ data study: median post-filing return for filings in the top decile of receivables-growth-versus-revenue-growth spread, against the rest of the universe. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 9,723 (1 month) to 1,012 (12 months) in the top-decile cohort.</sup></center>

<center><sup>GeminIQ data study: median post-filing return for the top decile of receivables-growth-versus-revenue-growth spread, against the universe base rate. Built from as-filed 10-K/10-Q data via GeminIQ.</sup></center>

The gap is modest at the one- and three-month checkpoints and widens by twelve months, where the top-decile cohort trails the broader universe by roughly **4 percentage points**. It is a real but not a dramatic effect, and it is sensitive to how the universe is defined. Restricting the comparison to companies with at least **$100 Million** in trailing revenue — filtering out the smallest, most illiquid names — narrows the gap at every checkpoint. At the three-month mark specifically, it even reverses, with the top-decile cohort modestly outperforming the base rate. The twelve-month gap holds up under that stricter filter, narrowing to roughly **2.25 percentage points** rather than disappearing, but the effect is not as clean or as universal as the headline full-universe numbers alone would suggest.

## The Extremes

**[SolarEdge Technologies](/stocks/SEDG)**, cited in the opening, sits in a well-documented moment for the solar-inverter industry: fiscal 2023 receivables growing 21.2% against revenue that actually declined 4.3%. Distributors worked through a channel inventory glut that became a widely covered story across the sector in the following year. **[Microchip Technology](/stocks/MCHP)** shows a similar shape in the semiconductor downturn that followed: receivables grew 20.1% in the 10-K covering the fiscal year ended March 2024 while revenue fell **9.5%**, a 29.6-point gap. The following twelve months produced a **-59.92%** return. Both cases sit inside industries that experienced genuine, publicly reported demand slowdowns in the same window — the receivables-versus-revenue gap was visible in the filing arithmetic before either became a widely covered story, not a standalone prediction of what followed.

<center><sup>GeminIQ Financial Statement view of SolarEdge's quarterly accounts receivable and revenue, December 2021 to December 2023.</sup></center>

<center><sup>GeminIQ Financial Statement view of Microchip Technology's quarterly accounts receivable and revenue, December 2022 to December 2024.</sup></center>

## The Method

Receivables Growth (1Y) compares each filing's trailing-twelve-month receivables figure — a rolling four-quarter sum built from each filer's raw receivables balance-sheet tag — to the trailing-twelve-month figure from four quarters earlier, the same TTM convention GeminIQ uses for its pre-calculated [Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth) metric. Revenue growth is GeminIQ's pre-calculated Revenue Growth (1-Year). Post-filing returns are cumulative from each filing's own filed date and are never compounded or added across checkpoints. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology); this specific check is also one of seven covered in GeminIQ's balance sheet red flags checklist.

## Check Your Holdings

Pull up any position's receivables trend on GeminIQ's [Financial Statements](/features#financial-statements) view, sum the trailing four quarters, and compare that total to the same trailing-four-quarter total from a year earlier, then check that growth rate against the position's Revenue Growth (1-Year) in [Calculated Metrics](/features#calculated-metrics). A wide, growing gap isn't a guaranteed warning sign on its own — the base rate above shows the effect is real but modest, and sensitive to company size. But it's a two-line comparison anyone can run directly against the filing, rather than waiting for the headline.

## Frequently Asked Questions

### What does it mean when receivables grow faster than revenue?

It means the company is collecting cash more slowly relative to what it reports selling. Common causes include loosened credit terms used to pull sales forward, revenue recognized before cash is actually collected, or a concentrated customer paying later than usual. It's visible directly by comparing the trailing-twelve-month receivables figure to reported revenue growth over the same period.

### How many filings does this finding cover?

**146,882** filing-periods across **5,679** companies have both a receivables-growth and revenue-growth figure computed. **98,668** of those also have post-filing return data, with the top-decile cohort ranging from **9,723** filings at the one-month checkpoint down to **1,012** at twelve months, since only annual filings carry the full twelve-month return window.

### Does a wide receivables-revenue gap always mean trouble ahead?

No. The effect narrows and becomes inconsistent once the comparison is restricted to larger, more liquid companies, and it reverses briefly at the three-month checkpoint under that stricter universe. It is a real but modest historical association at the full-universe level, not a reliable standalone signal for any individual company.

### What's the sample size for the strongest gap cohort?

The top-decile cohort — filings where receivables outpaced revenue by the widest margin — ranges from **9,723** filings at the one-month checkpoint to **1,012** filings at the twelve-month checkpoint. Both figures sit comfortably above the roughly 200-filing floor this kind of comparison requires at every checkpoint measured.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=receivables-growing-faster-than-revenue)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe of 5,679 companies drawn from GeminIQ's as-filed 10-K and 10-Q database, publicly available on [SEC EDGAR](https://www.sec.gov/). 146,882 filing-periods were screened for the spread between year-over-year growth in each filer's trailing-twelve-month receivables figure and GeminIQ's pre-calculated Revenue Growth (1-Year); 98,668 filings had matching post-filing return data, drawn from GeminIQ's partial price-history coverage. Accounts Receivable Growth (1Y) is derived from each filer's raw receivables balance-sheet tag, aggregated to a trailing-twelve-month basis, and is not itself a GeminIQ platform metric. The screen requires a prior-year receivables balance above $1 Million and a prior-year revenue balance above $10 Million, and winsorizes the top and bottom 1% of both the growth spread and the return figures to exclude divide-by-near-zero and extreme-outlier artifacts. Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Revenue Growth Slowdown: What 76,908 Filings Show
source: https://www.geminiq.com/blog/revenue-growth-slowdown-stock-returns

### Revenue Growth Slowdown: What 76,908 Filings Show
Revenue growth slowdown is the most-watched warning sign in growth investing, and this study measures what actually followed one across 76,908 as-filed 10-Q filings from 2004 to 2026. Quarters where GeminIQ's Revenue Growth metric fell more than 50 points were followed by a median three-month return of -1.8% against a universe base rate of +2.4%, and the gradient holds across all nine buckets.

**Across 76,908 as-filed 10-K and 10-Q filings from December 2004 through June 2026, quarters where the revenue growth rate fell by more than 50 points were followed by a median three-month return of -1.79% — 4.15 points below the universe base rate of +2.36%. The gradient holds across all nine buckets, but the total spread between the worst bucket and the best is roughly four and a half percentage points, not a cliff.**

[C3.ai](/stocks/AI) spent seven consecutive quarters accelerating. Its Revenue Growth climbed from **5.51%** to **25.27%**, quarter after quarter, right through the FY2025 10-K filed on June 23, 2025. Then the next 10-Q landed on September 9, 2025 and the same figure read **14.34%** — a drop of **10.93 points** in a single filing. Three months later the stock was down **8.20%**. The quarter after that, Revenue Growth fell to **1.84%**, and the three months following that filing took **50.41%** off the share price. By the FY2026 10-K, trailing revenue had fallen from **$389.056 Million** to **$250.268 Million** and Revenue Growth read **-35.67%**.

That is the story every growth investor thinks they already understand: growth slows, stock falls. But one company proves nothing. The question worth answering is what happens on average, across every company that ever posted a slowdown — and whether the size of the slowdown matters, or whether the market has already priced it by the time the filing hits EDGAR.

This study reads every 10-K and 10-Q in GeminIQ's as-filed database from December 2004 through June 2026 — **390,915 company-quarters** across **15,064 companies**, extracted directly from SEC EDGAR XBRL with no aggregator in between. The bucket analysis below runs on the **76,908** quarterly filings that carry both a measurable change in growth rate and a clean three-month post-filing return, joined to how each stock actually traded in the three months after its filing date.

## What Followed a Revenue Growth Slowdown

Filings where the revenue growth rate fell sharply were followed by weaker three-month returns than filings where it held steady or improved. The relationship is monotonic across the middle of the distribution: the further the growth rate dropped, the worse the subsequent median return, with no bucket breaking the sequence between a 50-point collapse and a 5-point improvement.

But the magnitude is smaller than the narrative suggests, and that is the more useful finding. The gap between the worst bucket and the best is roughly **four and a half percentage points** of median three-month return. That is a real tilt in the odds. It is not a verdict on any individual stock, and this is a historical association measured over the 2004–2026 sample window, not a forecast.

## Three-Month Returns by Size of the Slowdown

The gradient runs the full length of the table. Filings whose growth rate collapsed by more than **50 points** posted a median three-month return of **-1.79%** and were positive less than half the time. Filings whose growth rate barely moved posted **+2.79%** and were positive **59.3%** of the time. Every bucket is measured against the universe base rate — the median three-month return across all **76,908** filings, which was **+2.36%**, with a mean of **+3.49%**. Returns are cumulative from each filing's filed date, trimmed at the top and bottom **1%**, and never compounded.

| Change in Revenue Growth | Filings | Median 3-Mo Return | vs. Base Rate | Share Positive |
|---|---|---|---|---|
| Fell more than **50 pts** | **612** | **-1.79%** | **-4.15 pts** | **44.9%** |
| Fell **30–50 pts** | **635** | **-1.12%** | **-3.48 pts** | **46.9%** |
| Fell **20–30 pts** | **1,178** | **+0.49%** | **-1.88 pts** | **50.5%** |
| Fell **10–20 pts** | **4,178** | **+1.50%** | **-0.87 pts** | **53.6%** |
| Fell **5–10 pts** | **7,360** | **+1.48%** | **-0.89 pts** | **53.8%** |
| Fell **0–5 pts** | **26,072** | **+2.79%** | **+0.43 pts** | **59.3%** |
| Rose **0–5 pts** | **25,169** | **+2.83%** | **+0.47 pts** | **59.8%** |
| Rose **5–10 pts** | **6,349** | **+1.92%** | **-0.44 pts** | **55.6%** |
| Rose more than **10 pts** | **5,355** | **+0.96%** | **-1.40 pts** | **52.0%** |

The smallest bucket carries **612** filings, comfortably above the **200**-filing floor this series requires before drawing any conclusion, and the largest carries **26,072**.

<center><sup>GeminIQ data study: median three-month post-filing return by the change in Revenue Growth from the prior quarter, against the universe base rate. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 76,908 filings, December 2004 – June 2026.</sup></center>

Two things in that table deserve more attention than the headline. The first is how little a modest slowdown cost. A company whose growth rate slipped **5 to 10 points** still posted a median **+1.48%** over the next three months and was positive **53.8%** of the time — barely distinguishable from the universe. The panic that attaches to a single soft quarter is not supported by what followed one.

The second is the bottom row. Filings where growth *accelerated* by more than **10 points** returned a median **+0.96%**, worse than every bucket from a 5-point decline upward and **1.40 points** below the base rate. The market rewards improvement right up until improvement becomes extreme, at which point the filing is arriving into a price that already assumed it.

<center><sup>GeminIQ data study: share of filings followed by a positive three-month return, by the change in Revenue Growth from the prior quarter. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 76,908 filings, December 2004 – June 2026.</sup></center>

## C3.ai and Micron: Same Deceleration, Opposite Outcomes

[C3.ai](/stocks/AI) sits near the edge of this distribution, and its filings track the gradient almost exactly. Its Revenue Growth fell **10.93 points**, then **12.50 points**, then **18.06 points**, then **19.45 points** across four consecutive filings — a company sliding down the table one row at a time. Trailing revenue went from **$389.056 Million** to **$250.268 Million** over the same stretch. The market's reaction was not uniform, though. The three months after the September 2025 10-Q cost **8.20%**. The three months after the December filing cost **50.41%**. The three months after the March 2026 filing *gained* **16.31%**. Same direction of travel in the filings, three completely different outcomes.

<center><sup>GeminIQ Calculated Metrics showing C3.ai's Revenue Growth falling from 25.27% to -35.67% across four consecutive filings, with trailing revenue declining from $389.056 Million to $250.268 Million.</sup></center>

Then there is [Micron](/stocks/MU), which ran the same play and got the opposite result. Micron's Revenue Growth peaked at **79.80%** in its November 2024 quarter and then decelerated for four straight filings — **71.05%**, **58.22%**, **48.85%**, **45.43%**. On the table above, every one of those quarters lands in a bucket with a negative expected tilt. What actually followed each of those four filings was **+14.76%**, **+24.90%**, **+41.57%**, and **+49.04%** over the subsequent three months. A memory cycle decelerating from an extraordinary peak is still a business compounding at **45%**, and the market priced the level rather than the derivative.

<center><sup>GeminIQ Calculated Metrics showing Micron's Revenue Growth decelerating from 79.80% to 45.43% across four consecutive filings while the stock rose in each subsequent three-month window.</sup></center>

That contrast is the honest reading of this study. A bucket of **612** filings has a median. Your holding has an outcome.

## How Revenue Growth Deceleration Was Measured

Growth is measured with GeminIQ's pre-calculated [Revenue Growth](/metrics/growth-metrics/revenue-growth) metric — trailing-twelve-month revenue against the same period a year earlier, built from the as-filed Revenues tag in each company's XBRL. Deceleration is the change in that metric from one filing to the next. Nothing here is recalculated from a [normalized third-party feed](/competitor-comparison/sp-capital-iq), which matters more than it sounds: when an aggregator reclassifies revenue items during [normalization](/blog/financial-data-normalization-explained), the base changes and every growth rate built on it changes with it.

The screens are aggressive by design. Fiscal years where a company's quarterly revenue series fails an internal reconciliation are excluded entirely, along with the following year, because a single mis-tagged quarter fabricates a growth cliff a year later and a false deceleration the quarter after that. Two separate checks confirmed the result. Rebuilding the growth rate independently from raw XBRL tags reproduced the same curve. Re-measuring every return against other filings from the same calendar quarter — which strips out market direction entirely — preserved the gradient. That second test earned its keep, because it dissolved a different pattern in the twelve-month annual data that turned out to be recession timing rather than a real effect. The full ruleset is documented in our [filing data study methodology](/blog/filing-data-study-methodology), and the broader question of what filing quality does to subsequent returns is covered in [how stocks react after earnings](/blog/stock-price-reaction-after-earnings).

## How to Check a Slowdown in Your Own Holdings

You can run this on anything you own in about ninety seconds. Open a company in [Calculated Metrics](/features#calculated-metrics) and pull [Revenue Growth](/metrics/growth-metrics/revenue-growth) across its last eight quarters. Write down the change from each quarter to the next — that single column of differences is the entire study. If the most recent change is a drop of **20 points or more**, the filing sits in a bucket whose median three-month return was below the universe base rate of **+2.36%**. If it is a drop of **5 points or less**, history says that quarter was nearly indistinguishable from any other filing.

Then do the part most people skip and check the level, not just the change. Micron's growth rate fell **34 points** across four filings and never once dropped below **45%**. C3.ai's fell **46 points** and went negative. Same direction, entirely different businesses. The change in the growth rate tells you what the market is about to reprice. The level tells you what you actually own. You need the as-filed [Financial Statements](/features#financial-statements) to see both, and the [Price Variance](/features#price-variance) view to see what the market did with them last time.

## Four Current Filings: MercadoLibre, Eaton, Broadcom, Enphase

Three of the four companies below show clean, unflagged readings in their most recent quarter. The fourth carries two of the most extreme Point Changes in this entire dataset, earlier in its filing history — proof the 20-point threshold from the table above is a real, occasionally-triggered signal and not just a hypothetical bucket.

### MercadoLibre (MELI)

[MercadoLibre's](/stocks/MELI) TTM Revenue Growth reads **42.11%** for the quarter ended March 31, 2026 (filed May 8, 2026), up **+3.05 points** from the prior quarter. Growth did decelerate over the prior year, from a peak of **45.71%** in June 2024 down to a trough of **34.52%** in June 2025. But the sharpest single-quarter Point Change across that entire stretch was only **-8.12 points** — well inside the null-to-flagged range. Growth has since climbed back for two consecutive quarters.

<center><sup>GeminIQ Calculated Metrics showing MercadoLibre's Revenue Growth climbing from 34.52% in June 2025 to 42.11% by March 2026, a two-quarter reacceleration off the year's trough.</sup></center>

### Eaton (ETN)

[Eaton's](/stocks/ETN) TTM Revenue Growth reads **15.53%** for the quarter ended June 30, 2026 (filed July 31, 2026), up **+2.84 points** on the quarter — the fifth straight quarterly increase off a trough of **7.00%** in March 2025. No quarter in this stretch of Eaton's history produced a Point Change larger than roughly **2.4 points** in either direction. It's a growth rate that moves gradually, nowhere near the scale needed to trip the 20-point threshold.

<center><sup>GeminIQ Calculated Metrics showing Eaton's Revenue Growth rising for five consecutive quarters, from a trough of 7.00% in March 2025 to 15.53% by June 2026.</sup></center>

### Broadcom (AVGO)

[Broadcom's](/stocks/AVGO) TTM Revenue Growth reads **32.29%** for the quarter ended April 30, 2026 (filed June 9, 2026), up **+7.07 points** on the quarter — but the more instructive reading sits earlier in the series. Growth fell from a peak of **43.99%** in October 2024 to a trough of **23.87%** in October 2025 across four consecutive quarters of decline. No single one of those four quarters produced a Point Change past **-20 points** on its own — the sharpest was **-6.45 points**. Yet the cumulative four-quarter decline totaled just over **20 points**. That is exactly why the level and the full-year trend matter, not one quarter's change: a business that shed roughly half its growth rate over a year without a single quarter's reading ever tripping the flagged threshold by itself.

<center><sup>GeminIQ Calculated Metrics showing Broadcom's Revenue Growth falling from a peak of 43.99% in October 2024 to a trough of 23.87% in October 2025, then climbing back to 32.29% by April 2026.</sup></center>

### Enphase Energy (ENPH)

[Enphase Energy](/stocks/ENPH) is the company this check exists for. Its TTM Revenue Growth reads **-1.64%** for the quarter ended March 31, 2026 (filed April 28, 2026) — modest, and not itself a flagged reading. Three years earlier, though, Enphase produced two of the most extreme Point Changes in this metric's history. Growth fell from **153.02%** in December 2022 to **36.09%** in March 2023, a single-quarter Point Change of **-116.93 points** — nearly six times the flagged threshold on its own. Three quarters later, growth crossed from positive to negative outright, falling from **14.97%** to **-34.49%**, a Point Change of **-49.45 points**. Growth kept falling to a trough of **-60.36%** by September 2024, then spent the next six quarters climbing back to nearly flat.

<center><sup>GeminIQ Calculated Metrics showing Enphase Energy's Revenue Growth collapsing from 153.02% in December 2022 to -60.36% by September 2024, then partially recovering to -1.64% by March 2026.</sup></center>

## Frequently Asked Questions

### How many filings does this study cover?

The bucket analysis covers **76,908** quarterly filings with both a measurable change in Revenue Growth and a clean three-month post-filing return, drawn from a database of **390,915 company-quarters** across **15,064 companies** filed between December 2004 and June 2026.

### Does a revenue growth slowdown predict a stock decline?

No. This study measures historical association across a sample, not prediction. Quarters with a sharp growth-rate decline were followed by weaker median returns than the universe base rate over the 2004–2026 window. That is a statement about what happened in a large sample, not a forecast for any individual company, and the Micron case in this post is one of thousands where the association did not hold.

### Can a company decelerate without any single quarter tripping the threshold?

Yes, and it is the way a real slowdown most easily hides from this check. Broadcom's TTM Revenue Growth fell from a peak of **43.99%** in October 2024 to a trough of **23.87%** in October 2025 across four consecutive quarters of decline. The sharpest single-quarter Point Change in that stretch was only **-6.45 points** — nowhere near the flagged threshold — yet the cumulative four-quarter decline totaled just over **20 points**. A business can shed roughly half its growth rate over a year without one filing ever tripping the threshold by itself, which is why the column of differences is worth reading across a full year rather than one row at a time.

### What is the sample size for the sharpest deceleration bucket?

**612** filings across **383** companies. That clears the **200**-filing minimum this series requires before any conclusion is drawn from a bucket, though it is the smallest group in the study and the least precisely measured.

### Why measure growth on trailing-twelve-month revenue instead of a single quarter?

Quarterly revenue is seasonal — a retailer's fourth quarter dwarfs its first every year. Trailing-twelve-month revenue sums four quarters, which removes the seasonal distortion and makes the growth rate comparable across periods and across companies. It also proved far more robust to filing-level tagging faults during this study's data validation.

### Why does the study use a three-month window rather than twelve?

A 10-Q carries roughly three months of post-filing reaction before the next filing supersedes it; only a 10-K carries a full twelve. Since the quarter-over-quarter change in growth rate is measured on quarterly filings, three months is the window those filings actually support.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=revenue-growth-slowdown-stock-returns)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference MercadoLibre, Inc.'s Q1 FY2026 10-Q (filed May 8, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1099590/000109959026000017/0001099590-26-000017-index.htm).<br>
All financial figures cited in this article reference Eaton Corporation plc's Q2 FY2026 10-Q (filed July 31, 2026, period ending June 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1551182/000155118226000030/0001551182-26-000030-index.htm).<br>
All financial figures cited in this article reference Broadcom Inc.'s Q2 FY2026 10-Q (filed June 9, 2026, period ending April 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1730168/000173016826000054/0001730168-26-000054-index.htm).<br>
All financial figures cited in this article reference Enphase Energy, Inc.'s Q1 FY2026 10-Q (filed April 28, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1463101/000146310126000047/0001463101-26-000047-index.htm).</sup>

<sup>Data Appendix: Universe of 15,064 companies and 390,915 company-quarters filed December 2004 through June 2026, drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Growth is GeminIQ's pre-calculated Revenue Growth metric (trailing-twelve-month revenue versus the same period one year prior, built from the as-filed Revenues tag); deceleration is the change in that metric between consecutive filings. The bucket analysis uses the 76,908 quarterly filings carrying both a computable change and a three-month post-filing return. Fiscal years failing an internal quarterly-revenue reconciliation were excluded along with the following year; filings from financial-sector issuers, non-operating partnerships and trusts, and periods with a detected acquisition are flagged in the underlying extract. Post-filing returns are cumulative from each filing's filed date, winsorized at the top and bottom 1%, and never compounded; universe base rate +3.49% mean / +2.36% median across the 76,908 filings. Results were confirmed against an independently reconstructed growth measure and against returns re-measured relative to same-calendar-quarter filing cohorts. Methodology: [filing data study methodology](/blog/filing-data-study-methodology).</sup>

---

## Blog: roic.ai Alternative: Where the ROIC Number Comes From
source: https://www.geminiq.com/blog/roic-ai-alternative-sec-data

### roic.ai Alternative: Where the ROIC Number Comes From
roic.ai and GeminIQ both source financial data from SEC filings and both publish a calculated ROIC figure. The difference is what happens between the filing and the metric: roic.ai standardizes statements into its own templates, while GeminIQ preserves the as-filed structure with XBRL traceability. This comparison covers why that gap shows up in ROIC specifically.

There is no line in any SEC filing labeled ROIC. No company reports it, no accounting standard defines it, and no regulator specifies its inputs. Every platform publishing a ROIC figure built that figure — from a numerator that has to be tax-adjusted and a denominator that has to be assembled out of three separate balance sheet decisions. So the question worth asking about any platform named after the metric is not whether its ROIC is accurate. It is what happened to the filing between the moment it was submitted and the moment the number appeared on screen.

## What roic.ai Does Well

roic.ai is a well-built platform with a clear thesis, and several of its strengths have no equivalent here.

Coverage is the first and largest. Its data spans tens of thousands of companies across more than seventy global exchanges, which means a European industrial or an Asian semiconductor name gets the same treatment as a US large cap. GeminIQ covers SEC filers. For an investor holding anything outside the US reporting system, that difference settles the question before any other consideration enters.

History depth is the second. roic.ai carries decades of financial statements, well beyond what most retail-accessible platforms offer, and for long-cycle businesses or full-cycle analysis that depth is the point.

Programmatic access is the third. A REST API with a free tier, spreadsheet endpoints for Excel and Google Sheets, an MCP server, and a ChatGPT integration mean the data can move into a model, an agent, or a chat workflow rather than only being read on a page. Earnings call transcripts sit alongside the statements, and the single-page company overview is a clean piece of product design — everything about a business on one screen, which remains the fastest way to form a first impression of a company.

None of that is in dispute. The question this post is about is narrower.

## Standardization Happens Before You See the Number

Both platforms draw from the same source. Every US filing either one reads is the same 10-K or 10-Q sitting on EDGAR, tagged in XBRL by the company that filed it.

What differs is the step immediately after ingestion. roic.ai standardizes and reformats filings into its own presentation templates — a consistent set of line items applied across every company, so a balance sheet from one filer lines up visually with a balance sheet from another. That is a deliberate design choice with a real benefit: comparison across companies gets easier when everyone's statements share a shape.

GeminIQ skips that step. Filings are parsed into structured data with the issuer's own line items and XBRL tags preserved, which means the balance sheet on screen has the same rows, in the same arrangement, as the balance sheet the company filed. Two companies looking different from each other counts as information rather than as a formatting problem to solve.

Neither approach is wrong. They optimize for different things, and the tradeoff only becomes visible when a calculated metric sits downstream of the choice.

## Why ROIC Is the Metric Where It Shows

ROIC is the most standardization-sensitive metric in common use, and the sensitivity lives almost entirely in the denominator.

[Invested Capital](/blog/invested-capital-formula-step-by-step) is not reported anywhere. It gets built from total equity plus total debt minus excess cash, and each of those three inputs carries a decision the filing never makes. Which borrowings count as debt — and specifically whether operating lease liabilities and the current portion of long-term debt belong in the total. How much cash is excess versus operationally necessary. Whether the figure feeding the ratio is a single period's snapshot or a two-period average.

Standardizing a balance sheet means mapping the issuer's line items onto template rows, and that mapping is where debt classification gets decided. A filer reporting five separate borrowing lines under its own labels has to collapse into a template's debt row somehow, and the collapse is a judgment call made once, at ingestion, invisibly to whoever reads the resulting ROIC six steps later.

The consequence is not error. It is that the number becomes difficult to reproduce. An investor who calculates invested capital by hand from the 10-K and gets a different answer than the platform shows has no way to locate the divergence, because the intermediate step — which filing line became which template row — is never exposed.

## The Same Company, Two Defensible Figures

Two platforms reading the identical filing can publish ROIC figures a full percentage point or more apart without either one making a mistake.

Include the current portion of long-term debt in invested capital and the capital base grows, so ROIC falls. Exclude it and the base shrinks, so ROIC rises. Fold operating lease liabilities into debt and a retailer or airline looks materially more capital-intensive than it does under a convention that leaves leases out. Subtract all cash rather than only the excess above an operating threshold and a cash-rich business posts a dramatically higher return on a dramatically smaller base.

Every one of those is a defensible methodology. None of them is disclosed on the face of a ROIC figure. That is why a metric that looks like a fact is closer to a position — and why reconciling two platforms' ROIC figures is a methodology exercise rather than an arithmetic one.

## What Traceability Actually Buys

GeminIQ's answer is not a claim that its convention is the correct one. It is that the convention stays visible, consistent, and checkable.

Every figure in the [Financial Statements](/features#financial-statements) view carries its XBRL tag, so any number traces back to the specific tag in the specific filing that produced it. The metric library documents what each calculation includes: [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) states its denominator, [Invested Capital](/metrics/calculated-values/invested-capital) states its debt definition and its excess cash rule, [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) states what enters total debt. One convention applies to every company in the database, which is the property that makes a cross-company screen mean anything at all.

The practical test is simple. Take a ROIC figure, open the filing it came from, and rebuild it by hand. If the platform's inputs are traceable, the rebuild either matches or the difference is locatable in a specific decision. If the statements were reformatted on the way in, the rebuild will disagree and the reason will not be recoverable from anything on screen.

## Where Each One Fits

Choose roic.ai when coverage or access shape the requirement. Non-US holdings, decades of history, API or agent-based workflows, and earnings transcripts alongside the statements are all reasons it is the better tool, and no amount of traceability compensates for a company that isn't in the database.

Choose GeminIQ when the requirement is verification. As-filed line items with XBRL tags attached, calculated metrics whose conventions are documented rather than inferred, and a screener built on inputs that reconcile against the source filing are what the platform optimizes for — at the cost of covering SEC filers only.

The honest framing is that these tools disagree about what a financial statement is for. One treats it as data to be made comparable. The other treats it as a document that already said something specific, and holds that a metric derived from it should still be recoverable from the original. For most investors that distinction never surfaces. For anyone rebuilding a number and finding it doesn't match, it is the whole story.

## Frequently Asked Questions

### What is the best roic.ai alternative?

It depends on what roic.ai was being used for. For global coverage, deep history, or API and agent access, the alternatives are other broad-coverage data providers. For US filing data where every figure traces back to its XBRL tag in the source filing, the alternative is an as-filed platform — a different design, not a cheaper version of the same one.

### Does roic.ai use SEC data?

Yes, for US companies. Both roic.ai and GeminIQ read the same 10-K and 10-Q filings from EDGAR. The difference is what each does after ingestion: roic.ai standardizes statements into consistent templates, while GeminIQ preserves the issuer's own line items and XBRL tags.

### Why do ROIC figures differ between platforms?

Almost always because of the denominator. Invested capital is not reported in any filing and has to be assembled from equity, debt, and cash — and whether operating leases count as debt, whether the current portion of long-term debt is included, and how much cash counts as excess are three separate methodology choices. Each is defensible, and together they can move ROIC by a percentage point or more.

### Which platform has better data?

Neither, on accuracy. Both read the same filings. They differ on what gets preserved: standardized templates make cross-company comparison visually easier, while as-filed structure makes any individual figure reproducible from the source document. Which one is better depends entirely on whether the work involves scanning many companies or verifying one.

### Does GeminIQ cover non-US companies?

No. GeminIQ covers SEC filers, which means US-listed companies filing 10-K and 10-Q reports. Investors holding companies outside the SEC reporting system need a platform with international exchange coverage.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=roic-ai-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: ROIC vs ROE vs WACC: How the Three Fit Together
source: https://www.geminiq.com/blog/roic-vs-roe-vs-wacc

### ROIC vs ROE vs WACC: How the Three Fit Together
ROIC, ROE, and WACC are three percentages that look like the same kind of number and answer three different questions. This guide explains what each one actually measures, why a business can pass the ROE test while failing the ROIC test, and how to read all three together as a single framework for judging whether a company creates or destroys value.

**ROIC measures the return a company earns on all the capital invested in it, ROE measures the return on shareholders' equity alone, and WACC is the blended cost of that capital.** A business creates value when its ROIC exceeds its WACC; a high ROE can come from leverage rather than from a strong business.

Three percentages, all expressed the same way, all sitting on the same financial summary page: ROIC at **18%**, ROE at **31%**, [WACC](/blog/how-to-calculate-wacc-from-10k) estimated at **9%**. Every one of them looks like good news in isolation. Only one comparison among the three actually tells you whether the business created value last year — and it is not the comparison most investors reach for first. ROIC, ROE, and WACC measure three different things, and the businesses that reward the most scrutiny are the ones where the three numbers tell conflicting stories. This guide covers what each metric actually answers, the two separate value-creation tests hiding inside these three numbers, and the specific mechanism — leverage — that lets a company pass one test while quietly failing the other.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=roic-vs-roe-vs-wacc)**

---

## ROIC vs ROE vs WACC at a Glance

| | ROIC | ROE | WACC |
|---|---|---|---|
| **What it is** | Return on all capital deployed | Return on shareholder capital only | The minimum return required |
| **Formula** | NOPAT ÷ average invested capital | Net income ÷ average shareholders' equity | (Cost of equity × equity weight) + (after-tax cost of debt × debt weight) |
| **Denominator includes debt?** | Yes | No | Yes (as a weight) |
| **What it measures** | Operating efficiency, independent of how the business is financed | Profit generated per dollar of book equity at risk | The blended hurdle rate debt and equity investors demand |
| **Moves when leverage changes?** | Largely no | Yes — buybacks and borrowing raise it without any operating improvement | Yes |
| **Comes straight from filings?** | Yes | Yes | No — requires analyst assumptions (beta, equity risk premium) |
| **The test it belongs in** | ROIC > WACC — did the business create value? | ROE vs ROIC — is the gap leverage or genuine quality? | The hurdle both returns are measured against |

The single comparison that answers "did this business create value last year" is **ROIC vs. WACC**. Comparing ROE against WACC is the most common misuse of the three, and the section on [WACC as a hurdle](#wacc-is-a-hurdle-not-a-return) explains why it produces the wrong answer.

---

## Table of Contents

- [ROIC vs ROE vs WACC at a Glance](#roic-vs-roe-vs-wacc-at-a-glance)
- [What Each Metric Actually Measures](#what-each-metric-actually-measures)
- [Why These Three Get Confused](#why-these-three-get-confused)
- [WACC Is a Hurdle, Not a Return](#wacc-is-a-hurdle-not-a-return)
- [The Two Value-Creation Tests Hiding Inside Three Numbers](#the-two-value-creation-tests-hiding-inside-three-numbers)
- [How a Company Passes the ROE Test and Fails the ROIC Test](#how-a-company-passes-the-roe-test-and-fails-the-roic-test)
- [Reading All Three Together: A Simple Framework](#reading-all-three-together-a-simple-framework)
- [Where This Divergence Shows Up in Real Companies](#where-this-divergence-shows-up-in-real-companies)
- [When the Framework Breaks](#when-the-framework-breaks)
- [Where to Go Deeper](#where-to-go-deeper)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Each Metric Actually Measures

### What Is ROIC?

[Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) measures after-tax operating profit against the total capital deployed by both debt and equity holders combined. It answers a capital-structure-neutral question: how efficiently does this business convert a dollar of total capital — regardless of whether that dollar came from a lender or a shareholder — into operating profit? For the full formula, the NOPAT build, and platform-to-platform benchmarks, see [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained).

### What Is ROE?

[Return on Equity](/metrics/returns-and-profitability/return-on-equity) measures net income against shareholders' equity alone. It answers a narrower question: for every dollar of book equity shareholders have at risk, how much net income does the business generate? Unlike ROIC, ROE's denominator excludes debt entirely — which is precisely the property that makes it possible to move without any change in operating performance at all.

### What Is WACC?

The Weighted Average Cost of Capital is not a return a business earns. It is the minimum return a business must earn — a blended hurdle rate reflecting what both debt and equity investors require to keep funding the business, weighted by how much of each the company uses. GeminIQ does not calculate WACC as a platform metric, because it depends on assumptions — beta, equity risk premium, marginal cost of debt — that no filing reports directly. Every raw input needed to estimate it (interest expense, the [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), share count) comes straight from the filing; the discount rate itself is an assumption an analyst brings to the model. See [How to Build a DCF Model, Step by Step](/blog/dcf-valuation-model-step-by-step) for how WACC gets used once estimated.

---

## Why These Three Get Confused

All three numbers are percentages. All three get plotted on the same summary dashboard, in the same font size, next to each other — and two of the three, ROIC and ROE, do measure the same underlying concept: profitability against capital, just with a different capital base in the denominator. That similarity is exactly why they get treated as interchangeable "return" figures, when in fact only one of the three possible comparisons between them — ROIC against WACC — directly answers the question investors actually care about: is this business creating economic value.

The confusion compounds because ROE is the number most retail-facing platforms lead with. It requires only two inputs — net income and equity — both of which sit near the top of any summary page, while ROIC requires assembling NOPAT and invested capital, two figures no filing reports as a single line. The metric that is easiest to compute is not the metric that is hardest to game, and ROE is both the easiest to compute and the easiest to inflate.

---

## WACC Is a Hurdle, Not a Return

The single most common misreading of these three metrics is treating WACC as if it belonged on the same axis as ROIC and ROE — as a third "return" to compare against the other two directly. It isn't. ROIC and ROE measure what a business actually earned. WACC measures what a business was required to earn just to avoid destroying value, given what its capital costs.

That distinction matters because WACC is the denominator-neutral benchmark: the same WACC applies whether you're evaluating the return to all capital (ROIC) or the return to equity alone (the cost of equity component within WACC, evaluated against ROE). Confusing WACC for a return rather than a hurdle leads to the most common analytical error in this space. The theoretically correct comparison for equity holders is ROE against the cost of equity alone — not the blended WACC. Cost of equity is narrower and typically higher than WACC, because equity holders take on more risk than the debt holders whose lower required return gets blended into the average.

---

## The Two Value-Creation Tests Hiding Inside Three Numbers

Two separate value-creation tests hide inside these three numbers, and most investors run only one of them without ever realizing a second exists.

**Test One: ROIC vs. WACC.** This is the enterprise-level test. When ROIC clears WACC, the business generates more operating profit than the blended cost of every dollar funding it — value creation for the entire capital stack, debt and equity together. When ROIC falls short of WACC, the business destroys economic value regardless of what net income or ROE happen to show, because growth under those conditions means deploying more capital at an inadequate return.

**Test Two: ROE vs. Cost of Equity.** This is the narrower, shareholder-level test — and it is the one most platforms skip entirely, because the cost of equity alone, as opposed to the blended WACC, requires isolating just the equity-holder discount rate. Shareholders bear more risk than debt holders and require a higher return to compensate. A ROE figure that clears WACC but does not clear the true cost of equity can still look like a passing grade on a dashboard that only shows WACC as the reference point.

The two tests can disagree, and when they do, the disagreement is the entire story. A business can clear Test One comfortably while barely clearing Test Two — or clear Test Two spectacularly while failing Test One outright. The second pattern is the more dangerous one, and it has a specific, mechanical cause.

---

## How a Company Passes the ROE Test and Fails the ROIC Test

Leverage is the mechanism, and it works through simple arithmetic rather than any change in the underlying business. Consider two versions of the same hypothetical company, identical in every operating respect — same revenue, same operating margin, same NOPAT of **$100 Million**.

Version A carries no debt. Its invested capital is **$1 Billion**, entirely equity-funded, and its ROIC comes to **10%**. Because there's no debt to separate out, its ROE is also **10%** — identical to ROIC, since equity and invested capital are the same number here.

Version B carries **$600 Million** in debt against **$400 Million** in equity — the same **$1 Billion** capital base, just financed differently. NOPAT is unchanged at **$100 Million**. Leverage doesn't touch the numerator or the total capital in the denominator, so ROIC is still **10%** — identical to Version A's enterprise-level return. Net income tells a different story. After subtracting after-tax interest expense on the **$600 Million** in debt, net income might fall to roughly **$70 Million**. That smaller profit figure now divides into a much smaller equity base of just **$400 Million**, and the result is a ROE of **17.5%** — nearly double Version A's, on a net income figure that is actually lower.

Version B looks like the better business on any dashboard that leads with ROE. It is not a better business. It is the identical business wearing more debt, and its ROIC — the metric immune to this effect — confirms nothing has actually improved operationally. If Version B's WACC rises because lenders now demand a higher rate on the larger debt load, its **10%** ROIC may no longer clear the hurdle at all, even as its ROE keeps climbing. This is exactly how a company passes the ROE test and fails the ROIC test in the same reporting period: leverage shrinks the equity denominator far faster than it shrinks net income, and the resulting ratio looks like an improvement that never touched the operating business at all.

---

## Reading All Three Together: A Simple Framework

Reading the three metrics together is a short sequence, not three unrelated data points. Start with ROIC against WACC — the enterprise-level verdict, checked first because it is immune to the leverage distortion described above. If ROIC clears WACC by a wide, persistent margin across multiple years, the business is creating real economic value at the operating level, independent of how it happens to be financed.

Only after that verdict is established does ROE become informative — not as a standalone quality signal, but as a lens on capital structure. A ROE meaningfully higher than ROIC signals the business is using leverage to amplify shareholder returns; that can be a rational, value-accretive choice, or it can be a way to disguise a business whose unlevered economics are mediocre. The [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) is the fastest way to check which story applies — a modest, stable debt load alongside a persistent ROIC-ROE gap suggests deliberate, sustainable capital structure. A debt load climbing quarter over quarter alongside a widening gap suggests leverage doing the work operations no longer can.

---

## Where This Divergence Shows Up in Real Companies

[Costco](/stocks/COST) is a useful anchor for the ROIC side of this framework precisely because leverage isn't the story. GeminIQ's pre-calculated [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) shows Costco's ROIC at **33.4%** against a **3.8%** operating margin — a spread between margin and capital efficiency that has nothing to do with financial engineering and everything to do with the membership float and negative working capital cycle covered in the full [Costco 10-Q teardown](/blog/costco-stock-analysis-2026). Because Costco's leverage is modest relative to that capital efficiency, its ROIC and ROE tell a consistent story rather than a diverging one. The businesses where ROIC and ROE tell the *same* story are usually the ones where the balance sheet isn't doing any of the heavy lifting.

The airline sector illustrates the opposite condition at the industry level: heavy aircraft-financing debt loads sitting alongside an industry ROIC that has historically hovered near or below the estimated cost of capital through most economic cycles, detailed in the [Airline Sector Intel Brief](/blog/airline-sector-stock-analysis). In an industry structurally close to its WACC hurdle, the ROIC-vs-WACC test carries far more diagnostic weight than any single quarter's ROE — a debt-heavy capital structure sitting on top of a return that barely clears its cost of capital is a business one refinancing cycle away from an outright value-destroying period.

---

## When the Framework Breaks

All three benchmarks assume a reasonably stable capital structure and a business generating a genuine operating profit. A handful of situations distort the comparison badly enough to warrant caution.

Negative or near-zero equity — common among companies with long buyback histories or accumulated deficits — renders ROE meaningless or undefined. Dividing by a number near zero produces an arbitrarily large or negative result that reflects capital structure rather than performance. [ROIC](/blog/roic-return-on-invested-capital-explained) remains the more reliable read in these cases, because invested capital rarely approaches zero even when book equity does.

A single strong or weak quarter can swing ROE meaningfully more than it swings ROIC, because ROE's smaller equity denominator amplifies numerator volatility that a larger, debt-inclusive invested capital base absorbs. A three-to-five-year view of both metrics, rather than any single period, is what separates a genuine structural divergence from ordinary earnings noise.

And WACC itself is always an estimate, never an observed figure — small differences in the assumed equity risk premium or beta can shift it by two or three percentage points, which is often enough to flip a narrow ROIC-vs-WACC spread from value-creating to value-destroying. Treat the framework directionally, and demand a wide margin before drawing a firm conclusion from any comparison sitting close to the estimated hurdle.

---

## Where to Go Deeper

This guide is the map, not the full terrain. For the complete ROIC formula, the NOPAT build, and platform benchmarking, see [Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained). For exactly how the invested capital denominator gets built from a real filing, step by step, see [Invested Capital: How to Calculate It, Step by Step](/blog/invested-capital-formula-step-by-step). For how WACC functions as the discount rate inside a full valuation model, see [How to Build a DCF Model, Step by Step](/blog/dcf-valuation-model-step-by-step). And for the DuPont Decomposition — which breaks ROE itself into margin, turnover, and leverage components and shows mathematically why the Version A/B divergence above happens — see the [Value Investing Glossary](/blog/value-investing-glossary).

Once the framework above makes sense conceptually, GeminIQ's [Quality Compounder screen](/screens/stock-screeners/quality-compounder) applies it at scale — filtering for ROIC persistence at or above **20%** alongside a Debt-to-Equity ceiling of **0.5**, a direct, systematic way to surface businesses clearing the harder test without leaning on the leverage shortcut described above. Reading three numbers correctly for one company is a five-minute exercise. Screening the same relationship across the entire market is what turns a framework into an edge — and it only works if invested capital and ROIC are calculated the same way for every company in the comparison, not just the one under a microscope this quarter.

---

## Frequently Asked Questions

### Is a high ROE always a red flag?
No. High ROE driven by strong operating efficiency and a deliberately modest, low-cost debt load can be entirely healthy — plenty of high-quality businesses run with some leverage. The red flag is specifically a ROE meaningfully above ROIC, widening over time, alongside a rising Debt-to-Equity Ratio and a NOPAT that isn't growing. That combination signals leverage substituting for operating improvement rather than complementing it.

### Should WACC ever be compared directly against ROE?
Not in the theoretically strict sense — the correct benchmark for ROE is the cost of equity alone, which runs higher than the blended WACC because equity holders bear more risk than debt holders and require greater compensation. In practice, many analysts use WACC as a rough proxy when the cost of equity isn't separately estimated, but doing so understates the true hurdle rate for equity holders specifically.

### Can ROIC and ROE ever be identical?
Yes — for an all-equity-financed company with no debt, invested capital and shareholders' equity are the same figure, so ROIC and ROE converge exactly, as in the Version A example above. Any gap between the two metrics for a real company is, almost by definition, a leverage effect.

### Why doesn't GeminIQ calculate WACC directly?
WACC depends on assumptions no SEC filing reports as a hard figure — the equity risk premium, beta, and the marginal cost of new debt all require analyst judgment rather than XBRL extraction. GeminIQ provides every raw, as-filed input needed to estimate WACC independently — interest expense, debt levels, share count — without asserting a single "correct" discount rate that would necessarily embed someone else's assumptions into the number.

### Should ROIC be higher than WACC?

Yes. When ROIC is above WACC, each dollar the company invests earns more than it costs to raise, so growth creates value. When ROIC is below WACC, the company destroys value with every dollar it reinvests, even if its earnings are growing.

### What does a 12% WACC mean?

A 12% WACC means the company's lenders and shareholders, blended by how much capital each provides, require a 12% annual return. The business needs to earn a ROIC above 12% on new investments for them to add value; a project returning 10% would shrink value even though it is profitable.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=roic-vs-roe-vs-wacc)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Costco Wholesale Corporation's Q3 FY2026 10-Q (filed June 3, 2026, period ending May 10, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/909832/000090983226000051/cost-20260510.htm).

---

## Blog: Rule of 40: SaaS Formula, Benchmark, and Limits
source: https://www.geminiq.com/blog/rule-of-40-saas-metric-explained

### Rule of 40: SaaS Formula, Benchmark, and Limits
The Rule of 40 measures whether a software company's revenue growth rate plus its profit margin clears a combined 40% threshold, and understanding what the metric captures — and where it breaks down for companies outside subscription software — is what separates a truly useful growth-versus-profitability check from a number repeated without context.

A software company that's growing fast can still be a bad bet, and a highly profitable one can still be stalling out — a single growth number or a single margin number, read alone, won't tell you which. The Rule of 40 exists to combine the two into one comparable score investors can screen with in seconds. What it actually measures, what counts as a passing score, and — just as important — where the formula stops meaning anything once a company isn't a subscription software business is what turns it from a number repeated on earnings calls into something usable.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=rule-of-40-saas-metric-explained)**

| Input | Definition | Typical / Benchmark Range |
|---|---|---|
| Rule of 40 Score | Revenue Growth Rate (%) + Profit Margin (%) | Above 40 is the standard pass mark |
| Revenue Growth Rate | Trailing-twelve-month revenue growth, most often year-over-year | High-growth SaaS: 30%+; mature SaaS: high single digits to ~15% |
| Profit Margin | Most commonly free cash flow margin (TTM free cash flow ÷ TTM revenue); operating margin or EBITDA margin are also used | Roughly 0% to 40%+, depending on growth stage |

## Table of Contents

- [What Is the Rule of 40?](#what-is-the-rule-of-40)
- [The Rule of 40 Formula](#the-rule-of-40-formula)
- [What Counts as a Good Rule of 40 Score?](#what-counts-as-a-good-rule-of-40-score)
- [A Worked Example From a Real Filing](#a-worked-example-from-a-real-filing)
- [Why Growth and Margin Are Treated as Interchangeable](#why-growth-and-margin-are-treated-as-interchangeable)
- [Where the Rule of 40 Breaks Down](#where-the-rule-of-40-breaks-down)
- [Frequently Asked Questions](#frequently-asked-questions)

## What Is the Rule of 40?

The Rule of 40 is a single combined benchmark used to judge whether a software or subscription business is balancing growth and profitability in a healthy way. It adds a company's revenue growth rate to its [profit margin](/metrics/margin-metrics/net-profit-margin) — most commonly free cash flow margin, though some analysts substitute operating margin or EBITDA margin — and checks whether the sum clears 40%. A fast-growing company that isn't yet profitable can still pass the test if growth alone is strong enough; a slower-growing, highly profitable company can pass on margin alone. What the rule is built to catch is the company that's neither growing quickly nor generating real margin — the combination that's hardest to defend in a software business trading on a growth multiple.

## The Rule of 40 Formula

Rule of 40 Score = Revenue Growth Rate (%) + Profit Margin (%)

Both inputs are typically measured on a trailing-twelve-month basis, and the profit margin figure varies by which version of the rule an analyst is using — [free cash flow](https://www.geminiq.com/metrics/calculated-values/free-cash-flow) margin is the most common choice because it reflects actual cash generation rather than an accounting profit figure that can be affected by non-cash items like stock-based compensation. A company growing [revenue](https://www.geminiq.com/metrics/growth-metrics/revenue-growth) **25%** year-over-year with a **20%** free cash flow margin scores 45 — comfortably above the 40 threshold, even though neither individual number would necessarily stand out on its own.

## What Counts as a Good Rule of 40 Score?

A combined score above 40 is the standard pass mark venture investors and public-market software analysts use, though the threshold works better as a rough screening line than a precise cutoff. A score meaningfully above 40 — 60, 80, or higher — signals a company executing well on both dimensions simultaneously, which is rare enough that it typically draws a premium valuation multiple. A score below 40 doesn't automatically mean a company is in trouble; a business in a heavy investment phase can post a temporarily low score while building toward a larger addressable market, which is why the trend in the score over several quarters usually matters more than any single period's reading.

## A Worked Example From a Real Filing

**[Palantir Technologies'](/stocks/PLTR)** fiscal 2025 10-K illustrates what a truly strong Rule of 40 score looks like in practice — see [GeminIQ's full Palantir 10-K analysis](/blog/palantir-10k-analysis-2026) for the complete filing breakdown. Revenue grew **56.2%** year-over-year, and free cash flow margin came in near **47%** on $2.10 Billion in free cash flow against $4.48 Billion in revenue. Added together, that's a combined Rule of 40 score of roughly **103** — more than double the 40 threshold, and a score high enough that it's worth checking both inputs individually rather than treating the combined number as self-explanatory. A score that high can be driven predominantly by growth, predominantly by margin, or — as in this case — by both moving in the same direction at once, and the underlying mix matters for judging how durable the score is likely to be.

## Why Growth and Margin Are Treated as Interchangeable

The logic behind adding two different metrics together is that, for a subscription software business specifically, growth and profitability represent a genuine tradeoff a management team can choose between. A company can spend more on sales and marketing to accelerate growth at the cost of near-term margin, or pull back on growth spending to let margin expand — and within reasonable bounds, investors in this specific business model have historically been roughly indifferent between the two paths, as long as the combined score clears the bar. That indifference is specific to software's cost structure: incremental revenue carries very low marginal cost, so a dollar of growth this year and a dollar of margin this year both represent a similar underlying claim on the business's long-term cash generation.

## Where the Rule of 40 Breaks Down

The Rule of 40 was built for subscription software specifically, and it degrades quickly outside that context — which is exactly the qualification a passing score is most often quoted without. A capital-intensive business — a semiconductor manufacturer, an airline, a REIT — doesn't have software's near-zero marginal cost structure, so a **25%**-growth, **15%**-margin capital-intensive company clearing the same 40 threshold isn't making the same tradeoff a software company in that position is; a large share of its margin is consumed by maintenance capital expenditures the rule doesn't account for at all. The metric also says nothing about the quality or durability of either input — a growth rate driven by one large one-time contract, or a margin inflated by a temporary cost-cutting push, can produce a passing score that doesn't reflect the underlying trend. Applied outside subscription software, or applied to a single quarter without checking the trend, the Rule of 40 is a number repeated without the context that makes it useful in the first place.

## Frequently Asked Questions

### What is the Rule of 40 in SaaS?

It's a combined benchmark that adds a software company's revenue growth rate to its profit margin — most often free cash flow margin — and checks whether the sum clears **40%**. It's used as a quick screen for whether a subscription software business is balancing growth investment and profitability in a defensible way.

### What margin should be used in the Rule of 40 calculation?

Free cash flow margin is the most common and arguably the most rigorous choice, since it reflects actual cash generation rather than an accounting profit figure that can be shaped by non-cash items like stock-based compensation. Some analysts substitute operating margin or EBITDA margin, which can produce a meaningfully different score for the same company depending on how large the gap between accounting profit and cash generation is.

### Does the Rule of 40 apply outside of software companies?

Not reliably. The rule assumes a cost structure — very low marginal cost on incremental revenue — that's specific to subscription software. Capital-intensive businesses in other sectors face a different tradeoff between growth and margin, since a meaningful share of their margin is consumed by maintenance capital spending the Rule of 40 formula doesn't account for.

### Is a Rule of 40 score above 40 always a good sign?

Not on its own. The score can be inflated by a temporary factor — a large one-time contract driving growth, or a short-term cost cut driving margin — that doesn't reflect the durable trend in the business. Checking both individual inputs, and how the combined score has moved over several consecutive quarters, is a more reliable read than a single period's passing score.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=rule-of-40-saas-metric-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Palantir Technologies Inc.'s fiscal 2025 10-K (filed February 17, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/1321655/000132165526000011/pltr-20251231.htm).</sup>

---

## Blog: IPO Lockup Expirations: What the S-1 Tells You
source: https://www.geminiq.com/blog/s-1-lockup-expiration-filings

### IPO Lockup Expirations: What the S-1 Tells You
An IPO lockup expiration is the date, disclosed in the company's S-1 registration statement, when insiders and pre-IPO shareholders first become contractually free to sell — and academic research has repeatedly found it comes with a measurable increase in trading volume and a negative average stock-price reaction. This guide covers exactly where the lockup is disclosed in the S-1, how long it typically runs, the automatic-extension and early-release provisions most retail coverage never mentions, and how to track the date forward once the company is trading.

An IPO lockup expiration date is public information months before it arrives, disclosed in plain language in the company's own S-1. Academic research has repeatedly found that the stock still reacts when the date finally comes — measurably, on average, even though nobody involved could claim to be surprised.

[Our S-1 guide](/blog/what-is-s-1) covers the lockup as one of five things worth checking in a fresh IPO filing. This guide goes deeper into the mechanic itself: exactly where the agreement is disclosed, how long it actually runs, the extension and early-release provisions that change the date after the fact, and what the research says happens to the stock when the restriction finally lifts.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=s-1-lockup-expiration-filings)**

---

## Table of Contents

- [What a Lockup Agreement Actually Is](#what-a-lockup-agreement-actually-is)
- [Where to Find It in the S-1](#where-to-find-it-in-the-s-1)
- [How Long a Lockup Typically Runs](#how-long-a-lockup-typically-runs)
- [The Automatic Extension Trigger](#the-automatic-extension-trigger)
- [Early Release: When Underwriters Waive the Lockup](#early-release-when-underwriters-waive-the-lockup)
- [What Happens to the Stock When a Lockup Expires](#what-happens-to-the-stock-when-a-lockup-expires)
- [How to Track a Lockup Expiration Date](#how-to-track-a-lockup-expiration-date)
- [Step 1: Find the Lockup Section in the S-1 or 424B4](#step-1-find-the-lockup-section-in-the-s-1-or-424b4)
- [Step 2: Calculate the Expiration Date](#step-2-calculate-the-expiration-date)
- [Step 3: Watch for Form 4 Filings Around the Date](#step-3-watch-for-form-4-filings-around-the-date)
- [Tracking the Aftermath on GeminIQ](#tracking-the-aftermath-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What a Lockup Agreement Actually Is

A lockup agreement is not an SEC rule. It is a private contract between the company's underwriters and its pre-IPO shareholders — founders, executives, directors, and often venture and private equity investors — restricting them from selling, or even agreeing to sell, their shares for a set period after the offering. The restriction exists because underwriters don't want the stock they just priced and sold to the public immediately facing a wave of insider selling before a real trading market has formed.

That contractual nature matters for how the restriction can change. Because no regulator wrote the rule, no regulator has to approve a change to it. The underwriters who negotiated the agreement are also the ones who can waive it, extend it, or release it early — and they do all three, on terms the S-1 discloses up front.

---

## Where to Find It in the S-1

The lockup terms appear in two sections of every S-1: Shares Eligible for Future Sale, and Underwriting. The first states the duration and mechanics in the context of how many total shares become freely tradable and when. The second contains the full lockup agreement language, including any early-release discretion the underwriters have reserved for themselves. The Shares Eligible for Future Sale section is usually the faster read — it states the expiration trigger directly, in a sentence structured almost identically across nearly every S-1: shares become eligible for sale some number of days "after the date of this prospectus" or "after the effective date of the registration statement."

That distinction matters. The clock does not start on the day the company files its S-1. It starts on the day the offering actually prices and the final prospectus (Form 424B4) is filed, which can be weeks or months after the initial S-1 hits EDGAR. An investor calculating an expiration date from the S-1 filing date rather than the final pricing date will get the wrong day, sometimes by a significant margin.

---

## How Long a Lockup Typically Runs

**180 days** is the standard duration in the U.S. market, though **90-day** lockups appear as well, and the two aren't mutually exclusive within the same offering. A meaningful share of S-1 filings disclose a tiered structure: a portion of shares becomes eligible at 90 days, a second tranche at a middle point such as 135 days, and the remainder at the full 180-day mark. Reading the actual share counts tied to each tranche — not just the headline "180 days" figure most coverage repeats — tells you how much of the float is actually locked at each stage. A 180-day lockup where 90% of restricted shares release at day 90 behaves nothing like one where 90% waits for the full term.

The structures that show up across S-1 filings, and what can move each one:

| Structure | Typical length | What starts the clock | What can move the date |
|---|---|---|---|
| Standard single-tranche lockup | 180 days | Date of the final prospectus (Form 424B4), not the S-1 filing date | Automatic extension trigger; underwriter early release |
| Shorter single-tranche lockup | 90 days | Date of the final prospectus (Form 424B4), not the S-1 filing date | Automatic extension trigger; underwriter early release |
| Tiered lockup | Staged — a portion at 90 days, a tranche at a middle point such as 135 days, the remainder at 180 days | Date of the final prospectus (Form 424B4), not the S-1 filing date | Automatic extension trigger; underwriter early release |
| Rule 144 / Rule 701 eligibility | — (set by rule, not by contract) | — | Independent of the lockup agreement; in nearly every S-1 this eligibility arrives before the lockup lifts |

Rule 144 and Rule 701 add another layer underneath the contractual lockup. Both rules independently govern when restricted and compensatory shares become legally eligible for public resale, and in nearly every S-1 that eligibility arrives before the lockup does — meaning the lockup agreement, not federal securities law, is usually the binding constraint on when insiders can actually sell.

---

## The Automatic Extension Trigger

Many lockup agreements contain a provision that most retail coverage never mentions. If the company issues an earnings release, or discloses material news, within a defined window before the lockup's scheduled expiration — commonly the last **15 to 17 days** of the lockup period — the expiration date automatically extends. The new date typically lands roughly three business days after that earnings release or disclosure. The purpose is narrow: prevent insiders from being freed to sell into the exact window when the market is digesting fresh material information they may have had advance knowledge of.

The practical effect is that a lockup's calculated expiration date is provisional, not fixed, for any company whose earnings calendar happens to land near it. A lockup nominally set to expire 180 days after pricing can, and often does, extend automatically if the company's next quarterly release falls inside that trailing window — which is common, since many companies report quarterly roughly every 90 days.

---

## Early Release: When Underwriters Waive the Lockup

Underwriters retain discretion to release some or all locked-up shares before the scheduled date, and the S-1's Underwriting section states plainly whether they've reserved that discretion — nearly all do, while stating they have no current intention of using it. An early release for officers and directors specifically triggers a disclosure requirement. FINRA rules require the underwriter to announce the release publicly, by press release, and the waiver cannot take effect until at least **two business days** after that announcement.

That two-day announcement window exists because early releases for a small group of insiders — often to fund a specific liquidity need — are themselves market-moving information, and the rule gives the broader market notice before the shares can actually trade. A press release announcing an early lockup release for named executives, distributed ahead of the original expiration date, is worth reading closely: it names exactly who is being released and how many shares, which the S-1's original terms never could.

The 2025 IPO class made the point repeatedly. Three of its largest listings all carried a nominal 180-day lockup, and in all three the date that mattered was not the one 180 days out:

| Company | Nominal lockup | What actually moved the date |
|---|---|---|
| [CoreWeave](/stocks/CRWV) | 180 days from the March 2025 prospectus | An earnings trigger terminated it early. The lockup lifted on **August 14, 2025**, two trading days after the Q2 2025 earnings release on August 12 — roughly six weeks ahead of the calendar date |
| [Circle](/stocks/CRCL) | 180 days from the June 5, 2025 prospectus, expiring **December 2, 2025** | An early-release provision freed roughly **11.5 million** shares around August 13, 2025, more than three months before the headline date |
| [Figma](/stocks/FIG) | 180 days, with an extended agreement layered on top | A **price condition** was met after the close on September 4, 2025, releasing **25%** of eligible employee and service-provider securities at the open on **September 5**. Holders of roughly **54.1%** of Class A shares had separately signed extended lockups with staggered quarterly releases running through June 2026 |

Read down that column and the pattern is that the headline expiration date was the least useful number in each agreement. Two of the three were pulled forward by a trigger written into the original contract, and the third had a second, longer agreement sitting behind the one the prospectus described. None of that is visible from the 180-day figure alone.

---

## What Happens to the Stock When a Lockup Expires

Field and Hanka's 1,948-agreement study, published in the *Journal of Finance* in 2001, remains the foundational academic work on this question. It found a permanent **40%** increase in average trading volume once lockups expired, alongside a statistically significant three-day abnormal return of **-1.5%** around the expiration date. The pattern reads as insiders finally selling into a market that hadn't yet priced in the coming increase in tradable float. The effect was substantially larger for venture-capital-backed companies than for non-VC-backed ones, consistent with VC funds facing their own pressure to return capital to their limited partners rather than hold indefinitely.

The 2025 cohort offers an unusually clean read on this, because in all three cases the lockup came off at an earnings filing rather than on the calendar date. CoreWeave's Q2 10-Q was filed **August 13, 2025** and the lockup terminated the next day. Circle's Q2 10-Q was filed **August 12** and its early-release tranche freed shares the day after. Figma's Q2 10-Q was filed **September 3** and its price-condition release came at the open on **September 5**. Measuring forward from each of those filing dates:

| Company | Filing that released the lockup | 1 month | 2 months | 3 months |
|---|---|---|---|---|
| [CoreWeave](/stocks/CRWV) | Q2 2025 10-Q, filed Aug 13, 2025 | **-24.35%** | +14.46% | +13.54% |
| [Circle](/stocks/CRCL) | Q2 2025 10-Q, filed Aug 12, 2025 | **-29.81%** | -10.68% | -22.20% |
| [Figma](/stocks/FIG) | Q2 2025 10-Q, filed Sep 3, 2025 | **-22.34%** | -21.68% | -49.64% |

All three fell between **22%** and **30%** in the month that followed. Two of the three were still down at three months; CoreWeave recovered and finished the window higher. Three companies is not a base rate, and the filing date is not identical to the release date — it precedes it by one to two days in each case, and an earnings release moves a stock on its own merits regardless of what a lockup does. But it is worth noting how much larger these moves are than the **-1.5%** three-day average the academic literature describes, and that all three point the same direction.

Later studies across different markets and time periods have consistently found the same directional pattern — a volume spike and a modest average negative return — even though the expiration date is public information known months in advance. That persistence is itself the interesting part: a fully efficient market should have priced the coming supply increase in before it happened. The fact that researchers keep finding a measurable reaction anyway suggests the date matters more to how the market actually behaves than pure efficiency theory would predict. None of this is a guarantee for any individual stock — averages describe a tendency across many companies, not a forecast for one — but it's the reason lockup expiration dates draw disproportionate attention from short sellers and options traders in the weeks beforehand.

---

## How to Track a Lockup Expiration Date

Tracking a specific company's lockup expiration takes three steps, and the second one is the part investors most often get wrong.

## Step 1: Find the Lockup Section in the S-1 or 424B4

Search the company's final prospectus (Form 424B4) rather than the original S-1 for the exact day count. Pull up "Shares Eligible for Future Sale" for the headline terms and "Underwriting" for the full agreement language, including any early-release discretion. This is a filing-text lookup rather than a financial-data lookup — [how GeminIQ compares to BamSEC](/competitor-comparison/bamsec) covers where reading filing language ends and working with as-filed financial data begins.

## Step 2: Calculate the Expiration Date

Anchor the day count to the prospectus date, not the S-1 filing date. A "180 days after the date of this prospectus" clause means 180 days from when the offering actually priced — typically the same day the 424B4 is filed — not 180 days from whenever the company first filed its S-1 months earlier.

## Step 3: Watch for Form 4 Filings Around the Date

Once the calculated date approaches, watch the company's Form 4 filing activity directly. A cluster of S-coded sales landing right at or after the expiration date confirms insiders are exercising the freedom the lockup just released; an early press release announcing a waiver for named executives is a signal the actual date has moved up.

---

## Tracking the Aftermath on GeminIQ

The lockup agreement itself is contractual language in the S-1, not XBRL-tagged financial data, so it isn't something GeminIQ extracts directly. What GeminIQ tracks is everything that happens once the lockup does its work. GeminIQ's [Insider Transactions](/features#insider-transactions) feature pulls every Form 4 filing as it lands, which is exactly the data that confirms whether the academic pattern played out for a specific company — a spike in S-coded sales clustered right around the calculated expiration date. [Price Variance](/features#price-variance) shows the stock's actual post-filing price behavior over the same window, letting you compare what happened to this specific company against the broad, historical average researchers have documented, rather than assuming the average applies here by default.

---

## Frequently Asked Questions

### Is a lockup period an SEC rule?

No. It's a private contract between the company's underwriters and its pre-IPO shareholders, disclosed in the S-1 but not required or set by SEC regulation. Rule 144 and Rule 701 are the separate federal rules that govern when restricted shares become legally eligible for resale, and the contractual lockup is usually the tighter constraint of the two.

### How long does an IPO lockup usually last?

180 days is the most common duration, though 90-day lockups and tiered structures — partial releases at 90 days, an intermediate point, and the full 180-day mark — both appear regularly. The exact terms and share counts are disclosed in the S-1's "Shares Eligible for Future Sale" section.

### Can a lockup period be extended?

Yes. Many agreements automatically extend if the company releases earnings or discloses material news within a defined window — commonly the final 15 to 17 days — before the scheduled expiration, pushing the date out to roughly three business days after that disclosure.

### Does the stock always fall when a lockup expires?

No individual outcome is guaranteed. But academic research going back to a 1,948-agreement study published in the *Journal of Finance* has consistently found an average negative abnormal return and a sustained increase in trading volume around lockup expiration dates across many companies, even though the date is public information well in advance.

The date is never a secret. What most investors miss is that it's rarely fixed either — and reading the S-1's actual lockup language is the only way to know which date, extended or not, actually applies.

---

## Related Reading

- [Reading an S-1: The Complete Guide](/blog/what-is-s-1) — the full walkthrough of every S-1 section, including the other four financial metrics worth checking alongside the lockup.
- [Form 4 Transaction Codes: The Complete List](/blog/form-4-transaction-code-list) — how to read the S-coded sales that show up once a lockup lifts.
- [Insider Cluster Buying: What It Signals](/blog/insider-cluster-buying-signal-data) — the framework for reading insider transaction patterns once you're past the lockup window.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=s-1-lockup-expiration-filings)**

<sup>Sources: Field, Laura Casares and Gordon Hanka, "The Expiration of IPO Share Lockups," *Journal of Finance*, Vol. 56, No. 2 (2001). Lockup terms and release dates for the three 2025 listings are drawn from each company's prospectus and subsequent public announcements; CoreWeave's earnings-triggered termination and Circle's early-release tranche are documented in [contemporaneous reporting on 2025 IPO lockup expirations](https://quantabundancia.com/articles/ai-ipo-lockup-expirations), and Figma's price-condition early release and extended lockup structure in [Sherwood News, September 2025](https://sherwood.news/markets/figma-plunges-after-first-earnings-since-ipo-lock-up-expires-some-shareholders/). Verify any specific date against the company's own 424B4 and 8-K filings on [SEC EDGAR](https://www.sec.gov/) before acting on it. Post-filing returns for CoreWeave (CIK0001769628), Circle (CIK0001876042) and Figma (CIK0001579878) are GeminIQ's own, measured cumulatively from each company's Q2 2025 10-Q filed date at one, two and three months; n=3 and no base rate is claimed from it.</sup>

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Schedule 13D vs. 13G: Activist or Passive Stake?
source: https://www.geminiq.com/blog/schedule-13d-vs-13g-explained

### Schedule 13D vs. 13G: Activist or Passive Stake?
Schedule 13D and Schedule 13G both disclose an investor crossing 5% ownership of a public company, but only Schedule 13D signals intent to influence control. This guide covers the filing deadlines, the intent test, and how to read a real cover page correctly.

Schedule 13D and Schedule 13G exist because of the same trigger: cross **5%** beneficial ownership of a public company's voting stock, and the SEC requires you to tell the market. Financial media covers every one of these filings the same way — "a fund just disclosed a stake" — as if the form itself were incidental. It isn't. One of these filings tells you an investor may be coming for the board. The other tells you the opposite: that the investor has no such intention at all. Standard financial media doesn't read the footnotes that separate the two, and the difference changes what the filing actually means for a stock you own.

This guide covers what each form requires, the deadlines that govern both the initial filing and any amendment, the intent test that decides which one applies, and how to read a real cover page without falling into the traps that catch most first-time readers.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=schedule-13d-vs-13g-explained)**

---

## Table of Contents

- [What Is Schedule 13D?](#what-is-schedule-13d)
- [What Is Schedule 13G?](#what-is-schedule-13g)
- [13D vs. 13G Filing Deadlines: 5 Business Days vs. 45 Days](#13d-vs-13g-filing-deadlines-5-business-days-vs-45-days)
- [The Intent Test: When a Passive Filer Becomes an Activist](#the-intent-test-when-a-passive-filer-becomes-an-activist)
- [13F vs. 13G: Two Different Filings, Constantly Confused](#13f-vs-13g-two-different-filings-constantly-confused)
- [Reading the Cover Page: A Real 13D and 13G on the Same Company](#reading-the-cover-page-a-real-13d-and-13g-on-the-same-company)
- [Why This Distinction Matters Beyond the Filing Itself](#why-this-distinction-matters-beyond-the-filing-itself)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is Schedule 13D?

Schedule 13D is the disclosure required of any investor — individual or institutional — who beneficially owns more than **5%** of a public company's outstanding voting shares and has an intent to influence or control the company. It requires the filer to identify itself, disclose the source and amount of funds used for the purchase, and, in Item 4, spell out its plans: board representation, a merger or other extraordinary transaction, a change in capitalization, or any other action that would affect control of the issuer.

Item 4 is where an activist campaign announces itself in a public, filed record. A fund that wants board seats, a strategic review, or a sale of the company states that plan directly in Item 4. That's why a new 13D on a closely watched name draws immediate attention, and why markets often react to the filing itself, not to anything the company has said.

## What Is Schedule 13G?

Schedule 13G is the shorter, less disclosure-heavy alternative available to an investor who has crossed the same **5%** threshold but holds the position passively, with no intent to influence or control the company. There is no Item 4 in a 13G. In its place is a certification: the filer attests that the securities were not acquired, and are not held, with any purpose or effect of changing or influencing control of the issuer.

Eligibility to file the short form depends on which category the filer falls into. Qualified institutional investors — a defined set of regulated entities such as registered investment advisers, banks, and insurance companies — and exempt investors who held their position before the issuer registered under the Exchange Act generally qualify. So do passive investors more broadly, provided they genuinely hold without control intent. The form itself is short: identity, citizenship or place of organization, share counts, and the percentage of the class owned. What it does not contain is any statement of what the investor plans to do next, because by definition it isn't planning to do anything.

## 13D vs. 13G Filing Deadlines: 5 Business Days vs. 45 Days

The two forms diverge sharply on timing, and the SEC's 2023 amendments to the beneficial ownership reporting rules compressed nearly every window in the regime.

A Schedule 13D must now be filed within **5 business days** of crossing the threshold — down from the 10 calendar days that applied before the 2023 amendments took effect. Once filed, any material change to the information disclosed — a change in the size of the position, a shift in the stated purpose, a new plan disclosed in Item 4 — requires an amendment within **2 business days**, replacing the older, vaguer "promptly" standard that gave filers more room to delay.

Schedule 13G runs on a slower clock, and the clock depends on the filer category. Qualified institutional investors and exempt investors generally file within **45 days** after the calendar quarter in which they first exceeded 5% ownership. Other passive investors — those that don't qualify under either category — must file within **5 business days** of crossing the threshold, the same initial window as a 13D, even though the form itself carries none of a 13D's disclosure burden. Amendments to a 13G were historically an annual exercise; under the 2023 reforms, a material change now triggers an amendment within **45 days** after the calendar quarter in which the change occurred — the same quarterly cadence that governs the initial QII filing.

One more procedural shift is worth knowing. Since December 18, 2024, every Schedule 13D and 13G — the cover page, the reporting-person tables, the checkboxes — must be submitted in a structured, machine-readable format rather than free-form text and HTML. The forms themselves haven't changed. What changed is that the SEC now requires the underlying data to arrive as data, not prose a reader has to parse by eye.

## The Intent Test: When a Passive Filer Becomes an Activist

Everything about which form applies comes down to one question: does the investor have a purpose or effect of changing or influencing control of the company? Ownership percentage plays no role in that test — a 13G filer can hold well above **5%** indefinitely, provided the intent genuinely stays passive.

The test isn't static. An investor that files Schedule 13G because it started out passive, and later decides it wants board representation or a strategic change, must convert to Schedule 13D once that intent forms. It cannot keep filing the short form while quietly working toward an outcome the short form's own certification disclaims. That conversion — a 13G superseded by a fresh 13D from the same filer — is one of the clearest signals in the entire beneficial ownership record: a holder that told the market it was passive is now telling the market it isn't.

The test also extends beyond any single filer. Investors who coordinate — through a joint engagement letter, a shared voting commitment, or an agreement to nominate directors together — can be deemed a "group" under Section 13(d), even if no individual member crosses 5% alone. If the group's combined holdings exceed the threshold and any member has a control purpose, the entire group must file on Schedule 13D, not 13G — even if every individual member's own position looks entirely passive.

## 13F vs. 13G: Two Different Filings, Constantly Confused

Once the 13D and 13G distinction is clear, one more pairing is worth separating out, because the two get confused constantly and have almost nothing to do with each other. A 13F and a 13G share a number and a regulator. That is the entire overlap.

Schedule 13G is a beneficial ownership filing: one investor, one issuer, one stake that crossed 5%, with a certification about intent attached. Form 13F is a portfolio report: an institutional investment manager disclosing what it holds, quarter by quarter, across every position at once. A 13G answers "who owns a big piece of this company, and are they going to do anything about it." A 13F answers "what does this manager own." Neither answers the other's question.

| | Form 13F | Schedule 13G |
|---|---|---|
| What it reports | Every reportable position a manager holds, across issuers | One investor's single stake in one issuer |
| Who files it | Institutional investment managers, reporting their own portfolios | Qualified institutional investors, exempt investors, and passive investors that cross 5% of one company's voting stock |
| What triggers it | The calendar quarter — it's a periodic report, not an event | Crossing **5%** beneficial ownership of a specific issuer |
| What it says about intent | Nothing. There is no intent disclosure in a 13F | An explicit certification that the position is not held with any purpose or effect of changing or influencing control |
| What it's useful for | Total institutional ownership in a stock, and how it's trending | Name-level disclosure of one holder's size and posture |

The practical consequence: a manager can appear in a stock's 13F ownership data holding a position far below 5% and never file a 13G at all, and a 13G filer crossing 5% of a small issuer may barely register in that same aggregate. The two data sets are built from different populations and answer to different rules. Treating a 13F position as a beneficial ownership disclosure — or reading a 13G as evidence about institutional flows — is the most common way this gets misread.

## Reading the Cover Page: A Real 13D and 13G on the Same Company

Once you know which form applies, the next challenge is reading what's actually on it. The cover page of both forms shares a structure, and that structure is exactly where a reader who doesn't know what to look for gets misled. Every filing carries a CUSIP number — the identifier tied to one specific class of security — and a set of reporting-person rows disclosing sole voting power, shared voting power, sole dispositive power, shared dispositive power, the aggregate amount beneficially owned, and the percent of class that amount represents.

Two traps live in that structure. The first: the percentage on the cover page is percent of class, not percent of the company. If an issuer has more than one class of stock outstanding, that number applies only to the class named by the CUSIP on that page. The second, more common trap: a single filing frequently lists multiple reporting persons — a fund, its investment manager, its general partner, and the individual who controls the general partner — and each of those rows restates the same underlying shares. Adding the percentages or share counts across rows within one filing doesn't reveal a bigger position; it just double-, triple-, or quadruple-counts the same stake. The number that matters is the group's single aggregate figure, not the sum of the rows beneath it.

[Empery Digital Inc. (EMPD)](/stocks/EMPD) had both filings live on SEC EDGAR at overlapping points, which makes it a clean pair to read side by side.

| Filing | Reporting persons | Event date | Shares | % of class | Voting power | Stated intent |
|---|---|---|---|---|---|---|
| Schedule 13D/A (Amendment No. 2) | ATG Capital Opportunities Fund LP; ATG Capital Management LP; ATG Capital Management GP LLC; Gabriel Gliksberg | February 3, 2026 | **4,500,000** | **12.3%** | Shared voting and shared dispositive power, identical across all four rows | Control intent — a later soliciting filing from the same group named nine director candidates for the board |
| Schedule 13G/A (Amendment No. 1) | Sabby Volatility Warrant Master Fund, Ltd.; Sabby Management, LLC; Hal Mintz | December 31, 2025 | **479,428** | **1.3%** | Shared voting and shared dispositive power | Passive — certified as held without any purpose or effect of changing or influencing control |

The 13D/A row is the second trap in its most literal form: four reporting persons, one position, stated four times. Adding those four rows together would quadruple a position that only exists once. The cover page's Source of Funds field adds a detail most readers skip past: ATG Capital Opportunities Fund LP is coded "WC" for working capital, while the other three reporting persons are coded "AF," reflecting that they hold no shares directly and derive their beneficial ownership entirely through the fund. Item 3 put a number on the position: an aggregate purchase price of approximately **$21,578,487**, including brokerage commissions. The soliciting filing that followed named nine director candidates, including Gliksberg himself, for election to Empery Digital's board — a disclosed stake converting into an active board contest, in the public record.

Same issuer, same 5% disclosure regime, same cover-page structure — and two filings that mean nothing alike. One is an opening move in a board contest. The other says, in a filed and certified statement, that nothing is coming.

## Why This Distinction Matters Beyond the Filing Itself

A 13G-to-13D conversion, or a fresh 13D on a name that had none, is a real signal precisely because it's a filed, dated, legally certified statement of intent — not a headline built on speculation about what a large holder might be thinking. A 13G tells you almost nothing about near-term stock behavior; it's a passive holder disclosing size, not conviction. A 13D is the market's earliest formal warning that a specific investor plans to act.

It's worth separating this from what GeminIQ's [Institutional Ownership](/features#institutional-ownership) feature actually shows. That feature aggregates quarterly Form 13F data across every reporting manager holding a stock — a picture of total institutional ownership and how it's trending, not a name-level disclosure of any single holder's intent. The two data sources answer different questions: 13F tells you what the institutional base as a whole is doing; 13D and 13G tell you what one specific holder, crossing one specific threshold, says it plans to do about it. For more on how the 13F side of that picture works, see our guide on [how to read a 13F filing](/blog/how-to-read-13f-filing). For where 13D and 13G sit within the SEC's full filing regime — alongside the 10-K, 10-Q, 8-K, and DEF 14A — see our [complete guide to SEC filing types for investors](/blog/sec-filings-guide), and for how document-retrieval tools handle beneficial ownership filings specifically, our [comparison with BamSEC](/competitor-comparison/bamsec).

The next time a headline says a fund "just disclosed a stake," check which form triggered it before you read another word of the coverage — that single detail tells you whether to keep reading or move on.

## Frequently Asked Questions

### What is the difference between Schedule 13D and Schedule 13G?

Both disclose that an investor has crossed **5%** beneficial ownership of a public company's voting stock. Schedule 13D is filed by an investor with an intent to influence or control the company and requires a stated purpose in Item 4. Schedule 13G is filed by a passive investor — including qualified institutional and exempt investors — who certifies it holds no such intent.

### What is the difference between a 13F and a 13G?

They share a number and nothing else. Form 13F is a quarterly portfolio report: an institutional investment manager disclosing every reportable position it holds, across issuers. Schedule 13G is a beneficial ownership filing: one investor disclosing one stake in one company after crossing **5%** of that company's voting stock, with a certification that the position is held without any purpose or effect of changing or influencing control. A 13F tells you what a manager owns. A 13G tells you who owns a large piece of one issuer, and whether they intend to act on it.

### How quickly must an investor file a Schedule 13D after crossing 5%?

Under the SEC's 2023 amendments, a Schedule 13D is due within **5 business days** of crossing the threshold, down from the previous 10-calendar-day window. Any material change afterward requires an amendment within **2 business days**.

### Can a Schedule 13G convert into a Schedule 13D?

Yes. If a passive filer's intent changes — for example, it decides to seek board representation — it must convert to Schedule 13D, superseding its earlier 13G. That conversion is one of the strongest signals available in the beneficial ownership record, because it's a filed statement that a previously passive holder's posture has changed.

### Is a 13G-to-13D conversion a signal worth acting on?

It is a signal about intent, not a forecast of price. What the conversion establishes is specific and legally certified: a holder that previously attested it had no purpose of influencing control has now filed a document stating a plan, in Item 4, that it can be held to. Read Item 4 before drawing any conclusion — board representation, a strategic review, and a proposed sale of the company are all disclosed in the same field and are not the same event.

### Do multiple reporting persons on the same 13D each represent a separate 5% stake?

No. A single filing often lists several reporting persons — a fund, its manager, its general partner, and the individual controlling it — who each report the same underlying shares because they may each be deemed a beneficial owner. Their percentages should not be added together; the figure that matters is the group's single aggregate position.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=schedule-13d-vs-13g-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

The Schedule 13D and 13G examples referenced in this article are Empery Digital Inc.'s beneficial ownership filings on SEC EDGAR (CIK 0001829794), including the Schedule 13D/A (Amendment No. 2) filed by ATG Capital Opportunities Fund LP and affiliated reporting persons and the Schedule 13G/A (Amendment No. 1) filed by Sabby Volatility Warrant Master Fund, Ltd. and affiliated reporting persons. All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1829794/000092189526000219/xslSCHEDULE_13D_X01/primary_doc.xml).

---

## Blog: SEC Comment Letters: Reading UPLOAD and CORRESP
source: https://www.geminiq.com/blog/sec-comment-letters-upload-corresp

### SEC Comment Letters: Reading UPLOAD and CORRESP
SEC comment letters are the correspondence the SEC's Division of Corporation Finance sends when it reviews a company's filing and finds something worth questioning, filed publicly on EDGAR under the form types UPLOAD for the SEC's letter and CORRESP for the company's response. This guide covers what triggers a review, what the SEC's staff comments on most, how to read a comment letter thread, and how to find any company's correspondence history on EDGAR.

A public company's disclosure was flagged as inadequate by the regulator that oversees it, in writing, and the flag sat in the public record for months before anything else drew attention to it. That is not a hypothetical. It is the routine outcome of the SEC's filing review process, and the correspondence that documents it — the comment letter and the company's response — sits on EDGAR under two form types almost nobody outside compliance departments ever searches: UPLOAD and CORRESP.

Every U.S. public company gets its periodic filings reviewed by the SEC's Division of Corporation Finance at least once every three years, a requirement written into Section 408 of the Sarbanes-Oxley Act. When that review turns up something worth questioning, the SEC sends a comment letter — filed as UPLOAD — and the company responds — filed as CORRESP. Both become part of the public record, typically weeks or months before any earnings call or press release mentions the underlying issue, if one ever does. Neither form appears alongside the more familiar filings — our [guide to SEC filing types](/blog/sec-filings-guide) covers where the 10-K, 10-Q, 8-K, and DEF 14A fit; this correspondence sits alongside all of them, generated by the review process those filings trigger. This guide covers what triggers a review, what the SEC's staff comments on most often, how to read a comment letter thread, and how to find any company's correspondence history directly on EDGAR.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-comment-letters-upload-corresp)**

## Table of Contents

- [What Are UPLOAD and CORRESP Filings?](#what-are-upload-and-corresp-filings)
- [Why the SEC Sends a Comment Letter](#why-the-sec-sends-a-comment-letter)
- [What the SEC Comments on Most](#what-the-sec-comments-on-most)
- [Reading a Comment Letter Thread](#reading-a-comment-letter-thread)
- [Step 1: Open EDGAR Full-Text Search](#step-1-open-edgar-full-text-search)
- [Step 2: Filter by Filing Review Correspondence](#step-2-filter-by-filing-review-correspondence)
- [Step 3: Add the Company Name or Ticker](#step-3-add-the-company-name-or-ticker)
- [Step 4: Read the UPLOAD Before the CORRESP](#step-4-read-the-upload-before-the-corresp)
- [Why Comment Letters Rarely Show Up in the Data You're Using](#why-comment-letters-rarely-show-up-in-the-data-youre-using)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Are UPLOAD and CORRESP Filings?

**UPLOAD** and **CORRESP** are the two EDGAR form types that carry the SEC's filing-review correspondence. UPLOAD is the letter the SEC staff sends to a company — the actual comment letter. CORRESP is the company's written response. Neither form type is used for anything else. If a filing shows up under one of these two codes, it is part of a review correspondence thread, full stop.

The correspondence is not published in real time. The SEC releases it on EDGAR no earlier than **20 business days** after a registration statement is declared effective or a periodic-report review is completed. That is a rule the agency has tightened over time — before 2012, the standard release window was 45 days. That lag means a comment letter thread you find on EDGAR today reflects a review the SEC finished weeks or months earlier, not a live back-and-forth. It is a historical record of a completed review, not a real-time regulatory feed.

---

## Why the SEC Sends a Comment Letter

A company named in SEC correspondence looks, to most investors skimming a filing feed, like a company the regulator caught doing something wrong. Most of the time that reading is off: the letter is simply the paper trail from a periodic review every reporting company sits through on a fixed schedule, whether or not the filings raise any real concern. Section 408 of the Sarbanes-Oxley Act requires the SEC's Division of Corporation Finance to review every reporting company's periodic filings at least once every **three years**. Many companies are reviewed more often than that baseline. The SEC does not publish the exact criteria it uses to prioritize which filings get the closest look. Section 408 itself does point to factors Congress directed the agency to weigh: companies with material restatements of financial results, companies experiencing significant stock price volatility relative to peers, and companies with large market capitalization, among others. On top of the scheduled three-year cycle, the staff also runs targeted reviews triggered by something specific — an 8-K disclosure, a tip, a pattern noticed across an industry.

Not every review produces a comment letter. A company whose filings raise no questions completes its review with nothing new on EDGAR to show for it — a silent, clean review looks identical to no review at all from the outside. A comment letter only appears when the staff believes a company's disclosure or accounting can be meaningfully improved. Even then, most threads resolve through correspondence alone: the company explains, the staff accepts the explanation or asks a follow-up, and no restatement or amendment ever becomes necessary. When a review does conclude that a restatement is warranted, that is the exact chain of events that produces a [10-K/A or 10-Q/A](/blog/amended-sec-filings-10-k-a-explained), often alongside an [Item 4.02 8-K](/blog/how-to-find-restatements-in-filings) announcing the non-reliance determination first. The comment letter is where that chain starts.

---

## What the SEC Comments on Most

Non-GAAP financial measures and MD&A disclosures have been the two most frequent subjects of SEC staff comments for years running, and both categories actually grew in the twelve months ending June 30, 2025 even as the SEC's total comment letter volume declined. Revenue recognition, segment reporting, and goodwill and intangible asset impairment round out the perennial list.

The non-GAAP issue is almost always the same underlying complaint: a company gives a non-GAAP figure more visual or narrative prominence than the comparable GAAP measure, or reconciles it to something other than the GAAP figure Regulation G actually requires. In a 2025 comment letter, the SEC flagged [Sysco](/stocks/SYY) for disclosing the year-over-year change in adjusted EBITDA without disclosing the change in the comparable GAAP measure with equal prominence — a textbook Regulation G issue. Sysco's response committed to displaying the change in net earnings ahead of the change in EBITDA in future filings, giving the GAAP figure at least equal billing.

The MD&A issue usually comes down to a simpler test: can a reader reconstruct what drove a material change in the business from the MD&A discussion alone, in specific terms, without guessing? A March 2025 comment letter to Birkenstock Holding plc flagged exactly this gap — a key performance indicator introduced in the MD&A without the period-to-period comparison needed to show what actually changed and why.

Two categories are showing up in 2026 review letters that barely registered as recently as 2024: quantification of tariff impact on cost of goods sold and margin, and the adequacy of AI-related disclosures. Both are drawing staff attention in risk factors and in any operational claims a company makes about AI in its MD&A or investor materials. Companies making forward-looking claims about AI capability without corresponding risk disclosure are a live area of staff attention heading into the 2026 reporting season.

| Subject | What the staff typically challenges | Example in the public record |
|---|---|---|
| Non-GAAP financial measures | A non-GAAP figure given more prominence than the comparable GAAP measure, or reconciled to something other than what Regulation G requires | 2025 letter to Sysco on the change in adjusted EBITDA disclosed without the change in the comparable GAAP measure |
| MD&A | Whether a reader can reconstruct what drove a material change from the discussion alone, in specific terms | March 2025 letter to Birkenstock on a KPI introduced without the period-to-period comparison |
| Revenue recognition | — | — |
| Segment reporting | — | — |
| Goodwill and intangible asset impairment | — | — |
| Tariff impact (new in 2026 letters) | Quantification of the effect on cost of goods sold and margin | — |
| AI-related disclosure (new in 2026 letters) | Operational or forward-looking AI claims made without corresponding risk disclosure | — |

---

## Reading a Comment Letter Thread

A comment letter is not free-flowing prose. The SEC staff numbers each comment individually — Comment 1, Comment 2, and so on — and each one asks a specific, narrow question or requests a specific change. A company's CORRESP response typically restates each numbered comment before answering it directly underneath, which makes a thread easy to follow even when it runs for several rounds.

Responding to a numbered comment doesn't mean conceding a mistake, and most companies don't. The response itself falls into one of three postures. The company can agree and commit to a specific change in future filings — the most common outcome, and the one to watch for a stated timeline. The company can explain why the existing disclosure already satisfies the requirement, sometimes closing the issue on the first response. Or, less often, the company can propose a middle-ground revision that partially addresses the comment. A thread can run multiple rounds if the staff isn't satisfied with the first response, and every round is filed and public, which means the full negotiation is available to read, not just the conclusion.

| Stage | Form type | Filed by | What it contains |
|---|---|---|---|
| Filing review | — | — | No filing at all. A review that raises no questions leaves nothing on EDGAR |
| Comment letter | UPLOAD | SEC Division of Corporation Finance | Individually numbered comments, each asking a narrow question or requesting a specific change |
| Company response | CORRESP | The company | Each numbered comment restated, then answered — agree and commit to a change, explain why the existing disclosure suffices, or propose a middle ground |
| Further rounds | UPLOAD, then CORRESP | Alternating | Follow-up comments when the staff isn't satisfied with the first response, each round filed and public |
| Outcome | — | — | Most threads close through correspondence alone; a minority lead to an amendment |

The whole thread becomes public together, no earlier than **20 business days** after the review is completed.

None of this correspondence is confidential once released. Analysts, competitors, and short sellers read the same UPLOAD and CORRESP filings any retail investor can pull up. The market treats this correspondence as informative once it actually sees it — the problem is almost nobody looks until well after the fact.

---

Finding a company's comment letter history takes about the same effort as pulling up its 10-K, and requires nothing beyond EDGAR itself.

## Step 1: Open EDGAR Full-Text Search

Go to SEC EDGAR's Full-Text Search at sec.gov/edgar/search — the same tool used to search filing text across the entire system, not just periodic reports.

## Step 2: Filter by Filing Review Correspondence

Click "more search options" beneath the search box, then select "Filing review correspondence" from the "Filing category" dropdown. This narrows results to UPLOAD and CORRESP filings only, cutting out every other form type on EDGAR.

## Step 3: Add the Company Name or Ticker

Enter the company name or ticker to see that filer's complete correspondence history, or leave the field blank to browse the most recently released comment letters and responses across every company the SEC has completed a review of.

## Step 4: Read the UPLOAD Before the CORRESP

Open the earliest UPLOAD in the thread first. It states the staff's original comments in full, numbered, before any company response reframes them. Reading the response first means reading the company's framing of the issue before reading the issue as the regulator actually stated it.

---

## Why Comment Letters Rarely Show Up in the Data You're Using

A dashboard that surfaces every ratio and line item a filing discloses can look complete enough to also flag when a regulator has taken issue with those same numbers. It doesn't: comment letters do not show up in any financial data platform's metrics, GeminIQ included, and the reason is structural rather than a product gap. UPLOAD and CORRESP filings are plain-text correspondence — there is no XBRL tagging, no structured line items, nothing for an automated pipeline to extract into a comparable field across companies. The same [as-filed XBRL traceability](/features#financial-statements) that lets GeminIQ pull a clean, comparable figure from a 10-K's balance sheet has nothing to attach to in a letter that is, at its core, a written argument between a company and its regulator. That constraint applies to every platform built on structured filing data, at any price point — our [comparison with S&P Capital IQ](/competitor-comparison/sp-capital-iq) lays out what each side does and doesn't cover.

That does not make the correspondence less useful. It makes it a different kind of research, one that has to be read rather than queried. A comment letter thread is qualitative evidence: what the SEC questioned, how the company defended itself, and whether the company ultimately conceded the point. None of that reduces to a number a screener can filter on. The right way to use it is as a targeted check on a specific company already under research — pull the correspondence history alongside the Financial Statements for the periods the review actually covered, and read the two side by side. The filing shows what the company reported. The correspondence, when it exists, shows what the regulator questioned about it.

---

## Frequently Asked Questions

### Are SEC comment letters public?

Yes, but not immediately. The SEC releases the correspondence on EDGAR no earlier than **20 business days** after completing the review, which means a thread you find today documents a review that concluded weeks or months earlier — never an active, unresolved one.

### How often does the SEC review a company's filings?

At minimum once every **three years**, under Section 408 of the Sarbanes-Oxley Act. Companies with material restatements, unusual stock price volatility relative to peers, or other factors Congress specified in Section 408 tend to get reviewed more frequently than the statutory floor.

### Does every SEC review produce a comment letter?

No. A review that raises no questions ends with nothing new filed on EDGAR — from the outside, a clean review is indistinguishable from no review at all. A comment letter only appears when the staff believes a specific improvement is warranted.

### What happens if a company doesn't resolve a comment?

Most threads resolve through correspondence: the company explains its position or commits to a change in future filings, and the review closes. Escalation beyond that — an outright filing amendment or further action — happens, but it is the less common outcome, not the default one. The number of rounds a thread takes to close is itself worth watching on any company's correspondence history: a single round means the staff accepted the company's first answer, and a thread stretching to two or three rounds is usually where a closer read of the underlying filing pays off.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Sources: The 20-business-day release window, and the 45-day window it replaced effective January 1, 2012, are stated in the SEC Division of Corporation Finance announcement on [EDGAR correspondence release](https://www.sec.gov/divisions/corpfin/cfannouncements/edgarcorrespondence.htm). Comment letter volume and topic ranking for the twelve months ended June 30, 2025 — total volume down, with MD&A and non-GAAP each up more than 10% as a share of registrants commented on — are from EY's [Highlights of trends in 2025 SEC staff comment letters](https://www.ey.com/content/dam/ey-unified-site/ey-com/en-us/technical/accountinglink/documents/ey-secru28204-251us-09-11-2025.pdf). Tariff quantification and AI-disclosure adequacy as emerging 2026 comment areas are documented in [SEC Comment Letter Trends: Seven Issues and Three New Focus Areas](https://www.finrep.ai/blog/sec-comment-letter-trends-seven-issues-and-three-new-focus-areas), covering reviews through March 31, 2026.</sup>

---

## Blog: SEC Filing Analysis Tools Compared: 2026 Guide
source: https://www.geminiq.com/blog/sec-filing-analysis-tools-compared

### SEC Filing Analysis Tools Compared: 2026 Guide
SEC filing analysis tools fall into four functional categories: document search, normalized data platforms, as-filed source data, and stock screening. Most of the confusion in comparing them comes from treating tools in different categories as substitutes.

Every product in this category calls itself a research platform, and almost none of them are solving the same problem. Some search documents. Some license standardized fundamentals and layer a score or a model on top. Some screen a universe by ratio. One extracts what companies actually filed and stops there. The comparisons that read as contradictory ("Platform A is better than Platform B," "no, B is better") are usually two people evaluating tools built for different jobs against the same checklist.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filing-analysis-tools-compared)**

Sorting by function instead of by brand removes most of the confusion. Four categories cover essentially the whole market: document search, normalized and licensed data, as-filed source data, and stock screening. A tool can straddle more than one (TIKR both licenses fundamentals and screens on them), but almost every platform has one category it was actually built to win.

## Table of Contents

- [The 24 Platforms at a Glance](#the-24-platforms-at-a-glance)
- [Document Search: AlphaSense, BamSEC, Quartr, and Seeking Alpha](#document-search-alphasense-bamsec-quartr-and-seeking-alpha)
- [Normalized and Licensed Fundamentals Data](#normalized-and-licensed-fundamentals-data)
- [As-Filed SEC Data](#as-filed-sec-data)
- [Stock Screening](#stock-screening)
- [Choosing the Right Category for the Job](#choosing-the-right-category-for-the-job)
- [Frequently Asked Questions](#frequently-asked-questions)

## The 24 Platforms at a Glance

The categories below are easier to hold in view side by side. "What the number on screen is" is the question that actually separates these products; where a platform has not published or the sections below do not establish where its fundamentals originate, the last column says so rather than guessing.

| Platform | Category | What the number on screen is | Source of fundamentals |
|---|---|---|---|
| [AlphaSense](/blog/alphasense-alternative-sec-data) | Document search | A cited passage, not a typed fact | Not stated here; structured data sold separately |
| [BamSEC](/competitor-comparison/bamsec) | Document search | The figure as it sits in the filing document | SEC EDGAR filings |
| [Quartr](/blog/quartr-alternative-sec-filing-data) | Document search | Spoken and IR language, not a computed value | Not stated here |
| [Seeking Alpha](/blog/seeking-alpha-alternative-filing-data) | Document search / publishing | A contributor's figure inside an argument | Not stated here |
| [Bloomberg Terminal](/competitor-comparison/bloomberg-terminal) | Institutional terminal | A standardized figure mapped for cross-market comparability | Not stated here |
| [S&P Capital IQ](/competitor-comparison/sp-capital-iq) | Institutional terminal | A standardized figure in S&P's own template | Not stated here |
| [FactSet](/blog/factset-alternative-sec-filing-data) | Institutional terminal | A standardized figure reconciled across sources | Not stated here |
| [TIKR](/blog/tikr-alternative-sec-data) | Multi-asset platform + screening | A licensed standardized figure | S&P Capital IQ |
| [Koyfin](/competitor-comparison/koyfin) | Multi-asset platform | A licensed standardized figure | S&P Capital IQ |
| [YCharts](/competitor-comparison/ycharts) | Advisor-workflow platform | A licensed standardized figure | Licensed dataset; provider not stated here |
| [Fiscal.ai](/competitor-comparison/fiscal-ai) | AI research assistant | An AI answer citing a standardized figure | S&P Global Market Intelligence |
| [Morningstar](/blog/morningstar-alternative-sec-filing-data) | Scoring and rating layer | A star rating built on an analyst fair value estimate | Not stated here |
| [GuruFocus](/competitor-comparison/gurufocus) | Scoring and rating layer | A GF Score on top of licensed fundamentals | Morningstar-licensed fundamentals |
| [Simply Wall St](/blog/simply-wall-st-alternative-sec-data) | Scoring and rating layer | A Snowflake shape summarizing five inputs | Not stated here |
| [Value Line](/blog/value-line-alternative-sec-data) | Scoring and rating layer | A Timeliness Rank | Not stated here |
| [Zacks](/blog/zacks-alternative-sec-filing-data) | Scoring and rating layer | A Rank driven by estimate revisions | Not stated here |
| [Daloopa](/blog/daloopa-alternative-sec-data) | Model-building | A model-ready KPI with a source hyperlink | Filings, presentations, and transcripts |
| [Finbox](/competitor-comparison/finbox) | Model-building | A model output with consensus-estimate defaults | Standardized data; provider not stated here |
| [Wisesheets](/blog/wisesheets-alternative-sec-data) | Spreadsheet add-in | Whatever the spreadsheet function returns | Not stated here |
| [StockAnalysis.com](/blog/stockanalysis-com-alternative-filing-data) | Free and low-cost aggregator | A standardized figure on a fast page | S&P Global Market Intelligence and Fiscal.ai |
| [ROIC.ai](/competitor-comparison/roic-ai) | Free and low-cost aggregator | A processed figure at low or no cost | Not stated here |
| [Finviz](/blog/finviz-alternative-fundamental-data) | Screening | A single row of ratios | Not stated here |
| [Stock Rover](/blog/stock-rover-alternative-sec-data) | Screening | A computed metric from a large tier-gated library | Not stated here |
| GeminIQ | As-filed SEC data | The reported fact, with its XBRL tag still attached | SEC EDGAR 10-K and 10-Q filings |

## Document Search: AlphaSense, BamSEC, Quartr, and Seeking Alpha

These platforms answer "what has been said," not "what does the number equal." [AlphaSense](/blog/alphasense-alternative-sec-data) indexes more than **500 million** documents (filings, broker research, transcripts, news) and returns cited passages through Generative Search and Deep Research. After the 2024 Tegus acquisition it also carries a large expert-call transcript library. [BamSEC](/competitor-comparison/bamsec) is the filing-native member of this group: instead of indexing a corpus, it makes one company's 10-Ks, 10-Qs, and exhibits fast to move through, jumping straight to a section rather than scrolling a raw EDGAR document. The job is navigating the filing itself, which is why it sits here rather than with the data platforms below. [Quartr](/blog/quartr-alternative-sec-filing-data) covers the first-party side of the same problem: live earnings calls, transcripts, and IR material, which is where management's tone and word choice live and no filing ever will. [Seeking Alpha](/blog/seeking-alpha-alternative-filing-data) is different again: a publishing platform with data attached, where thousands of contributors produce more than **10,000** articles a month, which means every thesis on the site has a counter-thesis sitting next to it.

All four are retrieval tools. A search index ranks passages by relevance and returns the ones most likely to answer a query; it cannot rank fifteen thousand filers by a metric, because ranking requires the value to exist as a typed fact rather than as characters inside a paragraph. That is a structural boundary, not an execution gap. AlphaSense sells structured financial data and models as a separate add-on for exactly this reason.

## Normalized and Licensed Fundamentals Data

This is the largest and most crowded category, and nearly every platform in it starts from the same move: map each company's reported line items into a standardized, cross-company template. That makes comparison fast. It also means the number on screen answers "what is the standardized figure," not "what did the company file."

### Institutional Terminals: Bloomberg, S&P Capital IQ, and FactSet

[Bloomberg Terminal](/competitor-comparison/bloomberg-terminal) and [S&P Capital IQ](/competitor-comparison/sp-capital-iq) are the standard seats on a trading desk: global coverage, credit analytics, estimates, entity resolution across accounting regimes, none of which a filings-only product replicates. Neither publishes pricing; third-party procurement trackers commonly place a Bloomberg seat in five figures annually, and Capital IQ Pro is quote-only. [FactSet](/blog/factset-alternative-sec-filing-data) sits in the same tier, solving the same reconciliation problem for firms running multiple data sources that have to agree with each other.

### Broad Multi-Asset Platforms

[TIKR](/blog/tikr-alternative-sec-data) and [Koyfin](/competitor-comparison/koyfin) both license Capital IQ fundamentals underneath a broader research workspace. TIKR emphasizes global screening, valuation templates, and transcripts across **100,000+** stocks and **92** countries; Koyfin adds portfolio tools, macro dashboards, and client reporting, with paid tiers starting at **$39** a month. [YCharts](/competitor-comparison/ycharts) targets advisor and wealth-management workflows on the same kind of licensed dataset. [Fiscal.ai](/competitor-comparison/fiscal-ai) (the platform formerly known as FinChat) puts a citation-backed AI research assistant on top of S&P Global Market Intelligence data, which answers questions well but is only ever as accurate as what the AI is reading.

### Scoring, Rating, and Estimate Layers

[Morningstar](/blog/morningstar-alternative-sec-filing-data), [GuruFocus](/competitor-comparison/gurufocus), [Simply Wall St](/blog/simply-wall-st-alternative-sec-data), [Value Line](/blog/value-line-alternative-sec-data), and [Zacks](/blog/zacks-alternative-sec-filing-data) each compress fundamentals into a single output: a star rating, a GF Score, a Snowflake shape, a Timeliness Rank, a consensus-revision Rank. Every one of them is a real, useful filter, and every one of them is a conclusion rather than a measurement. Morningstar's star rating runs on an analyst's fair value estimate and an assumed cost of capital that appears in no filing. GuruFocus stacks a proprietary score on top of Morningstar-licensed fundamentals. Zacks Rank tracks estimate revisions, which is a different clock entirely from what a business actually earned. None of the five inputs behind these systems is purely a number the company reported.

### Model-Building and Spreadsheet Tools

[Daloopa](/blog/daloopa-alternative-sec-data), [Finbox](/competitor-comparison/finbox), and [Wisesheets](/blog/wisesheets-alternative-sec-data) solve the "get the data into my model" problem rather than the "what does the filing say" problem. Daloopa extracts model-ready KPIs from filings, presentations, and transcripts with source hyperlinks and better than **99%** claimed accuracy across roughly **6,000** tickers. Finbox prebuilds DCF, dividend discount, and comparable-company models on standardized data with consensus-estimate defaults, starting around **$10** a month. Wisesheets pulls fundamentals into Excel or Google Sheets through a spreadsheet function. All three are genuinely fast. None of them changes what data sits underneath the formula.

### Free and Low-Cost Aggregators: StockAnalysis.com and ROIC.ai

[StockAnalysis.com](/blog/stockanalysis-com-alternative-filing-data) is the standout here, with clean, fast pages, minimal advertising, coverage past **130,000** symbols, and unusually candid documentation about its own architecture. Its data-sources page names S&P Global Market Intelligence and Fiscal.ai as providers and tells users to confirm critical figures against the original filing before acting on them. Almost nobody follows that instruction, because doing it by hand takes roughly fifteen minutes per figure.

[ROIC.ai](/competitor-comparison/roic-ai) occupies the same slot from the other direction, aimed at investors who want statements and ratios without a subscription decision attached to the first look. The category economics hold either way: what a low-cost aggregator displays is a processed figure, and the price is low partly because the processing was done once, upstream, for everybody.

## As-Filed SEC Data

This category has exactly one kind of entrant: a platform that extracts directly from SEC EDGAR and stops there. GeminIQ pulls 10-K and 10-Q data straight from the filing, preserves each company's own reported line-item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value. A Free plan carries 3 years of history and 24 calculated metrics on that same pipeline at no cost; the paid Annual and Monthly plans extend it to 17-plus years, 90-plus metrics, and the Stock Screener. There is no mapping layer between the filing and the display, no template deciding which line items get combined, and no score sitting between the number and the reader.

That scope is deliberately narrow. No global coverage, no credit analytics, no analyst estimates, no expert-call library. What it buys instead is that a figure on screen is the reported fact rather than a representation of one. [Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, [Custom Tables](/features#custom-tables) assemble specific reported line items, [Visualizations](/features#visualizations) chart the reported structure over time, and [Calculated Metrics](/features#calculated-metrics) compute from those as-filed inputs rather than from a template's definition. The verification step every platform above tells its users to run ("confirm against the primary source") is the default state here instead of a fifteen-minute errand.

## Stock Screening

Screening is a distinct job from either search or normalization: reduce a universe to a shortlist using computed, filterable values. [Finviz](/blog/finviz-alternative-fundamental-data) does it fastest and cheapest: a free tier used by roughly **25 million** people a month, with Elite adding real-time data at **$299.50** a year. Its fundamental layer, though, is a single row of ratios with history capped at three years free, eight on Elite. [Stock Rover](/blog/stock-rover-alternative-sec-data) is the deepest pure screener, with somewhere between **275** and **800+** metrics depending on tier and up to twenty years of history, though tier-gating means the analytical question you can ask is partly set by what you paid.

Several of the licensed platforms above bundle screening on top of their normalized data (TIKR and Capital IQ both do), which means the screen inherits whatever mapping decisions sit underneath it. A screen is only as good as the fields behind it. GeminIQ's [Stock Screeners](/features#screener) run the same filtering operation directly against as-filed, XBRL-tagged data, including named strategy screens like the [Magic Formula Screener](/screens/stock-screeners/magic-formula) and the [Piotroski F-Score Screener](/screens/stock-screeners/piotroski-f-score). A company that passes can be checked against the filing that produced the result without ever switching platforms.

## Choosing the Right Category for the Job

Most of the frustration investors report with financial data tools traces back to using one category to answer a question built for another. A search platform cannot rank a universe. A scoring layer cannot show you why a company scored the way it did. A spreadsheet formula cannot tell you which XBRL tag produced the value it returned. None of that is a product failure. It is a category boundary, and every platform above is genuinely strong at the job it was built for.

The categories are not mutually exclusive in practice, and a serious research process typically uses more than one: search to shape the question, a licensed platform to screen broadly and fast, and the primary filing to settle anything a decision is actually going to rest on. As-filed data is not a replacement for the other three categories. It is the one category none of the other three can substitute for, because it is the only one answering what the company actually reported rather than what a representation of that report says.

## Frequently Asked Questions

### What's the difference between normalized and as-filed SEC data?

Normalized data has been mapped by a third-party provider into a standardized template so companies can be compared on the same line items. As-filed data preserves the company's own reported structure and XBRL tags exactly as submitted to the SEC. Normalization aids comparability; it can also combine, split, or relabel items in ways that change what a figure represents.

### Which SEC filing analysis tool is best for stock screening?

It depends on depth versus breadth. Stock Rover offers the deepest metric library among dedicated screeners; Finviz is the fastest and cheapest for a quick scan; several licensed platforms like TIKR and Capital IQ bundle screening with normalized fundamentals. Every screen is only as reliable as the data field it filters on.

### Do any SEC filing research platforms show data straight from EDGAR with no normalization?

That is a narrow category by design. GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR and preserves each company's own reported line items and XBRL tags without a standardization layer in between.

### Is document search the same as fundamental analysis?

No. Document search retrieves relevant passages from filings, research, and transcripts; fundamental analysis requires structured, computable values that can be sorted, filtered, and compared across periods and companies. Search platforms like AlphaSense are explicit that this is a different problem; several sell structured data and modeling as a separate product line.

### What is financial data normalization software?

In this context, normalization means mapping each company's own reported line items into one standardized, cross-company template so the same row means the same thing for every filer. It is not the data-science sense of the word, which rescales values into a common numeric range, and it is not normalized EBITDA, which adjusts a single company's earnings for items an analyst judges non-recurring. Every platform in the [normalized and licensed category](#normalized-and-licensed-fundamentals-data) above performs the first kind. The trade is always the same: comparison gets faster, and the figure on screen becomes the standardized version of what the company filed rather than the filing itself.

### Which SEC filing analysis tools are free?

SEC EDGAR is free and always has been, including the XBRL data behind every reported figure, though it leaves the extraction work to you. Among the commercial tools above, Finviz runs a genuine free tier used by roughly **25 million** people a month, StockAnalysis.com and [ROIC](/blog/roic-return-on-invested-capital-explained).ai are free to browse, and GeminIQ's Free plan carries **3 years** of as-filed history and **24** calculated metrics at no cost on the same pipeline as its paid plans. The institutional terminals publish no pricing at all, free or otherwise.

### What happened to QuickFS?

QuickFS has shut down. Its homepage is now a farewell note from founder Ted Cooper pointing users to FastFS.org. For investors looking for a replacement, the practical question is which category the tool was filling: if it was standardized statement history, the licensed and low-cost aggregators above cover it, and if it was traceability back to the filing, that is the as-filed category rather than a like-for-like swap.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filing-analysis-tools-compared)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Category placements and figures for AlphaSense, BamSEC, Quartr, Seeking Alpha, Bloomberg Terminal, S&P Capital IQ, FactSet, TIKR, Koyfin, YCharts, Fiscal.ai, Morningstar, GuruFocus, Simply Wall St, Value Line, Zacks, Daloopa, Finbox, Wisesheets, StockAnalysis.com, ROIC.ai, Finviz, and Stock Rover are drawn from GeminIQ's own published comparison research on each platform (linked above), reviewed August 2, 2026 from each platform's public materials and third-party reviews. Verify current pricing and plan details on each vendor's site before republication.
- GeminIQ Free, Annual, and Monthly plan features, limits, and pricing confirmed directly from https://www.geminiq.com/pricing, retrieved August 8, 2026.

---

## Blog: SEC Filing Deadlines by Filer Status: The Calendar
source: https://www.geminiq.com/blog/sec-filing-deadlines-by-filer-status

### SEC Filing Deadlines by Filer Status: The Calendar
SEC filing deadlines are not the same for every company. A 10-K can be due in 60, 75, or 90 days depending on filer status, and several other required filings run on entirely different clocks. This reference maps deadlines for the 10-K, 10-Q, 8-K, Form 4, 13F, and 13D/13G, and flags a pending SEC proposal that would reshape the filer status system itself.

Most explanations of SEC filing deadlines quietly assume every filing scales the same way: bigger company, faster deadline. That's true for exactly two filings — the 10-K and the 10-Q. It isn't true for the [8-K](/blog/what-is-8-k), [Form 4](/blog/form-4-transaction-code-list), 13F, or Schedule 13D and 13G, all of which run on entirely different clocks that have nothing to do with the size of the company being reported on. Confusing the two systems is the single most common mistake in casual explanations of SEC filing timing.

This reference separates the two systems cleanly: what "filer status" actually means, which deadlines it controls, which deadlines it has no bearing on at all, what happens when a company misses one, and a proposed SEC rule change that could reshape the entire filer status framework in the near term. For what each of these filings actually contains, see our [complete guide to SEC filing types for investors](/blog/sec-filings-guide).

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sec-filing-deadlines-by-filer-status)**

---

## Table of Contents

- [What Determines a Company's Filer Status?](#what-determines-a-companys-filer-status)
- [10-K and 10-Q Deadlines by Filer Status](#10-k-and-10-q-deadlines-by-filer-status)
- [When Is a Company's Next 10-K or 10-Q Due? A Worked Example](#when-is-a-companys-next-10-k-or-10-q-due-a-worked-example)
- [8-K, Form 4, 13F, and 13D/13G Deadlines (Not Set by Filer Status)](#8-k-form-4-13f-and-13d13g-deadlines-not-set-by-filer-status)
- [What Happens If a Company Misses Its Deadline? (Form 12b-25)](#what-happens-if-a-company-misses-its-deadline-form-12b-25)
- [The SEC's Proposed Filer Status Overhaul (May 2026)](#the-secs-proposed-filer-status-overhaul-may-2026)
- [How to Check a Company's Filer Status](#how-to-check-a-companys-filer-status)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Determines a Company's Filer Status?

Filer status is set by **public float** — the aggregate market value of a company's voting and non-voting common equity held by non-affiliates, measured as of the last business day of its most recently completed second fiscal quarter. A **large accelerated filer** has public float of **$700 million** or more. An **accelerated filer** has public float of at least **$75 million** but under **$700 million**. A **non-accelerated filer** has public float under **$75 million**, or simply hasn't yet met the additional tests required to be classified as accelerated. Those tests require at least one annual report already filed, and at least 12 months subject to Exchange Act reporting. Every newly public company starts out non-accelerated by default, regardless of how large its float is at IPO.

The thresholds aren't perfectly symmetric. A company doesn't exit accelerated filer status the moment its float dips below $75 million — it has to fall below **$60 million** (80% of the entrance threshold) before it exits down to non-accelerated. The same hysteresis applies at the top: a large accelerated filer doesn't drop a tier until its float falls below **$560 million**. That gap exists so a company hovering right at a threshold isn't flipping filer status, and the deadlines that come with it, every single year.

One category that's easy to conflate with filer status but isn't the same thing: **smaller reporting company (SRC)** status. SRC eligibility runs on a separate test — public float under $250 million, or float under $700 million combined with annual revenue under $100 million. It unlocks scaled disclosure accommodations instead, like reduced executive compensation tables and, in some cases, relief from the auditor's internal-control attestation. It does not change a company's 10-K or 10-Q deadline. A company can be both an accelerated filer and an SRC at the same time, filing on the accelerated filer's deadline while using the SRC's lighter disclosure rules.

## 10-K and 10-Q Deadlines by Filer Status

This is the one part of the SEC filing calendar where company size genuinely sets the clock.

| Filer Status | Public Float | 10-K Deadline | 10-Q Deadline |
|---|---|---|---|
| Large Accelerated Filer | $700 million or more | 60 days after fiscal year-end | 40 days after quarter-end |
| Accelerated Filer | $75 million to $700 million | 75 days after fiscal year-end | 40 days after quarter-end |
| Non-Accelerated Filer | Under $75 million | 90 days after fiscal year-end | 45 days after quarter-end |

The detail that trips up the most casual references: the 10-Q's 40-day deadline applies to accelerated filers, not just large accelerated ones. Accelerated and large accelerated filers share the same 40-day quarterly window; only non-accelerated filers get the extra five days, to 45. The gap between filer statuses only really shows up in the 10-K, where it spans a full 30 days between the fastest and slowest tier. For a complete walkthrough of what else separates these two filings beyond timing, see our [10-K vs. 10-Q guide](/blog/10-k-vs-10-q-differences-explained).

## When Is a Company's Next 10-K or 10-Q Due? A Worked Example

The table above is the rule. Applying it to a specific company takes two inputs: the fiscal year-end printed on the cover of its last filing, and the filer status box it checked on that same cover page. Everything else is counting days forward.

Take the most common case — a company whose fiscal year ends December 31. Counting forward from the period end using the deadlines above:

| Filing | Period ends | Large accelerated (60 / 40 days) | Accelerated (75 / 40 days) | Non-accelerated (90 / 45 days) |
|---|---|---|---|---|
| 10-K | December 31 | March 1 | March 16 | March 31 |
| Q1 10-Q | March 31 | May 10 | May 10 | May 15 |
| Q2 10-Q | June 30 | August 9 | August 9 | August 14 |
| Q3 10-Q | September 30 | November 9 | November 9 | November 14 |

Two things fall out of the arithmetic that the deadline table alone doesn't make obvious. The first is that the accelerated and large accelerated columns are identical for all three quarters and differ only once a year, on the annual report — the 30-day spread between the fastest and slowest 10-K tier is the entire practical difference between filer statuses for most of the calendar. The second is that a leap year moves the three 10-K dates one day earlier, to February 29, March 15, and March 30, because the count runs on days rather than months. The quarterly dates are unaffected, since each quarter-end that anchors those counts falls after February.

A company with a non-December fiscal year-end runs the same arithmetic off its own dates. There is no separate schedule for off-cycle filers; the day counts are the same, only the starting point moves.

## 8-K, Form 4, 13F, and 13D/13G Deadlines (Not Set by Filer Status)

Every other filing an investor regularly reads runs on a clock triggered by something other than the subject company's size.

| Filing | Deadline | What Actually Triggers It |
|---|---|---|
| 8-K | 4 business days (most items) | The reportable event itself — same window for every registrant |
| Form 4 | 2 business days | The insider's transaction date — same window for every reporting person |
| 13F | 45 days after calendar quarter-end | The institutional manager's own $100 million-plus threshold, not the size of any company it holds |
| Schedule 13D | 5 business days after crossing 5% | The investor's own stake crossing the threshold, not the issuer's filer status |
| Schedule 13G | 5 business days (passive filers) or 45 days after quarter-end (qualified institutional and exempt investors) | The filer's own investor category |

An **8-K** is event-triggered: most items must be filed within 4 business days of whatever happened, regardless of whether the company is a large accelerated filer or the smallest non-accelerated one on EDGAR. A **Form 4** works the same way from the insider's side — the 2-business-day clock starts on the transaction date, not on anything about the company's size. **Form 13F** deadlines are set by the reporting manager crossing $100 million in assets under management, a completely separate regulatory test from any company's public float. And **Schedule 13D and 13G**, which disclose an investor crossing 5% ownership of a company, run on deadlines set by the investor's own category — activist intent versus passive, qualified institutional or not. Never by the target company's filer status. Our [Schedule 13D vs. 13G guide](/blog/schedule-13d-vs-13g-explained) covers that investor-side deadline structure in full.

## What Happens If a Company Misses Its Deadline? (Form 12b-25)

A deadline that passes without a filing is not automatically a delinquency. A company that can't complete its 10-K or 10-Q on time files a **Form 12b-25** — a notification of late filing, which appears on EDGAR as an **NT 10-K** or an **NT 10-Q** depending on which report is late. It is the filing you should look for first when a periodic report you expected hasn't appeared.

The notification is itself a disclosure, and it is usually the most informative document a late filer produces. It states which report is late and why, in the company's own words. That explanation is what distinguishes a scheduling problem from a substantive one: an auditor still completing procedures, a recent acquisition whose accounting isn't closed, an unresolved accounting question, or an internal investigation are very different signals, and the company has to pick one and put it in writing. The notification also carries the company's own statement of whether it expects a significant change in results from the prior period.

Filing a 12b-25 gives the company a short additional window to complete the report. If the report lands inside that window, the filing is treated as having been made on time; if it doesn't, the company is a delinquent filer, with the reporting and eligibility consequences that follow. So the practical check on any missed date is a two-step one: look for the notification, then look for the actual report behind it. A 12b-25 with no report following it is a materially different situation from a 12b-25 followed by a complete filing days later.

## The SEC's Proposed Filer Status Overhaul (May 2026)

The filer status framework described above isn't necessarily permanent. On May 19, 2026, the SEC proposed a significant overhaul that would collapse the current multi-tier system into just two categories: large accelerated filer and non-accelerated filer, eliminating the accelerated filer and smaller reporting company categories entirely. The proposal would also raise the large accelerated filer threshold from **$700 million** to **$2 billion** in public float. It would also create a new "small non-accelerated filer" sub-category — companies with $35 million or less in total assets — eligible for extended deadlines of **120 days** for the 10-K and **50 days** for the 10-Q.

The public comment period on this proposal closed July 20, 2026, and as of this writing the SEC has not adopted final rules. If adopted as proposed, the table above would need a significant rewrite: the SEC's own estimate is that the expanded non-accelerated filer category would cover roughly 81% of domestic registrants, up from about 52% today. Nothing in this filer status framework changes until the SEC finalizes a rule, but it's worth watching if you track filing timing across a broad universe of names.

## How to Check a Company's Filer Status

A company's filer status isn't something you have to calculate yourself. Every 10-K and 10-Q cover page carries a checkbox section — large accelerated filer, accelerated filer, non-accelerated filer, smaller reporting company, emerging growth company — where the company self-identifies its own status for that specific filing. GeminIQ's [Financial Statements](/features#financial-statements) feature pulls the full as-filed document, cover page included.

If you check cover pages routinely across a list of names, this is the one task where a filing-retrieval tool earns its keep — [how BamSEC handles it](/competitor-comparison/bamsec) is a reasonable point of comparison, since the checkbox lives in the document itself and never in a normalized financial database. Before you assume a filing missed its deadline, check the box the company actually checked — the filer status on the cover page tells you which clock applied, before you draw any conclusion from the calendar.

## Frequently Asked Questions

### What is the deadline for a 10-K filing?

It depends on filer status: 60 days after fiscal year-end for a large accelerated filer, 75 days for an accelerated filer, and 90 days for a non-accelerated filer.

### Do accelerated filers and large accelerated filers have the same 10-Q deadline?

Yes. Both file the 10-Q within 40 days of quarter-end. Only non-accelerated filers get the longer 45-day window — the 10-Q deadline only has two tiers, not three.

### Does an 8-K deadline change based on company size?

No. Most 8-K items must be filed within 4 business days of the triggering event regardless of whether the company is a large accelerated filer or a non-accelerated one. The clock starts on the event, not on the company's public float.

### Is smaller reporting company status the same as non-accelerated filer status?

No. They're determined by different tests and serve different purposes. Smaller reporting company status unlocks scaled disclosure accommodations; it doesn't by itself change a company's 10-K or 10-Q deadline, which is set separately by large accelerated, accelerated, or non-accelerated status.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Which Financial Metrics Matter by Sector
source: https://www.geminiq.com/blog/sector-specific-metrics-that-matter

### Which Financial Metrics Matter by Sector
Current Ratio, Debt-to-Equity, and ROIC work reasonably well across most companies, and they stop meaning much the moment a business model diverges from the generic case those metrics were built around — a bank whose liabilities exceed its assets by design, a REIT whose net income is depressed by non-cash depreciation, an insurer whose real profitability question has nothing to do with net income at all. This guide covers the metrics that actually matter for seven distinct business models — banks, insurers, REITs, SaaS, retail, capital-intensive industries, and pre-revenue companies — and exactly where the standard toolkit breaks down for each.

Current Ratio, Debt-to-Equity, ROIC — the standard toolkit works, right up until it's applied to a bank, whose entire business model is holding more liabilities than assets by design. It works even less well applied to a real estate investment trust, whose net income is structurally depressed by a non-cash charge that has nothing to do with how the business is actually performing. A single set of metrics applied uniformly across every sector isn't wrong so much as it's incomplete. It produces a number for every company, but the number means something different depending on what kind of business generated it.

This guide covers the metrics that actually matter for seven distinct business models, and — just as important — the standard metrics that quietly stop meaning much once a company's business model diverges from the general-purpose case those metrics were built around. [Our general framework for value investors](/blog/financial-metrics-value-investors) covers the metrics that work reasonably well across most companies; this guide is specifically about where that general approach breaks down.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=sector-specific-metrics-that-matter)**

---

## Table of Contents

- [Why One Set of Metrics Doesn't Fit Every Business Model](#why-one-set-of-metrics-doesnt-fit-every-business-model)
- [Banks: Net Interest Margin and Efficiency Ratio, Not Current Ratio](#banks-net-interest-margin-and-efficiency-ratio-not-current-ratio)
- [Insurance: The Combined Ratio](#insurance-the-combined-ratio)
- [REITs: FFO and AFFO, Not Net Income](#reits-ffo-and-affo-not-net-income)
- [SaaS and Software: Deferred Revenue as the Leading Signal](#saas-and-software-deferred-revenue-as-the-leading-signal)
- [Retail and Consumer: Days Inventory Outstanding as a Demand Signal](#retail-and-consumer-days-inventory-outstanding-as-a-demand-signal)
- [Capital-Intensive Industries: Leases, Not Just Debt](#capital-intensive-industries-leases-not-just-debt)
- [Pre-Revenue and Biotech: Cash Runway, Not Profitability](#pre-revenue-and-biotech-cash-runway-not-profitability)
- [The One Question That Applies to Every Sector](#the-one-question-that-applies-to-every-sector)
- [Reading Sector-Specific Line Items on GeminIQ](#reading-sector-specific-line-items-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## Why One Set of Metrics Doesn't Fit Every Business Model

Every standard financial ratio carries an implicit assumption about what a healthy version of the underlying business looks like. [Current Ratio](/metrics/liquidity-ratios/current-ratio) assumes a business that needs current assets to exceed current liabilities for safety — true for most operating companies, false for a bank that is, by regulatory design, mostly liabilities. Net income assumes accounting profit approximates economic cash generation — true for most companies, false for a REIT whose largest expense, real estate depreciation, rarely reflects an actual decline in the value of the underlying property.

None of this means the standard metrics are wrong. It means they were built around the median company, and several major sectors sit far enough from that median that applying the standard toolkit produces a technically correct number that answers the wrong question.

The seven business models covered below, and what each one substitutes for the generic metric:

| Business model | Metric that actually matters | How it's built | What it replaces, and why |
|---|---|---|---|
| Banks | Net Interest Margin; Efficiency Ratio | (Interest income − interest expense) ÷ average earning assets; non-interest expense ÷ revenue | Current Ratio and Debt-to-Equity — a bank holds deposits, which are liabilities, and lends them out, so a generic leverage ratio flags the intended structure as alarming |
| Insurance | Combined Ratio | (Incurred losses + underwriting expenses) ÷ earned premiums; below 100% is an underwriting profit | Net income — which blends underwriting results with investment income earned on the float |
| REITs | FFO, then AFFO | FFO = Net Income + Real Estate D&A − Gains on Sale (+ Losses on Sale); AFFO subtracts recurring maintenance capex | Net income — real estate depreciation is a large mandatory non-cash charge that depresses reported profit |
| SaaS and software | Deferred revenue growth (with gross margin as a **70% to 90%** sector check) | — | Reading deferred revenue as a liability to worry about, when it's customer cash paid in advance and a leading indicator of bookings |
| Retail and consumer | Days Inventory Outstanding, inside the Cash Conversion Cycle | DIO, DSO and DPO combined into the days between paying for inventory and collecting cash on the sale | Headline earnings — rising DIO relative to revenue growth shows a demand slowdown earlier |
| Capital-intensive (airlines, utilities, telecom) | Debt-to-EBITDA with lease liabilities tracked separately | Total debt built with operating lease liabilities as an explicit, separately-tracked component rather than excluded or silently merged | A blanket "total debt" figure, which overstates actual financial risk when obligations are structured as leases rather than loans |
| Pre-revenue and biotech | Cash runway | Cash and short-term investments ÷ the burn rate for the same length of period (multiply a quarterly figure by three for months) | Profitability ratios — close to meaningless for a company with no product revenue yet |

---

## Banks: Net Interest Margin and Efficiency Ratio, Not Current Ratio

Current Ratio and Debt-to-Equity are close to meaningless for a bank, because a bank's core business is holding deposits — a liability — and lending them out, which is the entire point of the balance sheet structure a generic leverage ratio would flag as alarming. The metrics that actually describe a bank's performance come from a different part of the income statement entirely. Net Interest Margin, calculated as interest income minus interest expense divided by average earning assets, measures how profitably the bank is running its core spread business. Efficiency Ratio, non-interest expense divided by revenue, measures cost discipline independent of that spread — it states how many cents of overhead the bank spends per dollar of revenue, so a lower ratio is the better one, and it is expressed as a percentage rather than a multiple. Neither is a standard GAAP line item — both require pulling interest income, interest expense, and non-interest expense directly from the income statement and building the ratio by hand.

Provision for credit losses — the amount a bank sets aside against loans it expects to go bad — is the line item worth tracking as a trend, since a rising provision relative to the loan book is often the first visible sign of credit quality deteriorating, well before it shows up in reported net income.

---

## Insurance: The Combined Ratio

An insurer's core profitability question — is the underwriting business itself profitable, before any investment income — has its own dedicated metric with no equivalent in general corporate analysis: the Combined Ratio, calculated as incurred losses plus underwriting expenses, divided by earned premiums. A combined ratio below 100% means the insurer is making money on underwriting alone; above 100% means the underwriting business is losing money and the company depends on investment income from its float to be profitable overall.

A combined ratio persistently above 100%, offset by strong investment returns, is a materially different business than one running a genuine underwriting profit. The first is dependent on market conditions the company doesn't control, the second is dependent on underwriting discipline the company does. Both can produce the same bottom-line net income in a given year while describing completely different levels of underlying business quality.

---

## REITs: FFO and AFFO, Not Net Income

Net income is the wrong starting point for evaluating a REIT, because real estate depreciation — a large, mandatory GAAP non-cash charge — routinely makes a genuinely healthy, cash-generative REIT look barely profitable or unprofitable on the income statement. The industry's own standard alternative, Funds From Operations (FFO), developed by Nareit specifically to correct for this, adds real estate depreciation and amortization back to net income and removes gains or losses on property sales: FFO = Net Income + Real Estate D&A − Gains on Sale (+ Losses on Sale).

Adjusted Funds From Operations (AFFO) goes one step further, subtracting the recurring capital expenditures needed to actually maintain the properties — new roofs, tenant improvements, leasing costs — that FFO's add-back doesn't account for. AFFO is the closer approximation of the cash actually available to fund the dividend, and comparing AFFO per share against the dividend per share is the direct sustainability check: a dividend that exceeds AFFO per share is not fully covered by recurring cash earnings, regardless of how healthy FFO alone looks.

---

## SaaS and Software: Deferred Revenue as the Leading Signal

Deferred revenue growth is a genuine positive signal for a subscription business specifically, in a way it isn't for most other companies — customers paying in advance for a service not yet delivered is a source of interest-free financing and a leading indicator of bookings, not a liability to be concerned about. As a sector fact: healthy software businesses run [gross margins](/blog/gross-profit-margin-business-model-analysis) in the **70% to 90%** range, and a software company posting margins closer to a retailer's is either misclassified or running a more services-heavy business than its sector label suggests.

The genuine limitation here is that the metrics investors most associate with SaaS specifically — annual recurring revenue, net revenue retention, customer acquisition cost — are non-GAAP operational metrics companies disclose voluntarily, inconsistently, and outside the standard XBRL taxonomy entirely. None of them are filed data in the way revenue or gross margin are, which means they require reading the MD&A and investor presentations directly rather than pulling a tagged figure. [How GeminIQ compares to YCharts](/competitor-comparison/ycharts) covers where an as-filed database stops and a normalized data feed begins.

---

## Retail and Consumer: Days Inventory Outstanding as a Demand Signal

Inventory-heavy retail and consumer businesses are where the [Cash Conversion Cycle](/blog/cash-conversion-cycle-formula-explained) earns its place as close to a sector-specific metric, even though the formula itself is general-purpose. Days Inventory Outstanding, Days Sales Outstanding, and Days Payables Outstanding combine into a single number that measures how many days pass between paying for inventory and collecting cash from the eventual sale — and for a retailer specifically, a rising DIO relative to revenue growth is one of the clearest, earliest signals of a demand slowdown, well before it shows up in a headline earnings miss.

Same-store sales — revenue growth at locations open for at least a year, isolating organic performance from store-count expansion — is the other metric retail-specific analysis leans on heavily, and like the SaaS metrics above, it's a voluntarily disclosed operational figure rather than a standard XBRL-tagged concept.

---

## Capital-Intensive Industries: Leases, Not Just Debt

Airlines, utilities, telecoms, and other businesses running large physical footprints on leased or heavily financed infrastructure share the [operating-lease-versus-debt problem](/blog/operating-leases-vs-debt-asc-842) covered in full elsewhere on this site: a blanket "total debt" figure that doesn't separate interest-bearing borrowings from operating lease liabilities produces a leverage read that overstates the actual financial risk for a company whose obligations are structured as leases rather than loans.

[Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained), built with a total debt figure that deliberately includes lease liabilities as an explicit, separately-tracked component rather than either excluding or silently merging them, is the leverage metric that actually holds up for this category of business.

---

## Pre-Revenue and Biotech: Cash Runway, Not Profitability

Profitability ratios are close to meaningless for a company with no product revenue yet, which describes most clinical-stage biotech and a meaningful share of early-stage companies more broadly. The metric that actually matters is cash runway: current cash and short-term investments divided by the cash burn rate over the same length of period — trailing quarterly burn gives runway in quarters, so multiply by three to state it in the months it's usually quoted in. It answers the only question that determines whether the company survives to its next value-creating milestone — a clinical trial readout, an FDA decision, a partnership — without needing to raise dilutive capital first.

A pre-revenue company with a strong pipeline and eighteen months of runway is in a fundamentally different position than an identical pipeline with six months of runway, even though neither company's income statement tells that story in any conventional profitability metric.

---

## The One Question That Applies to Every Sector

Every sector-specific metric above answers the same underlying question in a form fitted to how that particular business model actually generates value: is the company's reported profitability an accurate reflection of the underlying economics, or is it distorted by an accounting treatment — deposit-funded leverage, real estate depreciation, deferred revenue, leased infrastructure, pre-revenue burn — that a generic ratio wasn't built to handle? Knowing which distortion applies to which sector is most of the work. The arithmetic itself, once the right inputs are identified, is usually simple.

---

## Reading Sector-Specific Line Items on GeminIQ

None of the metrics covered here that fall outside standard GAAP concepts — Net Interest Margin, Efficiency Ratio, Combined Ratio, FFO, AFFO — are single line items a company reports directly, which means no platform, GeminIQ included, can display them as a simple pre-tagged figure the way Revenue or Net Income can be. What GeminIQ does provide is every raw filed input each of these formulas actually needs: interest income and interest expense for a bank, incurred losses and earned premiums for an insurer, real estate depreciation and gains on sale for a REIT, all sourced directly from the [Financial Statements](/features#financial-statements) view exactly as filed.

The [Custom Tables](/features#custom-tables) builder is where the sector-specific formula actually gets assembled: pulling the two or three raw line items a given ratio needs, side by side, across as many quarters as the analysis requires, without having to reconstruct the underlying figures from a normalized template that may have already merged the inputs together.

---

## Frequently Asked Questions

### Why doesn't Current Ratio work for banks?

A bank's core business model is holding deposits, which are liabilities, and lending them out. A generic liquidity ratio built around current assets exceeding current liabilities flags this structure as risky by default, when it's simply how a bank's balance sheet is supposed to look.

### What's the difference between FFO and AFFO for a REIT?

FFO adds real estate depreciation and amortization back to net income and removes gains or losses on property sales, correcting for the largest non-cash distortion in REIT accounting. AFFO goes further, subtracting the recurring capital expenditures needed to actually maintain the properties, making it the closer approximation of cash genuinely available to fund the dividend.

### Does GeminIQ calculate Net Interest Margin or Combined Ratio directly?

These are industry-specific formulas built from raw filed line items — interest income and expense for NIM, incurred losses and earned premiums for combined ratio — rather than a single standard concept any company reports as one line. GeminIQ provides every raw input as-filed; assembling the sector-specific ratio itself is a build, not a lookup, on any platform.

### How do I know which sector-specific metrics apply to a company I'm researching?

Start from the business model, not the ticker's official sector classification. A company holding customer deposits and lending them out needs bank metrics regardless of its SIC code; a company collecting cash before delivering a service benefits from deferred revenue analysis whether or not it's formally classified as software.

The metric that matters most for any company is the one that answers what actually determines whether that specific business model succeeds — and that answer changes by sector far more than most generic screening tools admit.

---

## Related Reading

- [Financial Metrics for Value Investors: A Lululemon Case Study](/blog/financial-metrics-value-investors) — the general framework this guide's seven exceptions diverge from.
- [Operating Leases vs. Debt: The ASC 842 Problem](/blog/operating-leases-vs-debt-asc-842) — the full mechanics behind the capital-intensive sector section.
- [Cash Conversion Cycle Formula Explained](/blog/cash-conversion-cycle-formula-explained) — the full mechanics behind the retail sector section.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Seeking Alpha Alternative: Data Instead of Opinion
source: https://www.geminiq.com/blog/seeking-alpha-alternative-filing-data

### Seeking Alpha Alternative: Data Instead of Opinion
A Seeking Alpha alternative for investors who want the filing rather than the argument. With thousands of contributors publishing over 10,000 articles a month, every thesis has a counter-thesis; this post covers what the primary record settles that commentary cannot.

Seeking Alpha is not really a data platform, and treating it as one is the source of most complaints about it. It is a publishing platform with data attached — thousands of independent contributors producing more than 10,000 investment articles a month, wrapped in a quantitative rating system, a screener, transcripts, and a comment section where the arguments continue underneath.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=seeking-alpha-alternative-filing-data)**

That model produces something no institutional research shop can match: coverage of small caps that Wall Street ignores, contrarian arguments nobody with a job at a bank would publish, and a genuine diversity of view on every widely held name. Premium runs around **$299** a year at list, Pro sits near **$2,400**, and for an investor who wants to read the bull and bear cases side by side, the value is obvious.

It also means that for any position you are considering, someone has already published a persuasive case for it and someone else has published a persuasive case against it. Both are on the same site. Neither is the filing.

## Table of Contents

- [The Confirmation Bias Supermarket](#the-confirmation-bias-supermarket)
- [Figures in Articles Have No Provenance](#figures-in-articles-have-no-provenance)
- [A Quant Grade Is a Rank, Not a Fact](#a-quant-grade-is-a-rank-not-a-fact)
- [What Commentary Is Actually For](#what-commentary-is-actually-for)
- [The Layer Underneath the Argument](#the-layer-underneath-the-argument)
- [Reading Opinion Correctly](#reading-opinion-correctly)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Confirmation Bias Supermarket

Volume changes the nature of a research library, and the change is not linear.

At ten articles on a company, an investor reads all of them and forms a view. At two hundred, nobody reads all of them. Selection begins, and selection is where bias enters — not through the platform's editorial choices, but through which headline the reader clicks. An investor already leaning bullish clicks the bullish headline, finds it well argued and supported by numbers, and comes away with the sensation of having done research.

The bearish article was right there. It was also well argued and supported by numbers.

This is not a criticism of contributors, most of whom write in good faith and disclose their positions. It is a structural property of any large opinion marketplace: a sufficiently deep archive can confirm any prior. The platform's own defenders make the point in reverse when they praise it for surfacing contrarian views — a library that contains every view contains yours.

The only input in the process that does not bend to what you were hoping to find is the filing.

## Figures in Articles Have No Provenance

Here is the practical problem that shows up the moment you try to check something.

An article cites a revenue figure, a margin, a debt balance, a segment breakdown. Where did that number come from? It might be the 10-K. It might be a normalized dataset that combined two filed line items into one. It might be a non-GAAP adjusted figure from an earnings release, which is a different number than the GAAP figure in the filing. It might be trailing twelve months, calculated differently by different authors. It might be a typo carried forward from an earlier article.

Nothing in the format distinguishes these. A number in prose is a number in prose, and there is no tag, no source link, and no classification note attached to it.

That matters more than it sounds, because the numbers in an argument are load-bearing. An article's thesis frequently rests on one figure — a margin inflection, a debt ratio, a free cash flow conversion rate. If that figure came from an adjusted presentation rather than the filed statement, the thesis is standing on something the reader has not examined and cannot examine from inside the article.

Checking is possible. It requires leaving.

## A Quant Grade Is a Rank, Not a Fact

Seeking Alpha's Quant Ratings are the platform's most data-driven feature, running on a large set of factors updated daily and expressed as letter grades across categories like valuation, growth, profitability, and momentum.

The system is transparent about being factor-based, and it has real utility as a screening layer. But a factor grade is relative by construction. An A on valuation means the stock ranks well against its sector peers on the chosen valuation factors — it does not mean the stock is cheap in absolute terms, and it certainly does not mean the underlying figures match the filing.

Two additional layers sit alongside it: contributor consensus ratings and Wall Street sell-side consensus. An investor comparing all three is comparing three opinions with different methodologies, which is informative about disagreement and tells you nothing about the reported record.

Grades compress. That is their job. What they compress is the same thing every rating compresses — the specific line items that produced the conclusion.

## What Commentary Is Actually For

The case for reading investment commentary is strong and worth stating clearly, because dismissing it would be lazy.

Filings do not explain competitive dynamics. They do not tell you that a customer concentration risk is about to matter because the customer is retooling, or that a regulatory change three states away will reshape a business model, or that management's language on the last call shifted in a way that suggests guidance is soft. Someone who has followed an industry for fifteen years knows things that no document discloses.

That is what contributor research supplies at its best: context, industry knowledge, and the questions worth asking. Small-cap coverage in particular exists almost nowhere else.

What it cannot supply is verification, because every article is an argument and arguments select their evidence. The right relationship between the two is sequential rather than competitive — read the argument to learn what to check, then check it.

## The Layer Underneath the Argument

GeminIQ takes no position on any company. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value, so a figure cited in someone's article can be matched against the reported fact behind it.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, which is where a GAAP figure and an adjusted figure stop being confusable. [Custom Tables](/features#custom-tables) assemble the specific reported items a thesis depends on. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Free Cash Flow](/metrics/calculated-values/free-cash-flow), and [Net Debt](/metrics/calculated-values/net-debt) are computed from as-filed inputs rather than from an author's derivation. [Insider Transactions](/features#insider-transactions) and [Institutional Ownership](/features#institutional-ownership) sit alongside, on the quarterly cadence the underlying filings actually have. The step-by-step method is covered in [how to verify financial data against an SEC filing](/blog/verify-financial-data-against-sec-filing).

There are no articles, no ratings, and no community. The output is the reported record, which is the one thing an argument cannot be substituted for.

## Reading Opinion Correctly

The discipline that makes a commentary platform useful is simple to describe and hard to maintain: read the article for the question, not for the answer.

A bull case is a list of things that would have to be true. A bear case is a different list. Both are hypotheses, and both name specific, checkable claims — a margin that must expand, a debt maturity that must be refinanced, a segment that must keep growing. Those claims are the value in the article, and every one of them resolves against a filing.

Where a cited figure came from a licensed dataset rather than the filing, the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) post describes what standardization changes on the way.

Read enough commentary and you will find an argument for whatever you already believed. Read the filing and you find out what the company reported, which is the only part of the process that does not care what you were hoping to see.

## Frequently Asked Questions

### What are the best Seeking Alpha alternatives?

It depends on which half you are replacing. For investment commentary, contributor research, and community discussion, the substitutes are other publishing platforms and newsletters. For the underlying financial record, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability — which supplies no opinion at all, by design.

### Are Seeking Alpha Quant Ratings based on SEC filings?

Indirectly and partially. The system evaluates a large set of factors across categories such as valuation, growth, profitability, and momentum, and expresses them as relative grades against sector peers. Some inputs originate in reported financials, others come from price data and analyst estimates. A grade describes where a stock ranks, not what it filed.

### How do I verify a figure cited in a Seeking Alpha article?

Establish three things: which period the figure covers, whether it is GAAP or an adjusted presentation, and whether the scope matches the filing's caption. Adjusted and non-GAAP figures reported in earnings releases frequently differ from the GAAP line item in the 10-K or 10-Q, and article prose usually does not distinguish them. The filing settles all three.

### Is Seeking Alpha worth it for fundamental investors?

For idea generation, industry context, and small-cap coverage that institutional research does not touch, the contributor model has few peers. The limitation is that every article is an argument, and a large enough archive contains a persuasive case for any position. It works best as a source of questions rather than as a source of verified figures.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=seeking-alpha-alternative-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Seeking Alpha contributor volume, article volume, Quant Ratings factor structure, and Premium and Pro list pricing reviewed August 2, 2026 from Seeking Alpha materials and third-party platform reviews. Promotional pricing varies; verify current figures before republication.

---

## Blog: Shareholder Yield: Dividends + Buybacks as One Metric
source: https://www.geminiq.com/blog/shareholder-yield-dividends-buybacks-explained

### Shareholder Yield: Dividends + Buybacks as One Metric
Shareholder yield combines dividend payments and net share repurchases into a single capital return measure. Meb Faber's research showed top-quintile shareholder yield stocks outperform dividend-only screens over five-year periods — here is the formula, the academic evidence, and how to screen for it using as-filed SEC data.

Dividend yield is the metric every income investor knows, and it is incomplete by design. In the United States, share repurchases have been the dominant form of capital return for decades — companies have returned more cash through buybacks than dividends in most years since the early 2000s — yet the most commonly used income screens still rank stocks on dividend yield alone. Shareholder yield corrects this by combining dividends paid and net share repurchases into a single figure expressed as a percentage of market capitalization. A company paying a **1% dividend yield** and retiring **5% of its float** annually delivers **6% shareholder yield** to equity holders — far more total capital return than the **4% dividend yield** stock near the top of a traditional income screen. Meb Faber systematized this framework in his 2013 book _Shareholder Yield: A Better Approach to Dividend Investing_, building on earlier academic work by William Priest and Lindsay McClelland, and his research found that sorting stocks by total shareholder yield produced stronger five-year forward returns than sorting by dividend yield alone — particularly in international markets where the two signals diverged most sharply. This post covers the formula, the academic evidence behind it, the three data problems that make it nearly impossible to screen for accurately without raw SEC filing data, and a step-by-step walkthrough of the GeminIQ [Shareholder Yield Screener](/screens/stock-screeners/shareholder-yield) built on as-filed XBRL data.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=shareholder-yield-dividends-buybacks-explained)**

---

## Table of Contents

- [What Is Shareholder Yield?](#what-is-shareholder-yield)
- [Why Dividend Yield Alone Understates Total Capital Return](#why-dividend-yield-alone-understates-total-capital-return)
- [What the Faber Research Actually Shows](#what-the-faber-research-actually-shows)
- [The Three Data Problems That Break Standard Screeners](#the-three-data-problems-that-break-standard-screeners)
- [How to Run the GeminIQ Shareholder Yield Screener](#how-to-run-the-geminiq-shareholder-yield-screener)
- [Adding the Valuation Check](#adding-the-valuation-check)
- [Reading Your Results: What to Verify Beyond the Filters](#reading-your-results-what-to-verify-beyond-the-filters)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What Is Shareholder Yield?

### What Is the Shareholder Yield Formula?

Shareholder yield is the total cash return delivered to equity holders expressed as a percentage of market capitalization. It adds two distinct return mechanisms — dividends paid and net [share repurchases](/blog/do-buybacks-reduce-share-count) — into a single number:

**Shareholder Yield = (Dividends Paid + Net Share Repurchases) ÷ Market Capitalization**

"Net share repurchases" is the precision point that most implementations get wrong. This is actual cash spent buying back shares during the period, minus any new share issuance from stock compensation exercises and employee equity programs — the two flows netted against each other to arrive at what shareholders received in aggregate. A company that repurchased **$500 million** of its own stock but simultaneously issued **$200 million** in new shares through stock-based compensation vesting, restricted stock unit deliveries, and employee equity purchase programs delivered only **$300 million** in net buyback value. Using the gross repurchase figure without netting the new issuance overstates the effective yield, and most aggregator platforms use the gross figure because it is easier to source. The raw SEC cash flow statement captures both flows — the repurchases in the financing activities section and the share issuance from equity compensation through the same statement and the share count trend on the balance sheet. Only by reading both can you arrive at the true net figure.

Some practitioners extend the formula to include debt paydown — the reasoning being that reducing net leverage also accrues value to equity holders. This expanded version, sometimes called "net payout yield" or "triple yield," appears in Faber's later work and in academic research on capital allocation. In practice, the two-component version — dividends plus net buybacks — is the more widely used form. It requires no assumptions about the marginal benefit of debt reduction, it is reproducible directly from financing activities in the filed 10-K or 10-Q, and it has the most established empirical support across the academic literature.

### When Did Buybacks Become the Primary Capital Return Mechanism?

The shift is traceable to 1982, when the SEC adopted Rule 10b-18, giving companies a safe harbor from market manipulation charges when repurchasing shares in the open market under specified volume and pricing constraints. Before that, open-market buybacks were legally ambiguous and practically uncommon. After, repurchases grew steadily through the 1980s and accelerated sharply through the 1990s. By the early 2000s, total buyback spending across S&P 500 companies had surpassed total dividends paid in most calendar years.

The practical reason buybacks became the preferred lever is flexibility. A dividend cut is one of the most negatively received signals a management team can send — it implies distress or a fundamental reset in [earnings quality](/blog/earnings-quality-accruals-analysis). Suspending or slowing a buyback program carries no comparable market penalty. Companies in cyclical businesses, technology companies with variable free cash flow profiles, and capital-allocation-focused management teams leaned into buybacks precisely because of this asymmetry. Dividends became the stable floor; buybacks became the variable mechanism for returning excess capital above that floor. The result: a company generating extraordinary free cash flow may be returning **7%, 8%, or 9%** of its market cap annually to shareholders through repurchases alone — and still appear near the bottom of any dividend yield screen with a **1% dividend yield**.

---

## Why Dividend Yield Alone Understates Total Capital Return

The arithmetic case is direct. Suppose two companies each trade at a **$10 billion** market cap. Company A pays **$400 million** in annual dividends and does no buybacks: **4% dividend yield**, **4% shareholder yield**. Company B pays **$100 million** in dividends but spends **$600 million** per year reducing its float through repurchases: **1% dividend yield**, **7% shareholder yield**. A dividend yield screen ranks Company A near the top of any income universe and Company B near the bottom. The shareholder yield framework inverts that ranking — Company B is returning **75% more** capital to shareholders annually, and the dividend-only view not only misses this but actively misdirects analysis toward the lower-returning stock.

The problem compounds when you account for what a growing share count does to per-share value over time. A company paying a **4% dividend yield** while simultaneously issuing **3% of its float** through equity compensation is effectively delivering **1% net return** — the dividend and the dilution nearly cancel each other out. A standard dividend screen still ranks it as a **4% yield** stock. Shareholder yield, applied with net share repurchases, reflects this erosion because the dilution flows through the net buyback component as a negative. A company whose diluted share count is rising is not returning capital even when it pays a dividend; it is giving shareholders cash with one hand and splitting the ownership pie into more pieces with the other. The [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) captures this directly — tracking the net change in diluted shares outstanding as a percentage of shares outstanding, accounting for both repurchase activity and new issuance from equity compensation programs. Standard dividend screens do not see this. The as-filed share count data does.

---

## What the Faber Research Actually Shows

### What Did Meb Faber Find About Shareholder Yield?

Faber's core finding, published in 2013 and updated in subsequent research, was unambiguous: stocks in the top quintile by shareholder yield delivered superior five-year forward returns. The comparison held against dividend yield alone, P/E, and most other single-factor value signals tested. The mechanism is intuitive: high shareholder yield concentrates the universe on companies generating more cash than they can productively reinvest internally and distributing that excess to shareholders. This population tends to share structural characteristics — strong free cash flow, disciplined capital allocation, and management teams not empire-building through value-destructive acquisitions. Dividend yield captures a subset of this population: specifically, companies distributing through dividends. It misses the equally large and often higher-returning segment that distributes primarily through buybacks.

Faber built on earlier work by William Priest and Lindsay McClelland, whose research on combining free cash flow and total capital return established the foundational framework Faber would operationalize. Priest and McClelland focused on the free cash flow angle: companies generating high free cash flow relative to market cap and returning it to shareholders rather than deploying it at below-cost returns. Faber operationalized this into a cleaner two-variable screener, sorted by the combined dividend and net buyback figure, and tested it across multiple market cycles and geographies. The return data confirmed the thesis held. The central insight was that the mechanism of return — dividends or buybacks — matters far less than the total magnitude of cash returned to shareholders relative to the price paid to own the stock.

### Why Was the Shareholder Yield Effect Strongest in International Markets?

Outside the United States, share repurchases were structurally less common and, in some markets, legally restricted or culturally uncommon through much of the period Faber studied. This means that high-dividend-yield companies in international markets were already capturing most of the high-shareholder-yield population — the two signals overlapped significantly. But where a non-US company ran buybacks instead of, or alongside, dividends, the dividend-only screen missed that capital return entirely. The gap between dividend-yield ranking and shareholder-yield ranking in those cases translated directly into a return differential that dividend screens systematically failed to predict.

In the US market, where buybacks have been dominant since the mid-1990s, the gap between dividend yield and shareholder yield is wider and more systematic across sectors. The top-quintile dividend yield stocks in the US concentrate heavily in utilities, real estate investment trusts, and regulated businesses that pay dividends by structural necessity rather than because they generate the most excess free cash flow. The top-quintile shareholder yield stocks draw from a far broader sector universe — technology, consumer, healthcare, and industrial companies that pay modest dividends but run substantial repurchase programs funded by genuinely high free cash flow generation. A dividend-only screen does not reach this population.

---

## The Three Data Problems That Break Standard Screeners

### Problem 1: Authorized Buybacks vs. Executed Buybacks

Companies announce share repurchase authorizations as press releases and earnings call talking points. A **$10 billion** buyback authorization makes financial news. The actual buybacks executed under that authorization — which may be **$1 billion** spread over three years, or **$9 billion** completed in six months — appear in the cash flow statement of the 10-K or 10-Q, under financing activities, labeled "repurchases of common stock" or "payments for repurchase of common stock." The two numbers are frequently, sometimes dramatically, different.

Aggregator platforms that build buyback yield estimates from authorization announcements — a common shortcut — overstate actual buybacks in companies where the authorization was partially or slowly executed and understate it in companies that ran accelerated programs without formal announcement. GeminIQ sources buyback data from the as-filed cash flow statement, where actual cash paid for repurchases during each period is a reported financial statement figure, not an estimate derived from announcement history. The authorization tells you what management intended. The filing tells you what they did.

### Problem 2: Gross Buybacks vs. Net Buybacks — The SBC Erosion Effect

A company can spend **$1 billion** on buybacks in a fiscal year and simultaneously issue **$700 million** in new shares through stock-based compensation vesting, restricted stock unit deliveries, and employee equity purchase programs. The gross buyback yield on the **$1 billion** figure is very different from the net buyback yield on the **$300 million** net figure — and only the net figure represents real capital return to outside shareholders.

GeminIQ's screener addresses this through two filters. The [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) filter set to **≤ 0** identifies companies where the diluted share count is flat or declining, confirming that net buyback activity is reducing the total share count rather than merely offsetting new SBC issuance. The [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric further contextualizes how large the equity compensation issuance is relative to operating scale — a company running **3% stock-based compensation to revenue** may show a meaningful-looking gross buyback program that delivers very little net capital return once the SBC offset is accounted for. Standard screeners that display only gross buyback activity miss this erosion entirely. As-filed data captures both flows in the same filing.

### Problem 3: Debt-Financed Buybacks

Not all high shareholder yield companies are generating that yield from excess free cash flow. Some of the highest apparent shareholder yields in any given screening period come from companies that financed their repurchases by issuing debt — borrowing at fixed rates and using the proceeds to reduce their float. This is a leveraged recapitalization, not a sign of excess cash generation, and it changes the risk profile of the investment entirely. A company with genuine **7% shareholder yield** is distributing surplus cash produced by operations. A company with **7% apparent shareholder yield** built by issuing bonds to fund repurchases at elevated valuations has not returned value to shareholders — it has transferred it from future equity holders to current ones, at the cost of a more fragile balance sheet.

The GeminIQ screener filters for [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) **≤ 1.5**, reducing exposure to the most aggressively leveraged buyback programs. But the most direct diagnostic is the balance sheet trend: is long-term debt rising in parallel with a declining share count? When long-term debt trends upward alongside a declining share count, shareholders are not receiving a return from operations — they are receiving a transfer financed by creditors. That distinction is visible in the as-filed balance sheet and cash flow statement, and it appears in the filing data long before management acknowledges it publicly.

---

## How to Run the GeminIQ Shareholder Yield Screener

The GeminIQ [Shareholder Yield Screener](/screens/stock-screeners/shareholder-yield) applies five filters that together isolate companies delivering genuine, cash-flow-supported total capital return — with each filter sourced from as-filed XBRL data rather than aggregator-normalized estimates.

## Step 1: Open the GeminIQ Stock Screener

Open the GeminIQ [Stock Screener](/features#screener).

## Step 2: Apply the Five Core Filters

| Filter                                                                         | Operator | Value |
| ------------------------------------------------------------------------------ | -------- | ----- |
| [Dividend Yield TTM](/metrics/valuation-metrics/dividend-yield)                | ≥        | 1%    |
| [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio)            | =        | 1     |
| [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield)    | ≥        | 5%    |
| [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) | ≤        | 1.5   |
| [Net Profit Margin TTM](/metrics/margin-metrics/net-profit-margin)             | ≥        | 5%    |

Each filter targets a distinct dimension of the framework. The [Dividend Yield TTM](/metrics/valuation-metrics/dividend-yield) floor at **≥ 1%** establishes that some cash dividend component exists — a test that the company has committed to at least a baseline return mechanism beyond buybacks alone. The [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) at **≤ 0** confirms the share count is flat or shrinking, meaning buybacks at minimum equal new issuance from equity compensation programs. The [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield) at **≥ 5%** confirms the combined capital return is supported by actual free cash flow generation rather than balance sheet extraction or debt issuance. For a full explanation of how this metric is calculated from as-filed SEC data and where third-party platforms introduce divergence, see [Free Cash Flow Yield Explained: How to Find Undervalued Stocks](/blog/free-cash-flow-yield-explained). The [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) cap at **≤ 1.5** reduces exposure to companies sustaining capital return through borrowing rather than operational cash generation. And the [Net Profit Margin TTM](/metrics/margin-metrics/net-profit-margin) floor at **≥ 5%** provides a basic earnings quality gate — eliminating businesses where the shareholder yield is being maintained despite deteriorating operating profitability.

## Step 3: Set the Sort Order

Set **Sort By** to [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield), direction **Descending** — placing companies with the most cash flow available to sustain capital returns at the top of the results.

---

## Adding the Valuation Check

High shareholder yield at an expensive price is not an attractive screener result — and the GeminIQ screener supports an optional valuation overlay that addresses this directly. The concern is straightforward: a company buying back its own stock at **40× earnings** is destroying per-share value through those repurchases regardless of the dollar amount, because the equity being retired costs more than it is worth. The highest-quality shareholder yield results are companies where the repurchase program is value-accretive — where management is retiring shares at prices at or below a reasonable estimate of intrinsic value, concentrating future earnings power in the remaining shares.

To add the valuation check, apply these two additional filters:

| Filter                                                        | Operator | Value |
| ------------------------------------------------------------- | -------- | ----- |
| [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) | ≤        | 20    |
| [P/E TTM](/metrics/valuation-metrics/price-to-earnings-ratio) | ≥        | 1     |

The lower bound of **≥ 1** removes companies with meaningless or negative trailing earnings figures — avoiding the distortion that occurs when a one-time write-off or restructuring charge produces a technically low P/E with no real valuation signal attached to it. The upper bound at **≤ 20** is a probability filter, not a hard quality threshold: companies repurchasing their own stock at under **20×** earnings are more likely to be creating per-share value through those buybacks than companies executing the same program at **30× or 40×** earnings. This is consistent with Faber's observation that the shareholder yield strategy performs best when combined with some discipline around entry price — the optimal shareholder yield candidate returns capital from genuine free cash flow surplus, at a valuation that has not already fully priced in that return behavior.

---

## Reading Your Results: What to Verify Beyond the Filters

Screener output is the beginning of analysis, not the end. Three additional checks belong on every candidate before further research.

The most direct starting point is confirming the actual buyback dollars in the as-filed cash flow statement and comparing them against the share count trend across multiple periods. GeminIQ's pre-calculated [Treasury Stock Change](/metrics/remaining-metrics/treasury-stock-change) metric tracks the period-over-period change in treasury stock balance as a data-sourced proxy for net buyback activity. The most complete verification, however, is the financing activities section of the cash flow statement in GeminIQ's [Financial Statements](/features#financial-statements) view: locate the repurchases line and confirm the cash figure is material relative to market cap, then check diluted shares outstanding across the last six to eight quarters on the balance sheet. A company with a small buyback program that narrowly clears the [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) filter may technically qualify but deliver negligible effective yield through the buyback component. The share count trend over time is the proof.

Cross-checking the balance sheet debt trend against the buyback activity is the second check. In GeminIQ's [Financial Statements](/features#financial-statements) view, compare long-term debt across the last several quarters against the repurchase figures in the financing section. Rising long-term debt alongside a declining share count means the buyback program is at least partially debt-financed — the screener's [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) filter reduces this risk but does not eliminate it, because a company starting from a clean balance sheet can increase leverage meaningfully while remaining below the **1.5** threshold. The direction of travel matters as much as the current level.

The third check is whether the [Free Cash Flow Yield TTM](/metrics/valuation-metrics/free-cash-flow-yield) sustainably covers the combined capital return. Add the [Dividend Yield TTM](/metrics/valuation-metrics/dividend-yield) to the estimated net buyback yield — actual repurchase dollars from the cash flow statement divided by current market cap. If the combined total exceeds the free cash flow yield, the company is returning more capital than it generates, depleting cash reserves or borrowing to sustain the distribution. GeminIQ's pre-calculated [Free Cash Flow](/metrics/calculated-values/free-cash-flow) metric, sourced directly from as-filed operating cash flow and capital expenditure figures, gives you the numerator for this check without requiring any third-party normalization. A sustainable shareholder yield is one where free cash flow generation comfortably exceeds the combined dividend and net buyback outflow — with room remaining to invest in the business alongside the capital return program. When free cash flow coverage is thin, the yield is at risk. The filing data will show it before the press release does.

---

## Frequently Asked Questions

### Is Shareholder Yield Better Than Dividend Yield?

For the purpose of measuring total capital return to equity holders, shareholder yield is a more complete metric. It captures both primary return channels rather than one, and it corrects for dilution from equity compensation that dividend yield ignores. As a stock selection signal, Faber's research found the combined measure produced stronger five-year return predictions than dividend yield alone. Whether it is "better" in any single instance depends on context: for companies that distribute predominantly through dividends, the two metrics converge and the distinction is minor. For companies distributing predominantly through buybacks, dividend yield misses most of the picture. Shareholder yield is the more generalizable measure across the full range of capital allocation styles.

### Does Shareholder Yield Include Debt Paydown?

The standard two-component formula — dividends plus net buybacks divided by market cap — does not include debt paydown. Some practitioners use an expanded version that adds principal debt reduction to the numerator, on the logic that improving the balance sheet accrues value to equity holders. In practice, the two-component version is more widely used because it is reproducible directly from the financing activities section of the filed cash flow statement without requiring assumptions about the optimal leverage target or the marginal value of debt reduction. If debt paydown is a material part of a company's capital allocation strategy, it will typically show in the [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) trend over time — declining leverage is visible in the filed balance sheet data.

### What Is a Good Shareholder Yield?

There is no universally agreed absolute threshold, but academic research and quantitative practitioner studies focus on the top quintile of a screened universe — the highest **20%** of shareholder yield stocks in a given market or index. In practice, screener thresholds in the **5% to 10%** combined yield range tend to isolate this population. The absolute yield figure matters less than the combination of characteristics around it: the yield is supported by demonstrable free cash flow, the net share count is declining rather than flat, the balance sheet is not deteriorating in parallel, and the entry valuation does not already fully price in the capital return behavior. A company returning **7% of its market cap** annually from surplus operating cash flow, at a reasonable price, is a more attractive shareholder yield candidate than one returning **10%** financed by asset sales and debt.

### How Is Shareholder Yield Different From Total Shareholder Return?

Total shareholder return (TSR) is a backward-looking performance metric measuring actual price appreciation plus dividends received over a specific historical period. It is a realized return figure used to evaluate past investment outcomes. Shareholder yield is a forward-looking screening signal built from current fundamental data — how much capital is the company returning right now, as a percentage of the price paid, based on the most recently filed financial statements. TSR tells you how an investment performed; shareholder yield is one input into assessing where forward returns might be concentrated. The two metrics share no mathematical relationship despite the similar-sounding names, and conflating them is a common source of confusion in income investing discussions.

---

## Related Reading

For investors building a systematic capital-return screening process, these posts cover closely related frameworks and the data considerations that accompany them.

[Free Cash Flow Yield Explained: How to Find Undervalued Stocks](/blog/free-cash-flow-yield-explained) covers how free cash flow yield is calculated from as-filed SEC data and why aggregator-normalized FCF figures diverge from the as-filed figure — directly relevant because FCF yield is the sustainability check at the core of the shareholder yield framework.

[Magic Formula Investing: Greenblatt's Strategy Explained](/blog/magic-formula-investing-explained) covers Joel Greenblatt's systematic approach to combining an earnings yield signal with a capital efficiency signal — the original quantitative framework for pairing a yield measure with a quality measure, and the conceptual ancestor of strategies like shareholder yield.

[Return on Invested Capital (ROIC): Formula and Benchmarks](/blog/roic-return-on-invested-capital-explained) provides the framework for evaluating whether companies in a shareholder yield screen are generating high returns on the capital they retain, which determines whether the buyback program is competing with high-quality internal reinvestment opportunities or is genuinely the best available use of excess cash.

[Piotroski F-Score: How to Spot a Value Trap Before It Snaps Shut](/blog/piotroski-f-score-value-trap) is a nine-signal financial health scoring system that functions as a quality overlay on any quantitative screener output — useful for filtering shareholder yield candidates for deteriorating operating fundamentals before they show up in the yield or debt metrics.

[GARP Investing: Peter Lynch's PEG Ratio Strategy Explained](/blog/garp-investing-peter-lynch-explained) covers the PEG ratio approach and how growth-oriented investors pair valuation discipline with quality signals — a complementary entry point for understanding how the valuation check interacts with yield-based strategies.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=shareholder-yield-dividends-buybacks-explained)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Simply Wall St Alternative: The Underlying Filings
source: https://www.geminiq.com/blog/simply-wall-st-alternative-sec-data

### Simply Wall St Alternative: The Underlying Filings
A Simply Wall St alternative for investors who want the numbers behind the picture. The Snowflake compresses 30 pass/fail checks into one shape; this post explains what threshold scoring discards and where the checks stop being filing data.

The Simply Wall St Snowflake is the most successful piece of design in retail investing software. One shape, five axes, instant read. It took financial statement analysis — a discipline that intimidates most people out of ever attempting it — and made it glanceable. Millions of investors who would never open a 10-K have at least looked at a company's fundamentals because of it, and that is a real contribution.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=simply-wall-st-alternative-sec-data)**

Understanding what the shape is made of explains both its appeal and its ceiling. Simply Wall St's help documentation describes the Snowflake as a visual summary across five assessment criteria — Valuation, Future Growth, Past Performance, Financial Health, and Dividends — with six individual checks performed for each criterion. Thirty checks. Each one passes or fails. The results determine the size, shape, and color of the shape you see.

Thirty binary answers, rendered as a picture. That is an enormous amount of compression, and compression is lossy by definition.

## Table of Contents

- [What a Pass/Fail Check Throws Away](#what-a-passfail-check-throws-away)
- [Not Every Check Is Filing Data](#not-every-check-is-filing-data)
- [The Shape Is Not the Analysis](#the-shape-is-not-the-analysis)
- [Where Simply Wall St Earns Its Place](#where-simply-wall-st-earns-its-place)
- [Reading the Statements the Checks Were Run On](#reading-the-statements-the-checks-were-run-on)
- [Graduating From the Picture](#graduating-from-the-picture)
- [Frequently Asked Questions](#frequently-asked-questions)

## What a Pass/Fail Check Throws Away

A threshold converts a measurement into a verdict, and the cost is magnitude.

Consider any check of the form "is this ratio below a limit." A company sitting just inside the line and a company sitting far inside it both pass, and the check cannot distinguish them. A company just outside fails, alongside one in serious trouble. Three companies with materially different financial positions produce two identical outcomes and one that overstates the difference.

Direction disappears too. A metric improving rapidly toward a threshold and a metric deteriorating rapidly toward it from the other side can both fail this quarter, and the check treats them the same. Trajectory is usually the most informative thing in a filing history, and a binary snapshot has no way to carry it.

Then the thirty results get compressed again into five axis scores, and the five get rendered as one shape. By the time the picture is drawn, an investor is three transformations from the number.

None of that makes the checks wrong. It makes them a filter — useful for excluding, weak for deciding.

## Not Every Check Is Filing Data

The more consequential point is that some of the criteria cannot come from a 10-K at all.

Simply Wall St's own valuation documentation describes six checks in the valuation section, with the first two based on intrinsic valuation and the remaining four on relative valuation and analyst price target forecasts. Its published company analyses describe [discounted cash flow](/blog/dcf-valuation-model-step-by-step) models built on analyst and extrapolated projections, and its commentary states plainly that it works from historical data and analyst forecasts.

The Future Growth arm is, by construction, a forecast arm. Analyst estimates are not reported facts, they are not filed anywhere, and they revise continuously. A company's Snowflake can change shape without a single new filing, because the consensus behind the growth and valuation checks moved.

That is fine as long as you know which arms are which. It becomes a problem when the shape is read as a summary of the company rather than as a blend of what the company reported and what the sell side currently expects.

## The Shape Is Not the Analysis

There is a specific failure mode that visual scoring encourages, and it has nothing to do with the accuracy of the underlying checks.

A green shape produces confidence, and confidence does not require detail. An investor who has seen a large green Snowflake feels informed, and that feeling is exactly what stops the next question from being asked. Which check failed? Was the failure marginal or severe? Is the metric improving? What changed in the last filing? A picture designed for speed is not designed to prompt any of those.

Simply Wall St is candid about the intent — its documentation describes the Snowflake as a way to quickly scan a stock, a group of stocks, or a whole market. Scanning is exactly what it is for.

The mistake belongs to the reader who mistakes a scan for a decision. Nobody buys a house on a listing photo, and the Snowflake is a listing photo. Very good ones are still not surveys.

## Where Simply Wall St Earns Its Place

The product deserves credit for what it does well, and at roughly the price of a coffee a month there is not much to argue with.

Comparing thirty companies quickly is a real task and the Snowflake is close to the best tool for it. Portfolio-level views that show the shape of everything you own at once surface concentration and quality issues faster than a spreadsheet does. Automated alerts when the underlying data moves against a thesis are useful for anyone who cannot monitor positions daily. And for an investor early in their education, the checks function as a curriculum — each one names a concept worth learning.

None of that is diminished by saying the picture is a starting point. It is a very good starting point.

The question is what happens next, because the platform's own model has an answer built in: the checks tell you which arms are weak, which is a prompt to go look.

## Reading the Statements the Checks Were Run On

GeminIQ is the other end of that workflow. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value — the statements themselves, not a verdict about them.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, so a metric near a threshold can be read as a trajectory rather than a verdict. [Visualizations](/features#visualizations) chart the reported structure over time, which is where direction becomes visible. [Custom Tables](/features#custom-tables) assemble specific reported line items. [Calculated Metrics](/features#calculated-metrics) including [Current Ratio](/metrics/liquidity-ratios/current-ratio), [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, so the number behind a passed or failed check can be inspected rather than inferred. For learning what the checks are actually testing, [how to read a 10-K](/blog/how-to-read-10-k) and [how to calculate financial ratios from a 10-K](/blog/how-to-calculate-financial-ratios-10k) cover the mechanics.

[Carvana's](/stocks/CVNA) 2022 filings are the clearest available demonstration. Its [Altman Z-Score](/blog/altman-z-score-financial-distress) read **1.86** in March 2022, **1.42** in June, **1.30** in September, and **1.09** by December — below the **1.81** distress threshold for five consecutive quarters. A binary check run in March returns the same result as one run in December.

The two quarters were not the same company. [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) fell from **15.1%** trailing in December 2021 to **13.4%**, **11.9%**, **10.8%**, and **9.2%** across that year, and Total Shareholders' Equity turned negative for the first time in Carvana's public history at **-$1.05 Billion**. Direction was the entire signal, and a pass-or-fail check has no way to carry it. The [Carvana record](/blog/carvana-stock-crash-recovery) traces the whole sequence.

There is no shape, no score, and no forecast. What there is instead is the reported record the checks were run against.

## Graduating From the Picture

Every investor starts somewhere, and starting with a picture is better than starting with nothing.

The transition worth naming is the one from screening to owning. A visual summary is built for the first — narrowing a universe fast, at low cost, without needing to understand every metric on the page. Ownership is different, because the position moves and the questions get harder, and a shape has nothing more to give once you have already seen it.

For the same compression problem expressed as a composite rank rather than a shape, the [GuruFocus alternatives](/blog/gurufocus-alternative-sec-data) and [Morningstar alternatives](/blog/morningstar-alternative-sec-filing-data) posts cover scoring layers built on licensed data.

At that point the checks have done their job. They pointed at which arm was weak. The filings are where you find out why — and a thesis built on a shape is a thesis you cannot examine when it stops working.

## Frequently Asked Questions

### What are the best Simply Wall St alternatives?

It depends on what you are replacing. For visual screening and portfolio-level summaries, the substitutes are other retail platforms with scoring systems, all of which compress underlying data into a rating in some form. For the statements underneath, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability, which supplies the numbers rather than a verdict on them.

### How does the Simply Wall St Snowflake work?

Simply Wall St's documentation describes it as a visual summary across five assessment criteria — Valuation, Future Growth, Past Performance, Financial Health, and Dividends — with six individual checks performed for each criterion. The results of those checks determine the size, shape, and color of the Snowflake.

### Is the Snowflake based on SEC filings?

Partly. The Past Performance and Financial Health arms draw on reported financial data, while the Future Growth arm and several valuation checks depend on analyst forecasts and consensus price targets, which are not filed anywhere. A company's Snowflake can change without a new filing, because the estimates behind those checks revised.

### Is Simply Wall St good for beginners?

It is one of the better on-ramps available, because each check names a concept worth learning and the visual format removes the intimidation that stops most people from opening a financial statement at all. The limitation is the same as the strength — a pass or fail hides magnitude and direction, so it works better for narrowing a list than for deciding on a position.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=simply-wall-st-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Simply Wall St help center documentation on the Snowflake (five assessment criteria, six checks per criterion) and on the valuation section (six checks split between intrinsic and relative valuation plus analyst price target forecasts), reviewed August 2, 2026.
- Simply Wall St published company analyses describing DCF models built on analyst and extrapolated projections, and its standing note that its commentary is based on historical data and analyst forecasts.

---

## Blog: Stock-Based Compensation as a Percent of Revenue
source: https://www.geminiq.com/blog/stock-based-compensation-percent-of-revenue

### Stock-Based Compensation as a Percent of Revenue
Stock-based compensation as a percent of revenue is a direct measure of how much of a company's top line is being handed to employees in equity rather than earned as economic profit, and in GeminIQ's data, the highest-ranked company currently spends more on stock compensation than it collects in trailing revenue.

**[IonQ](/stocks/IONQ)** paid out **$354.709 Million** in trailing-twelve-month stock-based compensation against **$246.474 Million** in trailing revenue — stock compensation equal to **143.9%** of everything the company brought in. [Stock Compensation](/metrics/calculated-values/stock-based-compensation) as a share of revenue — GeminIQ's [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric — is one of the cleanest single-line checks on how much of a company's reported growth is being funded by handing out equity rather than earned as economic profit, and it requires no adjustment or estimate: both figures sit on the filing itself.

This leaderboard reads GeminIQ's calculated Stock Compensation and Net Revenue figures across GeminIQ's current cross-sectional filing snapshot — **6,095** companies with data through at least February 2025 — restricted to companies with at least **$100 Million** in trailing revenue. **2,446** companies meet that bar, ranked by stock compensation as a percentage of trailing revenue.

## The Ranking

| Rank | Company | Ticker | Stock Compensation (TTM) | Net Revenue (TTM) | SBC as % of Revenue |
|---|---|---|---|---|---|
| 1 | IonQ, Inc. | IONQ | **$354.709 Million** | **$246.474 Million** | **143.9%** |
| 2 | Joby Aviation, Inc. | JOBY | **$153.300 Million** | **$116.295 Million** | **131.8%** |
| 3 | Blue Owl Capital Inc. | OWL | **$716.191 Million** | **$623.172 Million** | **114.9%** |
| 4 | C3.ai, Inc. | AI | **$263.715 Million** | **$250.268 Million** | **105.4%** |
| 5 | Figma, Inc. | FIG | **$1,554.575 Million** | **$1,509.670 Million** | **103.0%** |
| 6 | StepStone Group Inc. | STEP | **$1,910.368 Million** | **$2,008.205 Million** | **95.1%** |
| 7 | AST SpaceMobile, Inc. | ASTS | **$100.432 Million** | **$115.299 Million** | **87.1%** |
| 8 | Hinge Health, Inc. | HNGE | **$662.101 Million** | **$843.886 Million** | **78.5%** |
| 9 | Freedom Holding Corp. | FRHC | **$91.282 Million** | **$121.732 Million** | **75.0%** |
| 10 | Ginkgo Bioworks Holdings, Inc. | DNA | **$86.854 Million** | **$132.421 Million** | **65.6%** |
| 11 | Kymera Therapeutics, Inc. | KYMR | **$63.426 Million** | **$105.000 Million** | **60.4%** |
| 12 | Arcus Biosciences, Inc. | RCUS | **$68.000 Million** | **$117.000 Million** | **58.1%** |
| 13 | Beam Therapeutics Inc. | BEAM | **$89.155 Million** | **$156.035 Million** | **57.1%** |
| 14 | StubHub Holdings, Inc. | STUB | **$1,516.676 Million** | **$2,764.301 Million** | **54.9%** |
| 15 | SpringWorks Therapeutics, Inc. | — | **$108.626 Million** | **$200.123 Million** | **54.3%** |

## IonQ: Stock Compensation Exceeds Total Revenue

**[IonQ](/stocks/IONQ)** tops this leaderboard at **143.9%** — trailing stock compensation larger than the company's entire trailing revenue. IonQ operates in quantum computing, a category where the underlying technology is still early and the labor market for the specialized talent required is both narrow and expensive, which is reflected directly in this ratio rather than left to a company's own characterization of its cost structure.

<center><sup>GeminIQ Custom Table for IonQ: quarterly Share Based Compensation and Revenues ($ millions), June 2026 back to March 2025.</sup></center>

## Joby Aviation: A Pre-Revenue-Scale Aerospace Story

**[Joby Aviation](/stocks/JOBY)** ranks second at **131.8%**, with **$153.300 Million** in stock compensation against **$116.295 Million** in trailing revenue. Joby is developing electric vertical takeoff and landing aircraft, a capital- and talent-intensive category still in early commercialization, and the ratio here reflects a company paying today for engineering talent its revenue base has not yet grown to support.

## Blue Owl Capital: The Largest Dollar Figure Outside Software

**[Blue Owl Capital](/stocks/OWL)** ranks third at **114.9%**, and stands out on this list for what it isn't: a pre-revenue technology or biotech name. Blue Owl is an alternative asset manager, and its **$716.191 Million** in stock compensation against **$623.172 Million** in trailing revenue shows the same dynamic — equity-heavy compensation outrunning the top line — showing up in a completely different industry than the rest of the leaderboard.

<center><sup>GeminIQ Custom Table for Blue Owl Capital: quarterly Share Based Compensation and Revenues ($ millions), June 2026 back to March 2025.</sup></center>

## The Method

Stock Compensation and Net Revenue are both GeminIQ calculated figures, built directly from as-filed cash flow statement and income statement data on a trailing-twelve-month basis. The ranking is restricted to companies with at least $100 Million in trailing revenue, to exclude small or newly-reporting companies where the ratio can be driven by a thin revenue base rather than a truly large compensation figure. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's Stock Compensation and Net Revenue on GeminIQ's [Financial Statements](/features#financial-statements) view and divide one by the other directly. A ratio climbing toward or past 50% of revenue is worth tracking over several periods — whether it's narrowing as the business scales, or holding flat while revenue grows, tells a different story than a single period's figure on its own.

## Frequently Asked Questions

### What does it mean when stock-based compensation exceeds 100% of revenue?

It means a company's trailing stock-based compensation expense is larger than its entire trailing revenue. This is most common at early-stage, technically specialized companies — quantum computing, advanced aerospace, and similarly talent-intensive categories are represented at the top of this leaderboard — where the labor cost of building the business currently outweighs the revenue the business has scaled to.

### How many companies are in this ranking's universe?

**2,446** companies with at least **$100 Million** in trailing revenue and a calculated Stock Compensation figure, drawn from GeminIQ's current **6,095**-company filing snapshot.

### Is a high stock-compensation-to-revenue ratio always a warning sign?

Not on its own. Early-stage, technically specialized businesses commonly run high ratios while scaling toward profitability, and several names on this leaderboard are pre-profitability by design at this stage. The more useful check is the trend over several periods — whether the ratio is narrowing as revenue scales, which is the pattern a maturing business is expected to show.

### Does this ranking include financial companies?

Yes. Unlike a [free-cash-flow comparison](/blog/stock-compensation-exceeds-free-cash-flow), a stock-compensation-to-revenue ratio doesn't depend on how a company's cash flow statement behaves, so this leaderboard includes companies like Blue Owl Capital, an alternative asset manager, alongside the technology and biotech names that otherwise dominate the list.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-based-compensation-percent-of-revenue)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe drawn from GeminIQ's calculated Stock Compensation and Net Revenue metrics across GeminIQ's current cross-sectional filing snapshot of 6,095 companies, restricted to companies with at least $100 Million in trailing revenue (2,446 companies), built from as-filed 10-K and 10-Q data publicly available on [SEC EDGAR](https://www.sec.gov/). Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Stock Buybacks vs. Stock Compensation: Running in Place
source: https://www.geminiq.com/blog/stock-buybacks-vs-stock-compensation

### Stock Buybacks vs. Stock Compensation: Running in Place
A ranked leaderboard of the companies where stock-based compensation issuance offset the entire share-count benefit of a multi-billion-dollar buyback program, built from ten years of as-filed SEC 10-K data via GeminIQ.

**Every buyback press release implies the same promise: fewer shares outstanding, a more concentrated ownership stake for whoever holds on. Stock buybacks vs. stock compensation is the fight actually happening underneath that promise, and GeminIQ's as-filed data shows it going the wrong way for a specific, named group of companies. Screening a decade of 10-K filings turns up fifty-four companies that spent $1 billion or more repurchasing their own stock while diluted shares stayed flat or climbed anyway — not because the buybacks were fake, but because stock-based compensation was issuing new shares just as fast, or faster, than the buyback was retiring them. The company leading the list spent $6.0 Billion on buybacks against $109.2 Billion in stock comp.**

This study reads the FY2015–FY2024 10-K filings of every company in GeminIQ's as-filed database with a complete ten-year filing history — 3,053 companies. From that universe, 614 companies spent more than $1 billion on buybacks over the decade; 126 of them saw diluted shares stay flat or rise anyway. This ranking excludes any company where a single fiscal year drove a 15%-or-larger jump in diluted shares — that pattern belongs to a stock-for-stock acquisition, not equity compensation, and folding the two together would misattribute the cause. What's left is 54 companies where the dilution reads as compensation-driven, ranked below by stock-based compensation as a percentage of buyback spend.

## The Leaderboard

Standard financial media coverage of a buyback announcement stops at the headline dollar figure. But standard financial media doesn't read the footnotes — specifically, the `Share Based Compensation` line sitting two rows below `Payments For Repurchase Of Common Stock` on the same cash flow statement. The fifteen companies below spent the most on repurchases while handing back the most through equity awards.

| Rank | Company | Buyback Spend (10-Yr) | Stock Comp (10-Yr) | SBC as % of Buyback | Diluted Share Change |
|---|---|---|---|---|---|
| 1 | [Amazon](/stocks/AMZN) | **$6.00 Billion** | **$109.21 Billion** | **1,820%** | **+12.4%** |
| 2 | [Carlyle Group](/stocks/CG) | **$1.33 Billion** | **$2.55 Billion** | **191%** | **+23.2%** |
| 3 | [Salesforce](/stocks/CRM) | **$11.62 Billion** | **$17.08 Billion** | **147%** | **+57.7%** |
| 4 | [Ford Motor Company](/stocks/F) | **$2.05 Billion** | **$2.88 Billion** | **141%** | **+0.3%** |
| 5 | [Costco](/stocks/COST) | **$4.52 Billion** | **$6.11 Billion** | **135%** | **+0.5%** |
| 6 | [Illumina](/stocks/ILMN) | **$2.15 Billion** | **$2.88 Billion** | **134%** | **+6.7%** |
| 7 | [American Tower](/stocks/AMT) | **$1.09 Billion** | **$1.35 Billion** | **123%** | **+10.7%** |
| 8 | [Vertex Pharmaceuticals](/stocks/VRTX) | **$4.11 Billion** | **$4.09 Billion** | **99.6%** | **+6.9%** |
| 9 | [Stryker](/stocks/SYK) | **$1.55 Billion** | **$1.46 Billion** | **94%** | **+1.2%** |
| 10 | [Invesco](/stocks/IVZ) | **$1.75 Billion** | **$1.52 Billion** | **87%** | **+6.6%** |
| 11 | [PTC](/stocks/PTC) | **$1.49 Billion** | **$1.26 Billion** | **85%** | **+4.1%** |
| 12 | [Incyte](/stocks/INCY) | **$2.00 Billion** | **$1.65 Billion** | **82%** | **+12.4%** |
| 13 | [Arista Networks](/stocks/ANET) | **$2.28 Billion** | **$1.58 Billion** | **69%** | **+12.1%** |
| 14 | [Intuitive Surgical](/stocks/ISRG) | **$5.93 Billion** | **$3.78 Billion** | **64%** | **+6.1%** |
| 15 | [Lumentum Holdings](/stocks/LITE) | **$1.16 Billion** | **$0.73 Billion** | **63%** | **+14.5%** |

<center><sup>GeminIQ data study: stock-based compensation as a percentage of buyback spend, ranked, for companies with $1B+ in FY2015–FY2024 buybacks and a flat-or-rising diluted share count. Built from as-filed 10-K `Payments For Repurchase Of Common Stock` and `Share Based Compensation` data via GeminIQ. n = 54 companies, FY2015–FY2024.</sup></center>

## Amazon: One Buyback in Ten Years, $109 Billion in Stock Comp

[Amazon](/stocks/AMZN) tops this list, but not because a buyback program spiraled out of control. It tops the list because there was barely a buyback program at all. Across the ten fiscal years in this study, Amazon's 10-K reports a nonzero `Payments For Repurchase Of Common Stock` figure exactly once.

**The Filing Data:** FY2022 shows **$6.0 Billion** in buybacks — the only year in the decade with a real number on that line. Every other year from FY2015 through FY2024, the figure is effectively zero. `Share Based Compensation`, meanwhile, climbed in nine of those ten years, reaching a peak of **$24.0 Billion** in FY2023 before easing slightly to **$22.0 Billion** in FY2024, and totaling **$109.2 Billion** across the full window.

**The GeminIQ Edge:** Weighted average diluted shares climbed from **9.54 Billion** in FY2015 to **10.72 Billion** in FY2024, a **12.4%** increase, while the one-time buyback barely registered against it. GeminIQ's [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric shows the dollar figure isn't even accelerating relative to the business: **2.7%** of revenue in FY2015, peaking at **4.2%** in FY2023 before easing to **3.45%** in FY2024 — low for a mature technology company by GeminIQ's own benchmark. The story here isn't stock comp overwhelming an active repurchase program, or stock comp spiraling as a share of the business. It's stock comp compounding for a decade in the near-total absence of a buyback program to offset it.

<center><sup>GeminIQ Financial Statements, Amazon's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` at **$6.0 Billion** in FY2022 — the only nonzero year in the decade — against `Share Based Compensation` climbing to **$22.0 Billion** in FY2024.</sup></center>

## Carlyle Group: The Year the Buyback Finally Grew, So Did the Stock Comp

[Carlyle Group](/stocks/CG) spent modestly on buybacks for most of the decade — well under $200 Million in most years — while stock-based compensation ran in the low hundreds of millions annually. Then FY2024 arrived.

**The Filing Data:** Carlyle's FY2024 10-K reports **$554.6 Million** in buybacks, more than double any prior year in the study window. `Share Based Compensation` for the same fiscal year came in at **$467.9 Million**, up from **$249.1 Million** the year before — nearly doubling in step with the buyback.

**The GeminIQ Edge:** The one year Carlyle got serious about repurchases, its equity compensation expense got serious about growing too. Weighted average diluted shares still finished the decade at **1.104 Billion**, up **23.2%** from **896.2 Million** in FY2015. The acceleration in buybacks didn't reverse a decade of dilution — it ran alongside a matching acceleration in the cause.

<center><sup>GeminIQ Financial Statements, Carlyle Group's Cash Flow Statement, showing FY2024 `Payments For Repurchase Of Common Stock` of **$554.6 Million** alongside `Share Based Compensation` of **$467.9 Million** in the same fiscal year.</sup></center>

## Salesforce: A Buyback Built to Fix Dilution, Undone by the Same Dilution

[Salesforce](/stocks/CRM) authorized its first-ever [stock buyback](/blog/do-buybacks-reduce-share-count) program in 2022, a move widely read at the time as a direct answer to years of shareholder pressure over stock-based compensation and dilution. For the first seven years this study covers, Salesforce had no repurchase program at all.

**The Filing Data:** Salesforce's 10-K shows **$0** in buybacks through FY2022, then **$4.0 Billion** in FY2023 and **$7.62 Billion** in FY2024. Over those same two years, `Share Based Compensation` came in at **$3.28 Billion** and **$2.79 Billion** — running at roughly a third to just over half the size of the buyback in the only years the buyback existed.

**The GeminIQ Edge:** A standard screener flags Salesforce's recent buyback activity as capital discipline finally arriving. But pulling the full ten-year Cash Flow Statement via GeminIQ shows diluted shares still finished the period at **984.0 Million**, up **57.7%** from **624.1 Million** in FY2015 — the steepest dilution of any company on this list with an active, ongoing buyback program. The buyback arrived to fix a problem it was too late, and too small relative to the prior decade's stock comp, to actually reverse.

<center><sup>GeminIQ Financial Statements, Salesforce's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` rising to **$7.62 Billion** in FY2024 against a ten-year diluted share count increase of **57.7%**.</sup></center>

## Ford Motor Company: Buybacks Too Small and Inconsistent to Matter

[Ford Motor Company](/stocks/F) spent **$2.05 Billion** on buybacks across the study window — more than every other name ranked above it except Salesforce. Its diluted share count barely moved at all: **4.02 Billion** shares in FY2024 versus roughly **4.01 Billion** in FY2015, a change of just **+0.3%**.

**The Filing Data:** Ford's buyback line went to **$0** twice in the decade, FY2020 and FY2021, both years the company suspended repurchases entirely. In every other year spending ranged from **$129 Million** to **$484 Million** — a modest, inconsistent program next to a `Share Based Compensation` line that grew from **$199 Million** in FY2015 to **$511 Million** in FY2024, more than doubling. By FY2024, Ford's stock comp expense alone exceeded that year's buyback spend outright.

**The GeminIQ Edge:** Ford's 10-K doesn't carry a direct diluted-share-count tag for FY2015 through FY2017. The figure above is reconstructed as Net Income divided by Diluted EPS for those three years, a standard fallback confirmed consistent with the directly-filed FY2018–FY2024 figures, which sit in the same **3.97 Billion** to **4.04 Billion** range throughout. What the reconstructed decade shows is a share count that's been essentially frozen the entire time — not because buybacks aggressively offset dilution the way they did at [Costco](/stocks/COST), but because both forces are small relative to Ford's roughly 4 billion outstanding shares. A buyback that retires a few tens of millions of shares in a good year and an SBC program issuing a comparable number back barely register against a base that size — a different route to the same treadmill effect as the other names on this list.

<center><sup>GeminIQ Financial Statements, Ford's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` suspended entirely in FY2020 and FY2021 against `Share Based Compensation` more than doubling from **$199 Million** to **$511 Million** over the decade.</sup></center>

## Costco: The Flattest Share Count on the List, for the Wrong Reason

[Costco](/stocks/COST) already came up in a prior GeminIQ [10-K teardown](/blog/costco-stock-analysis-2026) as a business built on cash-flow discipline, and its diluted share count backs that reputation up on the surface — barely moving from **442.7 Million** in FY2015 to **444.8 Million** in FY2024, a change of just **0.5%**.

**The Filing Data:** Costco's buyback spend grew steadily across the decade, from **$481 Million** in FY2015 to **$700 Million** in FY2024. Stock-based compensation grew right alongside it — from **$394 Million** to **$818 Million** over the same window — and overtook the buyback figure in every year from FY2018 onward.

**The GeminIQ Edge:** A standard screener flags Costco's flat share count as capital discipline. But pulling the raw Cash Flow Statement via GeminIQ shows the flatness isn't coming from buybacks outrunning dilution — it's coming from buybacks and stock comp rising together, in near lockstep, for ten straight years. The share count tells the story: it isn't shrinking, it's being held in place by two offsetting forces that happen to move at close to the same pace.

<center><sup>GeminIQ Financial Statements, Costco's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` and `Share Based Compensation` both roughly doubling from FY2015 to FY2024 while diluted shares moved just **+0.5%**.</sup></center>

## Illumina: Paused the Buyback Right When Stock Comp Peaked

[Illumina](/stocks/ILMN) ran a modest, fairly consistent buyback program for most of the decade, spending between **$200 Million** and **$736 Million** annually through FY2020 — then stopped entirely for three straight fiscal years.

**The Filing Data:** Illumina's 10-K reports no repurchase spending for FY2021, FY2022, or FY2023 — a filed **$0** for the first two years and the line item truly absent from the third, confirmed against a second, related equity-statement repurchase tag with no entry there either. `Share Based Compensation` in FY2021 came in at **$754 Million** — nearly four times the **$194 Million** reported the year before, and the single largest annual stock comp figure in the company's ten-year window. GeminIQ's [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) confirms the scale of that spike independently: it jumped to **16.6%** of revenue in FY2021, nearly double every other year in the study window and still the clear high point of the decade.

**The GeminIQ Edge:** The three fiscal years Illumina could have leaned hardest into offsetting a stock-comp spike, it instead suspended the buyback completely. Diluted shares finished the decade at **159.0 Million**, up **6.7%** from **149.1 Million** in FY2015 — a smaller increase than most names on this list, but one that happened despite the buyback's timing, not because of it.

<center><sup>GeminIQ Financial Statements, Illumina's Cash Flow Statement, showing `Payments For Repurchase Of Common Stock` at $0 or absent for FY2021 through FY2023 against a FY2021 `Share Based Compensation` spike to **$754 Million**.</sup></center>

## The Method

This ranking reads each company's FY2015–FY2024 10-K filings only, not the interim 10-Qs — annual figures already represent the full-year total, and summing both would double-count. Companies were included if cumulative buyback spend exceeded **$1 Billion** and diluted shares stayed flat or rose over the window; companies where a single fiscal year drove a 15%-or-larger share count jump were excluded to filter out stock-for-stock acquisitions rather than compensation-driven dilution. Full methodology, including the acquisition-jump filter and data completeness rules, is detailed in [How GeminIQ Builds a Filing Data Study](/blog/filing-data-study-methodology).

## Check Your Holdings

Run this on anything already in your portfolio. Open GeminIQ's [Financial Statements](/features#financial-statements) view for the company, pull `Payments For Repurchase Of Common Stock` and `Share Based Compensation` from the Cash Flow Statement for the last five or ten fiscal years, and sum each column independently — using the annual 10-K figures only, not the quarterly filings, to avoid double-counting. Divide total stock comp by total buyback spend. A result meaningfully above 100% means the company issued more in equity awards than it retired in stock over that window. GeminIQ's [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) metric — diluted shares divided by basic shares — offers a second, independent check on the same company. A ratio holding above the 1.00–1.03 range typical of a mature company, especially one that's climbing rather than flat, confirms sustained dilutive issuance without requiring the manual sum. Neither number says the buyback was a mistake. Both tell you whether it actually reduced the share count — the only claim a buyback press release makes in the first place.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-buybacks-vs-stock-compensation)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All figures are drawn from each named company's as-filed 10-K filings for fiscal years 2015 through 2024, publicly available on [SEC EDGAR](https://www.sec.gov/). Methodology: [How GeminIQ Builds a Filing Data Study](/blog/filing-data-study-methodology).</sup>

---

## Blog: Stock Compensation Exceeds Free Cash Flow
source: https://www.geminiq.com/blog/stock-compensation-exceeds-free-cash-flow

### Stock Compensation Exceeds Free Cash Flow
Stock compensation exceeds free cash flow at 262 companies in GeminIQ's current filing data, led by Amazon's $19.314 Billion in trailing stock-based compensation against negative free cash flow, and by Figma, where stock compensation alone came to more than the company's entire trailing revenue.

**[Figma](/stocks/FIG)** paid out **$1.555 Billion** in trailing-twelve-month stock-based compensation — more than the company's entire **$1.510 Billion** in trailing revenue, even though free cash flow is still positive. Stock-based compensation gets added back on the cash flow statement because it isn't a cash outflow. That accounting treatment is accurate. It also means a company can report cash flow figures that look far healthier than the actual economic cost being handed to employees in newly issued shares, a gap that stays invisible to anyone reading only the free cash flow line.

This leaderboard reads GeminIQ's calculated [Stock Compensation](/metrics/calculated-values/stock-based-compensation) and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) figures across GeminIQ's current cross-sectional filing snapshot — 6,095 companies with data through at least February 2025 — restricted to companies with at least $100 Million in trailing revenue, stock compensation equal to at least 2% of that revenue, free cash flow not driven to an extreme by unrelated capital-intensive capex, and the Finance, Insurance & Real Estate sector excluded, since a bank or asset manager's cash flow statement isn't comparable to an operating company's. **723** companies meet that bar. **262** of them — **36.2%** — currently show stock compensation exceeding free cash flow outright.

## The Ranking

| Rank | Company | Ticker | Stock Compensation (TTM) | Free Cash Flow (TTM) | Excess |
|---|---|---|---|---|---|
| 1 | Amazon.com Inc | AMZN | **$19.314 Billion** | **-$11.625 Billion** | **$30.939 Billion** |
| 2 | Oracle Corp | ORCL | **$4.811 Billion** | **-$23.686 Billion** | **$28.497 Billion** |
| 3 | Figma, Inc. | FIG | **$1.555 Billion** | **$0.298 Billion** | **$1.256 Billion** |
| 4 | Coherent Corp. | COHR | **$0.186 Billion** | **-$1.023 Billion** | **$1.210 Billion** |
| 5 | StubHub Holdings, Inc. | STUB | **$1.517 Billion** | **$0.513 Billion** | **$1.004 Billion** |
| 6 | Axon Enterprise, Inc. | AXON | **$0.633 Billion** | **$0.133 Billion** | **$0.500 Billion** |
| 7 | fuboTV Inc. | FUBO | **$0.066 Billion** | **-$0.409 Billion** | **$0.475 Billion** |
| 8 | Rocket Lab Corp | RKLB | **$0.090 Billion** | **-$0.379 Billion** | **$0.469 Billion** |
| 9 | Snowflake Inc. | SNOW | **$1.623 Billion** | **$1.170 Billion** | **$0.453 Billion** |
| 10 | Tempus AI, Inc. | TEM | **$0.186 Billion** | **-$0.263 Billion** | **$0.449 Billion** |
| 11 | Guardant Health, Inc. | GH | **$0.191 Billion** | **-$0.241 Billion** | **$0.432 Billion** |
| 12 | Liberty Global Ltd. | LBTYA | **$0.168 Billion** | **-$0.255 Billion** | **$0.422 Billion** |
| 13 | Sunrun Inc. | RUN | **$0.105 Billion** | **-$0.315 Billion** | **$0.420 Billion** |
| 14 | Hinge Health, Inc. | HNGE | **$0.662 Billion** | **$0.272 Billion** | **$0.390 Billion** |
| 15 | Confluent, Inc. | CFLT | **$0.397 Billion** | **$0.061 Billion** | **$0.337 Billion** |

## Figma: Stock Compensation Larger Than Total Revenue

**[Figma](/stocks/FIG)** is the most striking ratio on this list, not the largest dollar figure. Trailing stock compensation of **$1.555 Billion** is larger than the company's entire trailing revenue of $1.510 Billion — stock compensation equal to **102.9%** of everything Figma brought in. Free cash flow is still positive, at **$0.298 Billion**, which is precisely what makes the comparison worth making: a company can look cash-flow-positive while its stock-compensation expense alone would have erased more than the entire top line.

<center><sup>GeminIQ Custom Table for Figma (FIG): quarterly Share Based Compensation and Revenues ($ millions) alongside trailing Free Cash Flow of $298.19M. The $1.138 Billion in stock compensation recorded in the September 2025 quarter accounts for most of the trailing total.</sup></center>

## Oracle: The Largest Free Cash Flow Deficit on the List

**[Oracle](/stocks/ORCL)** carries the widest free cash flow deficit of any company in this leaderboard: **negative $23.686 Billion**, against **$4.811 Billion** in stock compensation — **7.1%** of trailing revenue. Oracle's free cash flow figure reflects a company spending well beyond its operating cash generation, and the stock-compensation line is a real, ongoing cost layered on top of that gap rather than a rounding error inside it.

<center><sup>GeminIQ Custom Table for Oracle (ORCL): trailing Free Cash Flow of -$23.69 Billion against $4.811 Billion in Share Based Compensation over the last four quarters — the widest free cash flow deficit in this leaderboard.</sup></center>

## Snowflake: A Smaller Gap, at a Company That's Already Cash-Flow Positive

**[Snowflake](/stocks/SNOW)** shows the pattern at a more mature scale: **$1.623 Billion** in stock compensation, still exceeding **$1.170 Billion** in free cash flow despite Snowflake generating meaningfully positive cash flow on $5.033 Billion in trailing revenue. Stock compensation here runs **32.2%** of revenue — high enough that even solidly healthy free cash flow doesn't fully cover it.

## Amazon: The Largest Dollar Gap, on a Different Comparison Than Its Buyback Record

**[Amazon](/stocks/AMZN)** tops this leaderboard by dollar scale rather than by ratio — stock compensation is a modest **2.5%** of trailing revenue, but free cash flow is running **negative $11.625 Billion** over the same trailing twelve months, wide enough that the **$19.314 Billion** stock-compensation figure alone exceeds the entire cash shortfall. This is a different comparison than Amazon's decade-long stock-comp-versus-buyback record covered in GeminIQ's [stock buybacks vs. stock compensation study](/blog/stock-buybacks-vs-stock-compensation): this leaderboard measures stock compensation against free cash flow, not against repurchase spending, and Amazon lands at the top of this one for a different reason — sheer scale, not an absent buyback program.

## The Method

Stock Compensation and Free Cash Flow are both GeminIQ calculated figures, built directly from as-filed cash flow statement data on a trailing-twelve-month basis. The universe excludes the Finance, Insurance & Real Estate sector, where operating and free cash flow are structurally different concepts, and excludes companies whose free cash flow is deeply negative relative to revenue for reasons unrelated to stock compensation — chiefly heavy, ongoing capital expenditure in capital-intensive industries like utilities and infrastructure buildout — so the ranking isolates the stock-compensation effect rather than mixing it with an unrelated capex story.

## Check Your Holdings

Pull up any position's Stock Compensation and Free Cash Flow figures on GeminIQ's [Financial Statements](/features#financial-statements) view and compare the two directly. A company where stock compensation regularly runs close to or above free cash flow is diluting shareholders at a pace the cash flow statement alone won't show — a method for spotting that gap, not a verdict on any individual company's prospects.

## Frequently Asked Questions

### What does it mean when stock compensation exceeds free cash flow?

It means the non-cash stock-based compensation expense a company reports is larger than the actual cash left over after operating expenses and capital spending. Free cash flow figures typically add stock compensation back as a non-cash item, which can make cash flow look stronger than the total economic cost — including dilution to existing shareholders — actually is.

### How many companies in GeminIQ's data show stock compensation exceeding free cash flow?

**262** companies, out of a **723**-company universe restricted to companies with meaningful stock compensation (at least **2%** of trailing revenue) and free cash flow not distorted by unrelated heavy capital spending — **36.2%** of that universe.

### Is a high stock-compensation-to-free-cash-flow ratio always a red flag?

Not automatically. Early-stage, high-growth companies frequently pay a larger share of compensation in equity while still building toward sustained free cash flow, and the pattern is common across recent technology-sector IPOs. It is a data point worth checking directly rather than a standalone verdict — the more useful question is whether the ratio is improving or worsening as the company matures.

### Why exclude the Finance, Insurance & Real Estate sector from this ranking?

Because operating cash flow at a bank, insurer, or asset manager reflects the ordinary movement of customer deposits, loans, and investment positions rather than the kind of operating cash generation a free cash flow comparison is designed to measure, making the figure not comparable to an operating company's.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-compensation-exceeds-free-cash-flow)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe drawn from GeminIQ's calculated Stock Compensation and Free Cash Flow metrics across GeminIQ's current cross-sectional filing snapshot of 6,095 companies, restricted to companies with at least $100 Million in trailing revenue and stock compensation equal to at least 2% of revenue, excluding the Finance, Insurance & Real Estate sector (723 companies), built from as-filed 10-K and 10-Q data publicly available on [SEC EDGAR](https://www.sec.gov/). Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: Stock Dropped After Earnings: What History Says Happens Next
source: https://www.geminiq.com/blog/stock-dropped-after-earnings

### Stock Dropped After Earnings: What History Says Happens Next
This is what actually happens in the year after a stock drops sharply following an SEC filing: using 264,286 post-filing price reactions across 5,637 companies and seventeen years of as-filed 10-K and 10-Q data, the worst-reacting fifth of filings stayed down at the median even as the group's average recovered.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for AMC Entertainment's August 2023 10-Q: cumulative post-filing return of -74.3% at one month, -84.3% at two months, -82.0% at three months.</sup></center>

AMC Entertainment's stock fell **74.3%** in the month after it filed its August 2023 10-Q — not a headline exaggeration, the actual cumulative move from the filing date, pulled straight from GeminIQ's [Earnings Market Reaction Heat Map](/features#price-variance). Two months later it was down **84.3%**. Three months out, still **82.0%**. Anyone holding [AMC Entertainment](/stocks/AMC) that week had one real question, and it had nothing to do with the balance sheet: does this come back, or does it keep going?

Every financial media outlet has an opinion on that question. None of them have run the numbers across enough filings to answer it. This study does.

This study reads every 10-Q and 10-K in GeminIQ's as-filed database from 2009 through mid-2026 — **264,286 filings** across **5,637 companies** — bucketed into quintiles by each stock's cumulative return in the month after filing, then tracked forward. A 10-Q carries three months of post-filing data; a 10-K carries the full twelve. Every result below is measured against the universe base rate, never against zero, and every bucket clears at least **8,487 filings** — never a handful of quarters standing in for a pattern.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-dropped-after-earnings)**

## The Pattern

Filings whose stock fell into the worst-reacting fifth in the first month were followed by continued underperformance at the median for a full year — not a rebound. Filings in the best-reacting fifth held onto their gains just as durably. Reversal is not the typical outcome at either end of the distribution. Persistence is.

But the average tells a softer story, and the gap between the two numbers is the real finding here. Across the **52,739 filings** in the worst-reacting fifth, the median cumulative return sat at **-16.7%** one month after filing and was still **-15.7%** twelve months later, among the **11,065** annual filings with a full year of tracked data. Over that same stretch, the group's winsorized mean return climbed from **-21.0%** to **-4.5%** — a very different trajectory. A minority of large recoveries pulled the average most of the way back toward even while the typical filing in the group never moved. That gap is the whole story: whether a big drop looks like it "recovers" depends entirely on whether the question is about the average filing or the one sitting in your portfolio. This is a historical association across the sample window, not a forecast — the next filing that drops this hard could land anywhere in that range.

## The Data

The pattern isn't a two-point comparison. It holds across every month tracked, in both directions.

**One Month After Filing**

| Quintile (by initial post-filing move) | N | Median Return | Winsorized Mean |
|---|---|---|---|
| Q1 — biggest drop | 52,739 | -16.7% | -21.0% |
| Q2 — moderate drop | 52,745 | -4.7% | -4.9% |
| Q3 — flat | 52,696 | 0.0% | 0.0% |
| Q4 — moderate gain | 52,712 | 4.1% | 4.3% |
| Q5 — biggest gain | 52,632 | 15.2% | 26.1% |
| Universe base rate | 263,524 | 0.0% | 0.3% |

**Twelve Months After Filing (10-K filings only)**

| Quintile (by initial post-filing move) | N | Median Return | Winsorized Mean |
|---|---|---|---|
| Q1 — biggest drop | 11,065 | -15.7% | -4.5% |
| Q2 — moderate drop | 9,492 | -0.8% | 3.3% |
| Q3 — flat | 9,354 | 4.5% | 12.7% |
| Q4 — moderate gain | 9,303 | 9.9% | 12.6% |
| Q5 — biggest gain | 8,487 | 17.3% | 42.0% |
| Universe base rate | 47,703 | 3.0% | 11.3% |

The month-by-month version of the same data is the chart below. The biggest-drop quintile's median line barely lifts off its opening level across all twelve months, while its mean line arcs back toward the base rate — the same divergence from the table, drawn out over time instead of compressed into two snapshots. The population shifts after month three, from the full 10-Q-plus-10-K pool to 10-K filings only, since a quarterly filing's tracked window ends there; that shows up as a small step in every line at that point, not a change in the underlying pattern.

<center><sup>GeminIQ data study: post-filing cumulative return by initial-reaction quintile, months 1-12. Built from as-filed 10-K/10-Q data via GeminIQ. n = 263,524 filings, 2009–2026.</sup></center>

The pattern holds up by company size too, with one wrinkle worth knowing before using it. Splitting the worst-reacting fifth into market-cap terciles, small-cap drops got worse at the median before they got better: **-18.5%** at one month, **-24.7%** at twelve months (n=**3,900**). Mid- and large-cap drops stabilized instead of deepening further — the large-cap median moved from **-15.6%** to **-11.8%** over the same span (n=**2,902**) — but neither group closed the gap to the universe base rate's **+3.0%** twelve-month median. Size didn't produce reversal anywhere in this dataset. It only changed how much further the typical filing drifted before it flattened out.

## The Extremes

Averages hide the range, and the range is the entire story for anyone holding one specific stock instead of a basket of 52,739 of them. The last week of February 2020 is as clean a natural experiment as this dataset contains: a cluster of leisure and travel names filed their FY2019 10-Ks within four calendar days of each other, all landed in the worst-reacting fifth as COVID-era selling hit immediately after, and all fell more than **70%** in the first month. A year later, they had split into two entirely different outcomes. (This period predates the three-year filing window GeminIQ's stock pages currently display by default; all the companies below remain live, and their 2020 filings sit on the full historical record, just not the default view.)

[Caesars Entertainment](/stocks/CZR)'s FY2019 10-K, filed February 28, 2020, fell **-82.4%** in the first month. By month six it had cut that loss to **-26.1%**. By month twelve it was **+58.5%** — a filing that started in the worst-reacting fifth and finished the year as a clear winner, against the backdrop of the William Hill acquisition and the broader reopening trade.

[Norwegian Cruise Line](/stocks/NCLH) filed its FY2019 10-K one day earlier, on February 27, 2020, and fell **-74.9%** in the same window. Six months out it was still down **-59.7%**. Twelve months out, **-29.2%** — a genuine recovery from the bottom, but nowhere close to even. [Royal Caribbean](/stocks/RCL), filed February 25, traced the same arc: **-73.2%** at one month, **-18.9%** at twelve.

Both companies absorbed the identical shock, filed inside the same four-day window, and started in the same quintile. One closed the year a winner. The other closed it still deeply underwater. Nothing about the initial drop told you which one you were looking at — that only showed up in what each company actually did afterward.

## The Biggest Recoveries: Eleven Drops That Came Back

The median says a big drop usually stays down. The mean says some come back hard, and these are the ones that did: the eleven largest round-trips in the worst-reacting fifth of all 264,286 filings, ranked by the gain that followed the first-month drop. They came back for eleven different reasons (a debt refinancing, a pandemic reopening trade, a meme-stock revival, a lending freeze easing, a first profitable quarter), and Carvana's is the one a reader could most plausibly have seen coming from the filing itself.

| Rank | Company | Filing | Initial Drop | Recovery Window | Return |
|---|---|---|---|---|---|
| 1 | [Wayfair](/stocks/W) | FY2019 10-K | **-56.9%** | 12 months | **+374.5%** |
| 2 | [Carvana](/stocks/CVNA) | FY2022 10-K | **-24.1%** | 12 months | **+345.6%** |
| 3 | [Etsy](/stocks/ETSY) | FY2019 10-K | **-45.3%** | 12 months | **+268.8%** |
| 4 | [Roku](/stocks/ROKU) | FY2019 10-K | **-23.7%** | 12 months | **+239.3%** |
| 5 | [Five Below](/stocks/FIVE) | FY2025 10-K | **-20.6%** | 12 months | **+170.6%** |
| 6 | [SoFi](/stocks/SOFI) | FY2023 10-K | **-20.2%** | 12 months | **+95.9%** |
| 7 | [MongoDB](/stocks/MDB) | FY2025 10-K | **-15.7%** | 12 months | **+91.3%** |
| 8 | [GameStop](/stocks/GME) | FY2024 10-K | **-32.8%** | 12 months | **+70.5%** |
| 9 | [Upstart](/stocks/UPST) | FY2022 10-K | **-18.1%** | 12 months | **+68.8%** |
| 10 | [Teladoc](/stocks/TDOC) | FY2015 10-K | **-22.0%** | 12 months | **+61.2%** |
| 11 | [Datadog](/stocks/DDOG) | FY2022 10-K | **-10.5%** | 12 months | **+70.0%** |

Three of the eleven — Wayfair, Etsy, and Roku, ranked first, third, and fourth — share a filing date that has nothing to do with any single company. All three filed FY2019 annual reports in the last week of February or the first days of March 2020, days before a pandemic crashed and then reflated the entire market. Standard financial media would tell each of those stories separately, as if three companies independently overreacted to their own numbers. The filing dates say otherwise. The other eight names on the list — including four of the five covered in detail below — are not tied to that week; whatever drove each of them, it wasn't a shared calendar.

<center><sup>GeminIQ data study: mean vs. median twelve-month return for the worst-reacting fifth of all 10-K filings. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 11,065 filings, 2009–2026.</sup></center>

These eleven are the extreme right tail of a bucket whose typical member did not recover. They are what pulls the group's mean back toward even while its median stays at **-15.7%**.

### Wayfair: A Pandemic Rewrote the Filing

Wayfair's FY2019 10-K, filed February 28, 2020, reported **$9.127 Billion** in trailing revenue, up **34.6%** year over year — a growth rate media coverage at the time treated as unremarkable for an e-commerce name still years from profitability. The net loss told a worse story: **-$984.6 Million** trailing twelve-month, worse than the prior year's **-$504.1 Million**, with diluted losses of **$10.68** per share. Total debt had roughly doubled in a single year, from **$738.9 Million** to **$1.456 Billion**, pushing the company into a net-debt position of **$873.4 Million** for the first time in the dataset. On the numbers alone, this was a filing that should have kept falling.

It fell **56.9%** in the first month — the steepest single-month drop of any filing in this study. Then COVID-19 turned e-commerce delivered-to-your-door furniture into one of the most in-demand categories in retail, and Wayfair's stock rose **374.5%** over the next twelve months. Nothing in the 10-K itself explains that outcome. The filing described a company burning cash faster every year; the market's verdict came from an external event the filing could not have anticipated.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Wayfair's FY2019 10-K (filed February 28, 2020): cumulative post-filing return of -56.9% at one month, +374.5% at twelve months.</sup></center>

### Carvana: $8.3 Billion in Debt and a 346% Comeback

Carvana's FY2022 10-K, filed February 23, 2023, is the cleanest debt-crisis story in the dataset. Revenue growth had decelerated from **123.9%** year over year in Q3 2021 to just **6.2%** by the panic quarter, and [gross margin](/metrics/margin-metrics/gross-profit-margin) compressed from **15.1%** to **9.2%** over the same stretch — a business that had scaled aggressively on the assumption growth would keep funding itself. GeminIQ's pre-calculated [Total Debt](https://www.geminiq.com/metrics/calculated-values/total-debt) shows the balance sheet growing from **$5.413 Billion** to **$8.309 Billion** over the year leading into the filing, largely the financing behind the ADESA acquisition. [Net Debt](https://www.geminiq.com/metrics/calculated-values/net-debt) stood at **$7.681 Billion** against just **$628 Million** in cash, and the company posted a trailing net loss of **-$1.587 Billion**.

That combination — decelerating growth, compressing margins, and a debt load that had grown sharply at the worst possible moment — is exactly the setup a distressed-debt short thesis is built on, and the stock dropped **24.1%** in the following month. What followed was one of the more written-about corporate turnarounds of the period: a debt exchange that cut leverage, a return to unit-economics discipline, and a stock that gained **345.6%** over the next twelve months, the second-largest twelve-month reversal in this entire study.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Carvana's FY2022 10-K (filed February 23, 2023): cumulative post-filing return of -24.1% at one month, +345.6% at twelve months, against Total Debt of $8.309 Billion.</sup></center>

### SoFi: The Quarter It Finally Turned a Profit

The number that made SoFi's FY2023 10-K worth a rally never made it into the trailing headline. Filed February 27, 2024, the filing still reported a trailing twelve-month net loss of **-$300.7 Million** on revenue growth of **34.9%** year over year — solid, but not obviously different from prior quarters that hadn't triggered anything. Buried inside it: the fourth quarter itself posted **$47.9 Million** in net income, the company's first quarter of GAAP profitability since going public. The trailing figure still showed red because it carried three losing quarters with it.

The stock dropped **20.2%** in the month after the filing regardless — a trailing-loss headline is a trailing-loss headline, whatever quarter produced it. Over the following twelve months, as the profitable quarter proved not to be a one-off, the stock gained **95.9%**. This is closer to a normal "the filing undersold its own good news" story than a Carvana-style crisis reversal — a case where the trailing metric and the forward-looking signal briefly pointed in opposite directions.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for SoFi's FY2023 10-K (filed February 27, 2024): cumulative post-filing return of -20.2% at one month, +95.9% at twelve months.</sup></center>

### GameStop: The Filing Didn't Move It

The filing explains the drop. It does not explain the recovery. GameStop's FY2024 10-K, filed March 26, 2024, reported trailing revenue of **$5.273 Billion**, down **11.0%** year over year — a real, ongoing sales decline. The one bright spot was a swing to **$6.7 Million** in trailing net income, up from the prior year's **-$313.1 Million** loss, sitting on **$938.9 Million** in cash against just **$28.5 Million** in debt. That combination — shrinking sales, barely-positive earnings, an unusually clean balance sheet — dropped the stock **32.8%** in the following month, a reasonable market reaction to a company still losing its core business even as it stopped bleeding cash.

The **70.5%** twelve-month gain that followed has almost nothing to do with any of that. On May 12, 2024 — roughly six weeks after the filing — Keith Gill, the investor known as "Roaring Kitty" who had driven GameStop's 2021 short squeeze, returned to social media for the first time since 2021. Shares gained over **100%** intraday on no company news whatsoever. This is the cleanest illustration in the entire study of why every finding here is stated as association, not prediction.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for GameStop's FY2024 10-K (filed March 26, 2024): cumulative post-filing return of -32.8% at one month, +70.5% at twelve months.</sup></center>

### Upstart: Flat on Paper, Cut in Half in Practice

Upstart's FY2022 10-K, filed February 16, 2023, reported trailing revenue of **$842.4 Million**, down just **0.7%** year over year — a headline that looks almost unremarkable next to the other filings on this list. The quarterly trend underneath it did not: revenue fell sequentially every quarter of the year, from **$314.0 Million** in Q1 to **$258.3 Million**, **$157.2 Million**, and finally **$112.9 Million** in Q4 — a top line cut by more than half in nine months as rising rates froze the loan-funding markets Upstart's AI-lending model depended on. Net income swung from **$58.9 Million** in Q4 2021 to a **-$55.3 Million** loss in Q4 2022, and GeminIQ's pre-calculated [Stock-Based Compensation to Revenue](https://www.geminiq.com/metrics/margin-metrics/stock-based-compensation-to-revenue) shows dilution accelerating in the opposite direction of the business, from **8.6%** of revenue a year earlier to **15.0%** by the panic quarter.

The stock dropped **18.1%** the following month and gained **68.8%** over the next twelve, as rate expectations eased and the lending-freeze thesis that had driven the sell-off started to reverse. The full-year revenue figure alone would have missed the entire story in both directions — flat on paper, collapsing and then stabilizing underneath.

<center><sup>GeminIQ Earnings Market Reaction Heat Map for Upstart's FY2022 10-K (filed February 16, 2023): cumulative post-filing return of -18.1% at one month, +68.8% at twelve months.</sup></center>

## The Method

None of this holds up unless the math behind it does. Every number above follows the same rules as every other filing data study on this site: post-filing return columns are cumulative and never compounded, every bucket is measured against the universe base rate rather than zero, and no bucket below roughly 200 filings gets a conclusion drawn from it — the tightest quintile cited here still clears **8,487**. The full rule set, including exactly how the twelve-month 10-K window and three-month 10-Q window combine without double-counting, lives in the [Filing Data Study Methodology](/blog/filing-data-study-methodology) post.

## Check Your Holdings

The method behind this study runs on any single stock in about two minutes, and it's worth running before reacting to a red print. Open a holding's page on GeminIQ and pull up the [Earnings Market Reaction Heat Map](/features#price-variance) — the same cumulative-return-from-filing-date figure used to build every bucket above. Find its most recent filing's one-month cumulative move. A drop of **-15%** to **-20%** or worse puts it in territory where, historically, the typical filing was still down double digits a full year later — not a rebound story, whatever the headline says that week.

Before assuming this one is different, pull its [Financial Statements](/features#financial-statements) and check whether [Return On Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and [Revenue Growth](/metrics/growth-metrics/revenue-growth) actually deteriorated alongside the price, or whether the underlying filing looks essentially unchanged and the move was purely a reaction. That distinction is the difference between a Caesars Entertainment and a Norwegian Cruise Line, and it's sitting in the filing, not in the stock chart. The same check separates the recoveries above: Carvana's and Upstart's rebounds traced back to numbers inside their filings, while Wayfair's and GameStop's did not. Cross-reference Total Debt and Net Debt against the prior quarter too. A leverage ratio that doubled in two quarters is a different risk from one holding flat. None of this forecasts which way a drop resolves; it tells you whether the sell-off and the filing were describing the same problem.

## Frequently Asked Questions

### Do stocks recover after a big drop on earnings?

Usually not, at the median. Across 52,739 filings in the worst-reacting fifth since 2009, the median return was -16.7% one month after filing and still -15.7% twelve months later. The group's average recovered to -4.5%, but only because a minority of large rebounds pulled it up.

### What were the biggest recoveries after an earnings drop?

Wayfair's FY2019 10-K fell 56.9% in its first month and then gained 374.5% over twelve, the largest round-trip in the dataset. Carvana's FY2022 10-K fell 24.1% and gained 345.6%, and Etsy and Roku, both FY2019 10-Ks filed just before the pandemic, gained 268.8% and 239.3%.

### Do small-cap stocks recover differently from large caps after a drop?

Small caps did worse. Their median fell from -18.5% at one month to -24.7% at twelve, while large caps improved from -15.6% to -11.8%. Neither group caught up with the universe's +3.0% twelve-month median.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-dropped-after-earnings)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All figures are drawn from each company's as-filed 10-K and 10-Q filings, publicly available on [SEC EDGAR](https://www.sec.gov/). Post-filing market reaction is measured from each filing's filed date, cumulative through each tracked month and never compounded. Sample: 264,286 filings across 5,637 companies, 2009–2026, quintiled by each filing's one-month cumulative post-filing return. Methodology: [Filing Data Study Methodology](/blog/filing-data-study-methodology).</sup>

---

## Blog: Stock Rover Alternative: Screening on Filed Data
source: https://www.geminiq.com/blog/stock-rover-alternative-sec-data

### Stock Rover Alternative: Screening on Filed Data
A Stock Rover alternative for investors who audit their screen inputs. Stock Rover offers 700+ screenable metrics gated by tier; this post explains why metric count is the wrong axis and what a derived metric hides about the line items underneath it.

Stock Rover is the best pure screening product retail investors can buy, and the numbers behind that claim are specific. Coverage across North American stocks, ETFs, and funds. Somewhere between 275 and 800-plus screenable metrics depending on tier. Up to twenty years of historical fundamentals. Ranked screening that weights criteria so results sort by strategy fit. Equation screening for custom formulas. More than 140 prebuilt screens. Portfolio analytics with broker sync, correlation analysis, and Monte Carlo simulation.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-rover-alternative-sec-data)**

Nothing on this page argues the screener is weak. It is the strongest in its category.

The argument is that metric count is the wrong axis to evaluate it on, and that the number investors should care about is much smaller than 700.

## Table of Contents

- [Seven Hundred Metrics, Far Fewer Facts](#seven-hundred-metrics-far-fewer-facts)
- [A Screen Inherits Every Definition It Uses](#a-screen-inherits-every-definition-it-uses)
- [Tier Gating Makes Data Depth a Pricing Decision](#tier-gating-makes-data-depth-a-pricing-decision)
- [Scores and Fair Value Are Another Opinion Layer](#scores-and-fair-value-are-another-opinion-layer)
- [What Screening on Filed Data Changes](#what-screening-on-filed-data-changes)
- [Screen First, Then Audit](#screen-first-then-audit)
- [Frequently Asked Questions](#frequently-asked-questions)

## Seven Hundred Metrics, Far Fewer Facts

Metric libraries expand faster than data does, and understanding why clarifies what depth actually means.

A financial statement contains a bounded set of reported line items. Everything on a screener beyond those is arithmetic performed on them. Return on equity is net income over equity. Return on invested capital is an operating result over a capital base. [Free cash flow yield](/blog/free-cash-flow-yield-explained) is a cash flow figure over a market value. Each ratio can then be produced in additional variants — trailing twelve months, five-year average, growth rate, percentile against sector, change versus prior period — and every variant counts as another metric.

Seven hundred metrics is therefore not seven hundred independent observations about a company. It is a much smaller set of filed facts, recombined.

That matters because the recombination is where definitions live. Two platforms reporting a different return on capital for the same company are usually not disagreeing about the filing. They are using different denominators, different tax treatments, or different decisions about what belongs in the capital base. The disagreement lives in the derivation, and the derivation is what a metric library does not show you.

Depth in a screener means how many derivations are offered. Depth in a dataset means how much of the filing survived.

## A Screen Inherits Every Definition It Uses

Run a five-criterion screen and you have accepted five definitions you did not write.

Most of the time that is fine, because most definitions are conventional and the differences are small. The exceptions cluster in exactly the places serious screening cares about. Anything involving debt depends on whether lease obligations are inside or outside the debt figure. Anything involving capital depends on what the platform included in invested capital. Anything involving cash flow depends on how capital expenditure was classified, and anything involving earnings depends on whether the figure is GAAP or adjusted.

Change one of those and the population that passes the screen changes with it. Not marginally — a leverage threshold with leases in or out produces two different lists.

The practical test is simple and rarely run: take a company your screen returned, open the filing, and reconstruct the metric yourself from the reported line items. If the number matches, the definition was what you assumed. If it does not, the screen was answering a slightly different question than the one you asked.

That test needs as-filed line items. It cannot be run inside a library of derived metrics.

## Tier Gating Makes Data Depth a Pricing Decision

There is a structural feature of the model worth naming, and it is common across the category rather than unique to any one product.

Screenable metric count scales with subscription tier, and so does historical depth. Entry tiers cap both. Equation screening, ranked screening, and screening against long historical fundamentals sit at higher tiers, which is a reasonable commercial design and produces an unusual consequence: the analytical question you are permitted to ask is set by what you paid.

An investor on a lower tier is not screening a smaller universe. They are screening the same universe through fewer fields and a shorter history, which quietly changes which patterns are findable. A metric that only becomes interesting across fifteen years is invisible to someone with five.

Filed data has no tiers. Every registrant's full filing history is public on EDGAR the day it lands, and the constraint is extraction rather than entitlement. GeminIQ's own Free plan is built on that same raw access: 3 years of history and 24 calculated metrics at no cost, with the full 17-plus-year archive and metric library reserved for the paid Annual or Monthly plan.

## Scores and Fair Value Are Another Opinion Layer

Higher tiers add proprietary stock scores, fair value estimates, margin of safety figures, and warning flags. These are useful for triage, and they belong in the same category as every other composite discussed across this series.

A score selects inputs, weights them, and compresses the result into a rank. A fair value estimate assumes a relationship between historical figures and intrinsic worth. Both are defensible constructions and neither is a measurement, which means they cannot be checked — only accepted or ignored.

The distinction that matters is between a screen and a verdict. A screen is a filter you specified: it returns companies meeting conditions you chose, and you can inspect the conditions. A score is a conclusion someone else reached, and its inputs are not yours to examine.

Using both is fine. Confusing them is where a screening workflow turns into an outsourced one.

## What Screening on Filed Data Changes

GeminIQ approaches the same problem from the other end. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value, so the inputs behind any metric are visible rather than assumed.

[Stock Screeners](/features#screener) run across that layer, and named strategy screens apply published criteria to filed data — the [Piotroski F-Score Screener](/screens/stock-screeners/piotroski-f-score), the [Magic Formula Screener](/screens/stock-screeners/magic-formula), the [High ROIC, Low Debt Screener](/screens/stock-screeners/high-roic-low-debt), and the [Net-Net Stocks Screener](/screens/stock-screeners/net-net-stocks) among them. When a company passes, [Financial Statements](/features#financial-statements) show the reported captions that produced the result, and [Custom Tables](/features#custom-tables) assemble the specific line items behind it. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Invested Capital](/metrics/calculated-values/invested-capital), and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) publish what they are computed from, which is what makes the reconstruction test possible.

The metric library is smaller. The set of facts underneath it is the same set the company filed, and every one of them can be pointed at.

## Screen First, Then Audit

The workflow that gets the most out of both products is a sequence, and most investors only run the first half.

Screening is a discovery operation. Its job is to reduce ten thousand companies to twenty, and for that job a deep metric library with ranked and equation-based filtering is exactly right. Stock Rover is excellent at it and no filings archive replaces the ergonomics of a well-built screen.

The half that gets skipped is the audit. Twenty names that passed a filter are twenty hypotheses, each resting on definitions you inherited. Checking two or three of them against the filings tells you whether the screen was measuring what you meant — and if it was not, every result from it was answering a different question.

For the shallower end of the same category, the [Finviz alternative](/blog/finviz-alternative-fundamental-data) post covers what a one-row ratio snapshot cannot carry.

A screen is only as good as the fields behind it, and the only way to know how good those fields are is to open the filing that produced them.

## Frequently Asked Questions

### What are the best Stock Rover alternatives?

It depends on the job. For deep screening with ranked and equation-based filters across North American stocks, funds, and ETFs, the substitutes are other screening platforms with large derived-metric libraries. For auditing what a screen actually measured, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### Does a screener with more metrics have better data?

Not necessarily. Most metrics on any screener are arithmetic performed on a much smaller set of reported line items, and additional variants — trailing twelve months, averages, growth rates, sector percentiles — each count separately. Metric count measures how many derivations are offered, not how much of the filing is preserved underneath them.

### Why do two platforms report different ROIC for the same company?

Usually because they define the capital base differently, treat taxes differently, or make different decisions about which balance sheet items to include. Both can be reading the same filing. The disagreement lives in the derivation, which is why a metric whose inputs are published can be checked and one whose inputs are not cannot.

### How do I verify a stock screener result?

Take a company the screen returned, open its most recent 10-K or 10-Q, and rebuild the metric from the reported line items. If your figure matches the screener's, the definition was what you assumed. If it does not, the difference is a methodology choice worth understanding before you act on the list.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stock-rover-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Stock Rover coverage, metric counts by tier, historical depth, ranked and equation screening capability, prebuilt screen count, portfolio analytics, and proprietary score and fair value features reviewed August 2, 2026 from Stock Rover materials and third-party platform reviews. Plan structure was restructured in 2026; verify current tiers and pricing before republication.

---

## Blog: StockAnalysis.com Alternative: Traceable Filing Data
source: https://www.geminiq.com/blog/stockanalysis-com-alternative-filing-data

### StockAnalysis.com Alternative: Traceable Filing Data
A StockAnalysis.com alternative for the verification step. StockAnalysis.com sources fundamentals from S&P Global Market Intelligence and Fiscal.ai and tells users to confirm critical figures against SEC filings; this post is about what that confirmation requires.

StockAnalysis.com is the rare free financial site that does not insult the person using it. Clean tables, fast pages, minimal advertising, no promoted tickers, a screener that outperforms products charging real money, and coverage running past 130,000 tradable symbols. Pro is **$79** a year and Unlimited is **$199** — pricing that undercuts most competitors by a factor of three or four.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stockanalysis-com-alternative-filing-data)**

It is also unusually candid about its own architecture. The site publishes a data sources page naming its providers, states that fundamental and historical financial data comes from S&P Global Market Intelligence and Fiscal.ai, acknowledges that errors and delays can occur, and tells users to confirm critical details against official filings before acting on them.

That last instruction is the honest center of the product, and almost nobody follows it — because the moment you try, you discover the verification step is the hard part.

## Table of Contents

- [The Instruction Most Users Skip](#the-instruction-most-users-skip)
- [What Verification Actually Requires](#what-verification-actually-requires)
- [The Data Source Selector Tells You Something](#the-data-source-selector-tells-you-something)
- [Where a Free Summary Layer Stops](#where-a-free-summary-layer-stops)
- [Making the Verification Step the Default](#making-the-verification-step-the-default)
- [Using Both, in the Right Order](#using-both-in-the-right-order)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Instruction Most Users Skip

"Verify against the primary source" is advice every serious research platform gives and almost no workflow accommodates.

The reason is friction. Confirming a single balance sheet figure against the original filing means finding the company's EDGAR page, identifying the correct filing among amendments and exhibits, locating the statement inside a document that frequently runs past a hundred pages, finding the caption, and then reading the footnote that explains what the caption contains. That is fifteen minutes for one number. Nobody does it fifteen times in an afternoon, so in practice it gets done zero times.

The instruction is correct. The workflow makes it impractical. And the gap between the two is where most retail research quietly stops being verified at all.

## What Verification Actually Requires

Verification is not eyeballing whether two numbers look similar. It is establishing that a displayed value and a reported value are the same fact.

Three things have to line up. The period has to match, which sounds trivial until a fiscal year ending in September gets compared against a calendar quarter. The scope has to match, meaning the displayed figure covers the same set of items the filing's caption covers. And the classification has to match, meaning nothing was combined, split, or reassigned between the document and the screen.

The third is where standardized data and filed data part company, and the divergence is rarely an error. Two distinct cash outflows can become one row because the template has one row where the filing has two. A single filed liability caption can be split into two so a component is separately trackable. A label can survive while its contents change — the version that costs the most, because the screen gives no signal that anything was decided.

Every one of those reconciles cleanly once you can see both sides. The problem is that a summary layer only shows you one side, so an investor comparing a screen to a 10-K is left guessing whether a variance is a mapping choice or a mistake.

## The Data Source Selector Tells You Something

There is a feature on StockAnalysis.com that is more informative than it appears.

Because history depth varies by provider, the site offers a data source selector on financial statement tables — free access runs to roughly five years, paid access extends to about ten from the primary provider, and switching providers reaches back forty years or more for established companies. The site documents this openly, which is more transparency than most platforms offer.

Sit with the implication. The same company's financial history can render differently depending on which provider you select, because each provider made its own decisions about how to represent filings that were themselves identical. The filings did not change. The rendering did.

That is the clearest available demonstration that standardized data is a representation rather than a record. Two providers reading the same 10-K can produce two defensible versions of it, and a selector is the honest way to surface that. It also means "what does this company's ten-year history look like" is a question with more than one correct answer on a licensed-data platform, and exactly one on the filings themselves.

## Where a Free Summary Layer Stops

None of this makes a summary layer bad. It makes the boundary of its usefulness locatable.

For screening, orientation, comparing valuation across a peer group, checking a dividend record, scanning growth trends, or answering a question in thirty seconds, a fast summary is the right tool and the price is close to irrelevant. StockAnalysis.com does that job better than most paid products, and its free tier is a public service — the same instinct GeminIQ's own Free plan follows, just built on as-filed data instead of licensed fundamentals.

The boundary arrives when the question stops being "roughly what does this look like" and becomes "is this number the number." That transition happens at a predictable moment: when capital is about to move, or when a conclusion has to survive somebody asking where it came from. At that point the summary has done its job and the filing becomes the only sufficient source.

The failure mode is not using a summary layer. It is failing to notice which question you have moved on to.

## Making the Verification Step the Default

GeminIQ exists to collapse that fifteen-minute lookup into a default state.

It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value. There is no mapping layer between the filing and the display, which means verification is not a separate errand — the figure on screen is the reported fact, with the tag that identifies it.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years rather than a template's rows. [Custom Tables](/features#custom-tables) build views from specific reported items. [Calculated Metrics](/features#calculated-metrics) such as [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and [Free Cash Flow](/metrics/calculated-values/free-cash-flow) are computed from as-filed inputs, so a metric can be checked against the numbers behind it. The step-by-step mechanics are covered in [how to verify financial data against an SEC filing](/blog/verify-financial-data-against-sec-filing).

A documented case shows how invisible a classification difference can be. [Carvana's](/stocks/CVNA) FY2025 10-K reports Other current liabilities at **$134M**. A widely used retail aggregator displays **$296M** under the same label — roughly **2.2 times** the filed figure — because its bucket absorbs lease and other obligations the filing reports elsewhere. The non-current side runs the same pattern: **$15M** as filed against **$2,243M** displayed, under an identical caption.

This is the label-value mismatch, and it is the version that defeats casual verification entirely. An investor glancing between a screen and a 10-K sees matching words, assumes matching numbers, and moves on. Catching it requires comparing the values themselves, which is the step the advice recommends and the workflow rarely permits. The [documented cases](/blog/third-party-financial-data-problems) post lists four of them across three large filers.

The tradeoff is real and worth stating. US public company fundamentals only. No international coverage, no ETF holdings, no analyst ratings, no dividend calendars. Coverage stops where the SEC's jurisdiction stops.

## Using Both, in the Right Order

These are not competing products, and treating them as substitutes gets the workflow backwards.

Start broad. Use a fast, free summary layer to find companies, compare peers, and decide what deserves a real afternoon — that phase rewards speed, and paying for precision you will discard is waste. Then, when a name survives the screen and money is about to be involved, switch sources rather than switch tabs.

The point is not that summary data is untrustworthy. It is that "verify against the official filing" should be a step you can actually complete, not a disclaimer you scroll past. StockAnalysis.com is right to tell users to do it. The filings are where it gets done.

Because the site's fundamentals come from S&P Global Market Intelligence and Fiscal.ai, the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) and [Fiscal.ai alternatives](/blog/fiscal-ai-alternative-sec-data) posts both describe the data layer sitting underneath what you are reading.

## Frequently Asked Questions

### What are the best StockAnalysis.com alternatives?

Which alternative fits depends on the job. For fast free summary data across a global universe of stocks and ETFs, the substitutes are other broad research sites, most of which license fundamentals from the same providers. For verifying a figure against the document a company filed, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### Where does StockAnalysis.com get its data?

The site publishes a data sources page stating that fundamental and historical financial data comes from S&P Global Market Intelligence and Fiscal.ai, with additional providers supplying price, ETF holdings, ratings, and forecast data. It also notes that errors or delays can occur and recommends confirming critical details against official filings.

### Is StockAnalysis.com accurate?

The platform runs automated and manual quality checks and is transparent about known limitations, which is more than most free sites offer. What it displays is standardized data from licensed providers, so a value can be accurate as a standardized figure while still differing in classification from the caption in the filing. That is a mapping question rather than an accuracy question, and only the filing settles it.

### How do I verify a financial figure against an SEC filing?

Match three things: the period, the scope of what the figure covers, and the classification. Locate the filing on SEC EDGAR, find the statement, read the caption, then read the footnote that explains what the caption contains — footnote detail is usually where a variance resolves. A platform that preserves as-filed line items and XBRL tags removes most of that lookup by keeping the reported structure intact.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=stockanalysis-com-alternative-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- StockAnalysis.com data-provider attributions, coverage figures, history-depth tiers, data source selector, and Pro and Unlimited pricing reviewed August 2, 2026 from the site's published data sources and pricing pages plus third-party platform reviews. Verify current figures before republication.

---

## Blog: Tesla Free Cash Flow Turns Negative: Q2 2026 Data
source: https://www.geminiq.com/blog/tesla-free-cash-flow-turns-negative

### Tesla Free Cash Flow Turns Negative: Q2 2026 Data
Tesla's free cash flow turned negative in Q2 2026 for the first time since Q1 2024, as capital expenditures grew 141.8% year-over-year against an 84.9% rise in operating cash flow. The Q2 2026 10-Q also shows operating income falling 56.9% even as revenue grew 25.5%.

**[Tesla](/stocks/TSLA) ($TSLA) filed its Q2 2026 10-Q on July 23, 2026, three days after reporting record quarterly revenue of $28.24 Billion. Most of the coverage has settled on the same framing: a beat on the top line, a miss on adjusted earnings, and a company entering what it called its "largest investment period." The filing tells a sharper story. Operating cash flow grew 84.9% year-over-year, but capital expenditures grew 141.8% — meaning the pace of cash going out the door now genuinely outruns the pace of cash coming in. The result: free cash flow just went negative for the first time in nine quarters, and almost nobody read past the headline to notice.**

| Field | Value |
|---|---|
| Ticker | $TSLA |
| Filing | Q2 2026 10-Q |
| Filed | July 23, 2026 |
| Period End | June 30, 2026 |
| Free Cash Flow (Quarterly) | **-$1.092 Billion** |
| Operating Income | **$398 Million** |

## The Capex Bet Just Flipped Free Cash Flow Negative

Tesla's shareholder letter frames the current spending as strategic — the company's entry into what it calls its largest investment period, aimed at transportation, energy, and AI. The cash flow statement shows what that actually costs in a single quarter.

**The Data:** [Tesla's](/stocks/TSLA) `Net Cash Provided By Used In Operating Activities` came in at **$4.697 Billion** for the quarter, up **84.9%** from **$2.540 Billion** in Q2 2025. `Payments To Acquire Property Plant And Equipment` grew faster, to **$5.789 Billion** from **$2.394 Billion** — a **141.8%** increase. Net the two together and quarterly free cash flow lands at **-$1.092 Billion**, the first negative quarter since Q1 2024, when free cash flow was **-$2.535 Billion**. Every one of the eight quarters in between was free-cash-flow positive.

**The GeminIQ Edge:** A trailing-twelve-month figure — which is what most platforms default to — would have shown this same quarter as barely a dent in a positive number. [Tesla's](/stocks/TSLA) GeminIQ [Free Cash Flow](/metrics/calculated-values/free-cash-flow) (TTM) still reads **$5.762 Billion**, down only modestly from **$7.000 Billion** last quarter. The single-quarter break only becomes visible when the cash flow statement is read one filing period at a time, in GeminIQ's [Financial Statements](/features#financial-statements) view — not smoothed into a trailing average that would have hidden the exact moment the spending outran the cash.

<center><sup>GeminIQ Financial Statements showing Tesla's quarterly Net Cash Provided By Used In Operating Activities and Payments To Acquire Property Plant And Equipment from Q3 2024 through Q2 2026, with free cash flow (the difference) turning negative at -$1.092 Billion in Q2 2026 for the first time since Q1 2024.</sup></center>

## Operating Expenses Are Growing Almost Twice as Fast as Revenue

Revenue set a record this quarter. The expense line next to it grew even faster, and that's the part of the filing that determines whether the record actually shows up as profit.

**The Data:** [Tesla's](/stocks/TSLA) revenue for the quarter came in at **$28.236 Billion**, up **25.5%** from **$22.496 Billion** a year ago. `Operating Expenses` grew to **$4.353 Billion** from **$2.955 Billion**, a **47.3%** increase — nearly double the pace of the top line. Inside that total, `Research And Development Expense` rose **49.2%** to **$2.371 Billion**, and `Selling General And Administrative Expense` rose **45.1%** to **$1.982 Billion**. `Operating Income Loss` fell **56.9%**, from **$923 Million** to **$398 Million**, in the same quarter revenue hit an all-time high.

**The GeminIQ Edge:** GeminIQ's pre-calculated [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) (TTM) confirms the direction independent of any single quarter's noise: **4.22%**, down from **6.06%** a year earlier. A revenue beat and a shrinking operating margin aren't contradictory — reading the income statement and the calculated metric side by side is what keeps a beat headline from burying a real deterioration in unit economics.

<center><sup>GeminIQ Financial Statements showing Tesla's Revenues (+25.5% YoY to $28.236 Billion) against Operating Expenses (+47.3% YoY to $4.353 Billion) and Operating Income Loss (-56.9% YoY to $398 Million), Q2 2025 vs. Q2 2026.</sup></center>

## The Net Income Number That Held Up for a Different Reason

Operating income fell 56.9%. Net income fell 3.75%. Both numbers are accurate, and neither one is measuring the same thing.

**The Data:** [Tesla's](/stocks/TSLA) `Operating Income Loss` of **$398 Million** is well short of the **$1.329 Billion** in `Income Loss From Continuing Operations Before Income Taxes Extraordinary Items Noncontrolling Interest` reported for the quarter. Non-operating income bridges the gap: `Other Nonoperating Income Expense` came to **$590 Million** (up **84.4%** from **$320 Million**), `Investment Income Interest` rose to **$422 Million** from **$392 Million**, and `Interest Expense Nonoperating` was **-$81 Million**. Combined, non-operating income rose **48.7%** year-over-year, from **$626 Million** to **$931 Million** — a bigger dollar increase than the entire decline in operating income. `Income Tax Expense Benefit` then came in at **$201 Million** against that **$1.329 Billion** in pretax income, a **15.1%** effective rate versus **23.2%** a year ago. `Net Income Loss` landed at **$1.128 Billion**, down just **3.75%** from **$1.172 Billion**.

**The GeminIQ Edge:** None of this is irregular accounting — it's the ordinary mechanics of a multi-line income statement. But it means the one number that leads every headline is the most cushioned line on the page. GeminIQ's [Financial Statements](/features#financial-statements) view lays out operating income, pretax income, and net income as three separate, traceable lines. A summary-only platform collapses straight to the bottom line — and never shows you how it got there.

<center><sup>GeminIQ Financial Statements bridging Tesla's Operating Income Loss ($398 Million) to Income Loss From Continuing Operations Before Income Taxes ($1.329 Billion) via $931 Million in combined non-operating income, then to Net Income Loss ($1.128 Billion) after a 15.1% effective tax rate. Q2 2026 10-Q.</sup></center>

## The Balance Sheet Still Has Room — For Now

One negative quarter doesn't threaten a company with tens of billions in liquidity. What it does is shrink the cushion the market has been pricing as unlimited.

**The Data:** [Tesla](/stocks/TSLA) closed the quarter with **$15.219 Billion** in `Cash And Cash Equivalents At Carrying Value` and **$28.305 Billion** in `Short Term Investments` — a combined **$43.524 Billion** in liquidity. Against that, GeminIQ's pre-calculated [Market Capitalization](/metrics/valuation-metrics/market-capitalization) stands at **$1.361 Trillion**, and the [Price-to-Earnings Ratio (P/E)](/metrics/valuation-metrics/price-to-earnings-ratio) (TTM) sits at **357.63x**. GeminIQ's [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) (TTM) — already thin at **0.55%** a year ago and **0.58%** last quarter — has fallen to **0.42%**.

**The GeminIQ Edge:** A **$43.524 Billion** liquidity position means one heavy-capex quarter isn't a solvency event — Tesla can fund several more quarters like this one without touching the balance sheet's structure. But a Free Cash Flow Yield already under half a percent, now trending lower, is the number that shows how little margin for error exists at a **357.63x** earnings multiple. Whether Q2 2026 was a single investment-heavy quarter or the start of a pattern is the question the next filing answers. GeminIQ's [Financial Statements](/features#financial-statements) will show it first, unfiltered, the day the 10-Q drops.

<center><sup>GeminIQ Calculated Metrics showing Tesla's Market Capitalization ($1.361 Trillion), Price-to-Earnings Ratio (357.63x TTM), and Free Cash Flow Yield (0.42% TTM, down from 0.58% last quarter), against $43.524 Billion in combined cash and short-term investments.</sup></center>

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=tesla-free-cash-flow-turns-negative)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Tesla, Inc.'s Q2 2026 10-Q (filed July 23, 2026, period ending June 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1318605/000162828026049270/tsla-20260630.htm).

---

## Blog: Apple FY2025: Normalized Financial Data vs. the As-Filed 10-K
source: https://www.geminiq.com/blog/tikr-alternative-sec-data

### Apple FY2025: Normalized Financial Data vs. the As-Filed 10-K
Three Apple FY2025 line items shown side by side — what TIKR's normalized view displays, what the as-filed 10-K reports, and why knowing which one you are looking at matters for model building.

TIKR is a useful research platform for investors who want global stock coverage, analyst estimates, transcripts, valuation tools, and broad screening. Its own site says its financial data is powered by S&P Global Capital IQ across 100,000+ stocks, 92 countries, and 136 exchanges.

But if your workflow depends on U.S. filing-level traceability, TIKR vs. GeminIQ becomes a different comparison. For a full feature-by-feature breakdown, see our [GeminIQ vs. TIKR comparison page](/competitor-comparison/tikr).

The important question is not whether normalized financial data is useful. It often is. The question is whether the number on your screen still traces back to the exact 10-K or 10-Q line item.

That is where GeminIQ is built differently.

## TIKR vs. GeminIQ: Breadth vs. Filing-Level Traceability

TIKR is built for scale. It helps investors analyze global companies, screen across international markets, review financials, study valuation multiples, access forecasts and transcripts, and follow investor portfolios. Its pricing page shows plan differences around global coverage, financial history, analyst estimate history, transcript history, saved screens, valuation models, and Excel export.

That makes TIKR a strong platform for broad research.

GeminIQ is built for source-level U.S. fundamental analysis. GeminIQ pulls 10-K and 10-Q data directly from SEC EDGAR, preserves as-filed GAAP line items and XBRL tags, and supports [Financial Statements](/features#financial-statements), [Custom Tables](/features#custom-tables), [Visualizations](/features#visualizations), [Calculated Metrics](/features#calculated-metrics), [Stock Screeners](/features#screener), [Custom Watchlists](/features#custom-watchlists), [Insider Transactions](/features#insider-transactions), [Institutional Ownership](/features#institutional-ownership), and [Earnings Market Reaction Heat Maps](/features#price-variance).

That makes GeminIQ a better fit when the analytical question is not “What does the normalized dataset show?” but “What did the company actually file?”

The distinction matters because every normalized financial platform has to make methodology choices. Line items may be combined. Lease obligations may be separated. Company-specific labels may be mapped into broader buckets. These decisions can improve comparability, but they can also change the meaning of a line item.

Apple’s FY2025 cash flow statement shows why.

## The Apple Buyback Example: One Total, Two Separate Filing Lines

TIKR’s cash flow statement showed **$96,671M for stock repurchases (FY2025)**, while [Apple's](/stocks/AAPL) FY2025 10-K shows two separate line items totaling that amount.

Apple reported:

**Repurchases of common stock: $90,711M (FY2025)**

**Payments for taxes related to net share settlement of equity awards: $5,960M (FY2025)**

Together, those equal **$96,671M (FY2025)**.

The reconciliation is clean:

**$90,711M + $5,960M = $96,671M**

Both views describe the same cash. The difference is the level of aggregation — and with it, the economic meaning of the line.

Apple’s **$90,711M repurchases of common stock (FY2025)** reflects the buyback program. The **$5,960M payment for taxes related to net share settlement of equity awards (FY2025)** reflects a separate compensation-related cash outflow. Apple reported them separately in its FY2025 Form 10-K cash flow statement, filed October 31, 2025.

For some workflows, combining them may be acceptable. If you only want a broad view of total financing cash outflows connected to equity, the combined number can help.

But if you are analyzing Apple’s capital allocation, buyback yield, diluted share count reduction, or shareholder return efficiency, the distinction matters. A buyback is not the same thing as a tax payment tied to equity award settlement.

This is the GeminIQ point: normalization has tradeoffs. A combined number can help with broad comparison, and it gives up filing-level context to get there.

GeminIQ preserves the source detail investors need to verify the analysis. In GeminIQ, Apple’s as-filed cash flow statement keeps the buyback line separate from the equity-award tax payment line.

## Other Non-Current Liabilities: Where the $11.6B of Leases Sits

The balance sheet shows the same pattern in a different form.

Apple’s FY2025 10-K reports **Other non-current liabilities: $41,549M (FY2025)** on the consolidated balance sheet. TIKR showed **Other Non Current Liabilities: $29,946M (FY2025)** and **Capital Leases: $11,603M (FY2025)**.

Again, the reconciliation is exact:

**$29,946M + $11,603M = $41,549M**

The 10-K supports why this works. Apple’s lease table shows lease liabilities included in “Other non-current liabilities,” including **$10,911M of operating lease liabilities (FY2025)** and **$692M of finance lease liabilities (FY2025)**. Together, those lease liabilities total **$11,603M (FY2025)**.

So the numbers reconcile cleanly. Both views are internally consistent, and both are traceable back to Apple's disclosures.

What changes is that the same label no longer covers the same contents.

If one platform shows Apple’s as-filed “Other non-current liabilities” at **$41,549M (FY2025)**, and another shows **$29,946M (FY2025)** after separating lease obligations, an investor needs to know which version they are using. Otherwise, the model may mix an as-filed line item with a normalized line item without realizing it.

That can affect leverage analysis, liability trend analysis, [enterprise value](/metrics/valuation-metrics/enterprise-value) adjustments, [invested capital](/metrics/calculated-values/invested-capital) calculations, and any custom model that uses balance sheet classifications.

GeminIQ’s advantage is not that it refuses analysis. It is that it keeps the source structure intact first. Investors can then calculate, adjust, or separate items intentionally, with the filing structure still visible underneath.

## Other Current Liabilities: Same Pattern, Current Side of the Balance Sheet

Apple’s FY2025 10-K reports **Other current liabilities: $66,387M (FY2025)** on the consolidated balance sheet. In the note detail, Apple breaks that total into **Income taxes payable: $13,016M (FY2025)**, **Accrued distribution and marketing: $8,919M (FY2025)**, and **Other current liabilities: $44,452M (FY2025)**.

TIKR showed **Other Current Liabilities: $42,335M (FY2025)** and **Current Portion of Capital Lease Obligations: $2,117M (FY2025)**.

The reconciliation is exact:

**$42,335M + $2,117M = $44,452M**

Apple’s lease table shows lease liabilities included in “Other current liabilities,” including **$1,579M of operating lease liabilities (FY2025)** and **$538M of finance lease liabilities (FY2025)**. Together, those total **$2,117M (FY2025)**.

Again, the two views reconcile. The normalized view presents current lease obligations on their own line, separate from the broader current liability bucket.

That is helpful if the investor wants lease obligations broken out. It is worth knowing about if the investor is assuming the displayed “Other Current Liabilities” line matches Apple’s filed “Other current liabilities” detail exactly — the two are measuring different contents.

This is why filing-level traceability matters.

When you are building a model, every line item has a job. A liability bucket is not just a label. It is an input into working capital, liquidity, leverage, invested capital, and valuation. If the number has been normalized, you need to know how.

GeminIQ is built to show the as-filed line first.

## Why This Matters for Investors Comparing TIKR Alternatives

Most investors searching for a TIKR alternative are not casually browsing. They already know TIKR. They are looking for a better fit because something about their workflow needs more precision, more transparency, or more control.

For those investors, the Apple examples show the real decision.

TIKR is strong for breadth: global coverage, estimates, transcripts, valuation tools, investor tracking, and broad screening.

GeminIQ is stronger for U.S. filing-level verification: direct SEC EDGAR sourcing, as-filed GAAP line items, XBRL tag preservation, custom tables, calculated metrics, and visualizations built from traceable 10-K and 10-Q data.

The distinction becomes especially important in four workflows.

First, buyback analysis. If a combined line pairs stock repurchases with taxes paid for net share settlement, the resulting capital return figure is broader than the buyback line Apple reported on its own.

Second, liability analysis. If lease obligations are presented separately from “Other current liabilities” or “Other non-current liabilities,” the resulting line covers different contents than the filing label of the same name.

Third, metric calculation. [ROIC](/blog/roic-return-on-invested-capital-explained), debt ratios, working capital metrics, and free cash flow analysis all depend on the underlying line items. If those line items have been normalized, the metric inherits the normalization.

Fourth, auditability. When a displayed number is presented differently from the filing, investors need to be able to trace how it was built. Without source-level context, the analyst has to reverse-engineer the mapping manually.

GeminIQ reduces that friction by preserving the filing structure.

## The Screener Question: More Filters or More Verifiable Inputs?

TIKR’s global screener is built for broad discovery. TIKR says investors can sift through 100,000+ stocks globally and apply filters by country, industry, financials, ratios, analyst forecasts, valuation multiples, capital structure, growth rates, and margins.

That is useful for idea generation.

But serious screening depends on input quality. A screen for high ROIC, low debt, [free cash flow yield](/blog/free-cash-flow-yield-explained), or margin expansion is only as good as the financial statement data behind it.

If the platform’s line items are normalized, the screen may still work for broad comparison. But when a company passes the screen, you still need to verify the underlying filing data before relying on the result.

GeminIQ’s Stock Screener is designed for that workflow. The investor can screen across SEC-derived metrics, then move back into the financial statements, custom tables, visualizations, and calculated metric inputs built from the same filing-level data.

That is the better workflow for investors who care less about browsing the widest possible global universe and more about validating the U.S. companies they actually plan to model.

## Where TIKR Fits Best

TIKR is not a bad platform. It is a strong platform for a specific type of investor.

Choose TIKR if your priority is global equity coverage, analyst estimates, valuation templates, transcripts, broad screening, or following investor portfolios. TIKR’s own materials emphasize global coverage across 100,000+ stocks, 92 countries, and 136 exchanges, along with financial data, valuation multiples, analyst forecasts, and transcripts.

That is a compelling value proposition for investors who want one broad research workspace.

But that is not the same job GeminIQ is designed to do.

## Where GeminIQ Fits Best

Choose GeminIQ if your priority is traceable U.S. fundamental analysis.

GeminIQ is the better TIKR alternative when you want:

- As-filed GAAP financial statements
- Direct SEC EDGAR sourcing
- XBRL tag-level traceability
- Company-specific line items preserved instead of collapsed
- Custom tables built from filing-level data
- Calculated metrics based on SEC-source inputs
- Visualizations that show filing trends across time
- Screeners grounded in traceable fundamental data
- Post-filing market reaction heat maps

That last point matters. Financial analysis is not only about what the company filed. It is also about how the market reacted after the filing. GeminIQ’s [Earnings Market Reaction Heatmaps](/features#price-variance) tracks post-filing price behavior across 12 months.

That gives investors a workflow TIKR alternatives usually do not emphasize: read the filing-level fundamentals, then study how the stock historically behaved after comparable filings.

## The Bottom Line: TIKR Is Broad. GeminIQ Is Verifiable.

TIKR is a strong financial research platform for global coverage, analyst data, transcripts, valuation tools, and broad stock discovery.

GeminIQ is a better platform when the investor needs to know whether the number still matches the SEC filing.

The Apple examples make the difference concrete.

TIKR’s cash flow statement showed **$96,671M for stock repurchases (FY2025)**, while Apple’s 10-K shows two separate line items totaling that amount: **$90,711M of repurchases of common stock (FY2025)** and **$5,960M of payments for taxes related to net share settlement of equity awards (FY2025)**.

TIKR showed **$29,946M of Other Non Current Liabilities (FY2025)** and **$11,603M of Capital Leases (FY2025)**, while Apple’s 10-K reports **$41,549M of Other non-current liabilities (FY2025)** with lease liabilities included in that line.

TIKR showed **$42,335M of Other Current Liabilities (FY2025)** and **$2,117M of Current Portion of Capital Lease Obligations (FY2025)**, while Apple’s 10-K note detail reconciles those values back to the filed current liability classification.

In every case the two views reconcile to the penny. They are simply built to answer different questions — and that is the tradeoff every investor should understand when comparing a normalized dataset against the source filing.

Normalization can make data easier to compare.

GeminIQ makes data easier to verify.

For high-level scanning, normalized data can be enough. For filing-level research, model building, metric validation, and serious due diligence, the better platform is the one that keeps the chain of custody intact from SEC filing to analysis.

That is why GeminIQ is the better TIKR alternative for investors who care about traceable financial data.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=tikr-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Related Blogs

- [See how third-party normalization changes Apple’s as-filed financial data](/blog/third-party-financial-data-problems)
- [Learn why XBRL is the verification layer behind reliable SEC data](/blog/what-is-xbrl)
- [Understand how financial data gets processed before it reaches investors](/blog/how-financial-data-reaches-investors)
- [Learn what investors miss when they stop at headline financials](/blog/what-investors-miss-in-sec-filings)

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Apple Inc. Form 10-K for fiscal year ended September 27, 2025, filed October 31, 2025: https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm
- TIKR platform outputs reviewed during research for AAPL FY2025 cash flow and balance sheet line-item displays.
- TIKR official homepage: https://www.tikr.com/
- TIKR pricing page: https://www.tikr.com/pricing
- TIKR stock screener page: https://www.tikr.com/stock-screener
- GeminIQ TIKR comparison page: /competitor-comparison/tikr

All Apple figures cited in this article reference Apple Inc.'s FY2025 Form 10-K (filed October 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K&dateb=&owner=include&count=40).

---

## Blog: How to Value a Company From Filings Alone
source: https://www.geminiq.com/blog/value-a-company-from-filings-only

### How to Value a Company From Filings Alone
Every valuation model blends two very different kinds of inputs: figures that trace directly to a specific line in a specific filing, and assumptions a reasonable analyst could disagree with. Most valuation discourse treats a target price as a single number of uniform confidence, when it's actually built from a foundation of filed fact and a superstructure of forward-looking judgment. This guide walks through exactly which inputs are filed and which are assumed across DCF, comparable multiples, asset-based valuation, and the dividend discount model — the framework for knowing how much of any valuation to actually trust.

Every valuation model — a DCF, a comparable-multiples analysis, a dividend discount model, a simple book-value screen — is built from two fundamentally different kinds of inputs, and almost no valuation discourse bothers to separate them. One kind traces directly to a specific line in a specific filing: revenue, cash flow, share count, historical margins. The other kind is a forward-looking judgment a reasonable analyst could disagree with: a discount rate, a terminal growth rate, a peer multiple, a projected margin five years out. A finished valuation presents both as a single number, with a single level of confidence — and that's the part worth unlearning.

This guide separates the filed from the assumed across every major valuation approach: what a 10-K and 10-Q actually give you directly, where every model has to reach past the filing for something the filing doesn't contain, and a general framework for auditing any valuation — yours or someone else's — by asking which half of it is fact and which half is judgment.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=value-a-company-from-filings-only)**

---

## Table of Contents

- [What Filings Alone Can Actually Tell You](#what-filings-alone-can-actually-tell-you)
- [Why Every Valuation Model Needs Something Filings Don't Have](#why-every-valuation-model-needs-something-filings-dont-have)
- [DCF: The Cash Flows Are Filed, the Discount Rate Isn't](#dcf-the-cash-flows-are-filed-the-discount-rate-isnt)
- [Comparable Multiples: Your Company's Numbers Are Filed, the Multiple Isn't](#comparable-multiples-your-companys-numbers-are-filed-the-multiple-isnt)
- [Asset-Based Valuation: Almost Entirely Filed, With One Open Question](#asset-based-valuation-almost-entirely-filed-with-one-open-question)
- [Dividend Discount Model: The History Is Filed, the Future Isn't](#dividend-discount-model-the-history-is-filed-the-future-isnt)
- [A Framework for Auditing Any Valuation](#a-framework-for-auditing-any-valuation)
- [What This Means for Reading GeminIQ's Metrics](#what-this-means-for-reading-geminiqs-metrics)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## What Filings Alone Can Actually Tell You

A 10-K and its preceding 10-Qs give you a complete, auditable record of what already happened: historical revenue and its growth rate, historical margins at every level of the income statement, historical free cash flow, the current balance sheet in full, share count, historical dividends paid, and enough history to compute trailing returns on capital. Every one of these traces to a specific XBRL tag in a specific filing, which means every one of them can be independently verified by anyone willing to open the document.

What filings cannot give you, under any circumstances, is anything about the future. That's not a limitation of any particular company's disclosure — it's structural. A filing reports what happened during a period that has already closed. Valuation is inherently a forward-looking exercise. The gap between those two facts is where every assumption in every valuation model has to live.

---

## Why Every Valuation Model Needs Something Filings Don't Have

No valuation methodology gets around this, because the problem isn't a gap in any particular model — it's a gap between what a filing is and what a valuation needs. A filing answers "what did this business generate." A valuation needs to answer "what is this business worth," which requires a view on what it will generate, and how much a dollar of that future generation is worth today. Filed data alone cannot answer either half of that question.

What varies by model is how much of the valuation gets built from the reliable, filed half before the assumption enters, and how exposed the final number is to a single judgment call. That's the actual difference between valuation methodologies worth understanding — not which one is "more accurate," but which one asks you to trust the least amount of unfiled judgment to get to an answer.

The four approaches covered below split like this:

| Valuation model | Inputs that are filed | Inputs that are assumed | Where the assumption concentrates |
|---|---|---|---|
| Discounted cash flow | Base-year free cash flow, margin structure, capital intensity — reconstructible from the cash flow and income statements | Future revenue growth, future margin trajectory, terminal growth rate, and the discount rate (risk-free rate, equity risk premium, beta) | The discount rate — the final output is as sensitive to that one rate as to every growth assumption combined |
| Comparable multiples | The company's own earnings, EBITDA, or revenue, and each peer's own reported figures | Which companies qualify as comparable, which period's figures to use, and the peer group's current multiple — a live market price, never reported in any filing | The multiple |
| Asset-based / book value | Every asset and liability line on the balance sheet | Whether filed book value approximates present worth — largest for goodwill and intangibles carried at historical acquisition price | Goodwill and intangibles, and historical-cost physical assets |
| Dividend discount | Every dividend actually paid, and the growth rate of that history, from the financing activities section | The future dividend growth rate and the required rate of return | Split across both — and the model only applies to companies with an established, stable dividend policy |

---

## DCF: The Cash Flows Are Filed, the Discount Rate Isn't

A discounted cash flow model's historical foundation — the free cash flow figures used to establish a base year, the margin structure, the capital intensity of the business — is entirely filed data, reconstructible from the cash flow statement and income statement directly. [Our full DCF walkthrough](/blog/dcf-valuation-model-step-by-step) builds exactly this foundation from a real 10-K, step by step.

Everything past that base year is assumption. Future revenue growth rates, future margin trajectories, and the terminal growth rate applied to the final projected year are all judgment calls a filing cannot supply, however carefully they're reasoned. The discount rate carries the same problem in a more concentrated form: [WACC requires a risk-free rate, an equity risk premium, and a beta](/blog/how-to-calculate-wacc-from-10k) — none of which appear anywhere in a 10-K, because none of them are company data at all. A DCF's final output is exactly as sensitive to that one rate as it is to every growth assumption combined, which is why the discount rate is the single highest-leverage assumption in the entire model. Platforms that publish a fair-value estimate have already made that choice on your behalf rather than exposing it — [how GeminIQ compares to Finbox](/competitor-comparison/finbox) covers that tradeoff directly.

---

## Comparable Multiples: Your Company's Numbers Are Filed, the Multiple Isn't

A comparable-multiples valuation looks deceptively simple: take the company's own [earnings, EBITDA](/blog/ev-ebitda-vs-pe-ratio-explained), or revenue — all filed — and multiply by whatever a peer group is currently trading at. The company's half of that equation is as reliable as any figure on this list. The multiple itself is not.

Three separate judgment calls sit inside "the multiple." Two are visible immediately: [which companies actually qualify as comparable](/blog/how-to-build-peer-comparison-set), and which period's figures to use for the peer group. The third gets skipped past most often: the peer group's current multiple is itself a live market price, not a filed number. A peer's own earnings are filed. What the market is currently willing to pay for those earnings is observed, continuously, in trading, and was never reported by anyone in a periodic filing. Applying "the industry trades at 15x" to a company's own filed earnings imports a market judgment wholesale, however precise the arithmetic looks once it's applied — and that imported judgment is itself an expectation about the future, [priced into the multiple](/blog/priced-for-perfection-explained) rather than filed anywhere.

---

## Asset-Based Valuation: Almost Entirely Filed, With One Open Question

Book value, net asset value, and liquidation-style approaches come closer than any other methodology to being fully derivable from a filing, because the inputs — every asset and liability line on the balance sheet — are filed by definition. This is the valuation approach with the smallest assumption-dependent surface area of anything on this list.

The one open question that remains is whether the filed book value of an asset approximates what it's actually worth today. Goodwill and intangibles carry the largest gap between book value and any real-world sense of value, since they represent historical acquisition prices rather than current market worth, and depend entirely on whether impairment testing has kept pace with reality. Physical assets carried at historical cost less depreciation can run either direction — understated for appreciating real estate, overstated for equipment nearing obsolescence. None of this requires a discount rate or a growth projection, which is exactly why this approach is the most filing-grounded of the four covered here.

---

## Dividend Discount Model: The History Is Filed, the Future Isn't

A dividend discount model's history — every dividend a company has actually paid, and the growth rate of that history — is filed data, directly reconstructible from the cash flow statement's financing activities section across as many periods as a company has reported. That history is also the least useful part of the model, because a DDM's output depends entirely on two things a filing cannot supply: the future dividend growth rate and the required rate of return applied to discount it.

The model is also structurally narrower than the others on this list — it only produces a meaningful answer for companies with an established, relatively stable dividend policy, which rules it out entirely for a large share of public companies regardless of how good the filed history looks.

---

## A Framework for Auditing Any Valuation

Every input in every model on this list falls into one of two categories, and naming which one applies to each line is the entire exercise. A filed input traces to a specific tag in a specific filing, is identical no matter who calculates it, and won't change until the next filing posts. An assumed input requires a judgment call a reasonable, informed analyst could make differently, and will shift depending on who's making it and when.

Applying that split to a finished valuation — anyone's, including your own — means asking, line by line: does this number come from a document I could open and verify, or does it come from a choice someone made? A valuation built mostly on the first kind deserves real confidence. A valuation that looks precise but is mostly the second kind, dressed up in enough decimal places to look objective, deserves exactly the confidence its weakest assumption can support — no more.

---

## What This Means for Reading GeminIQ's Metrics

GeminIQ's [Calculated Metrics](/features#calculated-metrics) are built entirely from the filed half of this framework, deliberately. [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained), historical margins, and growth rates all trace to specific XBRL tags with one published, consistent method — the same number, calculated the same way, for every company. GeminIQ does not calculate WACC, a target multiple, or a projected terminal value, for the same reason none of those numbers belong on this side of the line: doing so would mean silently picking a beta, a peer group, or a growth rate on the user's behalf and presenting the result with the same confidence as a figure that traces to an actual filing. [ROIC vs. ROE vs. WACC](/blog/roic-vs-roe-vs-wacc) covers why two of those three are reconstructible from filings and the third isn't.

The raw filed inputs every one of these models needs — cash flow, share count, capital structure, historical growth — are available directly. The judgment calls stay exactly where they belong: with the person building the valuation, made visibly rather than buried inside a number that looks more objective than it is.

---

## Frequently Asked Questions

### Can a company be valued using only its SEC filings, with no assumptions at all?

No. Filings report what already happened; valuation requires a view on the future, which no filing contains. What varies by methodology is how much of the final number rests on filed history versus forward-looking judgment — asset-based approaches lean furthest toward filed data, DCF and comparable multiples lean furthest toward assumption.

### Which valuation model relies least on unfiled assumptions?

Asset-based and book-value approaches, since nearly every input is a balance sheet line item filed directly. The tradeoff is that they answer a narrower question — what the assets are worth — rather than what the ongoing business is worth as a going concern.

### Why doesn't GeminIQ calculate a target price or fair value estimate?

A target price necessarily blends filed data with assumptions — a discount rate, a multiple, a growth projection — that require analyst judgment rather than being extracted from a filing. GeminIQ provides every filed input those models need and calculates every metric that's fully reconstructible from as-filed data, without asserting a single "correct" answer for the parts of any valuation that are inherently a judgment call.

### Is a comparable-multiples valuation more or less reliable than a DCF?

Neither is inherently more reliable — both blend filed and assumed inputs, just in different places. A comparable-multiples valuation concentrates its assumption in the multiple selected; a DCF spreads its assumptions across the discount rate, the growth trajectory, and the terminal value. Understanding where each model's assumption lives matters more than picking one model as universally superior.

Two valuations can use the same filed data and reach very different answers, and the entire difference will trace to the assumptions, not the facts. Knowing which parts of a number are which is the actual skill.

---

## Related Reading

- [Discounted Cash Flow (DCF) Model: Step-by-Step Walkthrough](/blog/dcf-valuation-model-step-by-step) — the full mechanics of the model covered briefly above.
- [How to Calculate WACC From a 10-K](/blog/how-to-calculate-wacc-from-10k) — the deep dive into exactly which half of a discount rate is filed and which half is market assumption.
- [ROIC vs. ROE vs. WACC: What Each One Actually Measures](/blog/roic-vs-roe-vs-wacc) — why GeminIQ calculates two of these three metrics and deliberately not the third.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=value-a-company-from-filings-only)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Value Investing Glossary: Terms, Ratios, and Mental Models Defined
source: https://www.geminiq.com/blog/value-investing-glossary

### Value Investing Glossary: Terms, Ratios, and Mental Models Defined
A comprehensive reference guide to every term, ratio, and mental model used in value investing — with plain-English definitions, formulas, and real-world examples from SEC filings.

**Value investing has its own language.** Pick up a Buffett shareholder letter, a Graham chapter, or a serious 10-K teardown and you will encounter dozens of terms that financial media uses loosely, aggregators define incorrectly, and beginners skip over entirely. This glossary exists to fix that. Every term below is defined in plain English, with the formula where it applies, a note on when the metric is most useful — and critically, a note on **when it breaks**, because knowing the limits of a tool is just as important as knowing how to use it.

This is a living reference. Bookmark it, link to it, and use it alongside your research.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=value-investing-glossary)**

---

## Table of Contents

- [Section 1: Balance Sheet Terms](#section-1-balance-sheet-terms)
- [Section 2: Income Statement Terms](#section-2-income-statement-terms)
- [Section 3: Cash Flow Terms](#section-3-cash-flow-terms)
- [Section 4: Valuation Ratios](#section-4-valuation-ratios)
- [Section 5: Quality and Return Metrics](#section-5-quality-and-return-metrics)
- [Section 6: Value Investing Concepts and Mental Models](#section-6-value-investing-concepts-and-mental-models)

---

## Section 1: Balance Sheet Terms

The balance sheet is a snapshot of what a company owns (assets), what it owes (liabilities), and what is left over for shareholders (equity) at a single point in time. It is the foundation of every solvency and capital structure analysis.

---

### What is Working Capital?

**Working Capital** is the difference between a company's current assets and its current liabilities. It measures a company's ability to meet its short-term obligations using assets it expects to convert to cash within the next twelve months.

**Formula:** Working Capital = Current Assets − Current Liabilities

A positive working capital number means the company can cover its near-term bills without borrowing. A negative number means it cannot — which is either a red flag or, in some businesses, a sign of extraordinary pricing power. Walmart and Amazon both run negative working capital because suppliers pay them after customers already have — meaning the business is, in effect, financed by its vendors. For most companies, however, sustained negative working capital is a warning sign worth investigating on the balance sheet directly.

**When it breaks:** Working Capital is a blunt instrument. It treats all current assets equally, but inventory that cannot be sold and receivables that will never be collected are not the same as cash. For businesses with perishable or illiquid inventory, strip out those items and look at the [Quick Ratio](/metrics/liquidity-ratios/quick-ratio) (Cash + Receivables divided by Current Liabilities) instead.

---

### What is Net Debt?

**Net Debt** is total debt minus cash and cash equivalents. It represents the debt burden a company would carry if it used all of its available cash to pay down borrowings immediately.

**Formula:** Net Debt = Total Debt − Cash and Cash Equivalents

Net Debt is more useful than gross debt for most analytical purposes because cash is essentially negative debt — it offsets the obligation. A company with $10B in debt and $9B in cash is in a very different position than a company with $10B in debt and $100M in cash, even though both show the same headline debt figure.

A negative Net Debt figure — meaning cash exceeds total debt — is referred to as a **net cash position** and represents a genuine balance sheet asset. [GameStop](/stocks/GME) is a good example of how this figure moves over time: after years of carrying almost no debt, the company added roughly $4.2 billion in 0% convertible notes during 2025 to fund its acquisition strategy, yet its cash pile is still large enough that it nets out to a **$3.25 billion net cash position** as of the most recent 10-Q — a reminder that "net cash" and "no debt" are not the same claim, and a distinction standard screeners often blur. See our [GameStop 10-Q teardown](/blog/gamestop-10k-analysis-2026) for a live breakdown.

**When it breaks:** Net Debt ignores lease obligations, pension liabilities, and off-balance-sheet commitments. For capital-intensive industries like airlines or retailers, add operating lease liabilities to get a complete picture of the true debt burden.

---

### What is Goodwill?

**Goodwill** is an intangible asset that appears on the balance sheet when a company acquires another business for more than the fair market value of its identifiable net assets. It represents the premium paid for things that cannot be separately valued — brand reputation, customer relationships, workforce quality, and proprietary processes.

**Formula:** Goodwill = Purchase Price − Fair Value of Net Assets Acquired

Goodwill does not amortize under U.S. GAAP (it did prior to 2001), but it must be tested for impairment annually. If the business acquired is worth less than what was paid, the company must write down the goodwill — taking a non-cash impairment charge that runs through the income statement and reduces equity. Large goodwill balances on the balance sheet are a signal to ask: how much of this company's book value is real, tangible assets versus accounting premium from past acquisitions?

**When it breaks:** Goodwill is only as reliable as management's impairment testing. Because impairment requires subjective fair value estimates, companies have significant latitude in determining when and how much to write down. A balance sheet loaded with goodwill that has never been impaired, despite acquisitions underperforming, is worth scrutinizing closely.

---

### What is Deferred Revenue?

**Deferred Revenue** (also called Unearned Revenue) is a liability on the balance sheet representing cash a company has already received from customers for goods or services not yet delivered. It is recognized as revenue only when the obligation is fulfilled.

From a value investing perspective, deferred revenue is one of the most interesting liability lines on any balance sheet — because it is actually a source of free capital. The customer has already handed over the cash. The company owes a future service, not a future cash payment. This dynamic is particularly powerful when the deferred revenue balance grows every year, as it does at [Costco](/stocks/COST), where **Deferred Membership Fees** grew from $1.6 billion (FY2018) to $3.16 billion (Q3 FY2026) — a compounding, interest-free float that funds the entire operation. See our [Costco 10-Q teardown](/blog/costco-stock-analysis-2026) for a detailed breakdown of how this works.

**When it breaks:** Not all deferred revenue is equal. Subscription-based deferred revenue (like Costco's membership fees) is highly reliable and low-risk to fulfill. Project-based deferred revenue in construction, aerospace, or government contracting carries real performance risk — if the project fails, the cash may need to be returned.

---

### What is Retained Earnings?

**Retained Earnings** is the cumulative sum of all net income a company has ever generated, minus all dividends it has ever paid out. It sits in the shareholders' equity section of the balance sheet and represents earnings that have been kept inside the business rather than distributed.

A growing retained earnings balance over time is a sign that a business is consistently profitable and reinvesting in itself. A declining retained earnings balance — or a negative one — means the company has paid out or lost more than it has earned. Negative retained earnings is sometimes called an **accumulated deficit** and is common in early-stage companies and in heavily levered businesses that have used debt-financed buybacks to hollow out their equity base.

**When it breaks:** Retained earnings alone tells you nothing about where the money went. A company could retain $10 billion over a decade and deploy it brilliantly into high-[ROIC](/blog/roic-return-on-invested-capital-explained) investments — or squander it on overpriced acquisitions that are already impaired. Always trace retained earnings alongside return on invested capital to understand the quality of that reinvestment.

---

### What is Treasury Stock?

**Treasury Stock** represents shares that a company has issued and subsequently bought back from the open market. These shares are held by the company itself, do not vote, receive no dividends, and reduce the total equity on the balance sheet.

Treasury stock appears as a negative number in the equity section, which is why companies that have aggressively repurchased shares can show dramatically reduced — or even negative — shareholders' equity. Starbucks is the canonical example: years of aggressive buybacks have produced persistently negative shareholders' equity that triggers screener "red flags" despite the underlying business being highly profitable. This is a case where raw balance sheet literacy matters more than any automated filter.

**When it breaks:** Treasury stock on its own reveals nothing about whether the buybacks were executed at good or bad prices. A company that bought back shares at 30x earnings when the stock was overvalued destroyed value; a company that bought back shares during a market dislocation created it. Always check the historical price at which buybacks were executed relative to intrinsic value.

---

### What is Book Value?

**Book Value** (also called Shareholders' Equity or Net Asset Value) is the accounting value of a company's equity — what would theoretically be left for shareholders if all assets were sold and all liabilities were paid at their stated balance sheet values.

**Formula:** Book Value = Total Assets − Total Liabilities

Book value is the foundation of the Price-to-Book ratio and was Benjamin Graham's preferred starting point for valuing companies. In Graham's era, most companies were asset-heavy manufacturers where book value was a reasonable proxy for liquidation value. In the modern economy, where the most valuable businesses are built on intellectual property, software, and brand — none of which appear on the balance sheet at fair value — book value has become far less reliable as a standalone measure of worth.

**When it breaks:** For asset-light businesses (software, consumer brands, financial services), book value is almost meaningless as a valuation anchor. For asset-heavy businesses (banks, insurers, industrial manufacturers), it remains highly relevant. Know which type of business you are analyzing before reaching for this ratio.

---

### What is Intrinsic Value?

**Intrinsic Value** is the true underlying economic worth of a business, independent of its current market price. It is what a rational, fully informed buyer would pay to own the entire business in a private transaction.

Unlike book value, intrinsic value is not reported anywhere — it must be estimated. The most common methods are [Discounted Cash Flow](/blog/dcf-valuation-model-step-by-step) (DCF) analysis, which projects future free cash flows and discounts them back to the present at an appropriate rate, and multiples-based approaches that apply a valuation ratio to a normalized earnings or cash flow figure. Buffett defines intrinsic value simply as the present value of all future cash distributions from the business.

The gap between intrinsic value and current market price is the central question of value investing. When price is meaningfully below intrinsic value, you have a margin of safety. When price exceeds intrinsic value, you are paying for growth that may or may not materialize.

**When it breaks:** Intrinsic value is only as good as the assumptions behind it. Small changes in growth rate or discount rate produce large changes in the output — a well-known problem called **garbage in, garbage out**. This is why Buffett emphasizes staying within your circle of competence: you can only make reasonable intrinsic value estimates for businesses whose economics you genuinely understand.

---

### What is Tangible Book Value?

**Tangible Book Value** is book value minus all intangible assets (goodwill, patents, trademarks, and customer relationships). It represents the liquidation value of the hard, physical assets of the business.

**Formula:** Tangible Book Value = Total Equity − Intangible Assets − Goodwill

For companies that have grown through acquisitions, there can be an enormous gap between book value and tangible book value. A company with $20 billion in book value and $18 billion in goodwill has only $2 billion in tangible assets backing its equity. This matters most in distress scenarios: if the business fails, goodwill is worth nothing. Physical assets — inventory, real estate, equipment — may recover something.

**When it breaks:** Tangible book value is a liquidation concept and has limited relevance for going-concern businesses with strong earnings power. A company with $1 of tangible book value per share and $10 of normalized earnings power per share is not cheap just because it trades above tangible book — the earnings power is the asset.

---

## Section 2: Income Statement Terms

The income statement (also called the Profit and Loss statement, or P&L) shows the revenues, costs, and profits generated over a specific period. Unlike the balance sheet, which is a snapshot, the income statement is a movie — it shows what happened over the quarter or the year.

---

### What is Gross Profit?

**Gross Profit** is revenue minus the direct cost of producing the goods or services sold (Cost of Goods Sold, or COGS). It represents what the company earns before accounting for operating expenses like salaries, rent, marketing, and administration.

**Formula:** Gross Profit = Revenue − Cost of Goods Sold

Gross profit and [gross margin](/metrics/margin-metrics/gross-profit-margin) (gross profit divided by revenue) are the first test of a business's pricing power. A high gross margin means the company retains a large portion of each revenue dollar before overhead — a hallmark of businesses with strong competitive advantages. Software companies routinely post 70-80% gross margins. Costco intentionally targets ~13% gross margin as a strategic moat — pricing merchandise near cost to drive membership value. The number itself is less important than understanding *why* it is what it is.

**When it breaks:** Gross margin comparisons across industries are meaningless. A 20% gross margin is excellent for a grocer and catastrophic for a software company. Always benchmark within the sector and ask whether management is choosing the margin (as Costco does) or constrained by it.

---

### What is Operating Income?

**Operating Income** (also called EBIT — Earnings Before Interest and Taxes) is gross profit minus all operating expenses: selling, general and administrative costs (SG&A), research and development, and depreciation and amortization. It represents the profit generated by the core business operations before accounting for how the company is financed (interest) or taxed.

**Formula:** Operating Income = Gross Profit − Operating Expenses

Operating income is the cleanest measure of business operating performance because it strips out financing decisions (interest expense) and jurisdictional quirks (tax rates) that are not part of the core operating model. Two companies in the same industry with identical operations but different capital structures will show the same operating income and very different net income. Operating income lets you compare the businesses, not the balance sheets.

**When it breaks:** Operating income includes depreciation — a non-cash charge that reduces reported income but does not consume cash. For asset-heavy businesses making large capital investments, depreciation can be a very real economic cost (because assets genuinely wear out and must be replaced). For asset-light businesses, it may overstate the actual cost burden.

---

### What is EBIT?

**EBIT** stands for Earnings Before Interest and Taxes. In most cases it is synonymous with Operating Income, though minor differences can arise in how companies classify certain non-operating items. EBIT is the standard input for the EV/EBIT valuation multiple.

See **Operating Income** above for the full definition and formula.

---

### What is EBITDA?

**EBITDA** stands for Earnings Before Interest, Taxes, Depreciation, and Amortization. It is operating income with depreciation and amortization added back — intended to approximate the cash-generating power of the business before capital investments.

**Formula:** EBITDA = Operating Income + Depreciation + Amortization

EBITDA became popular in leveraged buyout analysis and high-yield credit markets as a rough proxy for operating cash flow. Private equity firms use it to evaluate how much debt a business can service. It is also widely used as the denominator in the EV/EBITDA valuation multiple.

Warren Buffett famously despises EBITDA: *"Does management think the tooth fairy pays for capital expenditures?"* His point is that depreciation is a real economic cost — it represents the declining value of real assets that will eventually need to be replaced. Stripping it out produces a number that flatters capital-intensive businesses and enables them to appear far more profitable than they actually are.

**When it breaks:** EBITDA is most misleading for capital-intensive businesses where CapEx is large and recurring — airlines, telecom, manufacturing. It is least misleading for asset-light businesses where depreciation is minimal. Never use EBITDA without immediately asking: what does CapEx look like, and is depreciation roughly equal to maintenance CapEx?

---

### What is Net Income?

**Net Income** is the bottom-line profit remaining after all expenses — COGS, operating expenses, interest, taxes, and any extraordinary items — have been deducted from revenue. It is the number most screeners and media headlines focus on.

**Formula:** Net Income = Revenue − All Expenses − Interest − Taxes

Net income is the most commonly cited profitability figure and the least reliable one for value investors. It is subject to significant accounting discretion — revenue recognition timing, depreciation method choices, impairment decisions, and tax treatments all influence the reported number in ways that have nothing to do with underlying cash generation. The gap between reported net income and actual free cash flow is one of the most important things a fundamental analyst can measure.

**When it breaks:** Any time management has made significant non-cash adjustments, acquisition-related charges, or restructuring write-offs in the period. Always reconcile net income back to operating cash flow before drawing conclusions about profitability.

---

### What is Earnings Per Share (EPS)?

**Earnings Per Share (EPS)** is net income divided by the number of shares outstanding. It normalizes profitability to a per-share basis, enabling comparison across companies of different sizes and tracking of per-share earnings growth over time.

**Basic EPS Formula:** EPS = Net Income ÷ Basic Shares Outstanding

**Diluted EPS Formula:** EPS = Net Income ÷ Diluted Shares Outstanding (includes options, warrants, convertibles)

Diluted EPS is the more conservative and more relevant figure because it accounts for all securities that could convert into common shares and dilute existing shareholders. A company reporting strong basic EPS while issuing massive quantities of options and restricted stock awards is not growing per-share earnings the way the headline number implies.

**When it breaks:** EPS is meaningless for companies with negative net income, and it is easily manipulated through share buybacks — a company can grow EPS while shrinking in absolute terms simply by retiring shares. Always look at total net income alongside per-share figures.

---

### What is Stock-Based Compensation (SBC)?

**Stock-Based Compensation (SBC)** is the non-cash expense recorded when a company pays employees and executives with equity — options, restricted stock units (RSUs), or other equity awards — rather than cash. It runs through the income statement as an operating expense, reducing reported net income, but does not consume cash in the period it is recognized.

Because SBC is non-cash, many analysts add it back when calculating "adjusted" earnings or EBITDA — effectively treating it as if it does not cost the business anything. This is a significant analytical error. Stock-based compensation is absolutely a real cost: it dilutes existing shareholders' ownership percentage. Paying an employee $1 million in RSUs costs the company $1 million in value transferred from existing shareholders, regardless of whether any cash changed hands.

Amazon's SBC burden is one of the most discussed in the S&P 500. See our [Amazon 10-K teardown](/blog/amazon-10k-analysis-2026) for a detailed breakdown of how SBC inflates reported earnings and what the real cost looks like in the cash flow statement.

**When it breaks:** The relevance of SBC varies enormously by company. For a mature, profitable business issuing modest RSU grants, it is manageable. For a growth-stage company where SBC exceeds 20-30% of revenue, it represents a fundamental challenge to profitability that no amount of "adjusted EBITDA" can obscure.

---

### What is Revenue Recognition?

**Revenue Recognition** is the accounting principle governing when and how a company records revenue from the sale of goods or services. Under U.S. GAAP (ASC 606), revenue is recognized when the performance obligation is satisfied — i.e., when the promised goods or services are delivered to the customer — not when cash is received.

This matters enormously for investors because the timing of revenue recognition is a key lever for managing reported earnings. A company that ships products right before quarter-end to hit a revenue target, or a SaaS company that front-loads multi-year contract revenue, is engaging in the kind of accounting timing that can make reported revenue and cash flow diverge significantly.

**When it breaks:** Revenue recognition is one of the most litigated areas of accounting because it is highly judgment-dependent. Long-term contracts, bundled offerings, subscription services, and licensing arrangements all involve significant management discretion. Any time revenue is growing faster than cash collected, it is worth reading the revenue recognition footnotes in the 10-K carefully.

---

### What is Operating Leverage?

**Operating Leverage** describes the relationship between a company's fixed costs and its variable costs, and how that mix affects profitability as revenue changes. A business with high operating leverage has mostly fixed costs — meaning that as revenue grows, profits grow much faster (because each additional dollar of revenue carries little incremental cost). But when revenue falls, losses also amplify quickly.

Software businesses are classic high-operating-leverage models: building the software costs a lot, but selling one more copy costs almost nothing. Manufacturing businesses with large fixed plant and equipment also carry high operating leverage. This is why software margins can be extraordinary in growth phases and why industrial companies get crushed in recessions.

**When it breaks:** Operating leverage is not visible as a single line item — it must be inferred by looking at how margins change as revenue changes over multiple periods. A business can have identical margins in a given year regardless of its operating leverage structure; the difference only becomes apparent at the extremes of the revenue cycle.

---

## Section 3: Cash Flow Terms

The cash flow statement shows the actual movement of cash into and out of the business — segregated into operating, investing, and financing activities. Many value investors consider the cash flow statement the most honest of the three financial statements because cash is far harder to manipulate than accounting earnings.

---

### What is Operating Cash Flow (OCF)?

**Operating Cash Flow (OCF)** is the cash generated by a company's core business operations during a period. It starts with net income and adjusts for non-cash charges (adding back depreciation, amortization, and stock-based compensation) and changes in working capital (which can either consume or release cash depending on whether receivables, inventory, and payables are growing or shrinking).

**Formula:** OCF = Net Income + Non-Cash Charges ± Changes in Working Capital

OCF is a far more reliable measure of business health than net income for most analytical purposes because it captures the actual cash dynamics of the operating model. A business that reports positive net income but negative OCF is consuming more cash than its accounting profits suggest — often a warning sign of aggressive revenue recognition or deteriorating working capital management.

**When it breaks:** OCF can be temporarily inflated by favorable working capital changes — stretching payables, collecting receivables early, or drawing down inventory — that are not sustainable. Always look at OCF over multiple periods rather than a single quarter.

---

### What is Free Cash Flow (FCF)?

**Free Cash Flow (FCF)** is the cash remaining after a company has paid for the capital expenditures required to maintain and grow its business. It is the cash available for dividends, share buybacks, debt repayment, and acquisitions — the cash that actually flows to the owners.

**Formula:** Free Cash Flow = Operating Cash Flow − Capital Expenditures

FCF is the single most important number in intrinsic value analysis. Buffett's concept of Owner Earnings is closely related. A business that consistently converts a high percentage of its reported net income into free cash flow is a genuinely cash-generative business. A business that reports strong net income but minimal FCF is consuming its earnings in working capital or capital expenditure — a critical distinction that screeners miss entirely.

[Costco](/stocks/COST) has converted free cash flow at roughly 100% of net income in recent years — meaning it generates more cash than it earns in accounting profits — because of the deferred membership fee float and favorable supplier payment terms. See our [Costco 10-Q teardown](/blog/costco-stock-analysis-2026) for the full breakdown.

**When it breaks:** FCF can be temporarily distorted by the timing of large capital expenditures. A company building a new manufacturing plant will show depressed FCF for two or three years even if the underlying business is healthy. Always distinguish between **maintenance CapEx** (required to sustain current operations) and **growth CapEx** (investment in future capacity).

---

### What is Owner Earnings?

**Owner Earnings** is Warren Buffett's preferred measure of a business's true cash-generating power, introduced in the 1986 Berkshire Hathaway shareholder letter. It adjusts reported earnings for the economic reality of capital expenditure requirements.

**Formula:** Owner Earnings = Net Income + Depreciation and Amortization − Average Annual Maintenance CapEx ± Working Capital Changes

The key distinction between Owner Earnings and standard FCF is the treatment of capital expenditures. Standard FCF uses total CapEx as reported. Owner Earnings uses only the portion required to maintain the existing competitive position of the business — maintenance CapEx. Growth CapEx, Buffett argues, is an optional investment decision, not a cost of running the current business.

**When it breaks:** Separating maintenance CapEx from growth CapEx requires significant judgment and is not disclosed directly in most 10-K filings. Analysts typically estimate it based on depreciation as a percentage of gross assets or through industry benchmarks. The concept is most reliable for mature, stable businesses where CapEx patterns are consistent.

---

### What is Capital Expenditure (CapEx)?

**Capital Expenditure (CapEx)** is cash spent acquiring, upgrading, or maintaining physical assets — property, plant, equipment, and technology infrastructure. It appears as a cash outflow in the investing section of the cash flow statement, not as an expense on the income statement. Instead, CapEx is capitalized on the balance sheet and depreciated over time.

**Maintenance CapEx** is the portion required just to keep existing assets functional. **Growth CapEx** is the portion invested to expand capacity or capabilities. The difference matters enormously for free cash flow analysis: maintenance CapEx is a true cost, while growth CapEx is an investment with an expected future return.

**When it breaks:** Companies have wide discretion over whether to capitalize or expense a cost, which can significantly affect both reported earnings and CapEx figures. Aggressive capitalization shifts costs off the income statement and into CapEx, flattering near-term earnings while inflating the asset base.

---

### What is the Cash Conversion Cycle (CCC)?

**The [Cash Conversion Cycle](/blog/cash-conversion-cycle-formula-explained) (CCC)** measures how many days it takes a company to convert its investments in inventory and other resources into cash from sales. A shorter (or negative) CCC means the business collects cash quickly relative to when it pays its suppliers.

**Formula:** CCC = Days Inventory Outstanding + Days Sales Outstanding − Days Payable Outstanding

A negative CCC — which occurs when a company collects cash from customers before it pays its suppliers — is a powerful source of working capital financing. Amazon and Costco both achieve negative CCCs at scale, meaning their business models are self-financing. Walmart is similar. For capital-intensive businesses or those with long production cycles (aerospace, construction, shipbuilding), CCCs of 100+ days are common and require significant working capital funding.

**When it breaks:** CCC is most useful as a trend indicator. A rising CCC over time can signal that customers are taking longer to pay (receivables problem), inventory is building up (demand problem), or the company has lost negotiating leverage with suppliers (payables problem). Always look at which component is driving the change.

---

### What is FCF Yield?

**FCF Yield** is free cash flow per share divided by the current stock price. It is the cash-flow equivalent of earnings yield (the inverse of P/E) and represents how much free cash flow an investor receives per dollar of market price paid.

**Formula:** FCF Yield = Free Cash Flow Per Share ÷ Stock Price (or FCF ÷ Market Cap)

A higher FCF yield means you are getting more cash flow per dollar invested — generally indicating better value. A 5% FCF yield means you are paying 20x FCF; a 2% FCF yield means you are paying 50x FCF. FCF yield is particularly useful for comparing across companies where earnings are distorted by non-cash items or accounting differences, since cash is harder to manipulate.

**When it breaks:** FCF yield can be temporarily elevated by working capital releases or temporarily depressed by lumpy CapEx cycles. Always confirm that the FCF being used is sustainable and representative of a normal year's cash generation.

---

## Section 4: Valuation Ratios

Valuation ratios translate a company's financial performance into a price multiple — allowing you to compare what the market is paying for a dollar of earnings, cash flow, or assets across different companies and over time. No single ratio tells the whole story. Each one illuminates a different dimension of value.

---

### What is the P/E Ratio?

**The Price-to-Earnings Ratio (P/E)** is the market price per share divided by earnings per share. It represents how much investors are paying for each dollar of reported earnings. A P/E of 20x means investors are paying $20 for every $1 of annual earnings.

**Formula:** P/E = Market Price Per Share ÷ Earnings Per Share (TTM)

The P/E ratio is the most widely cited valuation multiple in finance — and consequently the most frequently misused. Its simplicity makes it powerful as a quick screen but dangerous as a sole analytical tool. A low P/E can indicate undervaluation, deteriorating business quality, cyclical trough earnings, or accounting distortions. A high P/E can indicate overvaluation, genuine high-quality compounders, or temporarily depressed earnings that make the denominator misleadingly small.

**When it breaks:** P/E is meaningless for unprofitable companies (the denominator is negative), misleading for cyclical businesses at peak or trough earnings, and unreliable when net income is heavily distorted by non-cash items, impairment charges, or tax anomalies. For mature businesses with clean accounting and stable earnings, it remains the clearest quick-check valuation tool available.

---

### What is Forward P/E?

**Forward P/E** uses estimated future earnings (typically the next twelve months' analyst consensus estimate) as the denominator rather than trailing reported earnings. It represents what investors are paying for expected future earnings.

**Formula:** Forward P/E = Market Price Per Share ÷ Next Twelve Months Estimated EPS

Forward P/E is useful when trailing earnings are known to be unrepresentative — after a restructuring, a large write-off, or during recovery from a cyclical trough. It is also the standard multiple cited by sell-side analysts in their coverage reports.

**When it breaks:** Forward P/E is only as good as the earnings estimates it uses — and analyst estimates are frequently wrong, especially at turning points in the economic cycle. In a downturn, "forward" P/E ratios often look deceptively cheap because estimates have not yet been revised down to reflect reality. Treat forward P/E as a directional tool, not a precise valuation anchor.

---

### What is the PEG Ratio?

**The PEG Ratio** (Price/Earnings to Growth) divides the P/E ratio by the expected earnings growth rate, attempting to normalize valuation for businesses growing at different rates. A PEG of 1.0 is often cited as "fair value" — meaning you are paying one dollar of P/E for each percentage point of growth.

**Formula:** PEG = P/E Ratio ÷ Expected Earnings Growth Rate (%)

The PEG ratio was popularized by Peter Lynch and is useful as a rough sanity check when comparing fast-growing companies. A company trading at 40x earnings with 40% expected growth has a PEG of 1.0; a company trading at 40x earnings with 5% expected growth has a PEG of 8.0 — far more expensive on a growth-adjusted basis.

**When it breaks:** PEG is extremely sensitive to the growth rate estimate used — and long-term growth rates are notoriously difficult to forecast accurately. It also assumes that all earnings growth is equally valuable, which is not true: growth funded by heavy CapEx or dilutive equity issuance is worth far less than organic, capital-light growth. Use PEG as a supplementary check, never as a primary valuation method.

---

### What is EV/EBITDA?

**EV/EBITDA** is Enterprise Value divided by EBITDA. It is one of the most widely used valuation multiples in professional investment analysis and M&A, because it is capital-structure neutral — it measures what buyers are paying for the operating business regardless of how it is financed.

**Enterprise Value Formula:** EV = Market Cap + Total Debt − Cash and Cash Equivalents
**EV/EBITDA Formula:** EV ÷ EBITDA

Because EV includes debt and subtracts cash, it represents the total cost to acquire the business outright. EBITDA approximates operating cash flow before capital investment. Together they produce a multiple that allows comparison across companies with very different debt levels, making it standard in leveraged buyout analysis and cross-company sector comparisons.

**When it breaks:** As discussed in the EBITDA definition above, this multiple is most misleading for capital-intensive businesses where the "DA" being added back represents real economic costs that will recur. Always pair EV/EBITDA with an assessment of typical CapEx as a percentage of EBITDA for the sector — if CapEx eats 80% of EBITDA, the multiple is far less attractive than it appears.

---

### What is EV/FCF?

**EV/FCF** (Enterprise Value to Free Cash Flow) is the capital-structure neutral version of the FCF yield — it tells you what you are paying for each dollar of free cash flow at the business level, regardless of how much debt the company carries.

**Formula:** EV ÷ Free Cash Flow

EV/FCF is considered by many serious value investors to be the most accurate single valuation multiple because it uses actual cash generation rather than accounting earnings or EBITDA estimates. It is harder to manipulate and more directly tied to intrinsic value. The inverse (FCF ÷ EV) gives you the FCF yield on the enterprise, which can be compared directly to bond yields or other investment alternatives.

**When it breaks:** FCF can be lumpy due to CapEx timing, working capital swings, or one-time items. Always use a normalized or TTM FCF figure rather than a single quarter's result, and confirm that the figure being used is representative of the business's ongoing cash-generating capacity.

---

### What is Price-to-Book (P/B)?

**Price-to-Book (P/B)** is market price per share divided by book value per share. It compares what the market is paying for the company to the accounting value of its net assets.

**Formula:** P/B = Market Price Per Share ÷ Book Value Per Share

A P/B below 1.0x means the market is valuing the company at less than its accounting net asset value — historically a starting point for deep value searches. Benjamin Graham built his net-net strategy around stocks trading below two-thirds of net current asset value, a form of extreme P/B screen. For banks and financial institutions, P/B remains the primary valuation anchor because their assets (loans, securities) are relatively close to market value.

**When it breaks:** P/B is nearly useless for asset-light businesses. A software company, consumer brand, or service business has most of its value in people, intellectual property, and customer relationships — none of which appear at fair value on the balance sheet. Apple, Google, and Microsoft all trade at very high P/B ratios not because they are overvalued but because their balance sheets dramatically understate the economic value of their businesses.

---

### What is Price-to-Sales (P/S)?

**Price-to-Sales (P/S)** is market capitalization divided by annual revenue. It measures what investors are paying for each dollar of revenue generated by the business.

**Formula:** P/S = Market Capitalization ÷ Annual Revenue

P/S is most useful for companies with no earnings — early-stage businesses, turnarounds, or cyclically depressed companies — where P/E is meaningless. It is also useful as a sanity check: a business trading at 20x sales needs to eventually generate very high margins to justify the price. At 1x sales, there is at least some margin of safety in the revenue base even if profitability is uncertain.

**When it breaks:** Revenue is not profit. A company with 5% net margins trading at 5x sales is far more expensive than a company with 30% net margins at 5x sales — the same P/S multiple represents very different valuations once profitability is considered. Always pair P/S with margin analysis.

---

### What is Dividend Yield?

**Dividend Yield** is the annual dividend per share divided by the current market price, expressed as a percentage. It represents the income return an investor receives from dividends relative to what they paid for the stock.

**Formula:** Dividend Yield = Annual Dividend Per Share ÷ Market Price Per Share × 100

Dividend yield is most relevant for income-oriented investors and for evaluating the relative attractiveness of dividend-paying stocks versus bonds. A rising dividend yield (from a falling stock price, not an increase in the dividend) can signal either an attractive entry point or a deteriorating business about to cut its payout.

**When it breaks:** A high dividend yield is not automatically attractive. If the dividend is unsustainable — if the payout ratio (dividends as a percentage of earnings or FCF) is above 100% — the company is borrowing to pay dividends and will eventually be forced to cut. A dividend cut typically causes a severe stock price decline. Always confirm that the dividend is covered by free cash flow, not just accounting earnings.

---

## Section 5: Quality and Return Metrics

Quality metrics measure not what a company earned, but how efficiently it used its capital to earn it. They are the metrics that separate genuinely great businesses from businesses that merely look profitable on a headline basis.

---

### What is Return on Invested Capital (ROIC)?

**Return on Invested Capital (ROIC)** measures how much operating profit a company generates for every dollar of capital it has deployed in the business. It is the single most important metric for evaluating business quality and the compounding potential of a long-term investment.

**Formula:** ROIC = Net Operating Profit After Tax (NOPAT) ÷ Invested Capital

Where:
- **NOPAT** = Operating Income × (1 − Tax Rate)
- **Invested Capital** = Total Equity + Total Debt − Cash and Cash Equivalents (or equivalently, Net Working Capital + Net Fixed Assets)

A business earning ROIC above its cost of capital (WACC) is creating value for shareholders with each dollar reinvested. A business earning ROIC below WACC is destroying value even if it is growing revenue. Charlie Munger has said that over the long run, the return a shareholder earns on a stock will roughly approximate the underlying business's ROIC — making it the foundational metric for long-term compounding analysis.

[Costco's](/stocks/COST) ROIC of 33.4% on a meager 3.82% operating margin is one of the most striking examples of capital efficiency in the S&P 500 — the product of the membership float, negative working capital, and supplier payment dynamics that together minimize the capital required to run the business. See our [Costco teardown](/blog/costco-stock-analysis-2026) for the full breakdown.

**When it breaks:** ROIC can be temporarily distorted by large impairments or restructuring charges that artificially reduce the invested capital base, producing a misleadingly high return. Always confirm that invested capital is representative of the normal operating asset base.

---

### What is Return on Equity (ROE)?

**Return on Equity (ROE)** measures net income as a percentage of shareholders' equity. It answers the question: for every dollar shareholders have invested in the business (at book value), how much profit does the company generate?

**Formula:** ROE = Net Income ÷ Average Shareholders' Equity

ROE was Benjamin Graham's primary quality filter. Consistently high ROE (15%+) over a long period typically indicates a durable competitive advantage. It is also the building block of the DuPont Decomposition, which breaks ROE into its component drivers.

**When it breaks:** ROE is inflated by financial leverage — borrowing money to amplify returns on equity. A company with 40% ROE funded primarily by debt may be taking on enormous financial risk to generate that number. Always pair ROE with a leverage analysis (Debt/Equity ratio or interest coverage) to confirm the return is operating-driven rather than leverage-driven. Companies with significant share buybacks can also show very high ROE simply because they have reduced the equity denominator.

---

### What is Return on Assets (ROA)?

**Return on Assets (ROA)** measures net income as a percentage of total assets. It represents how efficiently management is using the company's entire asset base — both debt-financed and equity-financed — to generate profit.

**Formula:** ROA = Net Income ÷ Average Total Assets

ROA is a less leverage-sensitive measure of profitability than ROE, because assets include both equity and debt. It is particularly useful for comparing companies in capital-intensive industries (banks, industrial manufacturers, utilities) where the asset base is the primary driver of business performance.

**When it breaks:** ROA is sensitive to the composition of a company's asset base. Companies with large goodwill balances from acquisitions inflate total assets, reducing apparent ROA even if the underlying operations are highly efficient. Banks are the most common use case for ROA analysis; for most other industries, ROIC is the preferred metric.

---

### What is Gross Margin?

**Gross Margin** is gross profit expressed as a percentage of revenue. It measures the profitability of a company's core product or service before operating expenses.

**Formula:** Gross Margin = (Revenue − Cost of Goods Sold) ÷ Revenue × 100

Gross margin is the first test of competitive advantage. A sustainably high gross margin suggests the company can price its products or services above cost — evidence of pricing power, brand value, or a structural cost advantage. Software companies routinely achieve 70-80%+ gross margins. Hardware companies, retailers, and commodity businesses are structurally lower.

**When it breaks:** As noted throughout this glossary, gross margins are only meaningful within-sector comparisons. A 15% gross margin is excellent for a grocery chain and disastrous for a SaaS business.

---

### What is Operating Margin?

**Operating Margin** is operating income expressed as a percentage of revenue. It measures the profitability of the core business after all operating costs — but before interest and taxes.

**Formula:** Operating Margin = Operating Income ÷ Revenue × 100

Operating margin is the clearest measure of management's ability to run the business efficiently at scale. Companies that maintain or expand operating margins over time while growing revenue are demonstrating genuine operating leverage. Companies where operating margins compress as revenue grows are failing to scale efficiently — a warning sign for long-term investors.

**When it breaks:** Operating margin can be temporarily inflated by cutting R&D or marketing — investments that support future growth but are not strictly required in the near term. A rising operating margin achieved by starving the business of investment is not the same as a rising margin achieved through genuine efficiency.

---

### What is Net Profit Margin?

**Net Profit Margin** is net income expressed as a percentage of revenue. It represents the percentage of each revenue dollar that falls to the bottom line after every expense — COGS, operating costs, interest, and taxes.

**Formula:** Net Profit Margin = Net Income ÷ Revenue × 100

Net margin is the broadest profitability measure and the most influenced by one-time items, tax rate changes, and financing costs. It is most useful as a long-term trend indicator and for cross-company comparisons within the same industry, where capital structures and tax situations are roughly similar.

**When it breaks:** Net margin is the most susceptible to distortion of any profitability metric. A large asset impairment, a favorable tax settlement, or a one-time gain on the sale of a business can swing net margin dramatically in a single quarter. Always look through one-time items to assess the underlying run-rate margin.

---

### What is ROIC vs. WACC?

**ROIC vs. WACC** is the fundamental test of whether a business is creating or destroying shareholder value. WACC (Weighted Average Cost of Capital) is the blended required return of a company's debt and equity holders — what the business must earn just to break even in economic terms.

**The Value Creation Test:** If ROIC > WACC, the business is generating returns above its cost of capital → it is creating economic value. If ROIC < WACC, the business is destroying economic value even if it shows positive accounting profits.

**WACC Formula:** WACC = (Weight of Equity × Cost of Equity) + (Weight of Debt × Cost of Debt × (1 − Tax Rate))

The spread between ROIC and WACC — (ROIC − WACC) — is the clearest quantitative expression of competitive advantage. A wide, sustainable positive spread means the business has a moat. A narrow or negative spread means competition or structural headwinds are eroding returns. This is why the airline industry, which earns ROIC near or below WACC through most cycles, has historically been one of the worst long-term investments despite consistent revenue growth.

**When it breaks:** WACC is estimated, not observed, and small differences in cost of equity assumptions can produce meaningfully different conclusions. Use ROIC vs. WACC directionally rather than as a precise calculation.

---

### What is the Altman Z-Score?

**The Altman Z-Score** is a quantitative model developed by NYU professor Edward Altman in 1968 to predict the probability of corporate bankruptcy using five financial ratios. Despite its age, it remains one of the most widely used credit stress tests in fundamental analysis.

**Formula:** Z-Score = 1.2(X1) + 1.4(X2) + 3.3(X3) + 0.6(X4) + 1.0(X5)

Where:
- X1 = Working Capital ÷ Total Assets
- X2 = Retained Earnings ÷ Total Assets
- X3 = EBIT ÷ Total Assets
- X4 = Market Value of Equity ÷ Book Value of Total Liabilities
- X5 = Revenue ÷ Total Assets

**Interpretation:**
- Z-Score above **3.0** → Safe zone
- Z-Score between **1.8 and 3.0** → Gray zone (elevated risk)
- Z-Score below **1.8** → Distress zone (high bankruptcy risk)

American Airlines posted an Altman Z-Score of 0.66 in our airline sector stress test — placing it deep in the distress zone, a conclusion that [Institutional Ownership](/features#institutional-ownership) data confirmed: smart money was actively avoiding the stock. See the [GeminIQ Airline Intel Brief](/blog/airline-sector-stock-analysis) for the full analysis.

**When it breaks:** The Altman Z-Score was calibrated on manufacturing companies in the 1960s. It is less predictive for financial institutions, utilities, and asset-light service businesses. Use it as a distress screening tool rather than a definitive verdict, and always pair it with cash flow coverage ratios.

---

### What is the DuPont Decomposition?

**The DuPont Decomposition** breaks Return on Equity into three component drivers, revealing *why* a company earns the ROE it does — whether through superior profitability, efficient asset utilization, or financial leverage.

**Three-Factor DuPont Formula:**
ROE = Net Profit Margin × Asset Turnover × Equity Multiplier

Where:
- **Net Profit Margin** = Net Income ÷ Revenue (profitability)
- **Asset Turnover** = Revenue ÷ Average Total Assets (efficiency)
- **Equity Multiplier** = Average Total Assets ÷ Average Shareholders' Equity (leverage)

Two companies can have identical ROE through completely different paths. Company A earns 20% ROE through 15% net margins and low leverage. Company B earns 20% ROE through 3% margins, high asset turnover, and significant debt. The businesses have identical headlines but completely different risk profiles and quality levels. DuPont reveals which is which.

**When it breaks:** The DuPont framework is a diagnostic tool, not a valuation tool. It tells you the source of returns, not whether those returns are sustainable or fairly priced.

---

## Section 6: Value Investing Concepts and Mental Models

Beyond the ratios, value investing has a vocabulary of concepts and mental models — frameworks for thinking about business quality, competitive advantage, and the relationship between price and value. These are the ideas that Buffett, Munger, Graham, and Lynch reach for repeatedly, and that separate disciplined long-term investors from the rest.

---

### What is Margin of Safety?

**Margin of Safety** is the discount between a security's market price and its estimated intrinsic value. It is Benjamin Graham's foundational concept — the principle that you should only buy something when it is priced significantly below what you believe it is worth, providing a cushion against errors in your analysis and unforeseen deterioration in business conditions.

If you estimate a business is worth $100 per share and it trades at $70, your margin of safety is 30%. Graham typically required a 33% margin of safety. The concept acknowledges that even careful analysis involves uncertainty — a margin of safety means that if you are modestly wrong, you still don't lose money.

**The key implication:** Margin of safety is not a permanent feature of a stock. It exists at a price, not a company. A great business at the wrong price offers no margin of safety. An average business at a sufficient discount may offer substantial safety. Buying Costco at 51x earnings and 51x FCF involves a fundamentally different margin of safety calculation than buying it at 30x earnings would.

---

### What is Circle of Competence?

**Circle of Competence** is the concept, articulated by Warren Buffett and Charlie Munger, that every investor has a defined domain of industries and business models they genuinely understand — and that the key to sound investing is knowing the boundaries of that domain and refusing to venture outside it.

The size of the circle is less important than knowing exactly where its edge is. Buffett declined to invest in technology companies for decades not because he thought they were bad businesses, but because he could not predict their economics with sufficient confidence. That discipline — knowing what you don't know — is as important as knowing what you do.

**The practical application:** Before buying any stock, ask: can I explain in plain English how this business makes money, what its competitive position is, what could go wrong, and what it would take for my thesis to fail? If you cannot answer all four with confidence, you are outside your circle.

---

### What is an Economic Moat?

**An Economic Moat** is a durable competitive advantage that protects a company's profits from competition over time — the business equivalent of a castle's defensive moat. The term was popularized by Warren Buffett. Morningstar's equity research framework identifies five primary moat sources:

**1. Cost Advantage** — The ability to produce goods or services at a lower cost than competitors, allowing the business to undercut on price or earn higher margins at the same price. Costco's warehouse model and scale purchasing create a structural cost advantage in retail.

**2. Switching Costs** — When customers face significant financial, operational, or psychological costs to switch to a competitor's product, they tend not to switch even when alternatives exist. Enterprise software (Oracle, SAP), payment networks, and industrial equipment with proprietary consumables all benefit from switching costs.

**3. Network Effects** — When a product or service becomes more valuable to each user as the total number of users grows, creating a virtuous cycle that makes it increasingly hard for new entrants to compete. Visa and Mastercard are the canonical examples — a payment network with more merchants is more valuable to cardholders, and vice versa.

**4. Efficient Scale** — When a market is large enough to support only one or a few competitors profitably, and new entrants would face economics so poor that rational competitors avoid entering. Regional monopolies like utilities and pipelines often benefit from efficient scale.

**5. Intangible Assets** — Patents, regulatory licenses, brand recognition, and proprietary databases that prevent competitors from replicating a product or command a price premium. Pharmaceutical companies' patent estates and consumer brand equity (Coca-Cola, Apple) are the most common examples.

**The key test:** A moat exists if the business can sustain returns on invested capital above its cost of capital over a long period. If competitors can easily replicate the business model and drive returns toward average, there is no moat.

---

### What is Float?

**Float** in investing refers to money held by a company that belongs, in an accounting sense, to someone else — but which the company can invest or deploy in the interim at no cost. It is one of Warren Buffett's favorite business characteristics and the structural advantage that built Berkshire Hathaway.

In insurance, float is premiums collected but not yet paid out in claims. Berkshire collects billions in insurance premiums every year, holds that capital, invests it for Berkshire's benefit, and only pays it out if and when claims arise. If underwriting is disciplined, the insurance is written at breakeven or better — meaning the float costs nothing and the investment returns are pure profit.

The same mechanic operates at [Costco](/stocks/COST) with its Deferred Membership Fees — $3.16 billion in cash collected from members upfront, sitting on the balance sheet as a "liability," being deployed at zero cost. It is one of the primary reasons Costco's ROIC is so far above what its thin operating margins would otherwise suggest. See our [Costco teardown](/blog/costco-stock-analysis-2026).

---

### What is Mr. Market?

**Mr. Market** is Benjamin Graham's famous metaphor for the stock market, introduced in *The Intelligent Investor*. Imagine a business partner — Mr. Market — who shows up every day and offers to either buy your share of the business or sell you his, at a price he names. Some days he is euphoric and names an absurdly high price. Some days he is despondent and offers to sell at a price far below intrinsic value.

The key insight: you are never obligated to transact with Mr. Market. You can ignore his daily quotes entirely. He will be back tomorrow with a different price. The intelligent investor uses Mr. Market's mood swings as an opportunity — buying when he is irrationally pessimistic and ignoring him when he is irrationally exuberant.

**The practical implication:** Market prices are not pronouncements of intrinsic value. They are offers from an emotional counterparty. Treating short-term price movements as signals about business quality — rather than as opportunities to buy or ignore — is one of the most common and costly mistakes in investing.

---

### What is Mean Reversion?

**Mean Reversion** is the empirical tendency for extreme values — unusually high profit margins, unusually high ROIC, unusually low valuations — to gradually return toward historical averages over time. In business terms, high profitability attracts competition that erodes margins; low profitability drives capital exit that eventually improves returns.

Mean reversion is both a risk and an opportunity for value investors. It is a risk when paying a premium for businesses whose high margins are being competed away faster than expected. It is an opportunity when buying businesses at cyclical troughs where temporarily depressed earnings are causing the market to undervalue durable, long-cycle assets.

**The key exception:** Businesses with genuine economic moats can sustain above-average ROIC for decades without mean-reverting. The history of Buffett's returns is largely the history of finding businesses where mean reversion does not apply.

---

### What is Capital Allocation?

**Capital Allocation** is the process by which management decides how to deploy the company's generated cash flow — reinvesting in the business (organic growth), acquiring other businesses, returning capital to shareholders (dividends and buybacks), or paying down debt.

The quality of capital allocation is arguably the most important determinant of long-term shareholder returns for mature, cash-generative businesses. A business that earns 25% ROIC on its reinvested earnings will compound shareholder wealth at a fundamentally different rate than a business that earns 8% on reinvestment — even if both generate the same free cash flow today.

Buffett's willingness to hold massive cash at Berkshire — over $330 billion in recent filings — rather than deploy it at inadequate returns is one of the clearest examples of disciplined capital allocation in the public market. Conversely, executives who pursue empire-building acquisitions at any price regardless of return on capital are among the most reliable destroyers of shareholder value.

---

### What is an Owner-Operator?

**An Owner-Operator** is an executive who has a substantial personal ownership stake in the company they run — meaning they think and act like an owner rather than a hired manager. The alignment of incentives between an owner-operator and outside shareholders is structurally superior to the typical executive-shareholder relationship, where executives may be incentivized by salary, short-term stock price performance, or empire-building.

Ryan Cohen's role at GameStop — taking exactly $0 in base salary and structuring all compensation around long-term acquisition milestones — is a textbook owner-operator setup. His personal capital is at risk alongside outside shareholders, creating genuine skin in the game. See our [GameStop 10-K teardown](/blog/gamestop-10k-analysis-2026).

The [Insider Transactions](/features#insider-transactions) data in GeminIQ is one of the best tools for identifying owner-operator behavior: executives who consistently buy stock on the open market (rather than merely receiving shares through compensation grants) are demonstrating genuine conviction with personal capital.

---

### What is Normalized Earnings?

**Normalized Earnings** are a company's earnings adjusted to remove one-time, non-recurring, or cyclical distortions — representing what the business would earn in a "normal" operating environment.

Reported earnings in any given year may be depressed by restructuring charges, asset impairments, litigation settlements, or cyclical revenue troughs. They may be inflated by one-time gains, favorable tax events, or cyclical peak revenue. Normalized earnings attempt to see through these temporary effects to the underlying earnings power of the business.

Normalized earnings are particularly important for cyclical industries — steel, oil and gas, shipping, semiconductors — where earnings swing dramatically with commodity prices or demand cycles. Buying a cyclical company at a low P/E on peak earnings (which makes it appear cheap) is one of the most common value traps in investing.

**When it breaks:** Normalization requires judgment about what is truly "one-time" versus what is a recurring feature of the business. Management has a natural incentive to label bad news as non-recurring and good news as core. Reading the 10-K footnotes carefully rather than relying on adjusted earnings releases is the only reliable way to make this determination.

---

### What is the Difference Between Price and Value?

**Price** is what you pay. **Value** is what you get. This is the central distinction of value investing — and the one most systematically confused by market participants who treat market prices as reliable signals of underlying worth.

Price is determined by the market: the collective result of every buyer and seller transacting at a given moment, reflecting information, emotion, liquidity needs, index mechanics, momentum, and narrative as much as fundamental economics. Value is determined by the business: its future cash flows, its competitive position, its management quality, and its reinvestment opportunities.

The two converge over long periods — a great business will eventually be recognized by the market, and an overpriced mediocre business will eventually disappoint. In the short term, they can diverge dramatically in either direction. The investor's edge comes from having a more accurate estimate of value than the market has priced in — and the patience to wait for the gap to close.

As Graham put it: *In the short run, the market is a voting machine. In the long run, it is a weighing machine.*

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Value Line Alternative: Filing-Sourced Fundamentals
source: https://www.geminiq.com/blog/value-line-alternative-sec-data

### Value Line Alternative: Filing-Sourced Fundamentals
A Value Line alternative for investors who need the full filing. Value Line covers roughly 1,700 stocks with analyst pages refreshed on a quarterly review cycle; this post explains what editorial curation adds and what a one-page format cannot carry.

Value Line has been doing something difficult since long before software: condensing a company onto one page in a format an investor can read in five minutes and compare against any other page in the survey. Roughly 1,700 of the most actively traded US-listed stocks across more than 90 industries, each with historical financials, three-to-five-year projections, an eighteen-month target price range, analyst commentary, and the proprietary Timeliness and Safety ranks.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=value-line-alternative-sec-data)**

The consistency is the achievement. Every page has the same shape, which makes comparison across companies almost frictionless, and libraries have stocked the survey for generations because it works.

Two structural properties of that format are worth understanding before it becomes the foundation of a process. It covers a curated subset of the market, and each page is refreshed on a review schedule rather than a filing schedule.

## Table of Contents

- [The Review Cycle Is Not the Filing Cycle](#the-review-cycle-is-not-the-filing-cycle)
- [Seventeen Hundred Out of Ten Thousand](#seventeen-hundred-out-of-ten-thousand)
- [One Page Is an Editorial Decision](#one-page-is-an-editorial-decision)
- [What the Ranks Are Made Of](#what-the-ranks-are-made-of)
- [The Complete Record Instead of the Summary](#the-complete-record-instead-of-the-summary)
- [Curation Has a Place in the Process](#curation-has-a-place-in-the-process)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Review Cycle Is Not the Filing Cycle

Value Line's own product descriptions state the cadence: roughly 130 reports are fully reviewed by analysts each week, which cycles the survey's coverage universe about once a quarter.

That is a considerable amount of analyst labor and it produces a consistent, well-maintained library. It also means a company's full-page report reflects the analyst's most recent review rather than the company's most recent filing.

The consequence is timing. A 10-Q filed shortly after a review sits outside the page until the next cycle comes around. For a stable large-cap in an ordinary quarter, that gap rarely matters. It matters most in exactly the situations where a page gets consulted urgently — a company that just reported something unexpected, a business whose position changed materially, a stock that moved sharply on news. Those are the moments when the most recent filing is the entire point, and a quarterly review cycle cannot guarantee it has been incorporated.

Filings have no cycle to wait for. A 10-Q is public the moment it is submitted.

## Seventeen Hundred Out of Ten Thousand

The coverage figure is the more consequential constraint, and Value Line is transparent about it.

The survey covers approximately 1,700 of the most actively traded US-listed stocks, which the company describes as representing around 90% of the market capitalization traded on US exchanges. Both statements are accurate simultaneously, and the tension between them is the point: 90% of market value can sit inside a small fraction of the companies, because value concentrates and companies do not.

The number of US-listed companies is several times 1,700, and the ones outside the survey are the small, thinly traded, and unfollowed. That population is where the least competitive analysis is being done, which is precisely why some investors go looking there.

An investor whose universe is defined by a research provider's coverage list has adopted somebody else's judgment about what deserves attention. That judgment is reasonable — covering illiquid microcaps for a subscription audience does not pay — and it still bounds the opportunity set before any analysis begins.

## One Page Is an Editorial Decision

The single-page format is the product's signature and its constraint, and both follow from the same fact.

Fitting fifteen years of financials, projections, ranks, a price chart, and written commentary onto one page requires choosing what fits. Someone decided which line items appear, at what level of aggregation, and what gets omitted. Those choices are consistent across the survey, which is what makes pages comparable, and consistency is achieved by applying the same template to every business regardless of what makes a particular business unusual.

The material that does not fit is not trivial. Footnote detail explaining what an aggregated caption contains. Segment reporting where a company presents more segments than a template row. Lease composition, debt maturity schedules, contingencies, and the accounting policy notes that determine what a number means.

A summary is a summary. The value is in the compression, and the cost is that the compressed material is unrecoverable from the page.

## What the Ranks Are Made Of

Timeliness and Safety are the survey's most cited outputs and they are constructed differently from each other.

Timeliness forecasts relative price performance over the coming six to twelve months. It is a forward-looking projection, and like every forecast, it is an opinion expressed numerically rather than a measurement.

Safety is derived from a company's Financial Strength rating and its stock's Price Stability score. Financial Strength is a proprietary assessment. Price Stability is a market-derived measure computed from price behavior, not from anything the company filed. So Safety blends a proprietary judgment with a market statistic, and neither component is a line item you could look up in a 10-K.

That is a legitimate way to build a risk indicator and it is not a filed fact. The pattern is familiar from every composite in this category: the rank is a conclusion, the filings are the evidence, and only one of the two can be independently reconstructed.

## The Complete Record Instead of the Summary

GeminIQ has no analysts, no commentary, no ranks, and no projections. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years at the granularity the filing used rather than the granularity a template allows. [Custom Tables](/features#custom-tables) assemble specific reported items, including ones a standard page would have aggregated away. [Visualizations](/features#visualizations) chart the reported structure over time. [Calculated Metrics](/features#calculated-metrics) including [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital), [Altman Z-Score](/metrics/leverage-and-debt-ratios/altman-z-score), and [Debt-to-Equity Ratio](/metrics/leverage-and-debt-ratios/debt-to-equity-ratio) are computed from as-filed inputs, so a risk indicator can be audited against the numbers behind it rather than accepted as a grade.

Coverage extends to every SEC filer, because inclusion is a filing requirement rather than an editorial decision, and updates arrive when a company files rather than when a review comes due.

## Curation Has a Place in the Process

Dismissing analyst-curated research would be the wrong lesson to take from any of this.

A well-written company page from someone who has followed a business for years compresses an enormous amount of context, and reading one is often the fastest way to understand what a company does, how its industry works, and which variables management is actually managing. That is real value, and it is the same value the best sell-side and independent research provides.

The failure is treating a summary as the record. A page is one analyst's rendering of a business, produced on a schedule, within a format, for a coverage list somebody else drew. Every one of those constraints is reasonable and every one of them stands between the reader and the document the company filed.

For the same coverage-and-conclusion question at a larger research publisher, the [Morningstar alternatives](/blog/morningstar-alternative-sec-filing-data) post covers analyst-assigned ratings and their scope limits.

Read the page for the orientation. Open the filing for the decision, because a summary tells you what an analyst concluded was worth including — and only the filing tells you everything the company was required to disclose.

## Frequently Asked Questions

### What are the best Value Line alternatives?

It depends on what you use it for. For analyst-written company pages, ranks, and projections, the substitutes are other curated research publishers, all of which cover a defined universe on a review schedule. For the complete filed record across every SEC registrant, the alternative is a platform that extracts from EDGAR and preserves as-filed line items with XBRL tag traceability.

### How many stocks does Value Line cover?

The Investment Survey covers approximately 1,700 of the most actively traded US-listed stocks across more than 90 industries, which Value Line describes as representing roughly 90% of the market capitalization traded on US exchanges. The number of US-listed companies is considerably larger, so coverage concentrates in the largest and most liquid names.

### How often are Value Line reports updated?

Value Line's materials describe approximately 130 reports being fully reviewed by analysts each week, which cycles the covered universe roughly once per quarter. A page reflects the analyst's most recent review, so a filing submitted shortly after a review may not appear until the next cycle.

### What is the Value Line Safety Rank based on?

Value Line describes Safety as derived from a company's Financial Strength rating and its stock's Price Stability score. Financial Strength is a proprietary assessment and Price Stability is computed from price behavior rather than from filed financial data, so the rank combines a judgment with a market statistic rather than reporting a figure from a 10-K.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=value-line-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Value Line Investment Survey coverage universe, industry count, weekly review cadence, report contents, projection horizons, and the composition of the Timeliness and Safety ranks reviewed August 2, 2026 from Value Line's own product pages and subscriber guides.

---

## Blog: How to Verify Financial Data Against the SEC Filing (Step-by-Step)
source: https://www.geminiq.com/blog/verify-financial-data-against-sec-filing

### How to Verify Financial Data Against the SEC Filing (Step-by-Step)
Verifying financial data against the SEC filing resolves discrepancies between platform numbers and the original 10-K or 10-Q. This four-step workflow uses EDGAR's XBRL Interactive Data viewer to identify the source and type of any discrepancy.

You pulled up a company on your research platform of choice, noted the figure, then opened the actual 10-K — and the numbers don't match. The labels look the same. The period is the same. But the value sitting in your platform is not the value the company filed. This is not a rare occurrence. It is a structural feature of how most financial data platforms work, and once you understand it, you can resolve any discrepancy in four steps.

This post walks through that workflow. Not why the pipeline exists — that is covered in [How Financial Data Reaches Investors and What Gets Lost Along the Way](/blog/how-financial-data-reaches-investors). Not which platforms normalize what — that question has its own answer elsewhere. This post is for the investor sitting with a discrepancy in front of them who wants to resolve it right now.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=verify-financial-data-against-sec-filing)**

---

## Table of Contents

- [Step 1: Identify the Exact Line Item in Dispute](#step-1-identify-the-exact-line-item-in-dispute)
- [Step 2: Find the Filing and Locate the XBRL Tag](#step-2-find-the-filing-and-locate-the-xbrl-tag)
- [Step 3: Compare the Tag to Your Platform's Value](#step-3-compare-the-tag-to-your-platforms-value)
- [Step 4: Diagnose the Discrepancy Type](#step-4-diagnose-the-discrepancy-type)
- [Why Financial Platform Data Sometimes Differs from the SEC Filing](#why-financial-platform-data-sometimes-differs-from-the-sec-filing)
- [The Hardest Case: When Labels Match But Values Don't](#the-hardest-case-when-labels-match-but-values-dont)
- [When Discrepancies Compound Into Metric Errors](#when-discrepancies-compound-into-metric-errors)
- [The Shortcut: Platforms That Preserve the XBRL Layer](#the-shortcut-platforms-that-preserve-the-xbrl-layer)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## Step 1: Identify the Exact Line Item in Dispute

Before you can trace a discrepancy, you need to be precise about what you are comparing. Two numbers can differ for legitimate reasons — one platform may be showing a trailing twelve-month figure while the other shows annual, or one may be displaying the value in millions while the other shows it in thousands, or one may be showing a fiscal year end while the other shows a calendar year. Rule these out first.

Confirm that you are comparing the same entity, the same period, the same fiscal year convention, and the same unit of measure. If all four align and the numbers still disagree, you have an actual discrepancy — and the source is almost certainly in how the platform handled the underlying SEC filing.

Write down three things before proceeding: the exact label as your platform displays it, the exact value your platform shows, and the exact value you found in the filing. That three-column comparison is the starting point for every step that follows.

---

## Step 2: Find the Filing and Locate the XBRL Tag

Go to [SEC EDGAR](https://www.sec.gov/search-filings) and search for the company by ticker or CIK number. Navigate to the filing type (10-K for annual, 10-Q for quarterly) and the specific period that matches your discrepancy. Open the filing index page and look for the Inline XBRL viewer link — it typically appears as a blue "Interactive Data" button on the filing index.

The Interactive Data viewer is the SEC's own interface for browsing XBRL-tagged financial data. It organizes the filing into the Income Statement, Balance Sheet, Cash Flow Statement, and Notes. Find the line item in question within the viewer. Click on the value — the viewer will display the full XBRL tag name associated with that data point, along with the exact value and the period it covers.

That tag name is your ground truth. For example, [Apple's](/stocks/AAPL) "Other non-current liabilities" carries the tag `OtherLiabilitiesNoncurrent`. [Apple's](/stocks/AAPL) stock repurchases appear as two separate tagged items: `PaymentsForRepurchaseOfCommonStock` and `PaymentRelatedToTaxWithholdingForShareBasedCompensation`. If your platform is showing a single combined buyback figure, that tells you immediately that two distinct XBRL-tagged line items were merged into one.

Note the tag name, the as-filed value, and the period context. You now have the source of truth from the primary document.

---

## Step 3: Compare the Tag to Your Platform's Value

Return to the platform showing the discrepancy and ask one question: does the label on the platform correspond to a single XBRL tag in the filing, or could it represent multiple tags that were merged?

This is where most discrepancies live. A platform label of "Stock Repurchases" might combine `PaymentsForRepurchaseOfCommonStock` with `PaymentRelatedToTaxWithholdingForShareBasedCompensation` — two economically distinct items. A platform label of "Other Non-Current Liabilities" might subtract lease obligations from the as-filed value and keep the original label. A platform label of "Short-Term Debt" might combine commercial paper and the current portion of long-term debt, even though these represent fundamentally different refinancing risks.

The merger is intentional and is not unique to any single platform. third-party data providers — the intermediary layer that most financial research tools license data from — design their templates for cross-company comparability. When two companies report structurally similar obligations under different labels, the aggregator maps both into a single standardized bucket. The result is data that compares cleanly across companies but no longer traces cleanly back to either company's filing. At this stage, you either find the matching XBRL value and confirm the platform is accurate, or you identify a gap. If there is a gap, the discrepancy has a type — and knowing which type determines what to do with it analytically.

---

## Step 4: Diagnose the Discrepancy Type

Not all discrepancies are the same, and diagnosing which type you are dealing with determines what to do with it analytically. There are four patterns worth knowing.

**Line-item consolidation.** Two or more XBRL-tagged line items were merged into one platform label. The sum of the merged items will match the platform's value. This is the most common type. The diagnostic is arithmetic: add the individual filing line items and see if they equal the platform figure. If they do, you are looking at consolidation, not error.

**Label-value mismatch.** The platform preserved the same label as the filing but changed the value by adding or subtracting another line item. This is the most dangerous type because it looks correct at a glance. The documented example from [Apple's](/stocks/AAPL) FY2025 10-K is instructive: a normalized platform showed **$29,946M** under "Other Non-Current Liabilities" while the as-filed value was **$41,549M** — an **$11.6 billion** difference under an identical label, caused by the aggregator subtracting capital lease obligations from the line. Without checking the XBRL tag value directly, this discrepancy is invisible. This case is detailed further in the [Third-Party Financial Data Problems](/blog/third-party-financial-data-problems) post.

**Company-specific item absorption.** A line item unique to the company was reclassified into a generic bucket. The individual item disappears from the display entirely. The value is not lost — it reappears inside a broader category — but the analytical identity of the asset or liability is gone. [Apple's](/stocks/AAPL) **$33.2 billion** Vendor Non-Trade Receivables (XBRL tag: `NontradereceivablesCurrent`) represents trade receivables from [Apple's](/stocks/AAPL) manufacturing partners for components [Apple](/stocks/AAPL) has already purchased on their behalf. On a normalized platform, this often folds into "Other Current Assets," removing the economic signal entirely.

**Retroactive taxonomy revision.** The aggregator updated its data model and reclassified a historical line item across prior periods. The number on your platform today differs from the number you saw six months ago — not because the company restated anything, but because the aggregator changed its taxonomy. This is the hardest discrepancy to catch because it happens silently and affects historical data. If you notice a value that contradicts your own prior notes and the company filed no restatement, check whether the aggregator's methodology has been updated.

---

## Why Financial Platform Data Sometimes Differs from the SEC Filing

The discrepancy you found is not a bug in any specific platform. Most financial research tools rely on licensed data from institutional financial data providers whose core product is a normalized, cross-company-comparable financial dataset. That dataset is built for breadth: tens of thousands of companies, dozens of countries, standardized templates that make any company's income statement look structurally similar to any other company's.

Building that standardization requires methodology decisions. When [Apple](/stocks/AAPL) reports commercial paper separately from term debt, the template has to decide whether those are two line items or one. When [Apple](/stocks/AAPL) reports vendor non-trade receivables separately from trade receivables, the template has to decide whether to preserve that distinction or fold it into a generic receivables category. When a company's cash flow statement separates equity award tax withholding from [share repurchases](/blog/do-buybacks-reduce-share-count), the template has to decide whether those are one cash outflow or two.

There is no universally correct answer to any of these questions for the purpose of broad comparison. But for the purpose of verifying a specific number against a specific filing, the methodology decision is the discrepancy. The platform made a choice. The filing made no such choice — it reported what the company actually recorded.

This is why the verification workflow above starts with the XBRL tag rather than the platform label. The tag is the one element in the chain that cannot be reinterpreted. `OtherLiabilitiesNoncurrent` means the same thing in every filing that uses it, because the SEC's GAAP taxonomy defines it. Once you have the tag and the as-filed value, you have a fixed reference point that no normalization decision can obscure.

The four-step workflow above applies regardless of which platform produced the discrepancy.

---

## The Hardest Case: When Labels Match But Values Don't

Of the four discrepancy types, label-value mismatches deserve extra attention because they are the ones most likely to produce downstream analytical errors without ever being noticed.

When a platform displays a value under the same label as the filing but the value has been adjusted, the analyst who does not cross-check will treat the platform figure as the as-filed figure. That assumption gets built into models, metrics, and investment theses. The error is invisible at the surface level — you are looking at a label you recognize, in a period you selected, for a company you know. Nothing triggers a verification check.

The way to protect against this category is to make the EDGAR XBRL viewer a routine part of your research process rather than a one-time diagnostic. For any balance sheet or cash flow line item where the absolute value matters to your analysis — total debt, capital lease obligations, buyback figures, specific working capital items — spend sixty seconds confirming the XBRL tag value before incorporating the platform figure into a model or thesis.

The SEC's Inline XBRL viewer makes this possible in two or three clicks for any filing since 2021, and for most large-cap filings going back to 2009. It requires no account, no subscription, and no additional software.

---

## When Discrepancies Compound Into Metric Errors

A single line-item discrepancy rarely stays isolated. Financial ratios and calculated metrics are built from multiple inputs, and a discrepancy in any one of them cascades through every calculation that uses it.

Consider [Return on Invested Capital](/blog/roic-return-on-invested-capital-explained) — a metric that GeminIQ's [Calculated Metrics](/features#calculated-metrics) derives directly from XBRL-tagged balance sheet and income statement data. ROIC requires Net Operating Profit After Tax divided by [Invested Capital](/metrics/calculated-values/invested-capital). Invested Capital, in turn, is calculated from total assets, cash, total debt, and operating lease obligations — several of which are precisely the line items most likely to differ between a normalized platform and the as-filed data.

If a platform combines commercial paper with current term debt into a single "Short-Term Debt" figure and uses the combined number in its Invested Capital calculation, the result is numerically close to correct but structurally different from a calculation built on the three distinct as-filed instruments. If a platform subtracts **$11.6 billion** in capital leases from "Other Non-Current Liabilities" and applies that adjusted figure to a leverage ratio, the ratio is wrong by the magnitude of the adjustment — and there is no way to identify the error from the ratio output alone.

This cascading effect is why the verification workflow matters most for the inputs to metrics, not just for standalone line items. A discrepancy in one balance sheet line silently distorts every ratio that touches it.

For investors who build their own financial models, the practical implication is simple: trace every model input to a specific XBRL tag before running the model. For investors who rely on platform-calculated metrics, the implication is to understand what the platform's methodology is for the key metrics in your thesis — and whether that methodology preserves or adjusts the as-filed inputs.

---

## The Shortcut: Platforms That Preserve the XBRL Layer

The four-step verification workflow above is thorough, but it is also time-consuming. For investors doing deep due diligence on a handful of positions, it is appropriate. For investors doing broad research across dozens of companies, it is not scalable.

The scalable alternative is to use a platform whose data starts at the XBRL tag level rather than at a normalized template. When the data source is the filing itself — not a third-party aggregator's interpretation of the filing — the verification step is built into the data rather than bolted on afterward.

GeminIQ pulls financial statement data directly from SEC EDGAR, preserves every XBRL tag as filed, and structures it for analysis without reclassification. The [Financial Statements](/features#financial-statements) on GeminIQ display each line item exactly as the company reported it, with its source tag available for audit. [Apple's](/stocks/AAPL) Vendor Non-Trade Receivables appears as its own line. [Apple's](/stocks/AAPL) three debt instruments appear separately. [Apple's](/stocks/AAPL) buyback figure and its equity tax withholding figure appear as two distinct cash flow line items — because that is how they appear in the filing.

The [Calculated Metrics](/features#calculated-metrics) GeminIQ pre-calculates — including ROIC, Free Cash Flow, Net Debt, [Debt-to-EBITDA](/blog/debt-to-ebitda-ratio-explained), and more than fifty others — are derived from those same as-filed inputs, not from a normalized template. When the metric shows a value, you can trace it to the formula, and from the formula to the specific XBRL tags that fed it.

This does not eliminate the need to read filings. Nothing does. But it does eliminate the verification overhead that comes from working with data that has already been processed before you see it. The step between "the number on my screen" and "the number in the filing" is removed, because they are the same number.

---

## Frequently Asked Questions

### Why does my financial platform show different numbers than the SEC filing?

Most financial research platforms license data from third-party providers who normalize SEC filings into standardized templates for cross-company comparability. The normalization process combines, reclassifies, or adjusts line items to fit a generic template. The result is data that compares cleanly across thousands of companies but no longer traces cleanly to any individual filing. The discrepancy is a feature of the normalization methodology, not a data error in the traditional sense.

### How do I access XBRL-tagged data directly from the SEC?

Go to [sec.gov/edgar](https://www.sec.gov/search-filings), search for the company, navigate to the relevant 10-K or 10-Q filing, and open the Interactive Data viewer from the filing index page. The viewer organizes all XBRL-tagged financial data by statement type. Clicking any value in the viewer reveals its XBRL tag, the exact period it covers, and the as-filed amount. The SEC's CompanyFacts API also provides bulk XBRL data programmatically for every filer.

### Is the discrepancy always the platform's fault?

Not always. Some discrepancies arise from legitimate definitional choices. Free cash flow, for instance, has no single GAAP definition — one platform might define it as operating cash flow minus capital expenditures, while another might subtract lease payments or include restricted cash. For metrics with established but non-universal definitions, the discrepancy reflects methodology, not error. The four-step workflow applies primarily to line items that have direct XBRL counterparts in the filing — income statement items, balance sheet items, and explicitly tagged cash flow items.

### How far back does XBRL data go on EDGAR?

Large accelerated filers began tagging in 2009. All public companies were required to tag by 2012. The Inline XBRL format — which embeds tags directly in the human-readable HTML filing — became mandatory for large accelerated filers in 2020 and for all filers by 2021. For most major companies, you have uninterrupted XBRL-tagged data going back to fiscal years ending in 2009 or 2010.

### What should I do if the discrepancy affects a metric I'm using in a model?

Identify which XBRL-tagged inputs feed the metric, verify each input against the filing, and rebuild the calculation from the as-filed values. For the most commonly used metrics — ROIC, Free Cash Flow, Net Debt, Debt-to-EBITDA — GeminIQ's [Calculated Metrics](/features#calculated-metrics) provides pre-calculated values derived directly from XBRL-tagged source data, which removes the input verification step from the workflow.

### Does this problem affect all companies equally?

Companies with simple, standard reporting structures lose less in normalization. Companies with unusual or company-specific line items — custom receivables categories, multi-instrument debt structures, non-standard working capital items, large off-balance-sheet arrangements — lose the most. The irony is that the companies where the discrepancy is largest are often the ones where accurate line-item data matters most to the analysis.

---

## Related Reading

- [Third-Party Financial Data Problems: What Gets Lost Before It Reaches You](/blog/third-party-financial-data-problems) — documented examples of normalization discrepancies, including the **$11.6 billion** Apple balance sheet gap
- [How Financial Data Reaches Investors and What Gets Lost Along the Way](/blog/how-financial-data-reaches-investors) — a stage-by-stage look at the pipeline from SEC filing to investor screen
- [What Is XBRL? How SEC Tagging Affects Your Investment Data](/blog/what-is-xbrl) — a full primer on the tagging system that makes verification possible
- [What Investors Miss in SEC Filings](/blog/what-investors-miss-in-sec-filings) — the information that lives in filings but disappears in any normalized dataset

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=verify-financial-data-against-sec-filing)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025, fiscal year ending September 27, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193&type=10-K).

---

## Blog: Warren Buffett's Portfolio: How to Read Berkshire's 13F
source: https://www.geminiq.com/blog/warren-buffetts-portfolio-13f

### Warren Buffett's Portfolio: How to Read Berkshire's 13F
Warren Buffett's portfolio is public record, disclosed every quarter through Berkshire Hathaway's Form 13F — including its actual current holdings, led by Apple at 22% of the disclosed portfolio. But the filing comes with a 45-day lag, covers U.S. long equity positions only, and gets misread constantly by investors chasing the headline 'Buffett bought X' rather than the position change underneath it. This guide covers Berkshire's real Q2 2026 holdings and how to read the filing correctly.

Warren Buffett's portfolio isn't a secret. It's public record, filed with the SEC every quarter, and available to anyone willing to read a Form 13F. What's actually hard isn't finding the filing — it's reading it correctly, because the way financial media covers it strips out nearly every detail that makes it useful and leaves behind a headline ("Buffett buys X," "Berkshire trims Y") that a 13F alone can't fully support.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=warren-buffetts-portfolio-13f)**

This guide covers what Berkshire Hathaway's 13F actually discloses, the specific limitations that make headline coverage misleading, how to read a position change the way the filing actually supports, and — using the actual Q2 2026 filing — exactly what Berkshire's disclosed portfolio holds today. (Its largest position, [Apple](/stocks/AAPL), alone accounts for just over a fifth of the entire disclosed portfolio — a position that large moves the portfolio's reported value with every swing in the stock, independent of whether Berkshire has traded a single share.)

---

## Table of Contents

- [What a 13F Actually Discloses](#what-a-13f-actually-discloses)
- [What Berkshire Actually Holds (Q2 2026 13F)](#what-berkshire-actually-holds-q2-2026-13f)
- [The 45-Day Lag Problem](#the-45-day-lag-problem)
- [What the Filing Can't Tell You](#what-the-filing-cant-tell-you)
- [How to Read a Position Change Correctly](#how-to-read-a-position-change-correctly)
- [Why Concentration Matters More Than Any Single Holding](#why-concentration-matters-more-than-any-single-holding)
- [Tracking Any 13F Filer on GeminIQ](#tracking-any-13f-filer-on-geminiq)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What a 13F Actually Discloses

Form 13F is a quarterly filing required of any institutional investment manager overseeing more than **$100 million** in qualifying securities, and Berkshire Hathaway — as the manager of its own equity portfolio — has filed one every quarter for decades. The filing lists each U.S.-listed equity position the manager holds at quarter-end: the company, the number of shares, and the market value at that date.

That's the entire scope. It's a snapshot of long equity holdings in U.S.-traded securities, filed once per quarter, nothing more. For the full mechanics of what a 13F requires and how the reporting threshold works, see our guide on [institutional ownership and 13F filings](/blog/institutional-ownership-13f-filing-explained).

---

## What Berkshire Actually Holds (Q2 2026 13F)

Berkshire's 13F-HR for the quarter ended **June 30, 2026** — filed **August 14, 2026**, signed by Vice Chairman Marc D. Hamburg — reported **29 distinct positions** across its disclosed U.S. equity portfolio, worth **$299.25 Billion** in aggregate at quarter-end prices. Here is the full ranked list:

| Rank | Company | Value | % of Portfolio |
|---|---|---|---|
| 1 | [Apple](/stocks/AAPL) | $65.95 Billion | 22.04% |
| 2 | [American Express](/stocks/AXP) | $51.28 Billion | 17.14% |
| 3 | [Coca-Cola](/stocks/KO) | $32.51 Billion | 10.86% |
| 4 | [Alphabet](/stocks/GOOGL) (Class A) | $28.16 Billion | 9.41% |
| 5 | [Bank of America](/stocks/BAC) | $27.54 Billion | 9.20% |
| 6 | [Chevron](/stocks/CVX) | $13.99 Billion | 4.67% |
| 7 | Occidental Petroleum | $12.87 Billion | 4.30% |
| 8 | Chubb | $11.67 Billion | 3.90% |
| 9 | Moody's | $11.17 Billion | 3.73% |
| 10 | Alphabet (Class C) | $9.61 Billion | 3.21% |

<sup>*Remaining 19 positions — Kraft Heinz, DaVita, Delta Air Lines, SiriusXM, Verisign, Kroger, Ally Financial, Lennar, Liberty Live Holdings, and others — together make up the remaining 11.5% of the portfolio.*</sup>

A few things worth reading directly off this table rather than trusting a secondhand summary. **Apple is the largest position by a wide margin**, at just over a fifth of the entire disclosed portfolio — confirming the point made earlier about how much a single holding this size moves the reported total on price movement alone. **Alphabet appears twice**, as Class A and Class C shares (different CUSIPs, same underlying company); combined, the two classes total **$37.76 Billion**, or **12.62%** — enough to rank as Berkshire's third-largest position on a combined basis, ahead of Coca-Cola. And the concentration is severe even by Berkshire's own standards: the **top 5 positions account for 68.7%** of the entire disclosed portfolio, and the **top 10 account for 88.5%** — against our [13F concentration](/blog/13f-portfolio-concentration-signal) framework, that's a manager making a small number of very large bets, not spreading risk across dozens of moderate ones.

None of this is a static fact. It's a photograph of one specific date, already six weeks old by its public filing date and older still by the time you're reading this — which is exactly why the next section matters.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=warren-buffetts-portfolio-13f)**

---

## The 45-Day Lag Problem

A 13F is due no later than **45 days** after the quarter it covers ends — meaning a position disclosed in a Q1 filing, submitted in mid-May, reflects where the portfolio stood on March 31, not where it stands the day the filing becomes public. By the time anyone reads "Berkshire bought X," the position could already be six weeks larger, six weeks smaller, or gone entirely.

This lag is the single most under-discussed limitation of 13F-based coverage, and it's why treating a 13F headline as current, actionable information about what a fund is doing *right now* is a category error the filing itself warns against, just not in language most readers stop to notice.

---

## What the Filing Can't Tell You

A handful of specific gaps matter more for Berkshire's filing than most, given how the market reads it:

**No short positions and no derivatives.** A 13F discloses long equity holdings only. Any hedge, short position, or options strategy layered around a disclosed position is invisible — the filing shows the long stock, not the full risk picture around it.

**No non-U.S. holdings.** Foreign-listed equities that don't trade as U.S.-listed securities or ADRs don't appear, regardless of size or conviction.

**No timing within the quarter.** A position that was built entirely in the first week of the quarter and one built entirely in the last week both show up identically as of quarter-end — the filing can't distinguish a decisive early conviction buy from a late, tentative toe-in.

**No context for the decision.** The filing shows what changed, never why. A trimmed position could reflect a change in thesis, a portfolio-level rebalancing unrelated to the stock itself, or simply a need to fund a larger purchase elsewhere.

---

## How to Read a Position Change Correctly

The mechanically correct way to read any 13F — Berkshire's included — is to compare the current filing against the *prior* quarter's filing for the same manager and look at the shares-held delta, not the headline. A "new position" means the manager held zero shares last quarter and some positive number this quarter. An "increased position" is a share count that rose. A position that disappears entirely between filings was fully exited sometime in that quarter — but again, without visibility into exactly when.

The number of *shares* is the reliable figure to compare, not the reported market value, because market value moves with the stock price even when the manager makes no trade at all — comparing quarter-over-quarter dollar values without checking whether the share count actually changed will misread ordinary price movement as a trading decision.

---

## Why Concentration Matters More Than Any Single Holding

Berkshire's 13F is unusually concentrated relative to the typical institutional filer — as the table above shows, 29 positions total, with the top 5 alone accounting for **68.7%** of the disclosed portfolio and the top 10 for **88.5%**. That's a pattern consistent with a genuine high-conviction approach rather than an index-tracking mandate, where a manager holding hundreds of positions in roughly market-cap-weighted proportions is making a fundamentally different kind of statement than one willing to put nearly a fifth of the portfolio in a single name. Our guide on [13F portfolio concentration](/blog/13f-portfolio-concentration-signal) covers how to calculate that ratio and what threshold separates genuine conviction from index-hugging noise, across the full universe of 13F filers, not just Berkshire.

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---

## Tracking Any 13F Filer on GeminIQ

Rather than reading a 13F filer's holdings in isolation, the more useful question for an individual stock you already follow is the reverse: which institutional holders — Berkshire included — appear in a given company's ownership base, and how has that holder count changed. GeminIQ's [Institutional Ownership](/features#institutional-ownership) feature shows exactly this for any covered company, built from the as-filed 13F data rather than a delayed aggregator feed, so a rising or falling institutional holder count is visible on the same page as the company's own [financial statements](/features#financial-statements) — letting you check whether a change in institutional interest lines up with anything happening in the underlying business.

---

## Frequently Asked Questions

### How often does Warren Buffett's 13F get updated?

Quarterly. Berkshire Hathaway, like every institutional manager overseeing more than $100 million in qualifying securities, must file a 13F no later than 45 days after each calendar quarter ends — meaning four snapshots a year, each already six-to-seven weeks old by the time it's public.

### Does Warren Buffett's 13F show everything Berkshire owns?

No. It shows only long positions in U.S.-listed equity securities as of the quarter-end snapshot date. It excludes short positions, derivatives, non-U.S.-listed holdings, Berkshire's wholly-owned operating businesses, and any timing detail about when during the quarter a position was built or trimmed.

### Why does 13F data lag by 45 days?

The SEC's filing deadline for Form 13F is 45 calendar days after the end of each quarter, giving institutional managers time to compile and certify their holdings. There's no faster public disclosure mechanism for this data — real-time institutional position data for most managers simply doesn't exist as a public filing.

### Is a new position in a 13F always a bullish signal?

It confirms a manager held shares at quarter-end that it didn't hold the prior quarter — nothing more specific than that. Without knowing when in the quarter the position was built, at what price, or whether it's since been trimmed in the following quarter, a single new position is directional information, not a complete trading signal.

### What is Warren Buffett's largest stock holding?

As of Berkshire Hathaway's 13F-HR for the quarter ended June 30, 2026 (filed August 14, 2026), Apple was the largest disclosed position at $65.95 Billion, representing 22.04% of the portfolio's total reported value. This is a single quarterly snapshot, already dated by the time it was public — check GeminIQ's Institutional Ownership feature or a fresh 13F filing for the current figure.

---

## Wall Street's data. Main Street's price.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. We built GeminIQ because we believe you deserve a better fundamental analysis tool—one that goes beyond basic price charts and processed numbers. We extract our data directly from SEC 10-K and 10-Q filings to ensure that when you check institutional ownership, you are seeing the numbers exactly how they were filed. Our goal is to give you the tools to verify the narrative for yourself using clean, traceable data. Start researching now at [GeminIQ.com](/).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=warren-buffetts-portfolio-13f)**

Holdings data in this article references Berkshire Hathaway Inc.'s Form 13F-HR for the quarter ended June 30, 2026 (filed August 14, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001067983&type=13F).

---

## Blog: How to Read an 8-K: Material Events That Actually Move Stocks
source: https://www.geminiq.com/blog/what-is-8-k

### How to Read an 8-K: Material Events That Actually Move Stocks
An SEC Form 8-K must be filed within 4 business days of a material event. This guide covers every major item type, the filed vs. furnished distinction, and which 8-Ks actually move stock prices.

The earnings press release hits at 4:05 PM. The stock moves **8%** in after-hours trading. By the time the financial media publishes its summary, the move is already made — and most retail investors are reading a journalist's interpretation of a document they never opened. That document is the 8-K. It arrived on EDGAR before the earnings call started. It contains the actual disclosure, in the company's own words, under SEC filing requirements. But standard financial media doesn't read the primary source — it reads the headline and calls it analysis.

The 8-K is the SEC's current report filing — the document companies must submit whenever something material happens between their periodic [10-K](/blog/how-to-read-10-k) and [10-Q](/blog/how-to-read-10-q) filings. CEO departures, major acquisitions, restructuring charges, auditor changes, debt agreements, and going concern disclosures all arrive in 8-Ks first. Knowing how to find it, read it, and interpret it separates the investor who knows what actually happened from the one who knows what the press release said. This guide covers every major 8-K item type, explains the critical filed-versus-furnished distinction that most platforms ignore, and shows how to use 8-K filings as a real-time research signal.

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## Table of Contents
- [What Is an SEC Form 8-K?](#what-is-an-sec-form-8-k)
- [The 8-K Item Types That Move Stocks](#the-8-k-item-types-that-move-stocks)
- [Filed vs. Furnished: The Distinction Most Investors Miss](#filed-vs-furnished-the-distinction-most-investors-miss)
- [How an 8-K Is Structured on EDGAR](#how-an-8-k-is-structured-on-edgar)
- [Red Flag 8-K Items Investors Overlook](#red-flag-8-k-items-investors-overlook)
- [How the 8-K Fits Into the Broader Filing System](#how-the-8-k-fits-into-the-broader-filing-system)

---

## What Is an SEC Form 8-K?

An SEC Form 8-K is a current report that every SEC-registered public company must file when a material event occurs. Unlike the 10-K or 10-Q — which are periodic filings with scheduled deadlines — the 8-K is triggered by the event itself. No material event, no filing. Material event, mandatory filing.

The SEC defines materiality in the context of 8-K reporting through a list of item types, each corresponding to a specific category of event. If an event falls within one of those categories, the company has no discretion — it must file. The item types range from earnings releases and acquisition completions to auditor resignations and notices that prior financial statements can no longer be relied on. Not all of them carry equal market weight, but understanding which ones do is the difference between reacting to news and reading the source of it.

### When Must Companies File?

Companies must file an 8-K within 4 business days of the triggering event. For most items — CEO departures, material agreements, acquisition closings — the clock starts the day the event occurs. For earnings releases filed under Item 2.02, the 8-K typically goes out simultaneously with the press release, often before the earnings call begins. This is the earliest moment the public has access to the reported numbers. The 10-Q with auditable GAAP financials follows weeks later.

There are two limited exceptions to the 4-business-day window. Item 8.01, the catch-all "Other Events" category, has no set deadline — it is a voluntary disclosure that companies use at their discretion. And companies can request a 15-calendar-day extension for Item 1.01 filings when the disclosure involves confidential business information. Extensions are rare. When they occur, they are worth noting.

---

## The 8-K Item Types That Move Stocks

The SEC's 8-K form is organized into sections, each containing specific numbered items. These are the ones that carry real investor significance.

### Item 2.02 — Results of Operations and Financial Condition

This is the earnings release 8-K — the most widely read filing for most investors. When a company reports quarterly results, it files an 8-K under Item 2.02 and attaches the earnings press release as Exhibit 99.1. That exhibit contains the revenue, net income, earnings per share, and guidance that hit EDGAR at the same moment they are distributed to financial media.

The Item 2.02 8-K is typically "furnished," not "filed" — a distinction covered in depth below. What matters here is the timing: this document arrives before the earnings call, before the transcript, and before any analyst commentary. Guidance updates are particularly important and often underemphasized in coverage. A company can beat the quarterly earnings estimate while simultaneously cutting full-year guidance — and both are in the same exhibit. The stock reacts to both. The move — as shown in our [analysis of post-earnings stock reactions](/blog/stock-price-reaction-after-earnings) — is often complete before the first analyst appears on air.

### Item 5.02 — Departure of Directors or Certain Officers

An unexpected CEO departure filed under Item 5.02 can be one of the most market-moving 8-Ks a company ever files. The requirement covers departures and appointments of principal officers — the CEO, President, CFO, COO, and any other executive the board designates — along with director elections, resignations, retirements, and committee changes.

The language in a 5.02 filing matters. "Mutual agreement" language for a CEO departure reads differently than "resigned to pursue other opportunities." "Terminated without cause" carries different implications than a brief statement that the executive is simply leaving. Companies must disclose the reason for the departure if they know it — and they almost always know more than a brief statement suggests. When a 5.02 8-K drops for a key officer, cross-referencing it against the company's [Form 4 insider transaction history](/blog/how-to-read-sec-form-4) adds essential context. If the departing executive had been selling shares aggressively in the months prior, that pattern — visible in GeminIQ's [Insider Transactions](/features#insider-transactions) data — is context the 8-K itself never provides.

### Item 1.01 — Entry into a Material Definitive Agreement

When a company signs a material contract — a major credit facility, an acquisition agreement, a joint venture, a licensing deal — it files an 8-K under Item 1.01 and attaches the agreement as an exhibit. This is the primary source document for any significant business transaction. It contains the terms, the price, the conditions, the covenants, and the closing timeline that media summaries almost always omit.

Debt agreements filed under Item 1.01 are particularly informative. The covenants in a new credit facility reveal what metrics the lender required the borrower to maintain: minimum liquidity thresholds, maximum leverage ratios, restrictions on dividends and [share repurchases](/blog/do-buybacks-reduce-share-count). These constraints are material to the investment thesis but are rarely discussed in earnings calls. The exhibit attached to the 8-K is the only place they appear in plain text before the next periodic filing.

### Item 2.01 — Completion of an Acquisition or Disposition of Assets

Item 1.01 is filed when an acquisition agreement is signed. Item 2.01 is filed when the deal closes. For cash deals, the closing 8-K under Item 2.01 often includes preliminary purchase price allocation data — the earliest view of how the acquired assets will appear on the combined balance sheet. When a company divests a business unit, Item 2.01 also covers the completion. The proceeds, the buyer, and the terms are disclosed here, and the impact on ongoing operations is material. Divestitures can be value-creating or they can signal that management is selling assets to fund operations. The 8-K text, read in the context of the prior 10-K, reveals which.

### Item 2.05 — Costs Associated with Exit or Disposal Activities

Restructuring announcements — layoffs, facility closures, business unit exits — are disclosed under Item 2.05. The 8-K provides the estimated total charge, its components (severance, lease termination costs, asset write-downs), and the period over which charges are expected to hit the income statement. This is the first quantified disclosure of restructuring costs. They will appear as formal line items in the next 10-Q, but the 8-K establishes the scale first.

The gap between the 8-K estimate and the eventual 10-Q charge is worth tracking over time. Companies that consistently underestimate restructuring charges in their 8-Ks — then disclose materially higher figures in the 10-Q — are signaling either poor planning visibility or managed disclosure timing. The pattern is only visible to investors who track both documents.

### Item 2.06 — Material Impairments

When a company determines that an asset — typically goodwill from a prior acquisition — is worth materially less than its carrying value on the balance sheet, it files an 8-K under Item 2.06. This is management formally acknowledging that a prior acquisition failed to generate the returns that justified the purchase price.

Goodwill impairments deserve close attention because goodwill is a non-cash accounting charge — it writes down the premium paid over book value in a prior deal. But its disclosure signals something real: management is conceding that the business they acquired is worth less than they paid. The magnitude of the impairment relative to the original acquisition price tells the story, and the 8-K typically discloses both figures. A **$2 billion** goodwill write-down on a **$2.4 billion** acquisition is a materially different disclosure than a **$200 million** adjustment on the same deal.

### Item 7.01 / 8.01 — Regulation FD and Other Events

Item 7.01 is the Regulation FD filing, used when a company discloses material non-public information to certain investors — analysts, institutional shareholders — and must simultaneously make that disclosure available to the general public. Investor day presentations, analyst briefings, and updated guidance delivered outside of a formal earnings release often arrive as Item 7.01 8-Ks. These are furnished, not filed, like the earnings release.

Item 8.01 is the catch-all for material events that don't fit the other defined categories. Significant legal settlements, regulatory decisions, or unusual business developments may be disclosed here. Because 8.01 has no prescribed deadline and no specific SEC definition of what belongs in it, companies have latitude in what they disclose and when. That latitude is sometimes used to bury time-sensitive disclosures in a low-profile category.

---

## Filed vs. Furnished: The Distinction Most Investors Miss

Not everything in an 8-K carries the same legal weight. The SEC distinguishes between documents that are "filed" and documents that are "furnished" — and the difference has direct implications for the liability attached to the numbers in those documents.

A filed document — an Item 1.01 agreement, an Item 5.02 departure disclosure, an Item 2.06 impairment notice — is subject to Section 18 liability under the Securities Exchange Act of 1934. That means shareholders can bring securities fraud claims based on material misstatements in a filed document. It carries the highest legal standard.

A furnished document — most importantly, the Item 2.02 earnings press release — is submitted under Sections 13(a) or 15(d) of the Exchange Act but is explicitly not subject to Section 18 liability. Companies furnish documents when they want the public to see the information, but without accepting the heightened legal exposure that comes with a formal filing.

The practical implication is direct: the non-GAAP "adjusted" earnings figures that companies present in their earnings press releases — the figures that move the stock — are in a furnished document. The actual GAAP financials, with stock-based compensation, restructuring charges, and one-time items properly included, appear in the 10-Q filed weeks later. The 8-K press release can be carefully worded to present the most favorable interpretation of performance. The 10-Q is auditable and carries full legal liability.

This is why the 10-Q matters as much as — often more than — the earnings 8-K. When the GAAP numbers in the 10-Q diverge significantly from the adjusted figures in the 8-K press release, that divergence is the story. Platforms that aggregate data from earnings press releases rather than from actual 10-Q XBRL filings may present adjusted figures as if they were the GAAP standard. GeminIQ pulls directly from 10-Q and 10-K XBRL data — not from earnings press releases — so the numbers reflect the auditable, filed standard. That distinction is explored in detail in our post on [verifying financial data against source SEC filings](/blog/verify-financial-data-against-sec-filing). It is also the reason why [financial data normalization](/blog/financial-data-normalization-explained) across platforms produces divergent figures for the same company in the same period.

---

## How an 8-K Is Structured on EDGAR

When you navigate to a company's 8-K on EDGAR, you see a filing index — a list of every document in the submission. Most 8-Ks contain a short main document and one or more exhibits.

The main document typically runs one to three pages. It identifies which items are being reported, states the date of the triggering event, and may contain a brief description. For earnings releases filed under Item 2.02, the main document is almost entirely a formality — it identifies that the press release is being furnished as Exhibit 99.1 and provides the event date. The exhibit is where the actual information lives.

Exhibit numbering follows SEC convention. Exhibit 10 numbers are for material contracts. Exhibit 99 numbers are for press releases and other furnished documents. Exhibit 23 numbers are for auditor consents. Exhibit 4 numbers are for instruments defining the rights of security holders. Opening the exhibit index first tells you immediately what a filing contains and which documents to prioritize.

For any Item 1.01 filing involving a credit agreement or major contract, the full agreement text is attached. These can run hundreds of pages. Reading the key sections — definitions, affirmative covenants, negative covenants, events of default, and the pricing grid — takes less time than it appears. The covenants in a credit agreement are among the most informative disclosures a company ever files, and they appear nowhere else in the standard financial data that platforms surface. That is precisely what [investors miss when they rely on processed financial data](/blog/what-investors-miss-in-sec-filings) instead of the source documents.

---

## Red Flag 8-K Items Investors Overlook

Most investor attention concentrates on earnings releases and executive departures, the two 8-K items that generate routine financial media coverage. Two item types receive far less attention and contain some of the most significant signals in the entire 8-K framework.

### Item 4.01 — Changes in the Registrant's Certifying Accountant

When a company changes its independent auditor, it must file an 8-K under Item 4.01 within 4 business days. The filing must disclose whether the change was voluntary or whether the prior auditor was dismissed, and the reasons cited. It must also disclose whether any disagreements existed between the company and the prior auditor on accounting principles or practices.

Auditor changes without a clear, explained rationale are among the most significant red flags in financial filings. An auditor who is dismissed — rather than completing the engagement voluntarily — may have had concerns about the company's accounting treatment that led to the separation. The 8-K disclosures in these cases are sometimes sparse, but the SEC requires the departing auditor to provide a letter confirming or disagreeing with the company's characterization of the circumstances. That letter is attached as an exhibit. If it describes disagreements on revenue recognition, asset valuation, or internal control conclusions, that is material information that goes well beyond what a headline "auditor change" suggests.

A routine transition between major firms for governance reasons reads very differently from an unplanned mid-engagement separation disclosed with vague language. The distinction matters — and the item receives a fraction of the media attention of an earnings beat or miss.

### Item 4.02 — Non-Reliance on Previously Issued Financial Statements

Item 4.02 is arguably the most serious 8-K filing a company can make. It is a formal disclosure that previously issued financial statements can no longer be relied upon — that investors should not treat prior reported figures as accurate. This typically triggers a restatement process and often accompanies an audit committee investigation or parallel SEC inquiry.

These filings are rare. When they occur, the market reaction is immediate and severe. But a more common early-warning version is the 8-K/A — an amendment to a previously filed 8-K that corrects a figure or adds a disclosure without formally invoking non-reliance language. A single 8-K/A to attach a missing exhibit is unremarkable. A pattern of amendments — particularly amendments that alter numbers or materially change the description of an event — indicates either that original disclosures were inaccurate or that the company lacks adequate disclosure controls. Frequent 8-K/A amendments correcting material figures are often an early signal of larger accounting problems ahead. Tracking the amendment history on EDGAR for companies you hold is a straightforward monitoring practice that most investors skip entirely.

---

## How the 8-K Fits Into the Broader Filing System

The [SEC's complete filing system](/blog/sec-filings-guide) is designed so that no single document tells the full story. The 8-K is the real-time layer — the mechanism by which material events enter the public record between scheduled periodic filings. But it functions as a disclosure trigger, not a financial data source. Numbers announced in an 8-K earnings release are previewed. The contracts filed in an Item 1.01 8-K establish terms. Neither becomes auditable GAAP financial data until the next 10-Q or 10-K is filed.

The [10-K and 10-Q](/blog/10-k-vs-10-q-differences-explained) are the documents that contain XBRL-tagged financial statement data, and they are what GeminIQ extracts and structures — with every line item tagged, calculated metrics derived from the source data, and [financial statements](/features#financial-statements) available for cross-referencing against the 8-K disclosures that preceded them. When an earnings 8-K reports adjusted net income that diverges significantly from the GAAP net income in the subsequent 10-Q, the divergence is immediately visible in GeminIQ's financial statement data. The 8-K press release shows what management wanted the market to see. The 10-Q shows what they actually reported.

The [Price Variance heatmap](/features#price-variance) within GeminIQ tracks the market's reaction to quarterly filings — including the post-earnings stock movement that follows an earnings 8-K. Cross-referencing the 8-K disclosure with the subsequent price reaction and then with the 10-Q GAAP financials gives a complete picture: what the market priced in, what the company actually reported under the auditable standard, and whether those two things are consistent.

For companies where officer departure 8-Ks arrive under Item 5.02, GeminIQ's [Insider Transactions](/features#insider-transactions) data provides the Form 4 history for that officer — every purchase and sale in company stock across years. That context does not appear in the 8-K. It exists in the Form 4 filing record, which surfaces alongside the stock price history. Taken together — the 8-K departure disclosure, the Form 4 transaction history, and the subsequent 10-Q results — the complete picture is available. The financial media typically covers only the first of those three documents.

The event is in the 8-K. The financial reality is in the 10-Q. The insider behavior is in the Form 4. Reading all three is what the earnings headline never tells you to do.

---

## Frequently Asked Questions

### Is an 8-K filing good or bad?

Neither by itself. An 8-K is required for a list of specific events, so it can report good news (an acquisition, a new contract, strong results under Item 2.02) or bad news (an impairment, an auditor change, a restatement under Item 4.02). The item numbers tell you which kind of event you are reading about.

### Which companies have to file an 8-K?

Every company that reports to the SEC under the Securities Exchange Act of 1934, which includes all U.S. companies with stock listed on a national exchange. Foreign private issuers report current events on Form 6-K instead.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Proxy Statement (DEF 14A): What Investors Look For
source: https://www.geminiq.com/blog/what-is-def-14a

### Proxy Statement (DEF 14A): What Investors Look For
The DEF 14A proxy statement is one of the most information-dense filings a public company submits — and one of the most consistently ignored. This guide covers what the proxy contains, which sections matter most, and how the executive compensation structure connects to the dilution data in your financial statements.

Every year, public companies file a document that discloses exactly how management is
compensated, whether the board is truly independent, what shareholders are voting on,
and what activist investors are trying to change. The document is free, publicly
available on SEC EDGAR, and filed on a predictable annual schedule. Most individual
investors have never read one.

The DEF 14A — the definitive proxy statement — is the governance and compensation
layer of a company's SEC filing record. It contains no income statement, no balance
sheet, no cash flow data. What it contains is the architecture that determines how
management is incentivized to run the business that generates those financial
statements. Standard financial aggregators parse 10-K and 10-Q data automatically.
Almost none of them structure proxy statement data into searchable databases. The
information is public and consistent — but it requires direct engagement with the
filing itself. Investors who read it operate with a picture of the company that no
aggregator can replicate.

This guide covers the DEF 14A section by section: what each part contains, what
investors should look for, and how the compensation disclosures connect directly to
the dilution figures that show up in the financial statements you're already reading.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-def-14a)**

---

## Table of Contents

- [What Is the DEF 14A?](#what-is-the-def-14a)
- [The Annual Meeting Ballot: What Shareholders Actually Vote On](#the-annual-meeting-ballot-what-shareholders-actually-vote-on)
- [Board Composition: Independence vs. Decoration](#board-composition-independence-vs-decoration)
- [Executive Compensation: The CD&A and the Summary Compensation Table](#executive-compensation-the-cda-and-the-summary-compensation-table)
- [Say-on-Pay: What the Vote Percentage Reveals](#say-on-pay-what-the-vote-percentage-reveals)
- [Equity Awards, Share Dilution, and the Authorization Math](#equity-awards-share-dilution-and-the-authorization-math)
- [Director Stock Ownership: Skin in the Game](#director-stock-ownership-skin-in-the-game)
- [Shareholder Proposals: Reading the Activist Agenda](#shareholder-proposals-reading-the-activist-agenda)
- [How the Proxy Connects to the Full Filing Picture](#how-the-proxy-connects-to-the-full-filing-picture)

---

## What Is the DEF 14A?

The "DEF 14A" designates the Definitive Proxy Statement — the final, legally binding
version of the document companies use to solicit shareholder votes before their annual
meeting. "DEF" distinguishes it from the preliminary proxy (PRE 14A) that some
companies file first for SEC review. The DEF 14A is the operative document — the one
containing the actual ballot items, compensation disclosures, and governance
descriptions that apply to the upcoming annual meeting.

The filing requirement stems from Section 14(a) of the Securities Exchange Act of
1934, which prohibits any solicitation of shareholder votes without providing the
material disclosures required under SEC Rule 14a-3. Companies must file the DEF 14A
at least 40 calendar days before the meeting date. For most S&P 500 companies, the
filing arrives in late March or early April, with annual meetings concentrated in May
and June. Fiscal year-end companies with non-calendar year schedules file on a
different cadence — but the rhythm is consistent year over year, making it easy to
anticipate.

Finding a proxy on SEC EDGAR requires only searching the company's filing history
under filing type "DEF 14A." The filing appears there the same day it is submitted,
before most media coverage of its contents.

What sets the proxy apart from every other SEC filing is not what it contains — it
is what it does not. There are no financial statements in a DEF 14A. No revenue
figure, no earnings per share, no operating margin. What the proxy contains instead
is a direct description of who governs the company, how the people running it are
compensated, and what major shareholders are trying to change. That combination of
disclosures appears nowhere else in the SEC filing record — and investors who read
the proxy operate with a materially different picture of the company than those who
never do.

---

## The Annual Meeting Ballot: What Shareholders Actually Vote On

The proxy organizes its content around the ballot items for the annual meeting, and
understanding each category is the first step in reading the document productively.

**Director elections** are the most routine item on every proxy ballot. Shareholders
vote on each nominated director for a term of one year (in a declassified board) or
three years (in a classified board). The vote outcome is almost never the signal.
What matters is whether any director receives meaningfully below-average approval
despite carrying the board's recommendation. A director who wins reelection with
**68%** support — when the company's other nominees win with **95%** — is flagging
institutional dissatisfaction that the headline result obscures. Directors who chair
the compensation committee and receive low approval are typically signaling investor
concern about pay practices. Directors who chair the audit committee and receive low
approval are flagging concerns about financial oversight quality. The percentages
tell the story; the outcomes do not.

**Say-on-pay** is a non-binding advisory vote on executive compensation, required by
the Dodd-Frank Act and conducted annually at most companies. Non-binding means the
board can legally ignore a failed vote and pay management exactly as before. But a
vote that falls below **70%** approval creates a formal, public record of
institutional investor dissent — and companies in that territory consistently face
escalating pressure from proxy advisors, direct engagement demands from major index
funds, and compensation committee scrutiny the following year.

**Auditor ratification** puts the company's independent auditor to a shareholder
vote. The vote passes with near-unanimous approval at virtually every company. The
analytical signal lives in the fee disclosure: the amounts paid to the auditor for
the core audit and for non-audit services. A significant year-over-year increase in
audit fees warrants investigation — it can signal scope expansion in response to
identified control weaknesses, complexity introduced by an acquisition, or
preparation for a restatement.

**Shareholder proposals** appear on the ballot when qualifying investors submit them
under SEC Rule 14a-8. The board's recommendation is almost uniformly against. The
meaningful data point is the vote percentage the proposal receives despite that
opposition — a figure that reflects the collective judgment of the institutional
investors who hold the vast majority of shares in most large-cap companies.

---

## Board Composition: Independence vs. Decoration

The proxy's director section describes every board member: their professional
background, the committees they serve on, other public company boards they sit on,
and their independence classification. Independence by SEC and stock exchange
definition is not the same as independence in practice, and the proxy provides enough
information to assess the difference.

The legal independence test excludes directors who receive material payments from the
company, are related to executives, or have material business relationships with the
company. Most board members satisfy these criteria. The practical independence
question requires a different analysis. Tenure is the first dimension: boards where
every member has served fifteen or more years tend toward self-perpetuation rather
than objective oversight. Board load is the second: Institutional Shareholder Services
flags directors sitting on five or more public company boards simultaneously as
"overboarded" — a designation that correlates with lower meeting attendance rates and
diminished oversight capacity. Professional background is the third: a technology
company whose board has no members with operational technology experience carries a
risk oversight mismatch that no independence definition captures.

The compensation committee is the highest-priority committee for investors evaluating
pay practices. Its members approve CEO compensation packages, set the equity award
structure, and bear direct responsibility for the say-on-pay vote outcome. The proxy
discloses who serves on each committee, how many meetings each held during the year,
and a brief narrative of what the committee accomplished. Reading the compensation
committee report alongside the say-on-pay vote percentage creates a clear picture of
whether the people setting executive pay are accountable to shareholders or insulated
from them.

---

## Executive Compensation: The CD&A and the Summary Compensation Table

The Compensation Discussion and Analysis — the CD&A — is the section of the proxy
that SEC rules explicitly require to be "written in plain English, in a clear, concise,
and understandable manner." It discloses the full architecture of how the five or six
most highly compensated executives — called named executive officers, or NEOs —
receive their pay.

The CD&A follows a standard sequence: compensation philosophy, peer group selection,
base salary rationale, annual incentive structure and performance targets, long-term
incentive structure and terms, and any special or one-time awards. Compensation tables
support each section, disclosing the actual dollar values of each component.

The peer group section is where the most consequential analysis lives — and where
standard financial media consistently fails to look. To benchmark executive pay to
"market," companies assemble a comparison group of companies of comparable size,
industry, and complexity. The stated rationale is straightforward: paying competitively
retains talent. The mechanical outcome is a structural ratchet. Every company targets
the **50th to 75th percentile** of peer group compensation. The median rises annually
as all companies seek above-median positioning. Peer groups are updated each year,
with companies where the analysis would show executives are well-paid removed and
replaced with larger, higher-paying peers. The result: aggregate executive
compensation climbs without reference to company performance, and the process repeats.
This pattern is documented in compensation research and visible every proxy season —
but only if you read the CD&A. Reading the peer group list year-over-year reveals
whether the company is adding larger peers specifically to justify an upward pay
adjustment.

The **Summary Compensation Table** is the standardized disclosure at the center of
the CD&A. It shows, for each NEO, the annual components of total compensation: base
salary, bonus, stock awards, option awards, non-equity incentive plan compensation,
change in pension value, all other compensation, and the total. The total column is
the headline figure. The stock awards and option awards columns are the most
analytically important — they represent equity granted to executives, which is
precisely the SBC expense that appears as a non-cash operating cost in the income
statement and a non-cash add-back in the cash flow statement.

GeminIQ's pre-calculated [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation)
metric tracks trailing twelve-month SBC expense directly from XBRL-tagged SEC filings —
the same economic cost disclosed at the individual executive level in the proxy's
Summary Compensation Table, aggregated across the full employee population.
[Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue)
puts that expense in proportion to the business: for technology companies, ratios
above **15%** indicate that equity compensation is consuming a meaningful share of
every revenue dollar generated, with the dilution cost borne entirely by existing
shareholders.

---

## Say-on-Pay: What the Vote Percentage Reveals

Say-on-pay votes above **90%** represent near-unanimous institutional endorsement of
the compensation structure. Votes in the **80–90%** range are normal for most
large-cap companies with defensible pay practices. A vote in the **70–80%** range
signals real institutional opposition — major index funds or leading proxy advisors
recommended a vote against, and the company faces an implicit obligation to engage
with shareholders and respond publicly to stated concerns. A vote below **70%** is a
governance crisis marker: rare, widely reported, and almost always preceding either
visible compensation restructuring or a formal public shareholder engagement process.

The most useful way to interpret say-on-pay is as a lagging indicator. The vote
reflects institutional shareholder judgment on the prior year's compensation design
and outcomes — not the current year. When a company's stock fell **20%** in the prior
fiscal year but the CEO received equity awards that vested at levels set three years
earlier, institutional investors recognize the pay-performance misalignment. The
say-on-pay vote reflects that judgment even if the current year's results have
improved. Reading the vote percentage alongside the prior year's total shareholder
return versus total CEO compensation tells you whether the board's compensation
committee is making decisions investors consider defensible. Two consecutive
below-average say-on-pay results at the same company, without meaningful compensation
restructuring between them, is the clearest possible signal that the board is not
listening.

---

## Equity Awards, Share Dilution, and the Authorization Math

Most proxy statements include at least one proposal asking shareholders to authorize
additional shares for the company's equity compensation plan. These proposals pass
with near-unanimous approval at most companies. The dilution math embedded in them
is real and cumulative — and it connects directly to the financial statements.

The key figure is the **share request as a percentage of shares outstanding**. A
company with **500 million** shares outstanding that requests authorization for
**25 million** new shares for its equity plan is asking shareholders to approve
potential dilution of up to **5%** of the float. Actual dilution depends on how
aggressively the authorized pool is used — which the proxy's plan summary discloses
through the prior year's grant history. That grant history yields the **grant rate**:
the percentage of shares outstanding issued through equity compensation each year,
which is the actual run-rate dilution rather than the maximum authorized amount.

GeminIQ's pre-calculated [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio)
connects the proxy's authorization math to the financial statement result. The metric
divides diluted shares outstanding by basic shares outstanding, using the XBRL-tagged
weighted average share counts from the SEC filing. A ratio between **1.00 and 1.03**
is typical for mature companies. Technology and growth companies with heavy equity
compensation plans frequently run ratios between **1.03 and 1.10**. A ratio above
**1.05**, sustained across multiple years, indicates that equity issuance is
meaningfully eroding each existing share's claim on earnings. GeminIQ's pre-calculated
[Diluted Earnings Per Share](/metrics/per-share-metrics/diluted-earnings-per-share)
captures the per-share consequence: a company growing total earnings by **8%** while
diluting shares outstanding by **6%** delivers only **2%** of genuine per-share growth
to long-term holders. The proxy authorizes the dilution; the financial statements
record it.

---

## Director Stock Ownership: Skin in the Game

The proxy discloses the stock ownership of every director and named executive officer
as of a specified record date near the filing. This section answers one of the most
fundamental governance questions an investor can ask: do the people making capital
allocation decisions for this company own a meaningful stake in it?

Most large-cap companies now maintain formal stock ownership guidelines — requirements
that executives hold a minimum multiple of their annual base salary in company stock,
and directors hold a minimum multiple of their annual cash retainer. A CEO ownership
guideline of **5x base salary** for a CEO earning **$1.5 million** in base salary
requires holding at least **$7.5 million** in company shares within a defined
accumulation period, typically five years from appointment. These guidelines are
disclosed in the CD&A and represent the board's stated commitment to alignment.

The ownership table itself shows what executives actually hold as of the record date.
Comparing that figure to cumulative compensation from prior years' Summary
Compensation Tables reveals a behavioral pattern that the table alone cannot: an
executive who has received **$30 million** in equity awards over five years but holds
only **$5 million** in company stock is liquidating equity substantially faster than
the minimum guideline requires. That pattern — holding the floor, selling the rest —
signals limited long-term alignment regardless of how the ownership guideline is
written.

GeminIQ's [Insider Transactions](/features#insider-transactions) view organizes Form 4
data chronologically by insider and transaction type, making multi-year behavioral
patterns visible at a glance. The proxy's ownership table is an annual snapshot;
Form 4 is the running transaction record between those snapshots. Reading both
together reveals whether executives are accumulating stock or systematically reducing
exposure as fast as equity vests. For a complete field-by-field guide to reading
Form 4 filings, see our breakdown of [how to read SEC Form 4](/blog/how-to-read-sec-form-4).

---

## Shareholder Proposals: Reading the Activist Agenda

Shareholder proposals occupy the final ballot section of the proxy and represent the
most direct expression of investor activism in the formal SEC filing record. They are
submitted by qualifying shareholders — under SEC Rule 14a-8, holding at least
**$2,000** in market value of the company's stock for at least one year, or greater
thresholds for shorter holding periods under recent rule amendments. The bar is
intentionally accessible to give minority shareholders a formal channel.

Proposals arrive in three broad categories. Governance proposals seek structural
changes: declassifying a staggered board, adopting majority-vote standards for
director elections rather than plurality voting, separating the Chairman and CEO roles,
or giving shareholders the right to nominate director candidates directly through the
proxy. Compensation proposals request architectural changes to pay structures:
requiring that long-term equity vesting be tied to multi-year performance outcomes
rather than time-based schedules, or making the CEO pay ratio — already a required
disclosure — more prominent in the filing. Environmental and social proposals request
specific disclosures: climate transition plans, political spending transparency, and
workforce demographic data beyond what companies currently volunteer.

The board's recommendation is nearly always against every proposal. The vote
percentage despite that recommendation is the operative signal. A proposal receiving
**40–50%** shareholder support — including near-unanimous institutional backing —
is a governance mandate in all but name. The major index funds that hold significant
positions in virtually every large-cap stock publish annual stewardship reports and
proxy voting guidelines. When a proposal receives **40%** or more in favor, those
institutional votes are reflected in the total, and a board that repeatedly ignores
high-vote proposals faces escalating consequences. The proxy vote record across three
or four consecutive years reveals whether management is genuinely responsive to
shareholder input or structurally insulated from it.

---

## How the Proxy Connects to the Full Filing Picture

The DEF 14A is the governance layer above the financial layer — and the two are
directly connected in ways most investors never trace.

The performance metrics written into the annual and long-term incentive plans in the
CD&A determine what management optimizes. Annual bonuses tied to revenue growth and
adjusted EBITDA produce companies that focus on revenue and non-GAAP margin.
Long-term incentive plans tied to total shareholder return against a peer group
produce companies that manage buybacks and dividends to maximize relative stock
performance. Plans tied to [return on invested capital](/blog/roic-return-on-invested-capital-explained) produce companies that scrutinize
every capital deployment before committing. The incentive metrics in the proxy are the
compensation committee's revealed preferences about what drives shareholder value.
The company's actual financial results across the incentive cycle reflect how well
those preferences translated into outcomes — and whether the metrics chosen were
genuinely aligned with long-term per-share value or engineered to maximize annual
payouts.

Reading the proxy once, before building a position, answers questions that no
financial statement can: Is the board genuinely independent or structurally deferential
to management? Is the CEO's personal wealth tied to the stock price in a way that
creates real alignment? Are major shareholders trying to change the governance
architecture — and what specifically are they trying to change? The 10-K gives you
the financial history. The DEF 14A tells you whether the incentive structure is
designed to improve it or to repeat whatever has already worked for the executives
running it.

For a complete overview of how the DEF 14A fits within the full SEC filing ecosystem —
alongside the 10-K, 10-Q, 8-K, S-1, and Form 4 — see our
[complete guide to SEC filing types for investors](/blog/sec-filings-guide). For the
counterpart filing that tracks what executives actually do with shares after
compensation is granted, see our guide on
[how to read SEC Form 4](/blog/how-to-read-sec-form-4). And for the institutional
ownership dimension — who the major holders are and what their Form 13F filings
disclose — see our breakdown of
[how to read a 13F filing](/blog/how-to-read-13f-filing).

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-def-14a)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: S-1 Filing Explained: How to Analyze an IPO Prospectus
source: https://www.geminiq.com/blog/what-is-s-1

### S-1 Filing Explained: How to Analyze an IPO Prospectus
An S-1 filing is the SEC registration statement every company must submit before going public — the most data-rich document available to investors before an IPO. This post breaks down S-1 structure section by section, the financial metrics that matter, and what IPO hype regularly conceals in the raw numbers.

The financial press runs IPO coverage like entertainment. The ticker, the valuation headline, the first-day price pop, the founder interview on the trading floor. The S-1 filing — the document containing every material fact a company is legally required to disclose before your money goes in — sits in an SEC EDGAR database, largely unread.

That is the information asymmetry. The investors reading S-1 filings and the investors who are not are making fundamentally different bets.

An S-1 runs hundreds of pages and contains audited financial statements, the complete share structure before and after the offering, management's narrative analysis of operational trends, every material risk the company felt legally compelled to disclose, and executive compensation details the roadshow never mentions. It is the closest thing to a full accounting of a company's financial reality that exists before the ticker ever trades. Understanding how to read one is understanding how to analyze an IPO.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=what-is-s-1)**

## Table of Contents

- [What Is an S-1 Filing?](#what-is-an-s-1-filing)
- [S-1 vs. 10-K and 10-Q: A Different Kind of Document](#s-1-vs-10-k-and-10-q-a-different-kind-of-document)
- [The S-1 Filing, Section by Section](#the-s-1-filing-section-by-section)
  - [The Prospectus Summary: Read It Last](#the-prospectus-summary-read-it-last)
  - [Business and Risk Factors: What They Are Warning You About](#business-and-risk-factors-what-they-are-warning-you-about)
  - [Use of Proceeds: Where the IPO Money Goes](#use-of-proceeds-where-the-ipo-money-goes)
  - [Capitalization Table and Share Structure](#capitalization-table-and-share-structure)
  - [Financial Statements: Three Years of Audited Numbers](#financial-statements-three-years-of-audited-numbers)
  - [Management's Discussion and Analysis (MD&A)](#managements-discussion-and-analysis-mda)
  - [Executive Compensation and Related Party Transactions](#executive-compensation-and-related-party-transactions)
- [Financial Metrics That Matter in an S-1](#financial-metrics-that-matter-in-an-s-1)
- [Red Flags in S-1 Filings: What the Hype Conceals](#red-flags-in-s-1-filings-what-the-hype-conceals)
- [From S-1 to 10-K: Tracking IPO Promises Against Reality](#from-s-1-to-10-k-tracking-ipo-promises-against-reality)

## What Is an S-1 Filing?

The S-1 is the registration statement companies file with the SEC before conducting a public offering. Governed by the Securities Act of 1933, it is required for any domestic company seeking to list on a U.S. exchange. The filing is publicly accessible on SEC EDGAR once the SEC declares it effective — or earlier, if the company makes draft filings voluntarily available to investors.

The document serves two legal purposes simultaneously: it registers the securities being offered for public sale, and it ensures prospective investors have access to the material information required to make an informed decision. The SEC does not endorse the accuracy of what's in an S-1. Its review process focuses on completeness and compliance with disclosure requirements. The agency typically issues a comment letter within 30 days of the initial filing, which the company must address in subsequent amendments before the registration becomes effective.

An S-1/A is a formal amendment to the original filing. Companies may file several of these in response to SEC comments or to update financial data before the offering concludes. After effectiveness, the final prospectus is typically filed separately as a Form 424B4 on EDGAR — the version investors actually receive. For an overview of where the S-1 sits within the broader SEC filing landscape, see our [SEC filings guide](/blog/sec-filings-guide).

One structural reality that materially affects the public review window: Emerging Growth Companies — a category the JOBS Act defines by annual gross revenue below a periodically adjusted threshold — may file their S-1 confidentially with the SEC before making it public. The public version can appear as few as 15 days before the IPO roadshow begins. Retail investors frequently encounter the S-1 for the first time during or after the roadshow, not before it. That timeline is not accidental.

## S-1 vs. 10-K and 10-Q: A Different Kind of Document

Reading an S-1 like a 10-K is a category error. The 10-K is written under decades of standardized SEC guidance, with auditor and attorney sign-off on every material assertion and an institutional expectation of candor on material risks. The S-1 is written to attract capital. Both documents contain audited financial data and mandatory risk disclosures. Only one of them is trying to sell you something. For a closer look at how the two periodic forms compare post-IPO, see [10-K vs. 10-Q: Differences Explained](/blog/10-k-vs-10-q-differences-explained).

The framing, emphasis, and language choices of an S-1 are fundamentally different from a 10-K even when describing identical facts. The same business described in an S-1 and then in its third annual 10-K will often read as two entirely different companies — not because the facts changed, but because the incentive structure for presenting them did.

The financial statements in an S-1 are audited, distinguishing them from the reviewed-but-not-audited financials in a quarterly 10-Q. Most S-1s include two full fiscal years of audited balance sheets and three years of audited income statements and cash flow data. Emerging Growth Companies may include only two years of income statement history. These figures were prepared under GAAP and independently verified — the most reliable financial data available on the company before it lists.

Once a company goes public and begins filing 10-Ks and 10-Qs, GeminIQ's [Financial Statements](/features#financial-statements) feature captures the XBRL-tagged data directly from SEC EDGAR, enabling precise comparison of post-IPO results against the trajectory the S-1 described.

## The S-1 Filing, Section by Section

Not every section of an S-1 deserves equal time. Understanding which sections contain the analytical substance — and the order in which to read them — is the first practical skill in IPO analysis.

### The Prospectus Summary: Read It Last

The Prospectus Summary opens almost every S-1. It is the shortest, most polished, and least analytically useful section of the entire document. The market opportunity is framed at its most expansive. The risks are summarized at their most abstract. The financial data that appears here is curated to support a narrative, not to complicate one.

Experienced analysts read the Prospectus Summary last — after the financial statements, after the Risk Factors, after the MD&A. The context built from the actual numbers makes the summary section legible in a way that reading it cold does not. Read it first and you are being briefed by the company's investment bankers. Read it last and you can measure the summary against what the data actually shows.

### Business and Risk Factors: What They Are Warning You About

The Business section describes the company's products, market position, competitive landscape, and growth strategy. It is predominantly management-curated narrative. The useful data here is specific rather than general: disclosed customer count, retention metrics where provided, revenue breakdown by product line, and total addressable market methodology where the company shows its math rather than just its conclusion.

The Risk Factors section is where the S-1 becomes a fundamentally different kind of document. Companies are legally required to disclose material risks, and while much of the language is boilerplate, specific risks deserve close attention: customer concentration above **10%** of revenue, dependency on named key personnel, regulatory exposure by jurisdiction, and active or threatened litigation. Financial coverage of IPOs focuses heavily on the Business section narrative. The Risk Factors section rarely makes the story.

One pattern consistently worth tracking: risks described in unusually precise, specific terms often reflect actual ongoing situations that management felt legally compelled to disclose rather than generic industry hazards. Vague risks are boilerplate. Precise ones sometimes are not.

### Use of Proceeds: Where the IPO Money Goes

The Use of Proceeds section tells investors what the company plans to do with the capital raised. The standard categories — "general corporate purposes," "working capital," "sales and marketing," "potential acquisitions" — are deliberately broad. The absence of specificity is informative in itself: companies that cannot articulate what they intend to do with hundreds of millions of dollars are either preserving optionality or have not yet committed to a plan.

The more material distinction is the primary versus secondary split. A primary offering directs IPO proceeds to the company's balance sheet, funding operations or growth. A secondary offering directs them to existing shareholders — venture capital firms, private equity sponsors, and early employees — who are converting equity to cash at the IPO price. An IPO that is predominantly secondary is a fundamentally different transaction from one raising growth capital, regardless of how the roadshow frames it. The split is always disclosed. It is rarely emphasized.

### Capitalization Table and Share Structure

The capitalization table — appearing in the Capitalization section — shows the company's full equity structure before and after the offering. It is among the most important sections in the document and among the least studied by individual investors.

The pre-IPO cap table reveals the complete dilution picture: common shares outstanding, preferred shares converting to common at the offering, stock options outstanding at various strike prices, unvested restricted stock units, and any warrants. The post-IPO column shows what the ownership structure looks like after the new shares are sold. The gap between those two columns — the fully diluted share count versus the basic share count highlighted in the summary — defines the dilution that every shareholder, including new IPO buyers, has already absorbed before trading begins.

A spread of **25%** to **35%** between basic and fully diluted share counts is common at technology company IPOs. That spread represents real economic dilution: it reduces per-share intrinsic value relative to the headline earnings or revenue multiples the coverage emphasizes. Once the company begins filing periodic reports, GeminIQ's [Dilution Ratio](/metrics/returns-and-profitability/dilution-ratio) tracks share count changes quarter over quarter directly from the as-filed XBRL data.

### Financial Statements: Three Years of Audited Numbers

The financial statements are where fundamental analysis of an S-1 actually begins. Unlike the narrative sections, these pages contain data prepared under GAAP, independently audited, and directly comparable to public peers filing the same forms.

The income statement shows revenue, cost of revenue, gross profit, and operating expenses broken out by function — research and development, sales and marketing, general and administrative. Most pre-profitability companies at the IPO stage report operating losses. The analytical question is the trend: is the [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) expanding as the revenue base scales? Is the [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) improving year-over-year even while still negative? A company whose gross margin expanded from **55%** to **68%** over three fiscal years is demonstrating fundamentally different business dynamics than one that held flat at **55%** while spending aggressively on customer acquisition.

The cash flow statement reveals whether the company is generating or consuming cash at the operational level. [Free Cash Flow](/metrics/calculated-values/free-cash-flow) — operating cash flow minus capital expenditures — separates companies building real economic value from those sustained entirely by successive fundraising rounds. A company can report GAAP losses while generating positive free cash flow; it can also report GAAP profitability while consuming cash through working capital dynamics. The income statement and the cash flow statement tell different parts of the same story, and reading only one produces a materially incomplete picture.

The balance sheet provides the capitalization snapshot at the S-1 filing date: cash on hand, total debt, and deferred revenue balances. [Net Debt](/metrics/calculated-values/net-debt) — total debt minus cash — shows the leverage position the company carries into the public markets before IPO proceeds arrive. A company entering the offering with significant net debt has a fundamentally different risk profile than a cash-rich, debt-free business, and that difference shapes how much financial flexibility the post-IPO management team actually has. The [Current Ratio](/metrics/liquidity-ratios/current-ratio) provides the immediate liquidity check: whether the company can meet its near-term obligations without relying on continued access to capital markets.

### Management's Discussion and Analysis (MD&A)

The MD&A is management's required narrative explanation of the financial statements. The SEC mandates that it discuss material trends and uncertainties, quantitatively explain year-over-year results, and describe known factors that will affect future performance. It is forward-looking in a regulated, factual way — not the open-ended optimism of the Prospectus Summary.

The metrics management chooses to emphasize in the MD&A — and the ones quietly omitted — are informative. Companies that define their own success metric (Annual Recurring Revenue, Net Revenue Retention, Gross Merchandise Value, Daily Active Users) and present it as the primary performance narrative without a clear bridge back to GAAP revenue are signaling something about what the GAAP trajectory does not show on its own. Non-GAAP metrics are not prohibited. Their relationship to the reported financials requires explicit scrutiny.

The MD&A is also where [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) is typically broken out. At IPO-stage technology companies, SBC routinely represents **20%** to **40%** of revenue — a figure that materially depresses GAAP operating income and is frequently added back in the non-GAAP presentations companies lead with in subsequent earnings releases. Reading the SBC line in the S-1 financial statements, before any non-GAAP adjustment, establishes the baseline for understanding what GAAP income will look like for the first several years of public life. GeminIQ's [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) metric tracks this ratio quarter over quarter once the company begins filing periodic reports.

### Executive Compensation and Related Party Transactions

Two sections near the back of most S-1 filings contain material that financial coverage of IPOs almost never mentions: executive compensation and related party transactions.

Executive compensation disclosures show the salary, bonus, and equity grant structure for named executive officers during the periods covered by the financial statements. More importantly, they disclose the equity awards — stock options and RSUs at specific strike prices and vesting schedules — that will produce Form 4 filings on EDGAR every time an insider executes a transaction post-IPO. Lock-up agreements, also disclosed in the S-1, typically restrict insider selling for **90 to 180 days** after the offering date. After lock-up expiry, those Form 4 filings become the real-time monitoring mechanism. GeminIQ's [Insider Transactions](/features#insider-transactions) feature captures them as they are filed — the same framework covered in depth in our post on [how to read SEC Form 4](/blog/how-to-read-sec-form-4).

Related party transactions are disclosed in a separate section and frequently dismissed as boilerplate. They are not always boilerplate. These disclosures cover transactions between the company and its executives, directors, or major shareholders — real estate leases, consulting agreements, service contracts, intercompany loans. Each transaction's dollar amount appears in the filing. The analytical question is whether the transactions are arm's-length, material relative to operating income, and structured in a way that benefits related parties at the company's expense. Governance patterns visible in the S-1 rarely improve once the company is public and the scrutiny from prospective investors is replaced by quarterly reporting obligations.

## Financial Metrics That Matter in an S-1

Five metrics establish the baseline fundamental picture from an S-1's financial statements.

[Revenue Growth](/metrics/growth-metrics/revenue-growth) year-over-year is the clearest indicator of trajectory. Analyzing it across all three available fiscal years — not just the most recent — reveals whether the rate is accelerating, decelerating, or inflecting. A company growing at **80%** in the most recent fiscal year but **140%** in the year prior is decelerating sharply. That deceleration profile belongs in the valuation analysis, not buried in a footnote on page 214.

[Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) reveals the fundamental economics of the business model. A software company running **70%+** gross margins has a categorically different cost structure and capital intensity than a logistics company running **25%**. The appropriate valuation framework for each differs accordingly, and gross margin expansion as revenue scales is the foundational indicator that operating leverage is real rather than theoretical. Comparing an S-1 company's gross margin to publicly traded sector peers using their 10-K data provides the essential benchmark.

[Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) tells the leverage story across time. Pre-profitability companies at the IPO stage should show a clear directional trend toward margin improvement. A company whose operating margin moved from **-60%** to **-52%** to **-43%** of revenue over three fiscal years is demonstrating real progress toward a self-sustaining cost structure. A company that ran at **-60%** for three consecutive years while revenue tripled is demonstrating that scale alone does not produce efficiency.

[Free Cash Flow](/metrics/calculated-values/free-cash-flow), or more precisely the rate of free cash consumption, defines the runway. Taking cash on the balance sheet plus expected IPO proceeds and dividing by the quarterly operating cash outflow produces a rough estimate of how long the company can operate without returning to capital markets. A post-IPO runway shorter than 18 months is a near-term dilution risk regardless of the narrative, because the next financing round will be either dilutive equity or expensive debt.

[Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) is the ratio most consistently excluded from IPO coverage summaries. An SBC-to-revenue figure above **25%** means the company is paying a substantial portion of its labor cost in equity. Those grants vest over time and add to the share count. The combination of operating losses plus high SBC creates the real economic picture that non-GAAP presentations are specifically structured to move the reader past.

## Red Flags in S-1 Filings: What the Hype Conceals

Customer concentration is the first pattern to identify. The SEC requires disclosure whenever a single customer represents **10%** or more of revenue. A company with one customer representing **45%** of revenue is structurally different from a business with a diversified demand base, regardless of what the aggregate top-line growth rate looks like. The concentration risk is always in the Risk Factors section. It is rarely in the headline description.

The gap between GAAP and non-GAAP metrics is the second. When a company presents non-GAAP operating income that is substantially larger than the GAAP figure, the excluded items — typically stock-based compensation, amortization of acquired intangibles, and sometimes restructuring charges — represent real economic costs that will continue affecting future cash flows. A reconciliation table between GAAP and non-GAAP results is required disclosure in the S-1. Reading it quantifies exactly what is being adjusted out and whether those adjustments are genuinely one-time or structurally recurring.

Deferred revenue dynamics are the third. A software company with large and growing deferred revenue balances has collected cash from customers that will flow through the income statement in future quarters — a structural positive that reflects demand ahead of recognized revenue. Accelerating accounts receivable without corresponding deferred revenue may indicate revenue recognition timing that deserves scrutiny. The balance sheet and the cash flow statement read together reveal which dynamic is operating.

The secondary selldown percentage is the fourth. When existing shareholders are selling a large portion of the total offering at the IPO price, it signals that the people with the most complete information about the business are choosing to convert equity to cash at that specific valuation. Diversification is a legitimate reason for insiders to sell. But when a large secondary component accompanies aggressive forward growth claims in the Prospectus Summary, a specific question follows directly: if the opportunity is as large as described, why is the informed capital exiting rather than holding?

The lock-up expiry window is the fifth. The **90 to 180 days** following lock-up expiration represent the period of maximum insider selling pressure on the stock. That window, and the insider behavior within it, is the first real test of whether the people who built the company believe in its post-IPO valuation. GeminIQ's [Insider Transactions](/features#insider-transactions) feature tracks the Form 4 filings that document insider activity as they land. For a deeper framework on reading and interpreting that pattern, see our post on [insider cluster buying signals](/blog/insider-cluster-buying-signal-data).

## From S-1 to 10-K: Tracking IPO Promises Against Reality

The S-1 is the promise. The 10-K is the delivery record. Most investors who do the analytical work to read an S-1 carefully never complete the follow-through — comparing the stated trends and financial trajectories against what the company actually reported in year one, year two, and year three as a public company. That comparison is where the real signal lives.

Once a company completes its IPO, the XBRL-tagged data from its 10-K and 10-Q filings becomes available on SEC EDGAR. GeminIQ extracts that data directly — as filed, without normalization or third-party adjustment — so the metrics that mattered in the S-1 can be tracked against real results: [Revenue Growth](/metrics/growth-metrics/revenue-growth) against the trajectory described in the MD&A, [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) against the expansion presented as evidence of operating leverage, [Free Cash Flow](/metrics/calculated-values/free-cash-flow) against the burn rate that defined the runway, and [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) relative to the operating cost structure the S-1 established as the baseline.

But standard financial media does not make this comparison. The quarterly earnings release covers headline EPS and revenue against analyst consensus estimates — not whether the current operating margin trajectory matches the thesis the S-1 established three years earlier. The comparison that actually matters requires going back to the source documents, not to a financial aggregator's normalized version of them.

This is where the data quality problem sharpens. Third-party financial data providers frequently normalize, restate, or reclassify XBRL-tagged figures in ways that diverge from the as-filed numbers — folding stock-based compensation into operating expenses, reclassifying revenue line items to match a standardized template, or restating historical periods without disclosure. A comparison of S-1 promises against subsequent 10-K results depends on consistent, untouched data across periods. For more on how that normalization process introduces errors, see our posts on [financial data normalization explained](/blog/financial-data-normalization-explained) and the [problems with third-party financial data](/blog/third-party-financial-data-problems).

For a practical framework on reading the 10-K itself once a company is public, see [how to read a 10-K](/blog/how-to-read-10-k). For quarterly monitoring after the IPO, see [how to read a 10-Q](/blog/how-to-read-10-q). For the XBRL infrastructure that makes filed-data comparison possible, see [what is XBRL](/blog/what-is-xbrl).

The S-1 tells you what the company claims to be. The 10-K tells you what it is. The only way to know whether those two descriptions converge is to read both — from the source, not from the summary.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

---

## Blog: Which SEC Filings Are Audited, and Which Aren't
source: https://www.geminiq.com/blog/which-sec-filings-are-audited

### Which SEC Filings Are Audited, and Which Aren't
Not every SEC filing carries the same level of verification. The 10-K is fully audited, the 10-Q only receives a limited review, and some filings — like the routine 8-K — carry no independent assurance at all. This guide maps audit status across the 10-K, 10-Q, 8-K, S-1, and proxy statement, and shows what a real going concern qualification looks like inside an audit opinion.

Every SEC filing looks equally official. A 10-Q has the same government letterhead energy as a 10-K, and an 8-K reads with the same formal authority as either one. Financial media treats every number pulled from EDGAR as if it carries the same weight, but the numbers inside these filings are not verified to the same standard, and the gap between them is bigger than most investors assume. Some filings are fully audited by an independent accounting firm. Others are only reviewed — a real but far lighter process. Others carry no independent check at all.

This guide maps audit status across the filings investors actually read — the 10-K, 10-Q, 8-K, S-1, and proxy statement — and covers what an auditor's opinion actually certifies, the difference between a qualified opinion and a going concern qualification, and what that qualification looks like in a real, filed audit report.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=which-sec-filings-are-audited)**

---

## Table of Contents

- [Which Filings Are Fully Audited?](#which-filings-are-fully-audited)
- [Are 10-Qs Audited? No — They're Reviewed, Not Audited](#are-10-qs-audited-no--theyre-reviewed-not-audited)
- [Which Filings Carry No Independent Check at All?](#which-filings-carry-no-independent-check-at-all)
- [The Four Audit Opinion Types: Unqualified, Qualified, Adverse, Disclaimer](#the-four-audit-opinion-types-unqualified-qualified-adverse-disclaimer)
- [What a Going Concern Qualification Looks Like in a Real Filing](#what-a-going-concern-qualification-looks-like-in-a-real-filing)
- [How to Check Any Company's Audit Status in Its Own 10-K](#how-to-check-any-companys-audit-status-in-its-own-10-k)
- [Why This Matters for How You Read a Filing](#why-this-matters-for-how-you-read-a-filing)
- [Frequently Asked Questions](#frequently-asked-questions)

---

**Audit status by filing type, at a glance:**

| Filing | Level of assurance | Who provides it | What that means |
|---|---|---|---|
| 10-K | Full audit | An independent registered public accounting firm | The records are examined, internal controls tested, and a formal opinion issued on whether the statements are presented fairly under U.S. GAAP |
| S-1 | Full audit | An independent registered public accounting firm | Typically two years of audited balance sheets and three years of audited income and cash flow statements, audited before the stock ever trades |
| 10-Q | Review only — limited assurance | The same independent firm | Analytical procedures and management inquiries, without the detailed testing and evidence-gathering a full audit requires. No formal opinion |
| 8-K (routine) | None | No auditor involvement | Leadership changes, material agreements, and preliminary earnings released under Item 2.02 are management's own disclosure, checked by nobody outside the company |
| 8-K (Item 9.01) | Audited historical statements plus unaudited pro formas | An independent registered public accounting firm, for the acquired business only | On a significant acquisition, the target's historical financial statements are audited; the combined-company pro forma figures alongside them are not |
| DEF 14A | None of its own | No auditor issues an opinion on the proxy | It incorporates or attaches the already-audited 10-K figures; the Summary Compensation Table and other pay disclosures are management's reporting under SEC rules |

---

## Which Filings Are Fully Audited?

The **10-K** is the baseline. Every U.S.-listed public company's annual report contains financial statements that an independent registered public accounting firm has fully audited: examining the records, testing internal controls, and issuing a formal opinion on whether the statements are presented fairly under U.S. GAAP. [Coca-Cola's](/stocks/KO) FY2025 10-K, filed February 20, 2026, carries exactly this structure. Ernst & Young LLP signed two separate opinions dated the same day — one on the financial statements themselves, a second on the effectiveness of internal control over financial reporting under Sarbanes-Oxley Section 404. Two opinions, one filing, both from the same firm. For a full walkthrough of what else the annual report contains beyond the audit itself, see our [10-K vs. 10-Q guide](/blog/10-k-vs-10-q-differences-explained).

The **S-1** registration statement, filed ahead of an IPO, also contains audited financial statements — typically two years of audited balance sheets and three years of audited income and cash flow statements. Emerging growth companies may include only two years of income statement history. This is a detail most first-time IPO investors miss: the numbers in an S-1 have already been through a full independent audit before the stock ever trades, even though the document's promotional framing makes it read nothing like a 10-K. Our [complete guide to the S-1](/blog/what-is-s-1) covers how to separate the audited figures from the sales narrative built around them.

## Are 10-Qs Audited? No — They're Reviewed, Not Audited

The **10-Q** is the filing most investors assume carries the same weight as the 10-K, and it doesn't. Quarterly financial statements go through a review, not an audit — the same independent firm performs analytical procedures and management inquiries, but not the detailed testing and evidence-gathering that a full audit requires. A review provides limited assurance. An audit provides a formal opinion. That gap is exactly why "are 10-Qs audited" is one of the more consequential questions an investor can get wrong. Quarterly numbers are almost always accurate for an established company, but they haven't been checked to the same standard. A material misstatement is more likely to slip through a review than through a full annual audit.

## Which Filings Carry No Independent Check at All?

The **8-K** is where audit coverage mostly disappears. A routine 8-K — a leadership change, a material agreement, a preliminary earnings press release furnished under Item 2.02 — carries no auditor involvement whatsoever. Those numbers are management's own disclosure, not independently checked by anyone. The one meaningful exception sits in Item 9.01: when a company completes a significant acquisition, it must file audited historical financial statements of the acquired business alongside unaudited pro forma figures showing what the combined company would have looked like. Everywhere else in a routine 8-K, "furnished" is doing a lot of quiet work — furnished exhibits carry a lower liability standard than filed documents. That's part of why companies route preliminary results through an 8-K press release before the audited or reviewed numbers land in the 10-K or 10-Q. Our [SEC filings guide](/blog/sec-filings-guide) covers the filed-versus-furnished distinction in more depth, and our [guide to the 8-K](/blog/what-is-8-k) covers what triggers one.

The **DEF 14A** proxy statement sits in its own category. It doesn't contain a freestanding set of audited financial statements at all — it either incorporates the annual report by reference or attaches it. That attached data is simply the same already-audited 10-K numbers, not a fresh audit performed on the proxy. The Summary Compensation Table and the other pay disclosures inside the proxy are figures management reports under SEC rules, not figures an auditor has issued an opinion on. Our [guide to the DEF 14A](/blog/what-is-def-14a) covers what the proxy does and doesn't disclose.

## The Four Audit Opinion Types: Unqualified, Qualified, Adverse, Disclaimer

An unqualified opinion — often called a "clean" opinion — states that the financial statements are presented fairly, in all material respects, in accordance with U.S. GAAP. That's the standard outcome for the overwhelming majority of large, established filers, and it's what Coca-Cola's FY2025 opinion delivered.

Three other outcomes exist, and they mean progressively worse things. A qualified opinion states that the statements are fairly presented except for one specific, identified issue — a scope limitation or a departure from GAAP on one item, with everything else standing. An adverse opinion states that the financial statements, taken as a whole, are not fairly presented — a rare and severe outcome. A disclaimer of opinion means the auditor couldn't gather enough evidence to form any opinion at all, which is functionally an admission that the audit couldn't be completed.

Auditors of large accelerated filers also disclose critical audit matters — issues that were especially difficult or judgment-heavy to audit, flagged in a separate section of the report so investors know exactly where the numbers required the most interpretation. A revenue recognition policy involving long-term contracts, a complex goodwill impairment test, or a large contingent liability estimate are typical candidates. None of this appears in a 10-Q review, which is one more reason the annual filing carries more analytical weight than the quarterly ones sitting between it.

## What a Going Concern Qualification Looks Like in a Real Filing

A going concern qualification is often described as if it were its own category of opinion, and that's not quite right. It's an additional explanatory paragraph an auditor adds after the opinion when there's substantial doubt about the company's ability to keep operating for a reasonable period. Under PCAOB auditing standards, that paragraph must use both the phrases "substantial doubt" and "going concern" directly — precisely so the disclosure can't be softened into vaguer language. The opinion underneath that paragraph can still be unqualified.

Bed Bath & Beyond's final 10-K, filed June 14, 2023 for the fiscal year ended February 25, 2023, is a clean, real-world example of exactly that structure. KPMG LLP issued an unqualified opinion on the financial statements and, in the same report, added the going concern paragraph: substantial doubt about the company's ability to continue. That doubt was tied directly to the Chapter 11 proceeding the company had already entered by the time the 10-K was filed. The opinion wasn't qualified. The going concern language sat alongside it as a separate, additional disclosure — a distinction that gets lost in most casual descriptions of what a going concern warning actually is. GeminIQ's own [forensic look at Bed Bath & Beyond's buyback history](/blog/bed-bath-beyond-buyback-bankruptcy) traces how the balance sheet deterioration that produced this opinion was visible in the company's own filings more than a year before the going concern language appeared.

## How to Check Any Company's Audit Status in Its Own 10-K

You don't need a third-party database to establish a company's audit status. The 10-K states it, and four fields settle the question. Read the auditor's report at the front of the financial statements and write down each one.

**1. Which firm signed it.** The audit report names the independent registered public accounting firm. Coca-Cola's FY2025 10-K, filed February 20, 2026, names Ernst & Young LLP.

**2. What kind of opinion it is.** Unqualified, qualified, adverse, or a disclaimer of opinion. Coca-Cola's FY2025 opinion is unqualified — the standard outcome for a large, established filer, and the one that means the statements are presented fairly in all material respects under U.S. GAAP.

**3. The date on the report, and how many reports there are.** Large filers usually carry two: one on the financial statements, one on the effectiveness of internal control over financial reporting under Sarbanes-Oxley Section 404. Coca-Cola's are both from Ernst & Young and both dated February 20, 2026. A report dated well after the period end, or a single opinion where the company previously filed two, is worth a second look.

**4. Whether a going concern paragraph is present.** This sits after the opinion, not inside it, and PCAOB standards require it to use the phrases "substantial doubt" and "going concern" directly. Bed Bath & Beyond's final 10-K is the illustration: KPMG LLP issued an unqualified opinion and added the paragraph in the same report. Its presence does not make the opinion qualified — check for it as a separate field, because that is how it is filed.

Four fields, one document, no intermediary. If you are pulling these fields for a list of companies rather than one, tools built for filing retrieval — [BamSEC](/competitor-comparison/bamsec) among them — index the documents themselves, and [GeminIQ's approach](/features#financial-statements) keeps each figure tagged to the filing it came from so the audit status travels with the number.

## Why This Matters for How You Read a Filing

Knowing which filing carries which level of check changes where you put your scrutiny. An anomaly in a 10-K — a margin that doesn't reconcile, a footnote that reads differently than last year's — has already survived a full audit, so it's either explainable or genuinely significant. The same anomaly in a 10-Q has only survived a review, which means it deserves more of your own attention, not less, precisely because fewer independent eyes have checked it. And anything sitting in an 8-K press release hasn't been checked by anyone but the company itself.

GeminIQ's [Financial Statements](/features#financial-statements) feature pulls every figure directly from the filing it actually came from, tagged to its source document. Before you act on any number, check which filing it came from and what level of check that filing received — an audited annual figure, a reviewed quarterly one, or an unaudited 8-K disclosure that nobody but the company itself has checked at all. That distinction gets flattened the moment a number is pasted into a headline instead.

## Frequently Asked Questions

### Are 10-Qs audited?

No. Quarterly financial statements in a 10-Q go through a review, which involves analytical procedures and management inquiries and provides limited assurance. Only the annual 10-K's financial statements go through a full audit with a formal opinion.

### How do I tell if statements are audited or just reviewed?

Look for an auditor's report. Audited statements are accompanied by a signed opinion from an independent registered public accounting firm, naming the firm and stating whether the statements are presented fairly under U.S. GAAP. A 10-Q carries no such opinion because a review produces limited assurance rather than one, and a routine 8-K carries no independent assurance at all. In practice the filing type tells you first: 10-K and S-1 audited, 10-Q reviewed, routine 8-K neither.

### What's the difference between a qualified opinion and a going concern qualification?

A qualified opinion means the auditor found one specific item that isn't fairly presented, with everything else standing. A going concern qualification is a separate explanatory paragraph about the company's ability to keep operating — the underlying opinion can still be unqualified even when a going concern paragraph is present.

### What is a critical audit matter?

A critical audit matter is an issue that was especially difficult or judgment-heavy to audit, disclosed by auditors of large accelerated filers in a separate section of the audit report so investors know where the numbers required the most interpretation. Typical candidates are a revenue recognition policy involving long-term contracts, a complex goodwill impairment test, or a large contingent liability estimate. Critical audit matters do not appear in a 10-Q review.

### Does an 8-K ever contain audited financial statements?

Occasionally. A routine 8-K carries no audited or reviewed figures at all. The exception is Item 9.01, which requires audited historical financial statements of an acquired business when a company completes a significant acquisition, alongside unaudited pro forma figures for the combined entity.

### Is the proxy statement's executive compensation data audited?

No. The DEF 14A's compensation tables are disclosures management reports under SEC rules, not figures an independent auditor has issued an opinion on. Any financial statements referenced in a proxy are typically the same already-audited 10-K figures, incorporated by reference rather than freshly audited.

### Who audited Coca-Cola's FY2025 financial statements?

Ernst & Young LLP. [Coca-Cola's](/stocks/KO) FY2025 10-K, filed February 20, 2026, carries two Ernst & Young opinions dated the same day: one on the financial statements, and a second on the effectiveness of internal control over financial reporting under Sarbanes-Oxley Section 404. The opinion on the financial statements is unqualified.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

All financial figures cited in this article reference The Coca-Cola Company's FY2025 10-K (filed February 20, 2026, period ending December 31, 2025). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000021344&type=10-K).

The Bed Bath & Beyond example is drawn from Bed Bath & Beyond Inc.'s (CIK0000886158) final 10-K, filed June 14, 2023 for the fiscal year ended February 25, 2023, publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000886158&type=10-K). This entity is no longer publicly traded; the Bed Bath & Beyond brand and ticker were subsequently acquired out of bankruptcy by a separate company and are not the subject of this analysis.

---

## Blog: Wisesheets Alternative: Filing Data for Spreadsheets
source: https://www.geminiq.com/blog/wisesheets-alternative-sec-data

### Wisesheets Alternative: Filing Data for Spreadsheets
A Wisesheets alternative for spreadsheet modelers who need provenance. A formula returns a value with a vendor field name attached, not an XBRL tag; this post covers what a live-refreshing cell hides and why it matters to a model.

Wisesheets solves the most tedious problem in spreadsheet-based investing. Instead of copying a decade of financials from a website into Excel by hand, you write `=WISE("AAPL","Revenue","2025")` and the number appears. The add-in works across Excel and Google Sheets, offers companion functions for prices, funds, and options, ships community templates including prebuilt DCFs, and covers global exchanges with up to two or three decades of history depending on plan.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=wisesheets-alternative-sec-data)**

For anyone who models in a spreadsheet, that is hours a week returned. The workflow is right, and the criticism worth making is not about the tool's execution.

It is about what a cell can carry. A formula returns a scalar. The number arrives with no filing behind it, no footnote, no classification note, and no XBRL tag — just a value and whatever field name you typed into the second argument.

## Table of Contents

- [The Second Argument Is a Vendor Field Name](#the-second-argument-is-a-vendor-field-name)
- [A Cell Cannot Hold a Footnote](#a-cell-cannot-hold-a-footnote)
- [Live Refresh Quietly Rewrites History](#live-refresh-quietly-rewrites-history)
- [Where the Add-In Model Is Right](#where-the-add-in-model-is-right)
- [Sourcing the Model From Filed Data](#sourcing-the-model-from-filed-data)
- [Building Provenance Into the Workbook](#building-provenance-into-the-workbook)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Second Argument Is a Vendor Field Name

Look closely at the syntax and the abstraction becomes visible.

In `=WISE("AAPL","Revenue","2025")`, the ticker is unambiguous and the period is unambiguous. The middle argument is neither. "Revenue" is a parameter name defined by the data provider, and it maps to whatever that provider decided revenue means for this company in this year. It is not the caption the company used on its income statement, and it is not an XBRL tag.

That distinction is invisible in the formula and consequential in the model. A company reporting revenue across several segments, a company that changed its revenue presentation between filings, a company whose filed caption differs from the standardized label — all of them return a clean number for the same parameter string, and the formula gives no indication that anything was reconciled on the way.

To the add-in's credit, Wisesheets exposes some filing metadata as parameters, including a filing date and a CIK, which is more than many spreadsheet tools offer. But a CIK identifies the filer, not the fact. Knowing which company and which filing a value is associated with is not the same as knowing which reported line item produced it.

## A Cell Cannot Hold a Footnote

Spreadsheet-first workflows have a structural constraint that no add-in can engineer around.

Financial statements are documents, not tables. The number on the face of a balance sheet is frequently meaningless without the note that explains what it contains — which items were aggregated into a caption, which obligations sit inside a broader line, what a change in presentation did to comparability. That context is the difference between a leverage ratio you can defend and one you inherited.

A spreadsheet cell holds a value. It can hold a comment you write yourself, which nobody does at scale across a hundred cells.

So the model gets built on values stripped of the qualifications that made them interpretable. Most of the time nothing goes wrong, because most of the time the standardization was reasonable and the footnote was unremarkable. The failure is concentrated and expensive rather than frequent: it shows up on the one company where a classification choice moved a number that a conclusion rested on.

## Live Refresh Quietly Rewrites History

This is the risk specific to formula-driven workbooks, and it is the one most modelers have not thought about.

A hardcoded number is a record of what you saw. A formula is a request for whatever the provider currently says. Those are different things, and the difference only becomes apparent after the fact.

Companies restate. Prior-period figures get revised in later filings, presentations change, segments get recut, and a data provider updates its history accordingly. When that happens, a workbook built on live formulas silently updates cells you populated months ago. The model still opens. The numbers are still current. And the historical base your original thesis rested on is no longer the base you actually analyzed.

There is no diff, no version note, and no flag. A model that changes underneath you without telling you is worse than a stale one, because a stale model at least reports what you knew when you decided.

The defense is provenance — being able to establish what was filed, when it was filed, and what changed between filings. That requires filing-level structure, not a refreshed scalar.

## Where the Add-In Model Is Right

The spreadsheet-first premise deserves defending, because a lot of platform companies would prefer you gave it up.

A spreadsheet is the correct environment for valuation work. It is auditable in the sense that every formula is inspectable, it is infinitely customizable, it does not force a methodology on you, and it belongs to you rather than to a vendor's roadmap. An investor who builds their own models in Excel is doing the thing platform dashboards only simulate.

Pulling data into that environment automatically is unambiguously better than typing it, and the errors introduced by manual entry are not hypothetical — transposed digits and misaligned periods are the most common defects in retail models. Automation removes an entire class of mistake.

The critique is narrower than "use a platform instead." It is that the automation currently delivers a number without its lineage, and lineage is what a model needs when it is questioned.

## Sourcing the Model From Filed Data

GeminIQ is not a spreadsheet add-in, and it does not try to be. What it supplies is the layer that a defensible model should be built from: 10-K and 10-Q data extracted directly from SEC EDGAR, with each company's reported line item structure preserved and the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, so a modeler can see the structure a formula would have flattened. [Custom Tables](/features#custom-tables) assemble exactly the reported line items a model needs, in one view, with the filed labels intact. [Calculated Metrics](/features#calculated-metrics) including [Free Cash Flow](/metrics/calculated-values/free-cash-flow), [Invested Capital](/metrics/calculated-values/invested-capital), [Net Debt](/metrics/calculated-values/net-debt), and [Working Capital](/metrics/liquidity-ratios/working-capital) are computed from those as-filed inputs, so a derived figure can be checked against the numbers behind it rather than accepted as a parameter string.

The build guides cover the modeling side directly: [DCF valuation step by step](/blog/dcf-valuation-model-step-by-step) for the model itself, and [invested capital](/blog/invested-capital-formula-step-by-step) for the input that standardization moves most often.

## Building Provenance Into the Workbook

There is a practical discipline that improves any spreadsheet model regardless of which tool fills the cells, and it costs almost nothing.

Separate the historical base from the forecast. Hardcode the historical figures rather than leaving them live, and note the filing and period each one came from. Let the forecast be formulas — that is where a model should be dynamic. When a restatement lands, you will see it as a difference between what you recorded and what the source now says, which is exactly the signal you want and exactly what a fully live workbook suppresses.

That structure turns a spreadsheet into a record of a decision instead of a snapshot of a vendor's current opinion. For the same inherited-inputs problem inside a platform's own prebuilt models, the [Finbox alternatives](/blog/finbox-alternative-sec-data) post covers what a model carries before you change an assumption.

The formula saved you the typing. The filing is what makes the model something you can still defend a year later, when the number has quietly changed and you are the only one who knows what it used to be.

## Frequently Asked Questions

### What are the best Wisesheets alternatives?

It depends on what you are optimizing. For pulling data into Excel or Google Sheets automatically, the substitutes are other spreadsheet add-ins and data APIs, most of which return values with a vendor field name rather than a filing reference. For provenance — knowing which reported fact produced a number — the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### Does a spreadsheet formula tell you which SEC filing a number came from?

Not by itself. The formula returns a value keyed to a ticker, a parameter name, and a period. Some add-ins expose filing metadata such as a filing date or CIK as additional parameters, which identifies the filer and the document but not the specific reported line item that produced the value.

### What happens to a spreadsheet model when a company restates?

Cells populated by live formulas update to the provider's revised history without notice. The workbook opens normally and the numbers are current, but the historical base your original analysis rested on has changed. Hardcoding the historical section and leaving only the forecast dynamic is the practical defense.

### Can I build a valuation model directly from SEC filings?

Yes. The entire historical half of a model — revenue, margins, capital expenditure, working capital movement, debt and cash for the equity bridge — comes from reported line items in the 10-K and 10-Q. What filings never contain is the forecast, which should be your own contribution regardless of which tool supplies the history.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=wisesheets-alternative-sec-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Wisesheets function syntax (WISE, WISEPRICE and companion functions), available parameters including filing date and CIK, template library, platform support across Excel and Google Sheets, and coverage and history claims reviewed August 2, 2026 from Wisesheets documentation, its marketplace listings, and third-party reviews. Verify current plan limits before republication.

---

## Blog: Working Capital Drain: Honeywell's $3.1 Billion Gap
source: https://www.geminiq.com/blog/working-capital-drain-cash-burn

### Working Capital Drain: Honeywell's $3.1 Billion Gap
Working capital drain occurs when a company's reported net income runs well ahead of the actual cash its operations generate, and as-filed data ranks the largest companies currently showing that gap.

**[Honeywell International](/stocks/HON)** reported **$8.2 billion** in net income against just **$5.1 billion** in operating cash flow over the trailing twelve months — a $3.1 billion gap, meaning roughly **38%** of the earnings figure that flows into the headline didn't show up as cash the business actually generated. Neither number is wrong; both are as-filed. But when reported earnings and operating cash consistently diverge by this much, the difference between the two is exactly where working capital movements, timing differences, and non-cash items live, and it's worth knowing which one is doing the heavier lifting in a given quarter's headline.

This study reads GeminIQ's as-filed universe as of the most recent trailing-twelve-month filing period, restricted to non-financial companies with **over $1 billion in trailing revenue**, positive net income above **$100 million**, positive operating cash flow, and a net margin sane enough to rule out one-time gain distortions. **15 companies** anchor the largest dollar-value gaps between net income and operating cash flow in the current snapshot.

## The Pattern

A persistent gap between net income and operating cash flow is not automatically a red flag — it's a prompt to look at what's driving it. Reported earnings include non-cash items (deferred taxes, unrealized gains, certain accruals) that operating cash flow strips back out, and operating cash flow reflects real working capital movements (receivables building, inventory growing, payables shrinking) that don't touch the income statement at all. A company where receivables and inventory are consistently absorbing cash faster than earnings are being booked is showing a specific, checkable signal in the cash flow statement — one that a headline EPS number will never surface on its own.

## The Data

| Rank | Company | Ticker | Sector | Net Income (TTM) | Operating Cash Flow (TTM) | Gap |
|---|---|---|---|---|---|---|
| 1 | Honeywell International Inc | HON | Manufacturing | **$8.2B** | **$5.1B** | **$3.08B** |
| 2 | Netflix Inc | NFLX | Services | **$13.6B** | **$12.0B** | **$1.68B** |
| 3 | Lam Research Corp | LRCX | Manufacturing | **$7.3B** | **$5.9B** | **$1.41B** |
| 4 | Carvana Co. | CVNA | Retail Trade | **$2.1B** | **$1.1B** | **$1.01B** |
| 5 | Ferguson Enterprises Inc. | FERG | Wholesale Trade | **$2.4B** | **$1.4B** | **$1.01B** |
| 6 | Solventum Corp | SOLV | Manufacturing | **$1.4B** | **$0.4B** | **$1.01B** |
| 7 | Martin Marietta Materials Inc | MLM | Mining | **$2.5B** | **$1.5B** | **$0.94B** |
| 8 | Applied Materials Inc | AMAT | Manufacturing | **$9.3B** | **$8.4B** | **$0.87B** |
| 9 | Lennar Corp | LEN | Construction | **$1.6B** | **$0.9B** | **$0.77B** |
| 10 | Dana Inc | DAN | Manufacturing | **$1.1B** | **$0.4B** | **$0.71B** |

<center><sup>GeminIQ Custom Table showing Honeywell's quarterly net income and operating cash flow, March 2025 to June 2026 (values in millions).</sup></center>

## Carvana: The Gap Worth a Second Look

**[Carvana](/stocks/CVNA)**'s gap stands out for a different reason than the industrials on this list. The company's net income of **$2.1 billion** against operating cash flow of **$1.1 billion** — a 47.5% shortfall — comes at a company still relatively early in a turnaround narrative that has been heavily rewarded by the market, which makes the earnings-versus-cash divergence a more consequential check than it would be at a mature industrial with decades of stable working capital patterns. Neither figure alone settles whether the gap is temporary financing-related working capital or a more persistent feature of the business; it is the kind of divergence worth tracking across future filings rather than reading once.

<center><sup>GeminIQ Custom Table showing Carvana's quarterly net income and operating cash flow, March 2025 to June 2026 (values in millions).</sup></center>

**[Netflix](/stocks/NFLX)** and **[Lam Research](/stocks/LRCX)** illustrate the more benign version of the same gap: both are large, mature, consistently profitable businesses where the net income/OCF divergence sits well below **20%** of earnings and has more to do with the timing of content amortization and receivables than any underlying earnings-quality concern.

## The Method

Net income and operating cash flow are both trailing-twelve-months, as-filed figures drawn from GeminIQ's Financial Statements data for each company's most recent filing period within the last fifteen months. This ranking restricts the universe to companies with a net margin under **40%** to exclude one-time gain distortions (deconsolidation gains, bargain purchase gains, and similar non-recurring items can otherwise produce an implausibly large gap that reflects an accounting event rather than a working capital pattern), and to companies with over **$1 billion** in trailing revenue and positive operating cash flow. Full methodology is covered in [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).

## Check Your Holdings

Pull up any position's net income and operating cash flow on GeminIQ side by side and check how far apart they run relative to earnings — a small, stable gap is normal, but a large or widening one is worth tracing to its source in the cash flow statement's working capital section before taking the headline earnings number at face value. Every reader can run that same comparison directly against GeminIQ's as-filed data.

## Frequently Asked Questions

### What does it mean when operating cash flow is lower than net income?

It means the earnings figure reported on the income statement includes items — non-cash gains, deferred taxes, or working capital movements like growing receivables and inventory — that haven't yet shown up as actual cash the business generated. In GeminIQ's data, Honeywell shows one of the largest current gaps: **$8.2 billion** in net income against **$5.1 billion** in operating cash flow.

### Is a gap between net income and operating cash flow always a red flag?

Not automatically. It's a prompt to check what's driving the divergence — non-cash items and normal working capital timing produce small, stable gaps at most mature businesses, while a large or widening gap, especially at a company still early in a turnaround narrative, is worth tracking more closely.

### How is this gap calculated?

It's trailing-twelve-months net income minus trailing-twelve-months operating cash flow, both read directly from as-filed data on GeminIQ's [Financial Statements](/features#financial-statements) view.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=working-capital-drain-cash-burn)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>Data Appendix: Universe drawn from GeminIQ's as-filed Financial Statements data, restricted to non-financial companies with over $1 billion in trailing revenue, positive net income above $100 million, positive operating cash flow, and a net margin under 40%, current as of the most recent trailing-twelve-month filing period within the last fifteen months, built from as-filed 10-K and 10-Q data publicly available on [SEC EDGAR](https://www.sec.gov/). Methodology: [How GeminIQ Builds Filing Data Studies](/blog/filing-data-study-methodology).</sup>

---

## Blog: XBRL Data Providers Compared: Why the Numbers Differ
source: https://www.geminiq.com/blog/xbrl-financial-data-providers-compared

### XBRL Data Providers Compared: Why the Numbers Differ
The SEC's XBRL taxonomy sits behind every reported figure in a 10-K or 10-Q, and it is revised every year. This post covers what the taxonomy is, what happens when an element is deprecated or replaced, when a filer is allowed to invent a custom tag instead, and why two financial websites can show different numbers for the same company as a result.

Every fundamental data platform on the market ultimately traces back to the same source: the XBRL-tagged financial statements companies submit to SEC EDGAR. That part is universal. What differs is the vocabulary question sitting underneath it — which tag a company picked, whether that tag still means what it meant three years ago, and whether anything downstream still shows it to you.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=xbrl-financial-data-providers-compared)**

Every reported figure in a modern 10-K or 10-Q carries a specific [XBRL](/blog/what-is-xbrl) tag identifying what it is, drawn from a published vocabulary called a taxonomy. [Apple's](/stocks/AAPL) [stock buyback](/blog/do-buybacks-reduce-share-count) figure, for instance, is not one number; it is two separately tagged line items, Payments For Repurchase Of Common Stock and Payment Related To Tax Withholding For Share Based Compensation. Whether a provider keeps that structure intact, collapses it into something else, or never shows it to you at all determines how far a number on screen actually is from what the company filed.

## Table of Contents

- [The SEC's Own Free XBRL Tools](#the-secs-own-free-xbrl-tools)
- [Why Two Sites Show Different Numbers for the Same Company](#why-two-sites-show-different-numbers-for-the-same-company)
- [What Happens When the Taxonomy Changes](#what-happens-when-the-taxonomy-changes)
- [When a Filer Invents Its Own Tag](#when-a-filer-invents-its-own-tag)
- [GeminIQ: The Tag Stays Attached](#geminiq-the-tag-stays-attached)
- [Choosing Based on What You Actually Need](#choosing-based-on-what-you-actually-need)
- [Frequently Asked Questions](#frequently-asked-questions)

## The SEC's Own Free XBRL Tools

The most complete XBRL data source is also the least used, because it requires the most manual work. The SEC's Inline XBRL viewer, reachable from the "Interactive Data" link on any filing's index page, lets you click a single reported value and see its exact tag, its period, and its as-filed amount. The CompanyFacts API returns every value one company has ever reported under a single tag as JSON; the Frames API flips that query, returning one tag across every filer for a single period. The SEC's Financial Statement Data Sets go further still, publishing the entire quarter's XBRL submissions as bulk downloadable files.

All of it is free, all of it is authoritative, and none of it is assembled into anything resembling a research workflow. Getting a five-year statement history for one company means either a dozen manual lookups in the Inline XBRL viewer or [writing code against the API](/blog/pull-sec-financial-data-python) — which carries its own set of traps around CIK formatting, rate limits, and restated periods. The SEC built the ground truth. It did not build the tool that makes the ground truth usable, and that gap is what every commercial provider below exists to fill, in one direction or another.

## Why Two Sites Show Different Numbers for the Same Company

Two research sites can show a different revenue, buyback, or debt figure for the same company and the same quarter without either one being wrong, and without either one having made an error. The difference is upstream of both screens: each has run the filing's tags through its own [data normalization](/blog/financial-data-normalization-explained) layer, and the templates disagree about which tagged items belong on which line. Every serious platform runs data normalization software financial filings must pass through before a single number reaches a screen, and no two implementations of it make identical choices — which is the whole reason the [problems with third-party data](/blog/third-party-financial-data-problems) show up as disagreement rather than as visible error.

What separates the platforms is not really price or coverage but how many normalization layers sit between the filing and the screen, and each layer is one more place the original tag structure gets left behind. Four tiers cover almost the entire market, and a platform's tier predicts what happens to the tag far better than its price does. A genuine head-to-head on pricing, coverage, and interface is a different question from this one, covered in [SEC Filing Analysis Tools Compared](/blog/sec-filing-analysis-tools-compared) and, for the institutional end of the market, in the [S&P Capital IQ comparison](/competitor-comparison/sp-capital-iq).

| Tier | What happens to the tag | Platforms |
|---|---|---|
| Institutional normalizers | Filings mapped into a proprietary taxonomy built for cross-company comparability rather than filing fidelity | [Bloomberg Terminal](/competitor-comparison/bloomberg-terminal), [S&P Capital IQ](/competitor-comparison/sp-capital-iq), [FactSet](/blog/factset-alternative-sec-filing-data) |
| Licensed re-packagers | The same Capital IQ / S&P Global data with a new interface — normalization decisions inherited, not made | [TIKR](/blog/tikr-alternative-sec-data), [Koyfin](/competitor-comparison/koyfin), [YCharts](/competitor-comparison/ycharts), [Fiscal.ai](/competitor-comparison/fiscal-ai), [StockAnalysis.com](/blog/stockanalysis-com-alternative-filing-data) |
| Score and rating layers | Standardized figures compressed further into a rating, score, or rank | [Morningstar](/blog/morningstar-alternative-sec-filing-data), [GuruFocus](/competitor-comparison/gurufocus), [Simply Wall St](/blog/simply-wall-st-alternative-sec-data), [Value Line](/blog/value-line-alternative-sec-data), [Zacks](/blog/zacks-alternative-sec-filing-data) |
| Extraction with citation | Modeled figures with a source hyperlink attached — closer to the filing, still a modeled figure rather than the tag | [Daloopa](/blog/daloopa-alternative-sec-data), [Finbox](/competitor-comparison/finbox), [Wisesheets](/blog/wisesheets-alternative-sec-data) |

StockAnalysis.com is the most transparent about where it sits: its own data-sources documentation names the licensed providers behind its numbers and tells users to verify critical figures against the original filing. That is a tacit admission that the platform itself is a step removed from the tag.

## What Happens When the Taxonomy Changes

The US GAAP Financial Reporting Taxonomy is not fixed. It is maintained by FASB, revised on an annual cycle, and accepted by the SEC for use in filings, which means the vocabulary companies tag against is a moving target rather than a permanent dictionary. Each revision adds elements for new accounting standards, deprecates elements that no longer fit, and in some cases replaces one element with a successor that means almost, but not exactly, the same thing. A company still reporting the same economic item has to move to the replacement element once the old one is retired.

Revenue is the clearest worked example, because the change touched nearly every filer at once. `us-gaap:SalesRevenueServicesNet` — the element that carried service revenue on countless income statements — was deprecated in the 2018 taxonomy alongside the arrival of ASC 606, the revenue recognition standard, and superseded by `RevenueFromContractWithCustomerExcludingAssessedTax`. Nothing about the underlying business changed. The element name carrying the number did. Anything querying the old element for periods after the switch finds nothing; anything querying the new element for periods before it finds nothing either, and neither result looks like an error.

Companies also change tags for reasons of their own, independent of the annual revision. A line item gets reclassified, its contents change, or a filer moves between a standard taxonomy element and a custom extension element created for a disclosure the standard vocabulary does not cover. The result in every one of these cases looks the same from the outside: one continuous economic series in the business, sitting under two different tags across two filings.

That is where providers have to make a choice nobody sees them make. A platform can stitch the old tag and the new tag into a single unbroken series, or it can keep them apart as two series with a discontinuity between them. Both are defensible. Stitching produces a clean decade-long line that quietly hides a definitional change in the middle of it; keeping them apart produces a series that appears to break for no reason a chart can explain. Neither choice is visible on the screen unless the tag behind each value is still there to inspect, which is the whole argument for keeping it attached. When it goes wrong in a way that is actually visible, it looks like [Microsoft's FY2017 Revenues tag](/blog/xbrl-tag-changes-between-filing-years).

## When a Filer Invents Its Own Tag

Deprecation is not the only way a standard element stops being where a number lives. A standard tag comes from one of a small number of taxonomies the SEC recognizes: `us-gaap` for U.S. GAAP concepts, `dei` for entity-level disclosure information, `srt` for a smaller set of standardized industry-specific concepts, and `ifrs-full` for foreign private issuers reporting under IFRS. Every element in these taxonomies is defined once, centrally, and updated on a predictable annual cycle. A custom tag — sometimes called an extension — is anything a filer defines itself, inside its own company-specific taxonomy extension, because none of the standard elements fit the line item being disclosed.

The rule governing when this is actually permitted is narrow. Under 17 CFR 232.405(c)(1)(iii)(B), "an electronic filer must create and use a new special element if and only if an appropriate tag does not exist in the standard list of tags for reasons other than or in addition to an inappropriate standard label." A custom tag is meant to be the exception a filer reaches for when the taxonomy has no equivalent at all, not a substitute for finding the right standard one.

What happens after the filing is where it becomes a data problem. `us-gaap:Revenues` means the same thing wherever it appears, so a query for it returns exactly the values it is supposed to. A custom tag has no such guarantee: every platform that wants to include a custom-tagged value in a standardized field has to decide, on its own, which standard concept that custom tag corresponds to — a mapping the SEC never defines and the filer never confirms. XBRL US's own published case study of this problem, built for Liberty Mutual Surety, documents what doing it properly costs. An automated tool ran the initial classification of custom extension tags against the standard taxonomy, and that automated output still required "a manual review... to make further refinements" before the mapping could be trusted. An organization with the resources to build a dedicated normalization framework still needed a human to check the algorithm's guesses. A platform without that review step publishes the algorithm's first guess as fact.

## GeminIQ: The Tag Stays Attached

GeminIQ is built around the opposite default: every reported value keeps its XBRL tag attached, and nothing gets combined, relabeled, or standardized away before it reaches the screen. When Apple's two buyback-related cash flow items appear on GeminIQ, they appear as two line items, because that is how they were filed, not as a single "buybacks" figure that a template decided to merge.

[Financial Statements](/features#financial-statements) display each company's own reported captions rather than a generic template's line items. [Calculated Metrics](/features#calculated-metrics), including [ROIC](/blog/roic-return-on-invested-capital-explained), Free Cash Flow, and Net Debt, compute from those same as-filed, tagged inputs, so a metric traces back through its formula to the specific tags that fed it. A Free plan carries this same tag-level traceability at no cost, with **3 years** of history and **24** calculated metrics; the paid Annual and Monthly plans extend it to **17-plus** years and **90-plus** metrics, plus the Stock Screener. The scope is narrower than an institutional terminal on purpose. What it buys instead is that the number on screen and the number in the filing are never two different things to reconcile.

## Choosing Based on What You Actually Need

Tag-level traceability is not the right requirement for every job, and it would be dishonest to pretend otherwise. Screening a universe fast, getting oriented on an unfamiliar name, or comparing valuation across a peer group is well served by the licensed platforms above, and their standardization is a feature for that specific job, not a flaw. The moment the question becomes "is this the number the company actually reported," the standardization stops helping and starts being the obstacle.

At that point there are exactly two options that keep the tag intact: doing the extraction yourself against the SEC's own free tools, or using a platform built to preserve that structure automatically. Everything in between, however useful for its own purpose, has already made the substitution that a filing-level check exists to catch.

## Frequently Asked Questions

### What is the SEC XBRL taxonomy?

It is the vocabulary of elements companies tag their reported figures against when they file with the SEC. The core of it is the US GAAP Financial Reporting Taxonomy, maintained by FASB and revised annually, with SEC-specific taxonomies covering cover-page and document data alongside it. Filers can also create custom extension elements for disclosures the standard vocabulary does not cover. Because the taxonomy is revised each year, an element that carried a figure in one filing can be deprecated or replaced by the next, which is the mechanic behind most tag changes an investor runs into.

### Why do two financial websites show different numbers for the same company?

Almost always because they mapped the same filing differently, not because one of them has bad data. Each platform maps the filing's tags into its own standardized template, and the templates disagree about which tagged items belong on which line, so an item one provider folds into a total another leaves out. Tag changes across filings compound it: if a company switches elements between periods, one provider may stitch the old and new tags into a continuous series while another keeps them apart. The only way to settle which is which is to look at the tag behind each value, which is what the as-filed approach preserves and the standardized approach discards.

### Are custom XBRL tags allowed by the SEC?

Yes, under specific conditions. Rule 17 CFR 232.405(c)(1)(iii)(B) permits a custom tag only when no appropriate standard element exists for the disclosure — not as a substitute for using an available standard tag with a label the filer does not like. A custom tag is invisible to any query built on the standard element it should logically roll up into, which is why a screen that looks complete can silently exclude a company.

### Which financial data providers show the actual XBRL tag?

Very few. The SEC's own Inline XBRL viewer and its CompanyFacts and Frames APIs expose the tag directly but require manual work or code to use at scale. Among commercial platforms, GeminIQ keeps the tag attached to every value; most licensed platforms standardize the figure into their own template and do not expose the originating tag to the user.

### Are the SEC's XBRL APIs free to use?

Yes. The CompanyFacts API, the Frames API, and the Financial Statement Data Sets are all free and require no registration. They are also unformatted for research use, returning raw JSON or bulk delimited files rather than a browsable research interface.

### Is GeminIQ's XBRL data free?

In part. GeminIQ's Free plan provides tag-level traceability at no cost, covering 3 years of financial history and 24 calculated metrics. The full 17-plus years of history, 90-plus metrics, and the Stock Screener are available on the paid Annual or Monthly plan.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=xbrl-financial-data-providers-compared)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Apple's XBRL tag structure referenced from Apple Inc.'s SEC filings via SEC EDGAR.
- SEC Inline XBRL viewer, CompanyFacts API, Frames API, and Financial Statement Data Sets are official SEC.gov resources; endpoint behavior described as documented at data.sec.gov.
- Custom extension tag rule quoted from 17 CFR 232.405(c)(1)(iii)(B) (Regulation S-T).
- Custom-tag mapping case study and quoted language from XBRL US's published [Liberty Mutual Surety custom data collection case study](https://xbrl.us/research/data-collection/).
- `us-gaap:SalesRevenueServicesNet`, `RevenueFromContractWithCustomerExcludingAssessedTax`, and the 2018 taxonomy / ASC 606 transition referenced from the FASB US GAAP Financial Reporting Taxonomy release notes.
- Category placements and figures for Bloomberg Terminal, S&P Capital IQ, FactSet, TIKR, Koyfin, YCharts, Fiscal.ai, Morningstar, GuruFocus, Simply Wall St, Value Line, Zacks, StockAnalysis.com, Daloopa, Finbox, and Wisesheets are drawn from GeminIQ's own published comparison research on each platform (linked above), reviewed August 2, 2026 from each platform's public materials.
- GeminIQ Free, Annual, and Monthly plan features, limits, and pricing confirmed directly from https://www.geminiq.com/pricing, retrieved August 7, 2026.

---

## Blog: When XBRL Tags Change Between Filing Years
source: https://www.geminiq.com/blog/xbrl-tag-changes-between-filing-years

### When XBRL Tags Change Between Filing Years
In Microsoft's FY2017 10-K, the standard us-gaap:Revenues tag captured only product revenue — not the company's real total — for all four quarters of the fiscal year, summing to a self-consistent annual figure that passes every structural check EDGAR runs. This case study walks the actual filing data quarter by quarter, the validation checks that pass anyway, and what a gross margin above 100% looks like when that figure feeds a calculation unchecked.

[Microsoft's](/stocks/MSFT) own FY2017 10-K carries a line item labeled "Total Revenues," tagged with the standard `us-gaap:Revenues` element, showing **$57.19 billion** for the fiscal year. Microsoft's actual total revenue for that year, reported everywhere else in the same filing and confirmed by every contemporary press account, was **$89.95 billion**. The gap isn't a typo, a restatement, or a filer error the SEC ever flagged. It's product revenue — one of two components that make up the real total — sitting under the tag that's supposed to mean the whole company.

What makes this dangerous is that the wrong number carries every mark of a right one. The four quarters tagged the same way across fiscal 2017 sum to the annual figure to the dollar, and nothing about the filing fails to foot. A screener pulling `Revenues` by tag alone gets a number that's internally consistent, cleanly traceable to a real filing, and still describes something other than what its label says.

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---

## Table of Contents

- [The Setup: A Tag That Looks Fine From the Outside](#the-setup-a-tag-that-looks-fine-from-the-outside)
- [What Microsoft's FY2017 "Revenues" Tag Actually Shows](#what-microsofts-fy2017-revenues-tag-actually-shows)
- [The Checks That Catch It, and the Ones That Don't](#the-checks-that-catch-it-and-the-ones-that-dont)
- [How Far the Error Travels: A 109% Gross Margin](#how-far-the-error-travels-a-109-gross-margin)
- [How Often This Actually Happens](#how-often-this-actually-happens)
- [Verifying the Numbers Yourself](#verifying-the-numbers-yourself)
- [Why As-Filed Traceability Is the Only Real Defense](#why-as-filed-traceability-is-the-only-real-defense)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Related Reading](#related-reading)

---

## The Setup: A Tag That Looks Fine From the Outside

Every quarter, GeminIQ's pipeline reads the `tag` column directly out of a company's XBRL submission — the same raw field this entire platform is built to preserve rather than normalize away. For Microsoft, pulling every value ever reported under the tag `Revenues` produces a clean, unbroken quarterly and annual series stretching back to 2009. Almost every one of those values matches Microsoft's own reported total revenue for the period. Fiscal 2016: **$85.32 billion**, matching the $85,320 million Microsoft reported. Fiscal 2018: **$110.36 billion**, matching the company's first year over $100 billion in revenue. Fiscal 2017, sitting directly between them, breaks the pattern.

<center><sup>GeminIQ Financial Statements view of Microsoft's Revenues line, FY2016 through FY2018 — the FY2017 annual figure ($57.19B) breaks the pattern set by FY2016 ($85.32B) and FY2018 ($110.36B).</sup></center>

---

## What Microsoft's FY2017 "Revenues" Tag Actually Shows

Here is the `Revenues` tag's full fiscal 2017 series, exactly as filed:

| Period | Filing | Accession Number | `Revenues` Tag Value |
|---|---|---|---|
| Q1 FY2017 (end 2016-09-30) | 10-Q | 0001193125-16-742796 | **$14.968 billion** |
| Q2 FY2017 (end 2016-12-31) | 10-Q | 0001564590-17-000654 | **$18.273 billion** |
| Q3 FY2017 (end 2017-03-31) | 10-Q | 0001564590-17-007547 | **$14.513 billion** |
| FY2017 (end 2017-06-30) | 10-K | 0001564590-17-014900 | **$57.190 billion** |

The four quarters sum to exactly $57.19 billion, matching the annual figure to the dollar — a filing that foots perfectly. The same 10-K's income statement also carries a second revenue line, tagged `Sales Revenue Services And Other Net` and labeled "Service and Other," showing **$32.76 billion** for the year. Add the two together — $57.19 billion plus $32.76 billion — and the result is **$89.95 billion**, exactly matching Microsoft's real, reported total revenue for fiscal 2017, disclosed in the same 10-K's segment footnote.

The `Revenues` tag, in other words, wasn't tagging total revenue in fiscal 2017. It was tagging Product revenue — one of the two lines a reader is supposed to add together to get the number the tag's own label claims to already be.

---

## The Checks That Catch It, and the Ones That Don't

This is worth being precise about, because "passes every check" is a claim that only holds for certain checks. The filing passes EDGAR's structural validation — the calculation linkbase Microsoft submitted ties out, because whatever relationship it declares between quarters and the annual total, both sides used the same (mistagged) figure consistently. It passes a naive quarterly-footing test, the kind a script would run to confirm Q1+Q2+Q3+Q4 equals the reported FY figure, because that's arithmetically true regardless of what the tag actually represents. Neither check has any way to know what a number is supposed to mean. They only confirm the numbers already in the filing agree with each other.

What it does not pass is a domain-aware sanity check applied to anything downstream of revenue. That's the part worth walking through directly, because it's exactly the layer most raw-XBRL pipelines skip.

---

## How Far the Error Travels: A 109% Gross Margin

GeminIQ's own trailing-twelve-month metrics for Microsoft show precisely what happens when this figure feeds into a calculation without a sanity check catching it first. For the trailing twelve months ending June 30, 2017 — the exact window built entirely from the four mistagged quarters above — the calculated [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) comes out to **108.95%**.

A gross margin above 100% is not a rounding artifact or an edge case. It states that the cost of the goods and services sold was negative, which is not something that happens in Microsoft's actual business. The same trailing-twelve-month window also shows a [net profit margin](/metrics/margin-metrics/net-profit-margin) of **44.57%** and an operating margin of **50.75%** — both roughly double Microsoft's real fiscal 2017 margins. The denominator (revenue) had been cut by **36%** while the correctly-tagged profit figures were divided against it. The distortion doesn't stay contained to the one quarter carrying the bad annual figure, either. A trailing-twelve-month window doesn't fully "age out" a bad quarter until four quarters later, so the calculated revenue growth rate for that same period shows a false **-32.97%** decline that never happened.

<center><sup>GeminIQ Calculated Metrics view of Microsoft's trailing-twelve-month Gross Profit Margin — the period ending June 30, 2017 shows 108.95%, a mathematical impossibility that flags exactly where the underlying revenue figure broke.</sup></center>

Every one of these calculated figures is arithmetically correct given its inputs. The math isn't broken. The input is.

---

## How Often This Actually Happens

Microsoft's case is unusually easy to catch after the fact, precisely because the downstream math is so obviously wrong — a margin over 100% is hard to miss once you're looking for it. The obvious follow-up question is how much of a typical filing sits outside the standard vocabulary in the first place, and the SEC measures one part of that directly.

The SEC's own Division of Economic and Risk Analysis (DERA) publishes a running trend analysis of custom tag rates in 10-K filings going back to fiscal year 2012 — custom tags being elements a filer defines itself when no standard element fits. DERA's staff observations put the average custom-tag rate at **17%** across U.S. GAAP filers in 2019, rising to **20%** in 2020, before reversing, with custom tag usage declining across most filer categories in the years since. Even at the low end of that range, roughly one in every five to six line items requiring a tag on a typical 10-K's financial statements is filed under a tag that exists nowhere outside that one company's own extension taxonomy.

That rate isn't distributed evenly. DERA's analysis breaks custom-tag usage out by filer status — large accelerated, accelerated, non-accelerated, and smaller reporting companies — and the pattern holds across nearly every year measured: smaller filers, with less XBRL tagging infrastructure and fewer specialized accounting staff, consistently run a higher custom-tag rate than large accelerated filers. A custom tag is a different failure mode from Microsoft's — it's a nonstandard element carrying the right number, rather than a standard element carrying the wrong one — but it's the one the agency quantifies, and it sets the floor for how much of any given filing a standard-tag query never sees.

There is also evidence that heavy custom tagging is not a neutral stylistic choice. A 2025 study in the *International Journal of Accounting Information Systems* found that firms with weak internal controls are more likely to create custom tags in their 10-K filings, and documented a positive association between excessive custom-tag usage and SEC oversight — specifically, a higher likelihood of receiving a comment letter. Firms reduced their custom-tag usage after SEC review. The rate is not just a data-quality statistic; it correlates with the control environment behind the filing.

Mistagging itself doesn't get published as a rate, only as individual cases. In August 2019, the SEC sent Compass Diversified Holdings a comment letter identifying that the company had tagged its total net deferred tax liability with `Deferred Tax Assets Liabilities Net` — a specific, wrong element. It was caught only because SEC staff reviewed the filing directly and requested the correct tag going forward. And the SEC's own September 2023 sample comment letter on XBRL disclosures names "inconsistent element selection across reporting periods" as a standing category of comment it issues. That's the agency's own acknowledgment, in an official published template, that companies routinely tag the same reported line item with different elements from one period to the next — with no guarantee any downstream number built on the assumption of consistency gets flagged before it's published.

---

## Verifying the Numbers Yourself

Every figure above traces to a specific accession number, which means none of it requires taking this article's word for it. Pull the FY2017 10-K's [filing index page](/blog/edgar-accession-number-url-structure) for accession `0001564590-17-014900`, open the primary document, and the "Total Revenues" line under the income statement reads $57,190 million — Microsoft's own filed number, not a transcription. The segment footnote a few pages later reports total revenue of $89,950 million for the same fiscal year, in the same document. Both numbers are real; only one of them is what the `Revenues` tag actually captured.

---

## Why As-Filed Traceability Is the Only Real Defense

There is no tagging rule this filing violated, which is exactly why the SEC's automated validation let it through and no subsequent comment letter corrected it. Microsoft simply presented Product and Service revenue as two separate lines in fiscal 2017 — a legitimate presentation choice, and one made independently of [the annual taxonomy revision](/blog/xbrl-financial-data-providers-compared) that accounts for most tag changes between filing years. Nothing outside this one filer's own presentation produced the gap.

GeminIQ's response to this isn't a rule that catches every case like it. It's that every figure on the platform carries its own accession number and tag value back to the specific filing it came from, the same traceability this entire investigation ran on. A number that looks wrong on GeminIQ can be checked against the identical filing in minutes, using nothing more than the [accession number and the tag it was pulled from](/blog/edgar-accession-number-url-structure). A number that's been silently normalized by an aggregator that discards the source tag offers no equivalent path back — the error, if one exists, is simply invisible. How that as-filed default compares to other filing-derived platforms is laid out in our [ROIC.ai comparison](/competitor-comparison/roic-ai).

---

## Frequently Asked Questions

### Was Microsoft's FY2017 10-K itself wrong?

Not necessarily. Microsoft's own filed numbers — both the $57.19 billion Product-revenue figure and the $89.95 billion total disclosed in the segment footnote — are accurate and consistent with each other. The issue is which XBRL context gets treated as the entity-level default for the `Revenues` tag, not an error in what Microsoft reported.

### How can a tag pass validation and still be wrong?

EDGAR's validation checks whether the numbers within a filing are internally consistent — whether a calculation linkbase ties out, whether quarters sum to the stated annual figure. None of those checks know what a tag is supposed to represent in the real world; they only confirm the filing agrees with itself.

### Does this only affect revenue tags?

No. The same underlying mechanism — a standard tag capturing one component of a multi-part disclosure rather than the consolidated total — can affect any line item a company breaks into sub-categories, including cost of revenue, which Microsoft's own FY2017 10-K also splits into Product and Service and Other components under the same pattern.

### How would an investor catch this without cross-checking every tag manually?

A margin, ratio, or growth rate that falls outside a plausible range — a gross margin above 100%, a growth rate that contradicts every other public account of the period — is usually the first visible symptom, even when the root cause is a single mistagged line several calculation steps upstream.

The tag said "Total Revenues." For one fiscal year, out of Microsoft's entire public filing history, it wasn't. Knowing how to check is the only difference between catching that and reporting it as fact.

---

## Related Reading

- [EDGAR Accession Numbers and Filing URL Structure](/blog/edgar-accession-number-url-structure) — how the accession numbers cited throughout this piece resolve to an exact filing.
- [How to Pull SEC Financial Data With Python](/blog/pull-sec-financial-data-python) — the free API this same tag problem shows up in for anyone pulling raw XBRL directly.
- [SEC XBRL Taxonomy Explained for Investors](/blog/xbrl-financial-data-providers-compared) — why the vocabulary behind these tags changes at all, and what providers do about it.
- [What Is XBRL and Why Does It Matter for Investors?](/blog/what-is-xbrl) — the underlying tagging standard this entire investigation depends on.
- [Verify Financial Data Against the Original SEC Filing](/blog/verify-financial-data-against-sec-filing) — the general version of the check run against Microsoft here.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

Custom-tag rates and the filer-status breakdown are drawn from the SEC Division of Economic and Risk Analysis (DERA) staff trend analysis of custom tag usage, published at [U.S. GAAP — XBRL Custom Tags Trend](https://www.sec.gov/data-research/structured-data/us-gaap-xbrl-custom-tags-trend); the fiscal 2018–2020 figures are from the SEC's [August 2021 trend announcement](https://www.sec.gov/newsroom/whats-new/osd-announcement-082721-trend-custom-tag-rates-xbrl). The internal-controls and SEC-oversight findings are from Daeun (Philip) Lee and Joung W. Kim, "Excessive Custom XBRL Tag Usage in 10-K Filings and SEC Oversight," *International Journal of Accounting Information Systems*, Vol. 56 (2025), [SSRN 5186126](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5186126). The Compass Diversified Holdings comment letter (August 2019) and the SEC's September 2023 sample comment letter on XBRL disclosures are published on SEC.gov.

All financial figures cited in this article reference Microsoft Corporation's FY2017 Annual Report (10-K filed August 2, 2017, period ending June 30, 2017). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/ix?doc=/Archives/edgar/data/789019/000156459017014900/msft-10k_20170630.htm).

---

## Blog: XBRL Tags for Fundamental Investors: The Essential Reference
source: https://www.geminiq.com/blog/xbrl-tags-fundamental-investors-guide

### XBRL Tags for Fundamental Investors: The Essential Reference
XBRL tags are the machine-readable identifiers behind every number in an SEC filing. These 20 tags across the income statement, balance sheet, and cash flow statement determine the accuracy of virtually every financial metric, ratio, and screener result you use.

The number on your research platform carries a label: "Revenue," "Long-Term Debt," "Operating Cash Flow." The label matches what you see in the 10-K. But the label is not the data — the XBRL tag is the data. When the SEC mandated XBRL tagging across all public company filings, it created something more useful than searchable financial data: a verifiable identity for every number in every 10-K and 10-Q. `Revenues` is not just a heading. It is a concept defined by the FASB taxonomy, attached to an exact value, for an exact period, for an exact filing entity. When a financial platform replaces that tag with a proprietary label during data normalization, the number may survive — but the verifiable link to the filing does not.

Twenty XBRL tags, spread across the income statement, balance sheet, and cash flow statement, determine the accuracy of virtually every metric, ratio, and screener result that fundamental investors depend on. This is a practical reference for those tags: what each one represents, where normalization most frequently changes the value under the label, and how each tag connects to the financial metrics built from it. For a broader explanation of what XBRL is and how the SEC mandate works, see [What Is XBRL? How SEC Tagging Affects Your Investment Data](/blog/what-is-xbrl).

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---

## Table of Contents

- [What Is an XBRL Tag?](#what-is-an-xbrl-tag)
- [What Is the XBRL Taxonomy?](#what-is-the-xbrl-taxonomy)
- [Querying US-GAAP Elements](#querying-us-gaap-elements)
- [Income Statement Tags](#income-statement-tags)
- [Balance Sheet Tags](#balance-sheet-tags)
- [Cash Flow Statement Tags](#cash-flow-statement-tags)
- [Extension Tags: What Company-Specific Labels Reveal](#extension-tags)
- [The XBRL-to-Metrics Chain](#the-xbrl-to-metrics-chain)
- [Frequently Asked Questions](#frequently-asked-questions)

---

## What Is an XBRL Tag?

An XBRL tag is a machine-readable identifier that binds a single reported number to a standardized accounting concept, a specific reporting period, and a specific filing entity. Every tagged fact has three parts that matter: the **element** — the concept itself, such as `NetIncomeLoss` — the **value**, the number as reported, and the **context**, which fixes the entity and the period the value belongs to. The label you see on a research platform ("Net Income") is a human-readable presentation of the element; the tag is the element underneath it.

The distinction is not academic. Two companies can each report a line called "Total Revenue," but one may tag it `Revenues` while the other uses `RevenueFromContractWithCustomerExcludingAssessedTax` — same label, different tag, different concept identity. The tag is what makes a number verifiable: it resolves to a formal definition in a published taxonomy, so any value can be traced back to its exact meaning in the filing. When a platform discards the tag and keeps only the label, the number survives but its provenance does not — which is the failure mode documented tag-by-tag in the [20-tag reference below](#income-statement-tags).

Throughout this guide each tag is written in its short element form — `Revenues`, `GrossProfit`, `OperatingIncomeLoss` — but every one carries a namespace prefix identifying the taxonomy that defines it, covered in the next two sections.

---

## What Is the XBRL Taxonomy?

An XBRL taxonomy is the dictionary of elements a filer is permitted to use — the complete set of defined concepts, their data types, their labels, and their relationships to one another. For US public companies the governing dictionary is the **US GAAP Financial Reporting Taxonomy**, maintained by the FASB and revised annually; the SEC specifies which taxonomy version is acceptable for a given filing year. It holds roughly **17,000 elements**, though only a few hundred appear in any typical filing.

The taxonomy is what gives a tag its meaning. `us-gaap:OperatingIncomeLoss` is not a free-floating string — it is a defined entry with a balance type (debit or credit), a period type (duration or instant), a documentation string, and calculation relationships to other elements. When a company reports a concept the taxonomy already defines, it uses that standard element; when it reports something the taxonomy does not anticipate, it creates an [extension tag](#extension-tags) instead. Standard elements and extensions are two halves of the same system — the dictionary, and the exceptions the dictionary can't hold.

Two taxonomies actually appear in every filing: the **US GAAP** taxonomy for the financial statements, and the **DEI** (Document and Entity Information) taxonomy for filing metadata such as entity name, CIK, and fiscal period. For the broader history of how the SEC mandate was built on top of these taxonomies, see [What Is XBRL?](/blog/what-is-xbrl).

---

## Querying US-GAAP Elements

Every standard tag in this guide belongs to the `us-gaap` namespace, written formally as `us-gaap:` followed by the element name in PascalCase: `us-gaap:Revenues`, `us-gaap:NetIncomeLoss`, `us-gaap:CashAndCashEquivalentsAtCarryingValue`. The prefix signals that the element is defined in the US GAAP taxonomy rather than in the DEI taxonomy or in a company's own extension namespace. Three tools let you look up and query these elements directly against the source:

- **FASB US GAAP Taxonomy viewer** — the authoritative reference for an element's definition, balance type, period type, and documentation. Use it to confirm what a `us-gaap:` element actually means before trusting any platform's label for it.
- **SEC Inline XBRL viewer** — open a 10-K or 10-Q from the [EDGAR](https://www.sec.gov/search-filings) filing index and click any value; the viewer reveals the exact `us-gaap:` element, the as-filed value, and the period context.
- **SEC EDGAR XBRL APIs** — for querying an element programmatically. The `companyconcept` endpoint returns every value one filer reported for a single element:

  `https://data.sec.gov/api/xbrl/companyconcept/CIK0000320193/us-gaap/Revenues.json`

  returns all `us-gaap:Revenues` facts for [Apple](/stocks/AAPL), whose CIK is zero-padded to ten digits. The `frames` endpoint flips the query — one element across every filer for a single period:

  `https://data.sec.gov/api/xbrl/frames/us-gaap/Revenues/USD/CY2024.json`

  Both resolve to the identical tags catalogued in this guide, which is the point: any `us-gaap:` element query you run against the SEC's own API can be reconciled against the metric GeminIQ builds from that same tag — the audit trail runs end to end.

---

## Income Statement Tags

Five tags cover the income statement figures that matter most to fundamental analysis. These appear straightforward — and for most companies in most periods they are. The problems emerge when platforms make aggregation decisions that aren't visible in the label.

### What is `Revenues`?

`Revenues` is the primary revenue tag in the US GAAP XBRL taxonomy, representing total net revenues as the company reported them on its income statement. For companies that adopted ASC 606 between 2018 and 2020, the equivalent tag is often `RevenueFromContractWithCustomerExcludingAssessedTax`. [Apple](/stocks/AAPL) uses `Revenues` — its FY2025 value under this tag is **$416.2 billion**. The two tags represent the same economic concept but carry different identifiers in the XBRL taxonomy.

**When it breaks:** A platform that treats `Revenues` and `RevenueFromContractWithCustomerExcludingAssessedTax` as interchangeable without auditing the transition period can create false discontinuities in historical revenue data — showing an apparent step-change that reflects a tag reclassification, not a real business change. Revenue-based metrics including GeminIQ's [Revenue Growth](/metrics/growth-metrics/revenue-growth) are directly affected by which tag the platform treats as the authoritative source across periods.

### What is `GrossProfit`?

`GrossProfit` is revenue minus cost of goods sold or cost of revenue — the amount remaining before operating expenses. It is one of the cleaner income statement tags: most companies report a standalone gross profit line that maps directly to this identifier. [Apple's](/stocks/AAPL) FY2025 `GrossProfit` is **$195.2 billion**, producing a gross margin of **46.9%**. For companies that file a standalone gross profit line — the majority of filers — the tag maps cleanly to the filing with no normalization required.

**When it breaks:** Companies in financial services and certain industrials do not always report a standalone gross profit line. Platforms that estimate or impute gross profit for these companies produce a figure that carries no corresponding XBRL tag and cannot be traced to any line item in the filing. GeminIQ's [Gross Profit Margin](/metrics/margin-metrics/gross-profit-margin) derives from `GrossProfit` where the tag is present in the filing.

### What is `OperatingIncomeLoss`?

`OperatingIncomeLoss` is operating income or loss — revenue minus all operating expenses including cost of goods sold, R&D, SG&A, depreciation, and amortization, but before interest expense and taxes. It is the primary earnings figure used in EV/EBIT and EV/EBITDA valuation and the basis for operating margin analysis.

**When it breaks:** This is among the most frequently adjusted income statement tags in normalized data. Platforms vary in their treatment of restructuring charges, impairment losses, and litigation settlements — some include them in operating income, others exclude them into a proprietary "adjusted" figure under the same label. When a platform presents an adjusted operating income number without disclosing which line items it removed, the figure is analytically useful only in relation to the platform's own prior periods, not in relation to the filing. GeminIQ's [Operating Profit Margin](/metrics/margin-metrics/operating-profit-margin) uses the as-filed `OperatingIncomeLoss` without adjustments.

### What is `NetIncomeLoss`?

`NetIncomeLoss` is bottom-line net income or net loss — what remains after all revenues, costs, interest, taxes, and non-controlling interest deductions. It is the most widely cited income statement figure and the numerator in profitability and return metrics across the board.

**When it breaks:** The tag itself is rarely reclassified, but the figure can differ between platforms for two reasons: discontinued operations handling and the treatment of net income attributable to non-controlling interests. Some platforms report the consolidated figure including minority interest; others report only the portion attributable to common shareholders. For conglomerates with significant minority-owned subsidiaries, the difference can be material across every downstream ratio. GeminIQ's [Net Profit Margin](/metrics/margin-metrics/net-profit-margin), [Net Income Growth](/metrics/growth-metrics/net-income-growth), and [Return on Equity (ROE)](/metrics/returns-and-profitability/return-on-equity) all use `NetIncomeLoss` as the primary input.

### What is `EarningsPerShareDiluted`?

`EarningsPerShareDiluted` is the diluted earnings per share figure as reported — net income divided by the weighted average diluted share count for the period. It is the most-quoted earnings metric in financial media and the comparison point in P/E ratio analysis.

**When it breaks:** Platforms that surface adjusted or non-GAAP earnings per share figures — rather than the as-filed `EarningsPerShareDiluted` — can show materially higher EPS values, particularly for technology and pharmaceutical companies where GAAP earnings are reduced by large stock-based compensation charges. The as-filed diluted EPS is what shareholders actually earned under GAAP, not what management chose to report as "adjusted." GeminIQ's [Diluted Earnings Per Share](/metrics/per-share-metrics/diluted-earnings-per-share) and [Earnings Per Share Growth](/metrics/growth-metrics/earnings-per-share-growth) use the as-filed `EarningsPerShareDiluted` value.

---

## Balance Sheet Tags

The balance sheet carries more XBRL complexity than the income statement. Companies have significant latitude in how they structure and label balance sheet items, which means the taxonomy must accommodate a wide range of reporting choices. These eight tags create the most analytical confusion when platforms fold them into generic categories.

### What is `CashAndCashEquivalentsAtCarryingValue`?

`CashAndCashEquivalentsAtCarryingValue` is cash and cash equivalents as reported on the balance sheet — the most liquid asset class, including currency, demand deposits, and instruments with original maturities of three months or less. The tag is universally used and rarely reclassified.

**When it breaks:** Some platforms add `ShortTermInvestments` to `CashAndCashEquivalentsAtCarryingValue` and present the combined figure as "Cash & Equivalents," overstating the immediately liquid cash position. For liquidity metrics that require the strictest cash definition, this consolidation can be significant. GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) and [Cash Ratio](/metrics/liquidity-ratios/cash-ratio) use `CashAndCashEquivalentsAtCarryingValue` as reported, without adding short-term investment balances.

### What is `ShortTermInvestments`?

`ShortTermInvestments` represents marketable securities and short-term instruments with maturities between three months and one year. For cash-rich companies, this balance sheet line can carry a substantial balance — financial flexibility that is real but meaningfully less liquid than cash.

**When it breaks:** Many platforms aggregate `CashAndCashEquivalentsAtCarryingValue` and `ShortTermInvestments` into a single "Cash & Short-Term Investments" line without labeling the consolidation. The merger is economically defensible as a measure of total liquidity, but it eliminates the distinction between cash available immediately and investments redeemable within the year. Liquidity metrics requiring the most restrictive cash definition become unreliable when the two are merged.

### What is `CommercialPaper`?

`CommercialPaper` is the balance sheet tag for outstanding commercial paper — short-term, unsecured debt obligations typically issued at a discount for maturities up to 270 days. Companies with strong credit ratings use commercial paper as flexible, low-cost short-term financing.

**When it breaks:** Platforms routinely merge `CommercialPaper` with `DebtCurrent` (current maturities of long-term debt) into a single "Short-Term Debt" category. The consolidated figure looks like one instrument, but commercial paper and a current term loan carry completely different refinancing profiles — one rolls continuously in the commercial paper market, the other is a fixed-maturity obligation. [Apple](/stocks/AAPL) reports `CommercialPaper` and current `TermDebt` as separate line items in its balance sheet; platforms that merge them obscure which portion of the short-term debt burden is rolling market exposure versus a discrete maturity event. This tag feeds GeminIQ's [Net Debt](/metrics/calculated-values/net-debt) and [Invested Capital](/metrics/calculated-values/invested-capital) calculations.

### What is `LongTermDebtNoncurrent`?

`LongTermDebtNoncurrent` represents the non-current portion of long-term debt — principal obligations due more than one year from the balance sheet date. It is the primary tag for leverage analysis and feeds directly into debt-to-equity, debt-to-EBITDA, and net debt calculations.

**When it breaks:** The problem arises at the intersection of this tag and operating lease liabilities. Following FASB ASC 842 in 2019, companies were required to recognize operating lease obligations on the balance sheet under dedicated tags (`OperatingLeaseLiabilityNoncurrent`). Platforms that add lease liabilities to `LongTermDebtNoncurrent` before you see the number produce an overstated debt figure — one that mixes contractual lease commitments with traditional financial borrowings. GeminIQ's [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) and [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda) use the as-filed `LongTermDebtNoncurrent` without folding in lease obligations.

### What is `OperatingLeaseRightOfUseAsset`?

`OperatingLeaseRightOfUseAsset` is the balance sheet asset representing the lessee's right to use an underlying asset for the duration of the lease term. It was created as a mandatory tag following FASB ASC 842, which took effect for most public companies beginning in FY2019. Before ASC 842, operating leases were off-balance-sheet obligations with no corresponding asset entry.

**When it breaks:** Because this tag was created in 2019, it has no pre-2019 counterpart in any filing. Platforms that impute operating lease values for pre-2019 periods produce a figure with no XBRL source in the filing. More importantly, the introduction of ROU assets in 2019 inflated reported total assets for companies with large operating lease footprints — particularly retailers, airlines, and restaurant chains — creating a structural shift in asset-based ratios that is not real economic change. GeminIQ's [Asset Turnover](/metrics/efficiency-and-turnover-ratios/asset-turnover) uses total assets as reported in each period without attempting to normalize across the ASC 842 transition boundary.

### What is `OperatingLeaseLiabilityNoncurrent`?

`OperatingLeaseLiabilityNoncurrent` is the non-current portion of operating lease obligations — the present value of future lease payments due beyond 12 months from the balance sheet date, also introduced as a mandatory tag under ASC 842 in 2019.

**When it breaks:** The most common normalization error with this tag is adding it to `LongTermDebtNoncurrent` to create a combined "Long-Term Debt" or "Total Non-Current Liabilities" figure. The consequence is material for companies with large lease footprints. The **$11.6 billion** documented discrepancy in [Apple's](/stocks/AAPL) "Other Non-Current Liabilities" balance — covered in detail in [Third-Party Financial Data Problems: What Gets Lost Before It Reaches You](/blog/third-party-financial-data-problems) — traces directly to how capital lease obligations were reclassified out of one balance sheet line and absorbed into another, with the original label kept intact.

### What is `OtherLiabilitiesNoncurrent`?

`OtherLiabilitiesNoncurrent` is the catch-all tag for non-current liabilities that don't fit neatly into more specific categories — deferred tax liabilities, pension obligations, unearned revenue beyond 12 months, and certain tax-related reserves.

**When it breaks:** This is the tag most likely to carry a material discrepancy when platform data is compared to the actual filing. Because it is a residual category, any normalization decision that moves an obligation into or out of it changes the as-filed value under the same label. [Apple's](/stocks/AAPL) documented example: the platform showed **$29.9 billion** under "Other Non-Current Liabilities" while the 10-K showed **$41.5 billion** — a **$11.6 billion** gap attributable to capital lease reclassification that left the label unchanged. The label looked right. The number was not.

### What is `RetainedEarningsAccumulatedDeficit`?

`RetainedEarningsAccumulatedDeficit` is the cumulative total of all net income and losses since the company's founding, minus all dividends paid. A positive value represents retained earnings; a negative value represents an accumulated deficit. For companies with aggressive buyback programs, this figure is often deeply negative even as the company generates substantial annual profits — because accumulated repurchases have exceeded cumulative retained earnings over the company's history.

**When it breaks:** The tag itself is rarely reclassified, but its interpretation requires context that normalized platforms don't always surface. Presented without the buyback history that explains it, the figure can signal structural impairment where none exists. GeminIQ's [Retained Earnings Growth](/metrics/growth-metrics/retained-earnings-growth) and [Retained Earnings to Equity](/metrics/remaining-metrics/retained-earnings-to-equity) track this figure across periods directly from the filing.

---

## Cash Flow Statement Tags

The cash flow statement is where XBRL fidelity provides the most analytical lift — and where normalization causes the most structural damage. The income statement benefits from clear GAAP definitions; the cash flow statement uses a format that makes merging adjacent tags look like a reasonable simplification. It is not.

### What is `NetCashProvidedByUsedInOperatingActivities`?

`NetCashProvidedByUsedInOperatingActivities` is total operating cash flow — the net cash generated or consumed by core business operations during the period, calculated by adjusting net income for non-cash items and working capital changes. It is the starting point for free cash flow analysis and the most reliable single-line test of whether reported earnings translate into actual cash.

**When it breaks:** The total is rarely reclassified directly, but the indirect method cash flow statement builds to this figure through a series of adjustments. If a platform reclassifies an operating adjustment into investing or financing activities — or vice versa — the total operating cash flow changes without the label changing. The disclosed number looks right; the component breakdown diverges from the filing. GeminIQ's [Free Cash Flow](/metrics/calculated-values/free-cash-flow) uses `NetCashProvidedByUsedInOperatingActivities` directly from the filing as the first input.

### What is `PaymentsToAcquirePropertyPlantAndEquipment`?

`PaymentsToAcquirePropertyPlantAndEquipment` is cash paid to acquire or improve physical assets — what most investors call capital expenditures. It appears in the investing activities section of the cash flow statement and is the second input to free cash flow: Free Cash Flow = `NetCashProvidedByUsedInOperatingActivities` − `PaymentsToAcquirePropertyPlantAndEquipment`.

**When it breaks:** Platforms sometimes combine this tag with other investing outflows — capitalized software development, acquisition of intangible assets, or certain lease payments — into a broader capital expenditure figure that exceeds the as-filed `PaymentsToAcquirePropertyPlantAndEquipment`. The combined figure produces a lower free cash flow estimate that is not traceable to any single line in the filing. For companies that capitalize significant software development, the difference can be substantial. GeminIQ's [Free Cash Flow](/metrics/calculated-values/free-cash-flow) and [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) use `PaymentsToAcquirePropertyPlantAndEquipment` as reported.

### What is `ShareBasedCompensation`?

`ShareBasedCompensation` is the non-cash stock-based compensation charge appearing as a positive add-back in the operating activities section of the cash flow statement. It represents total equity-based compensation expense recognized during the period — options, RSUs, and employee stock purchase plans combined — and is the cleanest verifiable source for total SBC across any company.

**When it breaks:** Platforms that reconstruct operating cash flow from income statement line items rather than reading the as-filed cash flow statement can miss non-standard compensation structures. More broadly, this tag matters because SBC is embedded across cost of revenue, R&D, and SG&A on the income statement — there is no standalone income statement line for it. The cash flow statement add-back is the only place where the total appears as a single figure. [Amazon's](/stocks/AMZN) `ShareBasedCompensation` reached **$19.5 billion** in its most recently filed annual report — a figure that is invisible as a standalone number anywhere on the income statement. GeminIQ's [Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) and [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) source directly from this tag.

### What is `PaymentsForRepurchaseOfCommonStock`?

`PaymentsForRepurchaseOfCommonStock` is the cash paid to repurchase common shares during the period, appearing as a negative item in the financing activities section of the cash flow statement. It is the XBRL identifier for share buybacks as filed.

**When it breaks:** Many platforms combine `PaymentsForRepurchaseOfCommonStock` with `PaymentRelatedToTaxWithholdingForShareBasedCompensation` into a single "[share repurchases](/blog/do-buybacks-reduce-share-count)" or "buybacks" figure. The two items are related — both reduce the share count — but they represent different decisions. [Apple](/stocks/AAPL) consistently files both as separate cash flow line items. Merging them overstates the buyback program relative to what management actually spent on open-market repurchases and confuses any capital allocation analysis that depends on the distinction.

### What is `PaymentRelatedToTaxWithholdingForShareBasedCompensation`?

`PaymentRelatedToTaxWithholdingForShareBasedCompensation` represents cash paid to tax authorities when vested RSUs are net-settled — the company withholds shares to cover the employee's tax obligation and remits the corresponding cash to the IRS. It appears in financing activities and is economically distinct from buybacks: the company is satisfying a mandatory tax obligation, not executing a capital allocation decision.

**When it breaks:** As noted above, this tag is routinely merged with `PaymentsForRepurchaseOfCommonStock`. For large technology companies with substantial RSU programs, the figure can represent billions of dollars annually. Including it in reported "buybacks" conflates a discretionary capital return decision with an involuntary tax obligation. GeminIQ's [Financial Statements](/features#financial-statements) display both tags as separate line items, exactly as they appear in the filing.

### What is `PaymentsOfDividendsCommonStock`?

`PaymentsOfDividendsCommonStock` is the cash paid as dividends on common stock during the period, as reported in the financing activities section. It is the direct XBRL source for dividend analysis across all dividend-based metrics.

**When it breaks:** The tag itself is stable, but normalization risk emerges in how platforms treat special dividends versus regular dividends. When a company pays a large special dividend, some platforms include it in dividend-per-share and payout ratio calculations; others exclude it in favor of "regular" dividends. Both approaches deviate from the as-filed figure, which includes all dividends paid regardless of management's characterization. GeminIQ's [Dividends Per Share](/metrics/per-share-metrics/dividends-per-share), [Dividend Yield](/metrics/valuation-metrics/dividend-yield), [Payout Ratio](/metrics/returns-and-profitability/payout-ratio), and [Dividends Paid Growth](/metrics/growth-metrics/dividends-paid-growth) all source from this tag as reported.

### What is `DepreciationDepletionAndAmortization`?

`DepreciationDepletionAndAmortization` is the total non-cash charge for asset depreciation and amortization during the period, appearing as a positive add-back in the operating activities section of the indirect method cash flow statement. It is the primary XBRL source for the "DA" component of EBITDA — and therefore a critical input to every EBITDA-based valuation multiple and leverage ratio.

**When it breaks:** EBITDA has no single XBRL tag because it is not a GAAP measure. Platforms construct it differently: some use `DepreciationDepletionAndAmortization` from the cash flow statement; others pull depreciation from the income statement or notes, where it may be disclosed across multiple components. The choice changes the EBITDA denominator and therefore every multiple and coverage ratio built on it. GeminIQ's [EV/EBITDA](/metrics/valuation-metrics/ev-ebitda), [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), and [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) all use `DepreciationDepletionAndAmortization` from the as-filed cash flow statement as the DA source.

---

## Extension Tags

The 20 tags above are all drawn from the standard US GAAP XBRL taxonomy — concepts defined by the FASB that apply across thousands of filers. But the taxonomy cannot anticipate every business model or every disclosure a company might need to make. When a company has a financial concept with no standard tag equivalent, it creates an extension tag: a custom identifier that carries the company's own label and links to a concept definition in the company's own filing.

Extension tags are where normalized financial data loses the most information. A generic aggregator template has no bucket for a line item that only one company reports. When [Apple](/stocks/AAPL) files its balance sheet showing **$33.2 billion** in `NontradereceivablesCurrent` — Vendor Non-Trade Receivables, a receivable from component manufacturers with no parallel in any other company's reporting structure — that tag has no home in a standard template. It gets folded into "Other Current Assets," losing its identity and its economic meaning in the process.

Extension tags are a signal in themselves. Companies with many extension tags have business models that don't compress cleanly into industry-standard reporting templates. Normalized data on these companies carries the highest risk of material discrepancy, because the most information-rich and company-specific line items are precisely the ones that don't fit the mold. GeminIQ's [Financial Statements](/features#financial-statements) preserve every extension tag as filed — displayed with the company's own label rather than remapped into a generic residual category. The **$33.2 billion** in Vendor Non-Trade Receivables appears as its own line in [Apple's](/stocks/AAPL) balance sheet on GeminIQ, not as an unmarked increment inside "Other Current Assets."

---

## The XBRL-to-Metrics Chain

The 20 tags above are not just reference material. They are the literal inputs to GeminIQ's [Calculated Metrics](/features#calculated-metrics) — the pre-computed ratios, profitability measures, and growth rates derived directly from XBRL-tagged filing data. Understanding which tag feeds which metric makes any calculated output independently auditable.

[Free Cash Flow](/metrics/calculated-values/free-cash-flow) is `NetCashProvidedByUsedInOperatingActivities` minus `PaymentsToAcquirePropertyPlantAndEquipment`. Both inputs trace to specific lines in the cash flow statement. If GeminIQ's Free Cash Flow figure diverges from a platform's, one of those two tags has been altered.

[Net Debt](/metrics/calculated-values/net-debt) is total financial debt — built from `CommercialPaper`, current `DebtCurrent`, and `LongTermDebtNoncurrent` — minus `CashAndCashEquivalentsAtCarryingValue`. Platforms that add operating lease liabilities to the debt inputs inflate Net Debt without changing the label, and the error flows through every leverage ratio that uses it.

[Return on Invested Capital (ROIC)](/metrics/returns-and-profitability/return-on-invested-capital) requires Net Operating Profit After Tax divided by Invested Capital. Invested Capital itself aggregates total equity, financial debt, and excess cash — drawing on several of the balance sheet tags above. A reclassification in `CommercialPaper` or `LongTermDebtNoncurrent` ripples directly through the ROIC denominator without touching the ROIC label on screen.

[Stock-Based Compensation](/metrics/calculated-values/stock-based-compensation) sources from `ShareBasedCompensation` in the cash flow statement. [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) divides that figure by `Revenues`. Both links are direct and traceable — which is why GeminIQ's SBC figures for companies like [Amazon](/stocks/AMZN) align with the cash flow statement rather than with aggregated income statement estimates.

Every EBITDA-based metric — [EV/EBITDA](/metrics/valuation-metrics/ev-ebitda), [Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/debt-to-ebitda), [Net Debt-to-EBITDA](/metrics/leverage-and-debt-ratios/net-debt-to-ebitda) — depends on `DepreciationDepletionAndAmortization` for the denominator, making that single sourcing decision the most consequential variable in any EBITDA-based comparison.

This is the practical consequence of XBRL fidelity: when data starts at the tag level, every calculated metric is independently auditable — you can check the output, trace the formula, and verify each input against a specific XBRL tag in a specific SEC filing. When data starts at a normalized template, the audit trail ends at the platform's proprietary data layer, and discrepancies become untraceable by design.

---

## Frequently Asked Questions

### How many XBRL tags are in the US GAAP taxonomy?

The US GAAP XBRL taxonomy maintained by the FASB contains approximately 17,000 standard concept elements. Of those, only a few hundred see widespread use across major public company filings. The 20 tags in this guide represent the subset that most directly determines the accuracy of calculated metrics and fundamental ratios in equity analysis.

### Do all companies use the same XBRL tags?

Standard taxonomy tags are used by any company reporting the corresponding concept. If a company reports gross profit, it uses `GrossProfit`. If it reports commercial paper, it uses `CommercialPaper`. The tag is determined by the concept being disclosed, not by the company disclosing it. Where companies diverge is in their use of extension tags — custom identifiers for line items that have no standard taxonomy equivalent.

### What is an extension tag and why does it matter?

An extension tag is a custom XBRL concept created by a company for a financial statement line item that has no appropriate standard taxonomy equivalent. Extensions are documented in the company's filing and carry the company's own label and concept definition. They are how the XBRL system handles company-specific reporting structures without forcing every filer into generic buckets — and they are the line items most likely to disappear during third-party normalization.

### Does GeminIQ preserve extension tags alongside standard taxonomy tags?

Yes. GeminIQ's [Financial Statements](/features#financial-statements) display financial data exactly as filed — preserving both standard taxonomy tags and company-specific extension tags. Every line item a company reports appears in GeminIQ with its original label, including items that would otherwise be consolidated into generic residual categories on normalized platforms.

### How does XBRL tag fidelity affect screener results?

Every screener filter built on a calculated metric — ROIC, free cash flow yield, net debt, gross margin — traces back to the XBRL tags that fed the calculation. If a source tag was reclassified or merged during normalization, the metric value differs from what the filing supports, and two screeners with identical filter thresholds but different source data produce different result sets. For more on how normalization alters the data inputs that screeners depend on, see [Financial Data Normalization Explained](/blog/financial-data-normalization-explained).

### How do I verify a specific XBRL tag value against the original SEC filing?

Navigate to [SEC EDGAR](https://www.sec.gov/search-filings), find the company's 10-K or 10-Q, and open the Inline XBRL viewer from the filing index page. Clicking any value in the viewer displays the exact XBRL tag name, the as-filed value, and the period context. For a step-by-step walkthrough of this process — including how to diagnose what type of discrepancy you're looking at — see [Verify Financial Data Against the SEC Filing](/blog/verify-financial-data-against-sec-filing).

---

## Related Reading

- [What Is XBRL? How SEC Tagging Affects Your Investment Data](/blog/what-is-xbrl) — a full explanation of the XBRL system, the taxonomy, and why most platforms discard the tagging layer during normalization
- [Financial Data Normalization Explained](/blog/financial-data-normalization-explained) — the four types of normalization decisions that change data before it reaches you, and how to identify each
- [Verify Financial Data Against the SEC Filing](/blog/verify-financial-data-against-sec-filing) — a four-step workflow for tracing any discrepancy back to the original XBRL tag in the filing
- [Third-Party Financial Data Problems: What Gets Lost Before It Reaches You](/blog/third-party-financial-data-problems) — documented discrepancy examples including the **$11.6 billion** Apple balance sheet gap
- [What Investors Miss in SEC Filings](/blog/what-investors-miss-in-sec-filings) — the data that lives in filings but disappears in any normalized dataset

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=xbrl-tags-fundamental-investors-guide)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures cited in this article reference Apple Inc.'s FY2025 10-K (filed October 31, 2025) and Q1 FY2026 10-Q (filed January 30, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193).<br>
All financial figures cited in this article reference Amazon.com, Inc.'s Q1 FY2026 10-Q (filed April 30, 2026, period ending March 31, 2026). All SEC filings are publicly available at [SEC EDGAR](https://www.sec.gov/Archives/edgar/data/1018724/000101872426000014/amzn-20260331.htm).</sup>

---

## Blog: YCharts Alternative: Filing-Sourced Financial Data
source: https://www.geminiq.com/blog/ycharts-alternative-sec-data

### YCharts Alternative: Filing-Sourced Financial Data
A YCharts alternative for filing-level research. YCharts is built for advisor client communication at $3,600 to $6,000 per seat per year; this post explains why presentation-grade data and audit-grade data are different products.

YCharts is one of the best-executed products in wealth management technology, and understanding why requires being precise about who it serves. The platform is built for registered investment advisors, broker-dealers, and asset managers — professionals whose work product is a proposal, a model portfolio comparison, or a branded report handed to a client. Standard runs **$300** per user per month billed annually and Professional runs **$500**, which works out to **$3,600** and **$6,000** a year per seat, with enterprise pricing by quote.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=ycharts-alternative-sec-data)**

That pricing tells you exactly what the product is. Nobody pays six thousand dollars a seat for charts. They pay it for the ability to put a chart in front of a client and have the conversation go well.

Which means the question for a fundamental investor evaluating YCharts alternatives is not whether the platform is good at its job. It is whether its job is your job.

## Table of Contents

- [The Deliverable Defines the Data](#the-deliverable-defines-the-data)
- [Presentation-Grade Versus Audit-Grade](#presentation-grade-versus-audit-grade)
- [Where the Numbers Come From](#where-the-numbers-come-from)
- [Time Series Is Not the Same as Filing History](#time-series-is-not-the-same-as-filing-history)
- [What Changes When the Filing Is the Source](#what-changes-when-the-filing-is-the-source)
- [Choosing on Workflow, Not Features](#choosing-on-workflow-not-features)
- [Frequently Asked Questions](#frequently-asked-questions)

## The Deliverable Defines the Data

Every research platform is shaped by what its users produce at the end of the session.

For an advisor using YCharts, the output is client-facing: a proposal comparing a prospect's current holdings to a recommended model, a fund comparison table, a dashboard for the investment committee, a branded PDF that goes into a meeting. The platform's feature set follows directly — model portfolios, proposal generation, firm branding, PDF and PowerPoint export, CRM integration, and connections into financial planning software so client holdings flow in without manual entry.

For a fundamental analyst, the output is a decision, and often one that has to survive a partner asking where a number came from.

Those two deliverables place opposite demands on the underlying data. A client-facing chart needs consistency, clean formatting, and comparability across funds and securities that report differently. An investment memo needs the number to match the document it came from. A platform can optimize for one without failing at the other, but it will always be better at the one it was built for.

## Presentation-Grade Versus Audit-Grade

The distinction is not about quality. It is about what happens when the number is questioned.

Presentation-grade data is built to be shown. It has to render cleanly across thousands of securities, hold up in a chart with a consistent axis, and let a stock, a fund, and an economic indicator sit on the same page. Achieving that requires a standardized layer — a template every security is mapped into so that a comparison is possible at all.

Audit-grade data is built to be checked. It has to answer, for any figure on screen, which reported fact produced it and whether that value matches the filing.

The tension shows up in the specific places standardization touches. Two distinct cash outflows can become one row because the template has one row where the filing has two. A single filed liability caption can be split so a component is separately trackable. A label can survive while its contents change, which is the version that costs the most, because the screen gives no signal that anything was decided.

For a proposal, none of that matters — the client is not reconciling the chart to a 10-K footnote. For a memo, it is the whole problem.

## Where the Numbers Come From

YCharts aggregates from institutional providers rather than extracting from primary filings. The company has described sourcing equity data from S&P Global, with fund data drawn from Morningstar, and it layers additional feeds for economic indicators and other datasets. The library runs to thousands of metrics with decades of history.

That is the correct architecture for an advisor platform. Multi-asset breadth across stocks, funds, ETFs, and macro indicators is not achievable by parsing 10-Ks, because most of what an advisor charts is not in a 10-K at all. Fund data, economic series, and index history have no SEC filing behind them.

But it does mean the equity fundamentals in YCharts arrive already mapped. Whatever standardization decisions were made upstream are present, unchanged, because YCharts did not make them and cannot expose them. That is not a knock on YCharts specifically — it is a property shared by every platform that licenses rather than extracts.

## Time Series Is Not the Same as Filing History

YCharts is best known for time-series analysis, and it is very strong there. Charting a company's margin, valuation multiple, or return metric across twenty years is the feature that sells the platform.

There is a subtle difference between a long time series and a long filing history, and it matters more than it sounds.

A time series is a sequence of values for a metric. A filing history is a sequence of documents, each with its own line item structure, its own footnotes, and its own restatements of what came before. When a company changes how it reports a segment, retires a caption, or restates a prior year, the time series absorbs that quietly — the chart still draws a smooth line. The filing history shows the seam.

Those seams are frequently where the analysis is. A metric that looks continuous across a reporting change is a metric that has hidden the change, and a smooth line through a restatement is a smooth line that is partly fiction.

## What Changes When the Filing Is the Source

GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own line item structure, and keeps the [XBRL tag](/blog/xbrl-tags-fundamental-investors-guide) attached to each value. There is no mapping layer between the filing and the display, so a figure that looks wrong sends you to the filing rather than to a methodology page.

[Financial Statements](/features#financial-statements) show a company's own captions quarter by quarter and year by year, seams included. [Custom Tables](/features#custom-tables) build views from specific reported items instead of template rows. [Visualizations](/features#visualizations) chart the reported structure over time. [Calculated Metrics](/features#calculated-metrics) such as [Return on Invested Capital](/metrics/returns-and-profitability/return-on-invested-capital) and [Free Cash Flow Yield](/metrics/valuation-metrics/free-cash-flow-yield) are computed from as-filed inputs, so a metric can be audited against the numbers behind it.

The documented version of this is a single line item. [Apple's](/stocks/AAPL) FY2025 10-K reports Other non-current liabilities at **$41,549M**. A widely used retail aggregator displays **$29,946M** under the identical label, having subtracted **$11,603M** of capital lease obligations while leaving the caption unchanged.

Now chart it. The series renders cleanly, holds a consistent level, and sits **$11.6 billion** below the filed value at every point on the axis. Nothing in the chart discloses the subtraction, because a time series inherits its level from whatever definition produced it and then draws a smooth line through the result. A leverage ratio built on that series is wrong by the magnitude of the adjustment, and the chart gives no way to know.

That case is documented against a retail platform rather than an advisor product, and it is the mechanism rather than the vendor that matters. Detail is in [third-party financial data problems](/blog/third-party-financial-data-problems).

The scope is narrower on purpose. No funds, no ETFs, no macro series, no proposals, no client branding. US public company fundamentals from EDGAR is the entire universe, and covering less is what makes the traceability work.

## Choosing on Workflow, Not Features

Feature grids will not settle this, because the two products barely overlap in what they are optimizing.

If you manage client assets and your day ends with a document someone else reads, YCharts is built for you and a filing archive is not a substitute — there is no version of EDGAR that produces a branded proposal. Advisors evaluating YCharts alternatives on price alone usually discover that the cheaper tool cannot do the client-facing half of the job, which was the expensive half.

If your day ends with a position and a thesis you have to defend, the calculus inverts. Presentation tooling adds nothing, and standardized inputs quietly add risk to every number downstream of them. What matters then is whether the figure on screen matches the document the company signed.

The most expensive research mistake is not paying for the wrong tool. It is building a thesis on a chart that was drawn to be shown rather than to be checked.

For the feature-level breakdown, see the [GeminIQ vs. YCharts comparison](/competitor-comparison/ycharts). The same standardization question sits under the [Capital IQ alternatives](/blog/capital-iq-alternative-sec-data) decision at the institutional tier. For the mechanics of what happens between EDGAR and a screen, [how financial data reaches investors](/blog/how-financial-data-reaches-investors) walks the chain.

## Frequently Asked Questions

### What are the best YCharts alternatives?

Which alternative fits depends on which half of YCharts you need. For advisor client communication — proposals, model portfolio comparisons, branded reports — the substitutes are other wealth management platforms, because a filing-based product does not produce those artifacts. For equity fundamental research, the alternative is a platform that extracts directly from SEC EDGAR and preserves as-filed line items with XBRL tag traceability.

### How much does YCharts cost?

YCharts lists Standard at **$300** per user per month billed annually and Professional at **$500** per user per month, which comes to **$3,600** and **$6,000** annually per seat. Enterprise pricing is quoted directly. The Professional tier adds time-series analysis, branded reports, and model portfolios.

### Where does YCharts get its data?

YCharts aggregates from institutional providers rather than extracting from primary filings, having described equity data sourced from S&P Global and fund data from Morningstar, alongside additional feeds for economic indicators and other datasets. Verify current attributions on the YCharts site, since provider relationships change.

### Is YCharts worth it for individual investors?

At **$3,600** a year for the entry tier, most of what an individual is paying for is the client-facing layer — proposals, branding, model portfolio presentation, and CRM integration — none of which an individual investor uses. The research capability is real, but the pricing is set by the advisor workflow rather than by the research alone.

---

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## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- YCharts tier pricing (Standard and Professional, billed annually; Enterprise by quote) and data-provider attributions reviewed August 2, 2026 from YCharts materials and third-party platform reviews. Verify current figures on the YCharts site before republication.
- GeminIQ YCharts comparison page: /competitor-comparison/ycharts

---

## Blog: Zacks Alternative: Filed Numbers, Not Estimates
source: https://www.geminiq.com/blog/zacks-alternative-sec-filing-data

### Zacks Alternative: Filed Numbers, Not Estimates
A Zacks alternative for investors who want reported results rather than forecasts. The Zacks Rank is built entirely on analyst earnings estimate revisions; this post explains what a revision measures and what it does not.

Zacks has the cleanest thesis of any research firm on this list, and it has held it since 1978. Len Zacks concluded that earnings estimate revisions were the most powerful force acting on stock prices, and the Zacks Rank has expressed that single idea ever since — aggregating revisions across roughly 3,000 analysts and more than 200,000 estimates, scored on components including how many analysts are revising, by how much, and how results have compared to consensus.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=zacks-alternative-sec-filing-data)**

Premium runs **$249** a year and Ultimate **$2,995**, with research reports, screens, industry rankings, and model portfolios layered on top of the Rank.

Here is what the system contains, stated plainly: no as-filed data whatsoever. Every input to a Zacks Rank is a forecast, a change in a forecast, or a comparison against a forecast. It is a measurement of analyst behavior, and that is not a criticism — it is the design.

## Table of Contents

- [A Revision Is Information About Analysts](#a-revision-is-information-about-analysts)
- [Beating Consensus Is Not a Statement About the Business](#beating-consensus-is-not-a-statement-about-the-business)
- [Coverage Determines Whether You Get a Signal at All](#coverage-determines-whether-you-get-a-signal-at-all)
- [Estimates Change, Filings Do Not](#estimates-change-filings-do-not)
- [What the Filed Record Answers Instead](#what-the-filed-record-answers-instead)
- [Two Timeframes, Two Questions](#two-timeframes-two-questions)
- [Frequently Asked Questions](#frequently-asked-questions)

## A Revision Is Information About Analysts

Start with what an estimate revision actually is.

An analyst covering a company publishes an earnings forecast. Something changes their view — a data point, a channel check, a competitor's results, a conversation, a change in their own model's assumptions — and they publish a new number. The revision records that an analyst changed their mind and in which direction.

That is a real and tradeable phenomenon, and the case for it is well documented: revisions cluster, other analysts follow, and prices tend to move with the aggregate. Nothing here disputes that.

What a revision does not record is anything the company did. The business did not change when the analyst updated a spreadsheet. Reported results did not move. The revision is a fact about a forecast, and the forecast is a fact about a person.

The distinction gets blurred because the language of estimates borrows the language of results. An "earnings estimate" sounds adjacent to earnings. One is a number a company filed under officer certification. The other is a number a stranger typed into a model.

## Beating Consensus Is Not a Statement About the Business

Earnings surprise deserves particular scrutiny, because it is the most misread figure in retail investing.

A surprise measures reported results against consensus expectation. It is a relative measure, and its denominator is a forecast that moves. That produces outcomes that look strange until the mechanics are clear.

A company can beat consensus while revenue declines, because the estimate had been revised down far enough. A company can miss consensus while growing strongly, because expectations ran ahead of it. Two companies with identical filed results can post opposite surprises purely because analysts approached them differently. And a company whose estimates were cut heading into a quarter has an easier bar than one whose estimates rose, which means the surprise partly measures how expectations were managed.

None of that makes surprise data useless — how a stock trades around a beat or a miss is a real market phenomenon, and the [stock price reaction after earnings](/blog/stock-price-reaction-after-earnings) study covers what the filed record shows about those moves. It makes surprise a measure of expectation-setting rather than a measure of performance.

The filed statement is the absolute number. The surprise is the gap between that number and what someone predicted.

## Coverage Determines Whether You Get a Signal at All

An estimates-based system inherits a hard structural limit: it requires analysts.

Zacks tracks thousands of analysts across a covered universe in the low thousands of companies. Outside that set the machinery has nothing to work with. A company with two analysts produces a fragile consensus that one revision can swing. A company with none produces no Rank at all.

Coverage correlates with size, liquidity, and institutional interest — which means the estimates layer is thinnest exactly where a fundamental investor is most likely to be looking. The small, unfollowed, and structurally ignored are the population where independent work has the best chance of finding something, and they are the population an estimate revision system cannot see.

Filings do not depend on anyone paying attention. Every registrant files on the same schedule whether or not a single analyst has ever written about it.

## Estimates Change, Filings Do Not

There is a durability difference that matters for anyone building a record of their own reasoning.

A consensus estimate is a moving object. It is revised continuously, it is superseded by the next quarter's, and the version that existed when you made a decision is frequently not recoverable afterward. Reconstructing why a stock looked attractive on a given date is difficult when the central input has since been overwritten.

A filed 10-K is fixed. It was submitted on a date, under signatures, with an audit opinion attached, and it stays exactly as filed. When a company restates, the restatement is itself a filing — the original remains in EDGAR, and the difference between them is visible and dated.

For a process that has to be reviewed later, that permanence is worth more than it sounds. Analysis built on filings can be reconstructed. Analysis built on a consensus that has moved cannot be.

## What the Filed Record Answers Instead

GeminIQ contains no estimates, no ratings, and no consensus. It extracts 10-K and 10-Q data directly from SEC EDGAR, preserves each company's own reported line item structure, and keeps the [XBRL tag](/blog/what-is-xbrl) attached to every value.

[Financial Statements](/features#financial-statements) show a company's own captions across quarters and years, so reported results can be read as a record rather than measured against a forecast. [Visualizations](/features#visualizations) chart the reported structure over time. [Custom Tables](/features#custom-tables) assemble the specific reported items a question turns on. [Calculated Metrics](/features#calculated-metrics) including [Earnings Per Share Growth](/metrics/growth-metrics/earnings-per-share-growth), [Revenue Growth](/metrics/growth-metrics/revenue-growth), and [Net Profit Margin](/metrics/margin-metrics/net-profit-margin) are computed from as-filed inputs, which means growth is measured against what the company previously reported rather than against what anyone expected.

The coverage universe is every SEC filer, because eligibility is a filing requirement rather than an analyst's decision.

## Two Timeframes, Two Questions

The honest reconciliation is that these systems operate on different clocks.

Estimate revisions are a short-horizon phenomenon. They describe expectations shifting now, and the trading implications play out over weeks to a few quarters. That is a legitimate strategy with decades of research behind it, and an investor operating on that horizon is right to track revisions.

Filed fundamentals operate on a longer one. What a business earns on capital, whether margins are durable, how the balance sheet behaves under stress, and whether management allocates capital well are questions that resolve over years, and they cannot be read from a revision at all.

For the other side of the forecast layer — where estimates feed a fair value rather than a rank — the [Morningstar alternatives](/blog/morningstar-alternative-sec-filing-data) and [Finbox alternatives](/blog/finbox-alternative-sec-data) posts cover what a model inherits from consensus.

The mistake is running one clock while believing you are running the other. A Rank tells you which way expectations are moving — and only the filings tell you what the company actually reported, which is the number that is still true after everyone has moved on.

## Frequently Asked Questions

### What are the best Zacks alternatives?

It depends on what you are replacing. For earnings estimate revisions and consensus data, the substitutes are other estimates providers, all of which depend on analyst coverage. For reported fundamentals, the alternative is a platform that extracts from SEC EDGAR and preserves as-filed line items with XBRL tag traceability — which contains no estimates at all, by design.

### What is the Zacks Rank based on?

It is built on analyst earnings estimate revisions, scored on components including how many analysts are revising estimates and in which direction, the magnitude of those revisions, and how reported results have compared to consensus. Every input is a forecast, a change in a forecast, or a comparison against one.

### Are earnings estimates the same as reported earnings?

No. An estimate is an analyst's forecast, published before results and revised continuously. Reported earnings are filed with the SEC in a 10-K or 10-Q, prepared under GAAP, audited, and certified by company officers. An estimate is a prediction about a company; a filing is a statement by one.

### Can a company beat estimates and still be shrinking?

Yes, and it happens routinely. A surprise measures results against consensus, so a company whose estimates were cut sharply enough can report declining revenue and still beat. The absolute performance is in the filing; the surprise measures the gap between that performance and what was predicted.

---

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=zacks-alternative-sec-filing-data)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

## Data Used / Sources

- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Zacks Rank methodology, founding history, analyst and estimate counts, covered universe, and Premium and Ultimate pricing reviewed August 2, 2026 from Zacks published materials and third-party platform reviews. Verify current pricing before republication.

---

## Blog: Pandemic Stocks That Crashed: Zoom, Teladoc, and DocuSign
source: https://www.geminiq.com/blog/zoom-teladoc-docusign-growth-deceleration

### Pandemic Stocks That Crashed: Zoom, Teladoc, and DocuSign
The pandemic stocks that crashed all decelerated in their own SEC filings before the market repriced them. This forensic study reads 106 consecutive 10-K and 10-Q filings from Zoom, Teladoc, and DocuSign to pinpoint the exact quarter each company's year-over-year revenue growth rate came in below the quarter before — and where the stock traded when that filing hit EDGAR.

<center><sup>GeminIQ data study: quarterly year-over-year revenue growth rate for each company, aligned on the quarter its own growth rate peaked. Built from as-filed 10-K/10-Q data via GeminIQ. n = 106 filings, 2015–2026.</sup></center>

**Zoom's year-over-year revenue growth rate fell from 368.8% to 191.4% in the 10-Q filed June 2, 2021, with the stock closing that quarter at $319.57. [Zoom Communications](/stocks/ZM) ($ZM) fell 87.0% from its October 2020 quarter-end close of $460.91 to $59.98 three years later. [Teladoc Health](/stocks/TDOC) ($TDOC) fell 97.5%. [DocuSign](/stocks/DOCU) ($DOCU) fell 87.0%. A pandemic-era runup that fully unwound in hindsight reads like something nobody could have called in advance. That reading survives only if you never open the filings. Read all 106 of them in the order they were submitted to EDGAR, and the same event shows up at each company: a specific quarter where the year-over-year revenue growth rate came in below the quarter before it. The second derivative went negative. It went negative in a filing published while the stock was still trading within striking distance of its high. Growth was still enormous. Growth was no longer accelerating. Those are different facts, and only one of them was in the price.**

Every figure below is drawn from Zoom Communications', Teladoc Health's, and DocuSign's own 10-K and 10-Q filings, filed between August 2015 and June 2026 — 29, 44, and 33 consecutive filings respectively, 106 in total. Each is read in the order the company filed it and joined to how the stock traded in the one to twelve months afterward. A [10-Q](/blog/10-k-vs-10-q-differences-explained) carries roughly three months of post-filing reaction; a 10-K carries twelve. Figures from 2020 and 2021 predate the three-year window shown on GeminIQ's stock pages and were pulled from the full as-filed history.

| Study Scope | Detail |
|---|---|
| Companies | Zoom Communications ($ZM), Teladoc Health ($TDOC), DocuSign ($DOCU) |
| Filing window | August 2015 – June 2026, 106 filings |
| Filing types | 10-K and 10-Q, as filed |
| Outcome explained | Peak-to-trough declines of **87.0%**, **97.5%**, and **87.0%** |
| Forward-return window | 1–3 months after each 10-Q; 12 months after each 10-K |

## Zoom's Revenue Growth Rate Turned From 368.8% to 191.4% in June 2021

Every extrapolation story dies the same way. Not when growth goes negative — that comes years later, if at all — but when the rate of growth stops climbing. The filings date that moment precisely for all three companies, and all three dates land in a nine-week stretch of 2021.

**The Filing Data:** [Zoom's](/stocks/ZM) `Revenues` grew **368.8%** year over year in the quarter ending January 31, 2021. In the next quarter, ending April 30, 2021, they grew **191.4%** — the first time the rate had come in below the prior quarter since the pandemic began. That filing hit EDGAR on June 2, 2021, with the stock closing the quarter at **$319.57**. [Teladoc's](/stocks/TDOC) rate peaked at **150.9%** in its March 2021 quarter and fell to **108.8%** in June, filed August 2, 2021, with the stock at **$166.29**. [DocuSign's](/stocks/DOCU) peaked at **57.9%** in its April 2021 quarter and fell to **49.6%** in July, filed September 3, 2021, with the stock at **$298.04** — its highest quarterly close on record.

**The Signal:** Zoom's sequential collapse was starker still than the annual figure. Quarterly `Revenues` grew **102.2%** over the prior quarter in the period ending July 31, 2020, then **17.1%** in the period ending October 31, 2020 — an **85.1-point** deceleration inside a single quarter, disclosed in a 10-Q filed December 4, 2020. That was the same quarter Zoom closed at **$460.91** on a [Price-to-Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) of **67.1** and a market capitalization of **$131.3 Billion**. Pulling the raw `Revenues` line quarter by quarter through GeminIQ's [Financial Statements](/features#financial-statements) makes that swing visible without any trailing-twelve-month smoothing to hide it. The deceleration and the all-time high are in the same filing.

## Deferred Revenue Turned First: Zoom 348.0% to 309.6%, DocuSign 61.9% to 53.6%

Recognized revenue is a lagging number for a subscription business — it reports contracts signed quarters earlier. The balance sheet gets there faster, and in two of these three cases it got there a full filing ahead of the income statement.

**The Filing Data:** Zoom's `Contract With Customer Liability Current` — the deferred revenue balance — grew **348.0%** year over year at October 31, 2020, then **309.6%** at January 31, 2021. That deceleration was filed March 18, 2021, one quarter before recognized revenue growth turned. [DocuSign's](/stocks/DOCU) deferred revenue growth peaked earlier still, at **61.9%** in its October 2020 quarter, falling to **53.6%** in January 2021 and **50.2%** in April 2021 — two consecutive declines filed before its recognized revenue growth rate ever came in light. DocuSign's [Billings](/metrics/calculated-values/billings), which adds the change in deferred revenue back to recognized revenue, tells the same story: **56.8%** growth in the January 2021 quarter, **55.5%** in April.

**The Signal:** Nobody needed a channel check or a management call to see this. The customers had already stopped prepaying at the old rate, and the company had said so in a document filed with the SEC. GeminIQ's pre-calculated [Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth) sits in the same [Calculated Metrics](/features#calculated-metrics) table as revenue growth, one row apart — which turns a two-quarter head start into something a reader notices on a single screen.

<center><sup>GeminIQ Calculated Metrics showing Zoom's Deferred Revenue Growth peaking at 348.0% (October 2020) and turning down to 309.6% (January 2021) — one quarter ahead of recognized revenue growth.</sup></center>

<center><sup>GeminIQ Calculated Metrics showing DocuSign's Deferred Revenue Growth falling from 61.9% (October 2020) to 53.6% (January 2021) to 50.2% (April 2021), two quarters before recognized revenue growth turned.</sup></center>

## The Market Took a Year: Zoom Fell 55.35%, Teladoc 68.49%, DocuSign 43.16%

The market did not punish the deceleration filings. It barely noticed them.

**The Filing Data:** In the three months after Zoom filed the 10-Q containing its first slower growth rate, the stock was up **2.98%**. Teladoc was down **8.18%** over the same window after its deceleration filing; DocuSign was down **15.07%** after its own. Now compare the annual reports. Each company's last 10-K filed while the growth story was still intact was followed by twelve months of cumulative returns that landed at **-55.35%** for Zoom, **-68.49%** for Teladoc, and **-43.16%** for DocuSign. DocuSign's path is the most instructive: six months after that 10-K, the cumulative figure stood at **+36.90%**. By month nine it was **-33.27%**, and by month twelve **-43.16%**.

**The Signal:** These are historical associations across a small named sample, not forecasts, and [three companies cannot establish a base rate](/blog/revenue-growth-slowdown-stock-returns). What they do establish is a sequence. The deceleration was disclosed, the market kept paying for two to four more quarters, and the repricing arrived long after the filing that justified it. Measured from the quarter each stock closed when its growth rate first came in light, [Zoom](/stocks/ZM) went on to fall **81.2%**, [DocuSign](/stocks/DOCU) **87.0%**, and [Teladoc](/stocks/TDOC) **96.7%**. Every one of those numbers was on file before the decline began. The gap between disclosure and repricing is where the money went.

<center><sup>GeminIQ data study: cumulative return in the three months after each company's deceleration 10-Q, against the subsequent decline from that quarter's close to its trough. Built from as-filed 10-K/10-Q data via GeminIQ, and post-filing market reaction. n = 3 filings, 2021–2026.</sup></center>

## Teladoc Wrote Off $13.403 Billion of Livongo Goodwill in FY2022

Teladoc's deceleration has a second layer the other two don't, and it sits on the balance sheet in a number large enough to be difficult to misread.

**The Filing Data:** [Teladoc's](/stocks/TDOC) `Goodwill` was **$742.3 Million** at June 30, 2020. By December 31, 2020 it was **$14.581 Billion**, following the Livongo acquisition, and it stood at **$14.504 Billion** in the FY2021 10-K. Against that, Teladoc's full-year `Revenues` for 2021 came to **$2.033 Billion** — roughly seven times more goodwill on the balance sheet than revenue on the income statement. The reckoning started in the quarter after the growth rate turned. `Goodwill Impairment Loss` was **$6.600 Billion** in the March 2022 quarter, **$3.030 Billion** in June, and **$3.773 Billion** in December, totaling **$13.403 Billion** for FY2022. `Goodwill` closed 2022 at **$1.073 Billion** and stood at **$283.19 Million** by June 30, 2024.

**The Signal:** Teladoc wrote off roughly **98%** of the goodwill it carried at the end of 2021 within thirty months. An impairment is management conceding in an SEC filing that the future cash flows it paid for will not arrive. Pulling the raw Balance Sheet quarter over quarter through GeminIQ's [Financial Statements](/features#financial-statements), the gap between a **$14.5 Billion** goodwill balance and a **$2.0 Billion** revenue base was visible in the FY2021 annual report — filed February 28, 2022, more than two months before the first write-down was disclosed.

<center><sup>GeminIQ Financial Statements showing Teladoc's Goodwill balance peaking at $14.504 Billion (December 2021) against $13.403 Billion of Goodwill Impairment Loss recognized across FY2022.</sup></center>

## Zoom's Stock Compensation Went From 10.4% to 29.3% of Revenue

Revenue growth rates fell by an order of magnitude at all three companies. One major expense line did not follow them down, and at Zoom it went the other way entirely.

**The Filing Data:** Zoom's annual `Share Based Compensation` was **$275.8 Million** in FY2021, or **10.4%** of `Revenues`. By FY2023 it reached **$1,285.8 Million**, or **29.3%** of revenue. Over those two years Zoom's revenue grew **65.7%** while its stock compensation grew **366.2%** — in a period when year-over-year revenue growth had already fallen to **7.1%**. DocuSign's `Allocated Share Based Compensation Expense` behaved differently but no better: **$286.9 Million** in FY2021 at **19.7%** of revenue, rising to **$616.8 Million** in FY2024 at **22.3%**, holding roughly one fifth of every revenue dollar while trailing-twelve-month revenue growth fell from **49.2%** to **9.8%**.

**The Signal:** A compensation structure sized for hypergrowth does not resize itself when hypergrowth ends. GeminIQ's pre-calculated [Stock-Based Compensation to Revenue](/metrics/margin-metrics/stock-based-compensation-to-revenue) makes that divergence a single trackable line rather than a two-statement reconciliation. Zoom's ratio nearly tripled in twenty-four months. That is what it looks like when a company keeps paying for a growth rate it no longer has.

<center><sup>GeminIQ Calculated Metrics showing Zoom's Stock-Based Compensation to Revenue rising from 10.4% (FY2021) to 29.3% (FY2023) as revenue growth fell to single digits.</sup></center>

## Zoom, Teladoc, and DocuSign Insiders Sold $2.034 Billion Across 2020 and 2021

What are the people actually running the company doing with their own money? Form 4 data is quarterly and lands with a lag, so it answers that question late — a hook rather than a trigger. Across two years and three companies, the answer is still hard to ignore.

**The Filing Data:** Across 2020 and 2021, insiders at the three companies filed **446** Form 4 sale records — one of them a `4/A` amendment restating an earlier filing — totaling **$2.034 Billion** in filed sale value, against exactly **two** purchase records totaling **$5.0 Million**. [Zoom](/stocks/ZM) accounted for **$1.216 Billion** across 199 sale records with no insider purchases in either year. [Teladoc](/stocks/TDOC) accounted for **$423.9 Million** across 182 records, also with no purchases. [DocuSign](/stocks/DOCU) accounted for **$393.6 Million** across 65 records against those two purchases.

**The Signal:** Between 2020 and 2021, at three companies whose growth rates were in the process of peaking, a net **$2.029 Billion** went out the door. Scheduled 10b5-1 plans explain a share of that volume, which is why GeminIQ's raw Form 4 feed inside [Insider Transactions](/features#insider-transactions) shows the [transaction code](/blog/form-4-transaction-code-list) on every line rather than collapsing everything into a single "insider activity" score. The direction was not ambiguous, and it pointed the same way at all three names simultaneously.

<center><sup>GeminIQ Insider Transactions showing Zoom's Form 4 activity across 2020 and 2021 — 199 sale records totaling $1.216 Billion, with no insider purchases in either year.</sup></center>

## Three Filings in Nine Weeks of 2021 Dated Every Decline

The warnings stacked to three deep in a single quarter, and the quarter is the same one at every company.

For [Zoom](/stocks/ZM), that quarter ended April 30, 2021, in the 10-Q filed June 2, 2021: recognized revenue growth had fallen from **368.8%** to **191.4%**, deferred revenue growth had already turned the filing before, and insiders had sold **$698.9 Million** across the prior calendar year without a single purchase. The stock closed that quarter at **$319.57**, still **341%** above where it would trade thirty months later. For [DocuSign](/stocks/DOCU), the quarter ended July 31, 2021, filed September 3: growth down from **57.9%** to **49.6%**, deferred revenue growth in its third consecutive decline, and stock compensation running at **19.3%** of revenue. The stock closed at **$298.04** — its record — and reached **$38.88** by October 2023. For [Teladoc](/stocks/TDOC), the quarter ended June 30, 2021, filed August 2: growth down from **150.9%** to **108.8%**, carrying **$14.45 Billion** of goodwill against a business generating **$1.63 Billion** of trailing-twelve-month revenue. The stock closed at **$166.29**. It traded at **$5.45** in March 2026.

Three companies, three different products, three different fiscal calendars, one shared sequence. In each case the growth rate turned in a filing the market read as fine. In each case the balance sheet had turned first. And in each case the twelve months after the last confident annual report were followed by declines of **43%** to **68%**. The filings were published, timestamped, and freely available to anyone who opened them.

## Check Your Holdings

The step-by-step version of this check — what to pull, what to subtract, and what counts as a turn — is written up separately in [how to check revenue growth deceleration](/blog/revenue-growth-deceleration-signal). The short version: read the year-over-year growth rate down the column and mark the first quarter it comes in below the quarter before, no matter how large the rate itself still is. Zoom's was **191.4%** on the quarter it turned.

Then run the same read on the deferred revenue balance, filed as `Contract With Customer Liability Current` or `Deferred Revenue Current` depending on the issuer. That is the version that turned a quarter to two quarters earlier at both Zoom and DocuSign. In GeminIQ, both are pre-computed as [Revenue Growth](/metrics/growth-metrics/revenue-growth) and [Deferred Revenue Growth](/metrics/growth-metrics/deferred-revenue-growth), sitting adjacent in the same [Calculated Metrics](/features#calculated-metrics) table across a company's full filing history ([how that compares with other filing-data platforms](/competitor-comparison/tikr)). It would have dated all three of these turns while every one of the stocks was still near its high.

## Frequently Asked Questions

### How many filings does this study cover?

106 as-filed 10-K and 10-Q filings — 29 from Zoom Communications, 44 from Teladoc Health, and 33 from DocuSign — filed between August 2015 and June 2026 and read in submission order.

### When did Zoom's revenue growth start slowing?

In the quarter ended April 30, 2021. Year-over-year `Revenues` growth came in at **191.4%**, down from **368.8%** in the quarter ended January 31, 2021 — the first time the rate had fallen below the prior quarter since the pandemic began. That 10-Q hit EDGAR on June 2, 2021, with [Zoom](/stocks/ZM) closing the quarter at **$319.57**. Sequential growth had turned earlier still: **102.2%** quarter over quarter in the period ending July 31, 2020, then **17.1%** in the period ending October 31, 2020, an **85.1-point** deceleration disclosed in a 10-Q filed December 4, 2020.

### How much Livongo goodwill did Teladoc write off?

**$13.403 Billion** across FY2022 — `Goodwill Impairment Loss` of **$6.600 Billion** in the March 2022 quarter, **$3.030 Billion** in June and **$3.773 Billion** in December. [Teladoc's](/stocks/TDOC) `Goodwill` had gone from **$742.3 Million** at June 30, 2020 to **$14.581 Billion** at December 31, 2020 following the Livongo acquisition, standing at **$14.504 Billion** in the FY2021 10-K. It closed 2022 at **$1.073 Billion** and stood at **$283.19 Million** by June 30, 2024 — roughly **98%** of the end-2021 balance written off within thirty months.

### Did DocuSign's decline show up in the filings first?

Its deferred revenue growth did. [DocuSign's](/stocks/DOCU) deferred revenue growth peaked at **61.9%** in the October 2020 quarter and fell to **53.6%** in January 2021 and **50.2%** in April 2021 — two consecutive declines filed before its recognized revenue growth rate ever came in light. Recognized growth turned from **57.9%** to **49.6%** in the July 2021 quarter, filed September 3, 2021, with the stock at **$298.04**, its highest quarterly close on record. It reached **$38.88** by October 2023. This is a sequence in one company's filings, not evidence that the filings caused the decline.

### What was Zoom's peak valuation?

At the October 2020 quarter close — the peak this study measures the **87.0%** decline from — [Zoom](/stocks/ZM) closed at **$460.91** with a market capitalization of **$131.3 Billion** and a [Price-to-Sales Ratio](/metrics/valuation-metrics/price-to-sales-ratio) of **67.1**. That is the same quarter in which Zoom's sequential revenue growth fell from **102.2%** to **17.1%**, disclosed in a 10-Q filed December 4, 2020.

### Does a growth-rate peak predict a stock decline?

No. This study documents a historical association across three named companies over a specific window, not a predictive relationship. Three companies is far too small a sample to establish a base rate, and none of these figures forecast any stock's future. The finding is that the deceleration appeared in the filings before it appeared in the price at all three.

### Is GeminIQ's insider data live?

No. Form 4 and 13F data are quarterly filings with a reporting lag, and GeminIQ presents them as such. Insider activity in this study is used as context alongside the fundamentals, not as a standalone trigger.

**[Start your 7-day free trial →](/pricing?utm_source=site&utm_medium=cta&utm_campaign=blogs&utm_content=zoom-teladoc-docusign-growth-deceleration)**

## Wall Street's data. Main Street's price.

Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at [GeminIQ.com](/).

<sup>All financial figures in this article are drawn from Zoom Communications Inc.'s 10-K and 10-Q filings, filed 2019–2026 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=1585521&type=10-K).
All financial figures for Teladoc Health, Inc. are drawn from its 10-K and 10-Q filings, filed 2015–2026 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=1477449&type=10-K).
All financial figures for DocuSign, Inc. are drawn from its 10-K and 10-Q filings, filed 2018–2026 and publicly available on [SEC EDGAR](https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=1261333&type=10-K).</sup>

---

## Section 11: Competitor Comparisons
source: all /competitor-comparison/ pages

---

### GeminIQ vs Bloomberg Terminal
source: https://www.geminiq.com/competitor-comparison/bloomberg-terminal

**Headline:** The Best Bloomberg Alternative for Independent Equity Analysts

**What Bloomberg Does Well:**
- Real-time data across every asset class and 350+ global exchanges
- Bloomberg IB messaging network (325,000+ finance professionals)
- Unmatched fixed income, forex, and commodities depth
- Integrated Bloomberg News (2,700+ journalists, 120 countries)
- Excel BDH/BDP formula integration with both standardized and as-reported financials
- AI-powered tools (Bloomberg GPT integration)
- Portfolio analytics, risk management, and trade execution
- The industry standard — no substitute for institutional trading desks

**Where GeminIQ Wins:**
- Direct SEC EDGAR data — same primary-source standard as Bloomberg
- XBRL tag traceability on every data point (Bloomberg doesn't expose these)
- Proprietary Earnings Market Reaction Heatmap
- Advanced screener with 100+ metrics and up to 10 stackable filters
- Accessible to any individual — no contract, no IT deployment
- 99% cheaper — $29/mo vs. $2,665/mo

**Who Should Switch:**
- Independent analysts and quantitative researchers
- Boutique equity firms and family offices
- Former Bloomberg users now focused on independent US equity research
- Data scientists building models on SEC filing data

**Why GeminIQ Was Built Differently:**
Bloomberg Terminal is expensive for a specific reason: they build and maintain their own data pipelines directly to primary sources across every asset class globally. GeminIQ was built on the same architectural principle, applied specifically to US equity fundamentals. We don't license data from S&P Capital IQ, Morningstar, or any aggregator. We build and maintain our own ingestion pipelines directly to SEC EDGAR — the same primary-source standard Bloomberg applies. Many retail platforms license their equity fundamentals from S&P Capital IQ, which normalizes raw SEC filings. GeminIQ and Bloomberg both bypass that intermediary. The difference is scope and price.

**Pricing:** GeminIQ Annual ($29/mo) vs. Bloomberg Terminal ($2,665/mo). 99% cheaper. GeminIQ requires no contract and includes a 7-day free trial.

---

### GeminIQ vs TIKR Terminal
source: https://www.geminiq.com/competitor-comparison/tikr

**Headline:** The Best TIKR Terminal Alternative for Analysts Who Need Raw, Auditable Data

**What TIKR Does Well:**
- Global coverage across 92+ countries and 136 exchanges
- Analyst estimates and consensus price targets
- Earnings call transcripts
- Superinvestor and hedge fund portfolio tracking (10,000+ funds)
- Free entry-level plan for US stocks

**Where GeminIQ Wins:**
- Direct SEC EDGAR data — no third-party middlemen
- XBRL tag traceability on every data point
- Raw, company-specific reporting preserved as-filed
- Proprietary Earnings Market Reaction Heatmap
- Advanced screener with 100+ metrics and stackable filters
- 24% cheaper than TIKR Pro annually; 29% cheaper month-to-month

**Who Should Switch:**
- US-focused fundamental and value investors
- Analysts who need to audit and trace their numbers
- Anyone frustrated by normalized data that doesn't match the 10-K & 10-Q

**Why GeminIQ Was Built Differently:**
TIKR sources its financial data from S&P Capital IQ, a third-party aggregator that processes raw SEC filings and redistributes standardized, normalized versions. GeminIQ builds its own ingestion pipelines directly from SEC EDGAR. Every data point carries its XBRL tag, so you can open the original filing and verify the number in under 30 seconds. No black boxes, no reclassified line items.

**Pricing:** GeminIQ Annual ($29/mo) is 24% cheaper than TIKR Pro ($37.95/mo annually). GeminIQ Monthly ($39/mo) is 29% cheaper than TIKR's month-to-month rate ($54.95/mo).

---

### GeminIQ vs GuruFocus
source: https://www.geminiq.com/competitor-comparison/gurufocus

**Headline:** The Best GuruFocus Alternative for Analysts Who Need Auditable Source Data

**What GuruFocus Does Well:**
- Guru portfolio tracking (8,000+ institutional investors, 15,000+ mutual funds)
- All-in-One Screener with 500+ filters and prebuilt value strategies
- Up to 30 years of historical financial data (Professional plan)
- Proprietary GF Score, GF Value, and Graham Number valuations
- Insider tracking with clusters and politician trading tracker
- GuruAI chatbot for natural-language research

**Where GeminIQ Wins:**
- Direct SEC EDGAR data — no third-party data vendor
- XBRL tag traceability on every data point
- Raw, as-filed reporting structure preserved without normalization
- Proprietary Earnings Market Reaction Heatmap
- 30% cheaper than GuruFocus Premium

**Why GeminIQ Was Built Differently:**
GuruFocus's underlying financial data comes from a third-party data vendor, not directly from the SEC. GuruFocus added click-through links from financial data points to source filings — but linking to the filing document is different from XBRL tag-level traceability. GeminIQ's data isn't processed by a vendor; you see what the company reported, exactly as they reported it. GuruFocus is ideal for learning from the masters and guru tracking. GeminIQ is for primary-source analysis without an interpretive layer.

**Pricing:** GeminIQ Annual ($29/mo, $348/year) is 30% cheaper than GuruFocus Premium ($499/year). To access 20+ years and backtesting on GuruFocus requires Premium Plus at $1,273/year — over 3.6x the cost of GeminIQ's Annual Plan.

---

### GeminIQ vs ROIC.ai
source: https://www.geminiq.com/competitor-comparison/roic-ai

**Headline:** The Best ROIC.ai Alternative for Analysts Who Need As-Filed Data

**What ROIC.ai Does Well:**
- ROIC-focused financial analysis in a clean, single-page layout
- AI chat and ChatGPT integration for natural-language financial queries
- 30+ years of historical financial statements
- Worldwide stock coverage (Individual plan and above)

**Where GeminIQ Wins:**
- XBRL tag traceability on every data point — verify any number in the source filing
- Raw, as-filed line items preserved without reformatting
- Advanced screener with 100+ metrics and up to 10 stackable filters
- Proprietary Earnings Market Reaction Heatmap
- Insider transactions, institutional ownership, and comps — all in one platform at $29/mo

**Why GeminIQ Was Built Differently:**
Both platforms source data from the SEC — but ROIC.ai processes filings into its own standardized template structure. GeminIQ preserves the raw, as-filed reporting structure with XBRL tags intact. ROIC.ai takes a philosophically disciplined approach through the lens of return on invested capital. GeminIQ doesn't impose a framework — it surfaces the metric as filed so you can apply your own.

**Pricing:** GeminIQ Annual ($29/mo) is 61% cheaper than ROIC.ai Professional ($74/mo).

---

### GeminIQ vs S&P Capital IQ
source: https://www.geminiq.com/competitor-comparison/sp-capital-iq

**Headline:** The Best S&P Capital IQ Alternative for Independent Analysts

**What Capital IQ Does Well:**
- Unmatched breadth: 109,000+ public companies, 60M+ private companies
- M&A deals database, credit ratings, and private markets data
- Both templated and as-reported financial views
- Analyst estimates with Visible Alpha integration (1M+ data points)
- Excel CIQ add-in with 250+ prebuilt templates
- Industry-standard platform for investment banking and equity research

**Where GeminIQ Wins:**
- XBRL tag traceability on every data point
- Raw, as-filed reporting structure preserved without transformation
- Proprietary Earnings Market Reaction Heatmap
- No enterprise contract, no IT deployment
- 97% cheaper — $29/mo vs. $1,000+/mo

**Why GeminIQ Was Built Differently:**
S&P Capital IQ is the financial data platform that Wall Street runs on. Its breadth is unmatched — but it costs $12,000–$25,000+ per user per year. GeminIQ provides primary-source US equity data with XBRL traceability at 97% lower cost, with no contract and no IT deployment. GeminIQ was built around a single premise: if your universe is US public companies filing with the SEC, you don't need a vendor to repackage that data.

**Pricing:** Capital IQ Essentials starts at ~$12,000/year. GeminIQ Annual is $348/year — 97% cheaper.

---

### GeminIQ vs BamSEC
source: https://www.geminiq.com/competitor-comparison/bamsec

**Headline:** The Best BamSEC Alternative for Analysts Who Want More Than Document Search

**What BamSEC Does Well:**
- Full-text search across millions of SEC filings and transcripts
- Filing comparison with side-by-side redline diff view
- Table extraction and historical table tracking to Excel
- Team collaboration with highlighting and shareable Link-to-Text
- Email alerts for new filings, search terms, and ownership changes

**Where GeminIQ Wins:**
- Automated metrics extraction — no manual spreadsheet work
- 90+ calculated financial KPIs, ready on every company page
- Advanced screener with 100+ metrics and up to 10 stackable filters
- Interactive multi-metric visualizations with trend analysis
- Proprietary Earnings Market Reaction Heatmap
- 58% cheaper than BamSEC Pro ($29/mo vs. $69/mo)

**Why GeminIQ Was Built Differently:**
BamSEC is a document research platform, not a quantitative analysis platform. It helps you find the right table in the filing — then the analytical work begins. GeminIQ automates the entire quantitative layer. We parse each SEC filing directly from EDGAR, calculate over 90 financial KPIs, and present results as interactive visualizations. You get the depth of BamSEC's source-data accuracy, plus the quantitative terminal layer, at 58% less per month.

**Pricing:** BamSEC Pro: $69/month. GeminIQ Annual: $29/month. 58% cheaper.

---

### GeminIQ vs Finbox
source: https://www.geminiq.com/competitor-comparison/finbox

**Headline:** The Best Finbox Alternative for Analysts Who Need Raw, Auditable Data

**What Finbox Does Well:**
- Prebuilt valuation models (DCF, Dividend Discount, Comparable Company Analysis)
- Powerful stock screener with 1,000+ metrics
- Fair value estimates for every stock covered
- Global coverage across 100,000+ stocks on 130+ exchanges
- Accessible Starter plan at $10/mo

**Where GeminIQ Wins:**
- Direct SEC EDGAR data — no third-party normalization
- XBRL tag traceability on every data point
- Proprietary Earnings Market Reaction Heatmap
- Insider transactions and institutional ownership tracking
- 56% cheaper than Finbox Professional (annual plans)

**Why GeminIQ Was Built Differently:**
Finbox's models are built on S&P Global-normalized data. When a company reports across four custom segments, S&P's template may collapse them. GeminIQ doesn't offer prebuilt DCF models — instead, it provides the raw, verified data foundation that makes any model you build more trustworthy. Finbox for prebuilt models on normalized data; GeminIQ for the foundation that makes your own models accurate.

**Pricing:** GeminIQ Annual ($29/mo) is 56% cheaper than Finbox Professional ($66/mo annually).

---

### GeminIQ vs YCharts
source: https://www.geminiq.com/competitor-comparison/ycharts

**Headline:** The Best YCharts Alternative for Independent Equity Analysts

**What YCharts Does Well:**
- Exceptional data visualization — industry-leading charts and visuals
- Stock screener with 4,500+ metrics across 28,000+ equities
- Client-ready branded PDF reports and proposals
- Economic indicators and macro data dashboards
- Model portfolio construction and portfolio analytics
- NLP-powered "Fast Track" screener (natural language screening)

**Where GeminIQ Wins:**
- Direct SEC EDGAR data — no third-party normalization
- XBRL tag traceability on every data point
- Proprietary Earnings Market Reaction Heatmap
- Insider transactions and institutional ownership tracking
- 90% cheaper — $29/mo vs. $300/mo

**Why GeminIQ Was Built Differently:**
YCharts was designed for financial advisors — client-ready PDFs, branded proposals, compliance documentation, and model portfolio construction. GeminIQ strips away the advisor layer entirely and focuses on primary-source accuracy for fundamental equity analysts. YCharts has more features; GeminIQ has more data accuracy at 90% less cost.

**Pricing:** YCharts Standard: $3,600/year. GeminIQ Annual: $348/year. 90% cheaper.

---

### GeminIQ vs Fiscal.ai
source: https://www.geminiq.com/competitor-comparison/fiscal-ai

**Headline:** The Best Fiscal.ai Alternative for Analysts Who Need XBRL-Level Data Traceability

**What Fiscal.ai Does Well:**
- AI Copilot for natural-language conversational research
- Proprietary segment and KPI data for 2,100+ companies (sourced from filings)
- 100,000+ global companies covered
- Stock screener with 500+ filters and custom formulas
- Earnings call transcripts and investor relations content
- Real-time data updates (financials within minutes of earnings)
- Robust free tier

**Where GeminIQ Wins:**
- XBRL tag traceability on every data point — not just source filing links
- Raw, as-filed reporting structure preserved without normalization
- 17+ years of historical data on paid plans
- Proprietary Earnings Market Reaction Heatmap
- Visual insider sentiment timeline with granular Form 4 detail
- 26% cheaper than Fiscal.ai Pro, with deeper history

**Why GeminIQ Was Built Differently:**
Fiscal.ai's standardized financial data comes from S&P Global Market Intelligence, which normalizes raw SEC filings. Fiscal.ai adds proprietary KPI data for 2,100+ companies. GeminIQ sources ALL financial data directly from SEC EDGAR with XBRL tags intact. A filing link takes you to the full document; an XBRL tag takes you to the exact data point. GeminIQ is deterministic by design — every metric traces to a specific XBRL element in a specific EDGAR submission. Fiscal.ai for AI-powered global research; GeminIQ for structured quantitative data with an auditable chain of custody.

**Pricing:** GeminIQ Annual ($29/mo) is 26% cheaper than Fiscal.ai Pro ($39/mo annually) and 63% cheaper than Fiscal.ai Max ($79/mo).

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## Disclaimer

The content on GeminIQ is for educational and informational purposes only and does not constitute financial, legal, or tax advice. GeminIQ LLC is not a registered investment advisor. Investing involves risk, including the loss of principal.

Most financial websites rely on third-party aggregators that simplify or process data before you ever see it. GeminIQ extracts data directly from SEC 10-K and 10-Q filings to ensure that when you look at a balance sheet or cash flow statement, you are seeing the numbers exactly how the company reported them.