# GeminIQ — Full Content Reference --- ## 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, 50+ 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 aggregators. 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. Our system standardizes filings to eliminate inconsistencies and aligns them to industry-standard formats. 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 50 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 50 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. **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. --- ## Section 3: Pricing source: https://www.geminiq.com/subscription-page All plans include a 7-day free trial. All features included on every plan. No feature tiers. ### Founders Plan — $29/month (billed annually) - 40% discount over monthly - Exclusive founders rate - Limited to first 500 subscribers - Price locked for life (see terms) - 17+ years of financial data - Over 50 core financial metrics - Fully customizable analysis tools - Institutional ownership data - Advanced filing search - Custom watchlists - Insider transaction tracking - Interactive filing timelines - Price variance & market reaction tools - Next-day filing availability - Every number traceable to its SEC source - Unlimited watchlist and saved metrics - 7-day risk free trial ### Annual Plan — $39/month (billed annually) - 20% discount over monthly - Includes all features listed above - 7-day risk free trial ### Monthly Plan — $49/month - Flexible pay-as-you-go billing - Includes all features from 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. ### Founders Plan — Terms Summary The Founders Plan price lock is guaranteed for the lifetime of a continuous, uninterrupted subscription. The promotional rate is permanently forfeited — and cannot be reinstated — if the subscriber voluntarily cancels, if a payment fails and is not resolved within 5 days, or if the account is suspended for a Terms of Service violation. The rate is non-transferable and tied strictly to the original account. --- ## 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 aggregators that simplify, alter, or delay crucial information. GeminIQ removes the middleman, delivering raw, unadulterated SEC data directly to your screen alongside powerful visualization and behavioral analysis tools. Explore the core features designed to help you research faster, invest smarter, and uncover the fundamental truth behind the ticker. ### Direct-from-Source SEC Financial Statements Stop relying on standardized templates that obscure a company's unique reporting structure. Our primary data ingestion engine pulls directly from the SEC's EDGAR database, providing a "Zero-Dependency" architecture. - **Raw & Unfiltered Data:** View 10-Q (quarterly) and 10-K (annual) financial data exactly as the company reported it, without the normalization filters applied by large aggregators. - **XBRL Traceability:** Every data point includes its specific XBRL tag, giving you 100% auditability to verify the numbers directly in the source filing. - **Next-Day Availability (T+1):** Filings are processed overnight, ensuring you have clean, structurally accurate datasets by the time the market opens. - **Unrestricted Historical Data:** Analyze full market cycles without being restricted by arbitrary 3-year or 5-year paywalls common on tiered pricing platforms. ### Customizable Data Tables Dense financial reports can be overwhelming. GeminIQ's Custom Tables act as your personal investment checklist, allowing you to filter out the noise and focus exclusively on the data that matters to your strategy. - **Bespoke Dashboards:** Select specific line items from the balance sheet, income statement, or cash flow statement to build a streamlined view. - **Save-able Templates:** Build your ideal metric template once and instantly apply it to any new ticker you research, drastically speeding up your analysis workflow. - **Instant Toggling:** Seamlessly switch between the 10-K for a broad historical view or the 10-Q to catch the latest quarterly trends. ### Interactive Financial Visualizations Reading numbers in a static table is accurate, but it doesn't reveal the velocity of a trend. GeminIQ transforms complex 10-K and 10-Q data into dynamic, interactive timelines. - **Trend Identification:** Plot multiple metrics against each other to visually confirm if a company's financial safety gap is widening or shrinking. - **Flexible Charting:** Choose between line graphs, bar charts, or area charts for every individual metric. - **Advanced Transformations:** Toggle between linear and logarithmic scales to accurately assess percentage growth rates over time. ### Earnings Market Reaction Heat Map (Price Variance) Traditional tools tell you if a company beat earnings estimates; GeminIQ tells you how the market actually behaved. Our proprietary Heat Map tracks post-earnings price drift. - **Behavioral Pattern Recognition:** Spot historical trends in how a stock digests its filings by viewing a grid of fiscal years plotted against 1-month, 2-month, and 3-month performance windows. - **Identify "Sell the News" Events:** Spot companies that consistently sell off following an annual report. - **Macro-Context Correlation:** Understand whether a stock's historical drawdown was caused by poor fundamentals or broader macro events. ### Comprehensive Calculated Metrics GeminIQ automatically calculates over 50 core financial metrics and key performance indicators (KPIs) directly from the raw data. - **Capital Efficiency Focus:** Track ROIC to see exactly how effectively management turns a dollar of investment into profit. - **Margin Expansion:** Monitor gross profit margin and operating profit margin to confirm whether a company's competitive moat is intact or deteriorating. - **Velocity and Turnover:** Audit operational efficiency using metrics like inventory turnover. - **Long-Term Growth Rates:** Analyze 3-year and 5-year growth columns to identify sustained structural shifts. ### Insider Transactions Tracker The GeminIQ Insider Transactions module transforms raw SEC Form 4 filings into a clear, visual timeline of executive behavior. - **Visual Sentiment Timeline:** Charts instantly visualize trailing 12 months of insider activity. Red bars represent open-market sales; green bars represent open-market purchases. - **Identify High-Conviction Clusters:** Spot critical clusters where multiple insiders are aggressively transacting. - **Granular Transaction Context:** See the individual's specific relationship to the company and the exact price per share they transacted at. ### Institutional Ownership Monitoring GeminIQ's Institutional Ownership tool allows you to track the aggregate footprint of Wall Street's largest funds. - **Aggregate Ownership Tracking:** Map the total percentage of outstanding shares held by major institutions and track if they are increasing their stake quarter over quarter. - **Confirm Your Fundamental Thesis:** A strong investment thesis should be backed by institutional ownership that remains steady or trends upward. ### Stock Screener GeminIQ's Stock Screener lets you define precisely what you're looking for — and returns only the companies that match, backed by data you can trace to the source filing. - **100+ Financial Metrics:** Screen across profitability, valuation, growth, leverage, efficiency, and liquidity metrics — all derived directly from XBRL-tagged SEC filings. - **Up to 10 Stackable Filters:** Build highly targeted screens by layering multiple conditions in a single query. - **Precise Filter Logic:** Each condition supports less than, less than or equal to, greater than, greater than or equal to, equal to, not equal to, and between operators. - **Built on Auditable Data:** Every GeminIQ screener result traces directly to the company's SEC filing. ### Custom Watchlists & Comparable Company Analysis (Comps) The GeminIQ Watchlist is a powerful Comparable Company Analysis (Comps) engine. - **Side-by-Side Data Grids:** Compare critical metrics for all saved companies side-by-side. - **Filing Period Customization:** Compare companies across their latest 10-Q, 10-K, or a specific historical fiscal year. - **Multi-Ticker Visualizations:** Plot fundamental data points for multiple companies on the same graph. - **Active Portfolio Health Checks:** Track stocks you already own with metrics like net revenue growth and operating profit margin. --- ## Section 5: Why Direct SEC Data Matters source: https://www.geminiq.com/blog/Third_Party_Data_Miss ### What Third-Party Financial Data APIs Miss — And Why It Costs You (2026) 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. 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:** 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:** 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:** 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 from Apple's FY2025 10-K (filed October 31, 2025), comparing what the SEC filing says to what one widely-used retail platform displays: **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 — Cash Flow Statement (10-K page 33)** - As filed: Proceeds from/(Repayments of) commercial paper, net — **$3,960M** - Platform display: Total Debt Issued — **$3,960M** - What happened: A line item labeled as a net proceeds/(repayment) figure — which in the prior fiscal year was a net repayment — was reclassified by the platform as "debt issued." The economic direction of the transaction was inverted. **3. Other Current Liabilities — Balance Sheet (10-K page 40)** - As filed: Other current liabilities — **$44,452M** - Platform display: Other Current Liabilities — **$42,335M** - What happened: The platform subtracted the Current Portion of Capital Lease Obligations ($2,117M) from the line and still labeled it "Other Current Liabilities" — a $2,117M discrepancy under the exact 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 edge cases or obscure mid-cap stocks. These are documented discrepancies in the most widely followed company in the world, from its most recent annual filing. ### 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 calculations, and any model that depends on understanding Apple's actual balance sheet structure. On [GeminIQ](https://www.geminiq.com), 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 requires 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](https://www.geminiq.com) 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](https://www.geminiq.com/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 [50+ financial KPIs](https://www.geminiq.com/features#calculated-metrics) — ROIC, ROE, margins, growth rates, Altman Z-Score, and more — directly from the XBRL-tagged source data. When GeminIQ shows Apple's FY2025 gross 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. --- ## 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](https://www.geminiq.com/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](https://www.geminiq.com/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](https://www.geminiq.com/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](https://www.geminiq.com/features#insider-transactions) and [institutional ownership trends](https://www.geminiq.com/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](https://www.geminiq.com/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 50+ calculated metrics and 100+ screener metrics?** GeminIQ automatically calculates 50+ 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 Apple examples above show, this isn't abstract. It's an $11.6 billion gap under the same label. A cash outflow labeled as debt issuance. A buyback merged with a tax payment. On the most analyzed company on earth. 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. --- --- ## Section 6: Hidden Information in SEC Filings source: https://www.geminiq.com/blog/Hidden_Info_In_Filings ### How to Find Hidden Information in SEC Filings (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 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. 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 actual SEC data, and show how [GeminIQ](https://www.geminiq.com) surfaces them automatically. --- ## 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 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](https://www.geminiq.com/features#financial-statements), across 17+ years of history. You can build a [Custom Table](https://www.geminiq.com/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. 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 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 "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](https://www.geminiq.com/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 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 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](https://www.geminiq.com/features#insider-transactions) for Apple spans from 2008 to present and reveals a striking pattern: across 428 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 executive — not Tim Cook, not any SVP, not any CFO — has ever bought Apple stock on the open market in the entire dataset. The remaining 424 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. --- ## 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](https://www.geminiq.com/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. --- ## 5. Institutional Ownership Trends That Confirm (or Contradict) Your Thesis Individual investor sentiment is noisy. Institutional ownership — tracked through 13F filings — shows what professional capital is actually doing with its money, quarter by quarter. GeminIQ's [Institutional Ownership](https://www.geminiq.com/features#institutional-ownership) data for Apple reveals a decade-long accumulation trend. From 55.7% 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. --- ## 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](https://www.geminiq.com) 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](https://www.geminiq.com/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. --- ## Section 7: How to Read a 10-K source: https://www.geminiq.com/blog/How_to_10-K_Apple ### How to Read a 10-K: 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. 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 fiscal year 2025 filing** (filed October 31, 2025) as our working example. We'll also show you how [GeminIQ](https://www.geminiq.com) automatically extracts, structures, and visualizes the data inside these filings — so you spend less time copying numbers into spreadsheets and more time analyzing them. --- ## 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) - **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 FY2025 10-K, Item 1 reveals a few things that matter for valuation. Apple 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** 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](https://www.geminiq.com/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 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](https://www.geminiq.com/features#calculated-metrics) automatically compute over 50 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 85.4% (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. --- ## 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:** $99.3 billion ($91.3B 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:** 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](https://www.geminiq.com/features#financial-statements), every segment, and every XBRL tag. You can build [Custom Tables](https://www.geminiq.com/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](https://www.geminiq.com/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. ### Institutional Ownership GeminIQ's [Institutional Ownership](https://www.geminiq.com/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. ### Earnings Market Reaction GeminIQ's proprietary [Earnings Market Reaction Heatmap](https://www.geminiq.com/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. --- ## 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](https://www.geminiq.com/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 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. --- ## Section 8: How to Read a 10-Q source: https://www.geminiq.com/blog/10-Q_In_Under_30 ### How to Read a 10-Q in Under 30 Minutes (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. 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 **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](https://www.geminiq.com) structures this quarterly data automatically — so you can skip the manual extraction and go straight to analysis. --- ## 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 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 margins 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](https://www.geminiq.com/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 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](https://www.geminiq.com/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. --- ## 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 settled by releasing escrowed funds. If you didn't know about that one-time item (disclosed in Apple's 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 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 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 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](https://www.geminiq.com/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 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 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 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 €500 million in the DMA Article 5(4) investigation (Apple 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 to charge a commission on link-out purchases — a partial win for Apple, 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](https://www.geminiq.com/demo/research) 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](https://www.geminiq.com/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. --- ## 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](https://www.geminiq.com/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. --- ## 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](https://www.geminiq.com/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 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. --- ## Section 9: Complete Guide to SEC Filings source: https://www.geminiq.com/blog/Complete_Guide_SEC_Filings ### A Complete Guide to SEC Filings: 10-K, 10-Q, 8-K, DEF 14A, S-1, and Form 4 (2026) 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. 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. --- ## 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](https://www.geminiq.com/blog/How_to_10-K_Apple). 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](https://www.geminiq.com/features#financial-statements), calculates [50+ KPIs](https://www.geminiq.com/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](https://www.geminiq.com/blog/10-Q_In_Under_30). The priority items: **Gross 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](https://www.geminiq.com/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 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, 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](https://www.geminiq.com/features#insider-transactions) shows 428 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](https://www.geminiq.com/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](https://www.geminiq.com/features#price-variance) that tracks post-filing stock performance across 17+ years. The [Stock Screener](https://www.geminiq.com/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 50+ metrics from the source data, and integrating insider transactions, institutional ownership, and post-filing price reactions into a single research platform. --- ## Section 10: What Is XBRL? source: https://www.geminiq.com/blog/What_Is_XBRL ### What Is XBRL and Why Does It Matter for Investors? (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. 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. --- ## 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 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 reports a line item that only Apple 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 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 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 FY2025 revenue tag carries a context indicating it covers the 12 months ending September 27, 2025, for entity CIK 0000320193 (Apple 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 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 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 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 "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](https://www.geminiq.com/blog/Third_Party_Data_Miss) — the aggregator subtracted $11.6 billion in capital leases and kept the label.) **Identify company-specific line items.** If an aggregator maps Apple's 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](https://www.geminiq.com/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 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](https://www.geminiq.com/features#screener) filters across 100+ metrics with up to 10 stackable conditions. Every metric behind the screen — [ROIC](https://www.geminiq.com/metrics/roic_ttm), [Free Cash Flow Yield](https://www.geminiq.com/metrics/free_cash_flow_yield_ttm), [Debt-to-Equity](https://www.geminiq.com/metrics/debt_to_equity), [Gross Margin](https://www.geminiq.com/metrics/gross_profit_margin_ttm) — 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](https://www.geminiq.com/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 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 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 reported them. The [financial statements](https://www.geminiq.com/features#financial-statements) on GeminIQ reflect the company's own reporting structure, not a template. **Every metric traces to its inputs.** GeminIQ calculates [50+ financial KPIs](https://www.geminiq.com/features#calculated-metrics) — ROIC, ROE, margins, growth rates, Altman Z-Score, and more — directly from XBRL-tagged data. When GeminIQ shows Apple's 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. --- ## 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](https://www.geminiq.com/features#screener), [visualizations](https://www.geminiq.com/features#visualizations), [insider tracking](https://www.geminiq.com/features#insider-transactions), and [institutional ownership](https://www.geminiq.com/features#institutional-ownership) data that turns raw filings into investment insight. --- ## Section 11: 50 Financial Metrics source: https://www.geminiq.com/blog/50_Financial_Metrics ### The 50+ Financial Metrics Every Value Investor Should Know (2026) A comprehensive reference guide to every calculated financial metric available on GeminIQ — organized by category, with plain-English definitions, formulas, and links to explore each one. Use this as your analytical starting point. Value investing is a numbers game, but only if you're looking at the right numbers — and only if those numbers match what the company actually reported. GeminIQ calculates 50+ financial KPIs directly from XBRL-tagged SEC filing data, and the [Stock Screener](https://www.geminiq.com/features#screener) makes 100+ metrics filterable with up to 10 stackable conditions. This guide defines every calculated metric on GeminIQ, organized by category: valuation, profitability, growth, leverage, efficiency, dividends, and financial health. Each definition explains what the metric measures, why it matters for value investors, and links to the metric page where you can screen for it. Think of this as the reference card you keep open while analyzing companies. --- ## Valuation Metrics Valuation metrics answer a single question: what are you paying for what you're getting? A cheap stock isn't necessarily a good investment, and an expensive stock isn't necessarily a bad one — but knowing the price you're paying relative to earnings, cash flow, revenue, or assets is the starting point for every investment decision. ### P/E Ratio (Price-to-Earnings TTM) **What it measures:** The stock price divided by trailing twelve-month earnings per share. A P/E of 20 means you're paying $20 for every $1 of annual earnings. **Why it matters:** The most widely used valuation metric. A low P/E can signal undervaluation or a business in decline. A high P/E can signal overvaluation or justified premium for growth. The number alone is not useful — it needs context from growth rates, margin trends, and industry norms. **Screener applications:** [GARP Screen](https://www.geminiq.com/screens/garp-screen) (P/E ≤ 25 with earnings growth ≥ 10%), [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen) (P/E ≤ 30 with high ROIC), [Deep Value Screen](https://www.geminiq.com/screens/deep-value-screen) ### P/S Ratio (Price-to-Sales TTM) **What it measures:** Market capitalization divided by trailing twelve-month revenue. Measures how much you're paying per dollar of sales, regardless of profitability. **Why it matters:** Useful for companies with volatile or negative earnings, where P/E is undefined or misleading. A low P/S on a company with improving margins can signal a turnaround opportunity. Also useful for comparing companies within the same industry where accounting policies affect earnings but not revenue. **Screener applications:** [Contrarian Low Price-to-Sales Screen](https://www.geminiq.com/screens/contrarian-low-ps) ### P/B Ratio (Price-to-Book) **What it measures:** Stock price divided by book value per share. Measures what you're paying for the company's net assets. **Why it matters:** Central to classic Graham-style value investing. A P/B below 1.0 means the market is pricing the company below its accounting net worth — either because the assets are impaired, the business is in decline, or the market is mispricing the stock. The Piotroski F-Score was specifically designed to identify high-quality companies within the low P/B universe. **Screener applications:** [Net-Net Stocks Screen](https://www.geminiq.com/screens/net-net-stocks), [Piotroski F-Score Screen](https://www.geminiq.com/screens/piotroski-f-score) ### EV/EBITDA (Enterprise Value to EBITDA TTM) **What it measures:** Enterprise value (market cap + debt - cash) divided by trailing twelve-month EBITDA. A capital-structure-neutral valuation multiple. **Why it matters:** EV/EBITDA adjusts for leverage differences between companies, making it the preferred valuation metric for comparing companies with different debt levels. It's also the primary metric used in M&A valuation. A low EV/EBITDA relative to peers suggests the stock may be undervalued — but high depreciation can make EBITDA overstate true economic earnings, so always check EV/EBIT alongside. **Screener applications:** [Low EV/EBITDA Screen](https://www.geminiq.com/screens/low-ev-ebitda) ### EV/EBIT (Enterprise Value to EBIT TTM) **What it measures:** Enterprise value divided by trailing twelve-month operating income (EBIT). Like EV/EBITDA but includes the depreciation and amortization charge. **Why it matters:** More conservative than EV/EBITDA because it accounts for the capital consumption embedded in D&A. A company where EV/EBIT and EV/EBITDA are close is asset-light; a company where they diverge significantly has heavy capital requirements. Joel Greenblatt's Magic Formula uses a variant of this metric (earnings yield = EBIT / EV). **Screener applications:** [Magic Formula Screen](https://www.geminiq.com/screens/magic-formula), [High Earnings Yield Screen](https://www.geminiq.com/screens/high-earnings-yield) ### Free Cash Flow Yield TTM **What it measures:** Free cash flow per share divided by the stock price. The cash return the business generates relative to what you're paying for it. **Why it matters:** FCF yield is the value investor's alternative to earnings yield. It measures actual cash generation — stripping out non-cash accounting charges — relative to the stock price. A high FCF yield means the business generates significant cash per dollar of market value. For Apple, FY2025 free cash flow of $98.8 billion against a roughly $3.5 trillion market cap yields approximately 2.8% — modest, but backed by extraordinary cash generation consistency. **Screener applications:** [High Free Cash Flow Yield Screen](https://www.geminiq.com/screens/high-fcf-yield), [Cash Rich Undervalued Screen](https://www.geminiq.com/screens/cash-rich-undervalued) ### Market Cap **What it measures:** Total market value of a company's outstanding equity. Share price multiplied by shares outstanding. **Why it matters:** Defines the size category of the investment. Market cap affects liquidity, analyst coverage, index inclusion, and institutional ownership patterns. Also the numerator in P/S and the equity component of enterprise value. ### Net Debt **What it measures:** Total debt minus cash and cash equivalents. A negative net debt means the company has more cash than debt — a net cash position. **Why it matters:** Net debt is the purest measure of balance sheet leverage. A company with $500M in market cap and ($300M) in net debt (net cash) is offering the operating business at an implied $200M. GeminIQ computes net debt from as-filed balance sheet data, preserving the distinction between cash, marketable securities, and restricted cash. **Screener applications:** [Cash Rich Undervalued Screen](https://www.geminiq.com/screens/cash-rich-undervalued), [Net-Net Stocks Screen](https://www.geminiq.com/screens/net-net-stocks) --- ## Profitability Metrics Profitability metrics tell you how efficiently a business converts revenue into returns for shareholders. They are the quality indicators — the metrics that distinguish businesses worth owning at a premium from those that are cheap for a reason. ### ROIC (Return on Invested Capital TTM) **What it measures:** Net operating profit after tax (NOPAT) divided by invested capital. The return the business earns on every dollar of capital deployed. **Why it matters:** ROIC is the single most important quality metric in value investing. A business that consistently earns ROIC above its cost of capital is creating value; one that doesn't is destroying it. Buffett's "wonderful business at a fair price" thesis is, at its core, about finding companies with high and sustainable ROIC. Apple's FY2025 ROIC of 85.4% reflects its extraordinary capital efficiency — massive earnings on a relatively small invested capital base. **Screener applications:** [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen), [High ROIC Low Debt Screen](https://www.geminiq.com/screens/high-roic-low-debt), [Quality Compounder Screen](https://www.geminiq.com/screens/quality-compounder), [Magic Formula Screen](https://www.geminiq.com/screens/magic-formula) ### ROE (Return on Equity TTM) **What it measures:** Net income divided by shareholders' equity. The return earned on the equity shareholders have invested. **Why it matters:** ROE measures how effectively management deploys shareholder capital. High ROE can indicate a great business — or it can indicate high leverage (low equity from heavy debt). Always check ROE alongside debt-to-equity to distinguish between operational quality and financial engineering. **Screener applications:** [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen), [Quality Compounder Screen](https://www.geminiq.com/screens/quality-compounder) ### ROA (Return on Assets TTM) **What it measures:** Net income divided by total assets. The return earned on all assets, regardless of how they're financed. **Why it matters:** ROA strips out leverage effects, making it useful for comparing companies with different capital structures. It also reveals the economic productivity of the asset base. In a DuPont decomposition, ROA = net profit margin × asset turnover — companies can achieve high ROA through high margins (luxury brands), high turnover (discount retailers), or a combination. **Screener applications:** [Efficient Asset Turnover Screen](https://www.geminiq.com/screens/efficient-asset-turnover), [Piotroski F-Score Screen](https://www.geminiq.com/screens/piotroski-f-score) ### Gross Profit Margin TTM **What it measures:** Gross profit divided by revenue. The percentage of revenue retained after direct production costs. **Why it matters:** Gross margin is the first measure of pricing power. A company with consistently high gross margins has either a differentiated product, a strong brand, or a cost advantage. Gross margin trends — especially quarter-over-quarter changes visible in 10-Q data — are the earliest indicator of competitive pressure or pricing strength. Apple's blended gross margin of 46.9% in FY2025 reflects the mix between Products (36.8%) and Services (75.4%). **Screener applications:** [GARP Screen](https://www.geminiq.com/screens/garp-screen), [Quality Compounder Screen](https://www.geminiq.com/screens/quality-compounder), [Contrarian Low P/S Screen](https://www.geminiq.com/screens/contrarian-low-ps) ### Operating Profit Margin TTM **What it measures:** Operating income divided by revenue. The percentage of revenue remaining after all operating expenses (COGS, R&D, SG&A) but before interest and taxes. **Why it matters:** Operating margin measures the profitability of the core business — stripped of capital structure (interest) and tax jurisdiction effects. Expanding operating margins alongside revenue growth is the highest-quality earnings pattern. **Screener applications:** [Low Debt High Growth Screen](https://www.geminiq.com/screens/low-debt-high-growth) ### Net Profit Margin TTM **What it measures:** Net income divided by revenue. The percentage of revenue that flows to the bottom line after all expenses. **Why it matters:** The final measure of profitability. Comparing net margin to operating margin reveals the impact of interest expense and taxes — useful for assessing how leverage and tax planning affect shareholder returns. ### Stock Compensation to Revenue TTM **What it measures:** Share-based compensation expense as a percentage of revenue. **Why it matters:** A high-ROIC technology company with 25% SBC-to-revenue has a very different economic picture than one with 2% — even if the income statement looks identical. SBC is a real dilutive cost. This metric lets you quantify it. Apple's SBC of $12.9 billion in FY2025 represents approximately 3.1% of revenue — moderate for a tech company. --- ## Growth Metrics Growth metrics measure the trajectory. A company can be cheap and profitable today, but if revenue and earnings are declining, the current valuation may be justified — or even too high. ### Revenue Growth (1-Year and 3-Year TTM) **What it measures:** Year-over-year and three-year trailing revenue growth rates. **Why it matters:** Revenue growth is the top-line signal. Is the market the company serves expanding? Is the company gaining or losing share? Three-year growth smooths out one-time effects and gives a more sustainable view of the trajectory. | **[Revenue Growth 3Y →](https://www.geminiq.com/metrics/growth-metrics/revenue-growth)** **Screener applications:** [GARP Screen](https://www.geminiq.com/screens/garp-screen), [Low Debt High Growth Screen](https://www.geminiq.com/screens/low-debt-high-growth) ### Net Income Growth (1-Year and 3-Year TTM) **What it measures:** Year-over-year and three-year trailing net income growth. **Why it matters:** Earnings growth drives valuation over time. Compare earnings growth to revenue growth: if earnings are growing faster than revenue, margins are expanding. If slower, margins are compressing. The gap tells you the quality of the growth. | **[Net Income Growth 3Y →](https://www.geminiq.com/metrics/growth-metrics/net-income-growth)** **Screener applications:** [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen) ### EPS Growth (1-Year and 3-Year TTM) **What it measures:** Year-over-year and three-year trailing earnings per share growth. Includes the effect of share buybacks (which reduce the share count and boost per-share earnings even when total earnings are flat). **Why it matters:** EPS is what shareholders actually receive per share. Apple's FY2025 EPS grew 22.7% while net income grew 19.5% — the 3+ point gap was entirely driven by the buyback program. EPS growth is the metric most directly correlated with stock price appreciation over time. | **[EPS Growth 3Y →](https://www.geminiq.com/metrics/growth-metrics/earnings-per-share-growth)** **Screener applications:** [GARP Screen](https://www.geminiq.com/screens/garp-screen) ### Dividends Paid Growth (3-Year TTM) **What it measures:** Three-year growth rate in total dividends paid. **Why it matters:** For income investors, dividend growth rate is more important than current yield. A company growing dividends at 8–10% annually will double its payout within a decade. Sustainable dividend growth requires underlying earnings and cash flow growth. **Screener applications:** [Dividend Growth Screen](https://www.geminiq.com/screens/dividend-growth-screen) ### Deferred Revenue Growth (1-Year) **What it measures:** Year-over-year growth in deferred revenue — cash collected for services not yet delivered. **Why it matters:** A leading indicator of future recognized revenue, particularly for subscription and SaaS businesses. Growing deferred revenue means the contracted revenue pipeline is expanding — a positive signal that appears on the balance sheet before it shows up on the income statement. --- ## Leverage Metrics Leverage metrics measure financial risk. A great business financed with too much debt can become a bad investment if cash flows decline and debt service becomes burdensome. ### Debt-to-Equity **What it measures:** Total debt divided by total shareholders' equity. The ratio of borrowed money to owner's money. **Why it matters:** The primary leverage gauge. A ratio above 1.0 means the company has more debt than equity. Conservative value investors typically screen for ratios below 0.5. However, context matters: capital-light businesses (like Apple) can operate efficiently with higher leverage because their cash flows comfortably cover debt service. **Screener applications:** [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen) (≤ 0.5), [High ROIC Low Debt Screen](https://www.geminiq.com/screens/high-roic-low-debt) (≤ 0.3) ### Debt Ratio **What it measures:** Total liabilities divided by total assets. The percentage of assets financed by debt and other obligations. **Why it matters:** A broader measure than debt-to-equity because it includes all liabilities, not just funded debt. A debt ratio below 50% means shareholders own more than half the company's assets. **Screener applications:** [Low Debt High Growth Screen](https://www.geminiq.com/screens/low-debt-high-growth), [Altman Z-Score Screen](https://www.geminiq.com/screens/altman-z-score-safe) ### Interest Coverage TTM **What it measures:** EBIT divided by interest expense. How many times the company's operating income covers its interest payments. **Why it matters:** The margin of safety for debt service. Interest coverage below 3.0 is concerning for most industries; below 1.5 is a warning sign. A company with 10x+ interest coverage can comfortably service its debt even if earnings decline substantially. ### Current Ratio **What it measures:** Current assets divided by current liabilities. A snapshot of short-term liquidity. **Why it matters:** A current ratio above 1.0 means the company can cover its short-term obligations with short-term assets. Below 1.0 means it depends on future cash flow or refinancing. Apple's current ratio of 0.89 looks concerning in isolation but is perfectly manageable given $111.5 billion in annual operating cash flow. **Screener applications:** [Net-Net Stocks Screen](https://www.geminiq.com/screens/net-net-stocks) (≥ 2.0), [Cash Rich Undervalued Screen](https://www.geminiq.com/screens/cash-rich-undervalued) (≥ 1.5) ### Dilution Ratio **What it measures:** Net change in diluted share count — tracking whether share count is increasing (dilution from SBC) or decreasing (net buyback activity). **Why it matters:** A company repurchasing $500M in shares annually but issuing $300M through SBC has a net buyback of only $200M. The dilution ratio captures this net effect, distinguishing companies with genuine shrinking share counts from those where buybacks merely offset dilution. **Screener applications:** [Shareholder Yield Screen](https://www.geminiq.com/screens/shareholder-yield) (≤ 0, indicating net buyback) --- ## Efficiency Metrics Efficiency metrics measure how well the business converts its assets and operations into revenue and cash. ### Asset Turnover TTM **What it measures:** Revenue divided by total assets. How many dollars of revenue each dollar of assets generates. **Why it matters:** One leg of the DuPont decomposition. A high asset turnover means the business is capital-efficient — it generates significant revenue per dollar invested. Retailers and distributors tend to have high turnover; capital-intensive industrials and utilities tend to have low turnover. **Screener applications:** [Efficient Asset Turnover Screen](https://www.geminiq.com/screens/efficient-asset-turnover) ### Receivables Turnover TTM **What it measures:** Revenue divided by accounts receivable. How quickly the company collects from customers. **Why it matters:** Declining receivables turnover (receivables growing faster than revenue) can signal deteriorating collection efficiency, customer credit stress, or aggressive revenue recognition. Apple's receivables jumped 19% in FY2025 while revenue grew 6.4% — a divergence that only shows up if you track this ratio. ### Inventory Turnover TTM **What it measures:** Cost of goods sold divided by average inventory. How quickly the company sells through its inventory. **Why it matters:** Rising inventory relative to COGS can signal demand weakness. Falling inventory can signal either efficiency improvements or supply chain constraints. Apple's inventories fell 22% in FY2025 — driven by the iPhone 17 product transition. ### Payables Turnover TTM **What it measures:** Cost of goods sold divided by accounts payable. How quickly the company pays its suppliers. **Why it matters:** A lower payables turnover (paying suppliers more slowly) can be a sign of negotiating power — the company is effectively borrowing from its supply chain at zero cost. Apple's massive payables balance reflects its dominant position with component suppliers. ### Deferred Revenue to Revenue **What it measures:** Deferred revenue as a percentage of trailing revenue. **Why it matters:** For subscription businesses, a high ratio means a large portion of future revenue is already contracted and collected as cash. It's a balance sheet indicator of revenue quality and forward visibility. --- ## Dividend Metrics ### Dividend Yield TTM **What it measures:** Annual dividends per share divided by the stock price. **Why it matters:** The current income return on the investment. A yield of 3% means you receive $3 in annual dividends for every $100 invested. But yield alone is insufficient — a very high yield often signals an impending dividend cut. **Screener applications:** [Dividend Growth Screen](https://www.geminiq.com/screens/dividend-growth-screen) (≥ 1.5%), [Shareholder Yield Screen](https://www.geminiq.com/screens/shareholder-yield) ### Payout Ratio TTM **What it measures:** Dividends paid divided by net income. The percentage of earnings distributed as dividends. **Why it matters:** A payout ratio above 80% means the company is distributing most of its earnings, leaving little for reinvestment. Above 100% means the dividend exceeds earnings — sustainable only temporarily via cash reserves or debt. Apple's FY2025 payout ratio of 13.8% is conservative, reflecting that the vast majority of capital return comes through buybacks, not dividends. **Screener applications:** [Dividend Growth Screen](https://www.geminiq.com/screens/dividend-growth-screen) ### Treasury Stock Change (1-Year) **What it measures:** Year-over-year change in treasury stock — a proxy for net buyback activity. **Why it matters:** A declining share count through buybacks is a form of shareholder return that doesn't create tax events (unlike dividends). Tracking treasury stock changes reveals the magnitude of the buyback program. **Screener applications:** [Shareholder Yield Screen](https://www.geminiq.com/screens/shareholder-yield) --- ## Financial Health Metrics ### Altman Z-Score **What it measures:** A composite score using five financial ratios (working capital/assets, retained earnings/assets, EBIT/assets, market cap/total liabilities, revenue/assets) that predicts the likelihood of bankruptcy within two years. **Why it matters:** Developed by Edward Altman in 1968, the Z-Score remains one of the most reliable quantitative measures of financial distress. A score above 3.0 indicates a healthy company; between 1.81 and 2.99 is a gray zone; below 1.81 indicates distress. GeminIQ computes all five components (labeled Altman A through Altman E) directly from as-filed data. **Screener applications:** [Altman Z-Score Financial Safety Screen](https://www.geminiq.com/screens/altman-z-score-safe) --- ## The 18 Pre-Built Screeners GeminIQ provides 18 pre-built screener strategies that combine these metrics into established investment frameworks. Each screener page explains the strategy's intellectual history, the specific filter criteria, how to run it in GeminIQ, and what aggregator data misses for that particular screen: | Screen | Core Metrics | Strategy | |--------|-------------|----------| | [Buffett-Style Screen](https://www.geminiq.com/screens/buffett-style-screen) | ROIC, ROE, D/E, Earnings Growth, P/E | Quality at a fair price | | [Magic Formula](https://www.geminiq.com/screens/magic-formula) | EV/EBIT, ROIC | Greenblatt's earnings yield + capital efficiency | | [GARP Screen](https://www.geminiq.com/screens/garp-screen) | P/E, EPS Growth, Revenue Growth | Growth at a reasonable price | | [Deep Value Screen](https://www.geminiq.com/screens/deep-value-screen) | P/E, P/B, EV/EBITDA | Classic deep value | | [High ROIC Low Debt](https://www.geminiq.com/screens/high-roic-low-debt) | ROIC, D/E | Capital-efficient, conservative balance sheet | | [Quality Compounder](https://www.geminiq.com/screens/quality-compounder) | ROIC, ROE, Gross Margin, Revenue Growth | Durable compounders | | [High Free Cash Flow Yield](https://www.geminiq.com/screens/high-fcf-yield) | FCF Yield, D/E | Cash generators | | [Net-Net Stocks](https://www.geminiq.com/screens/net-net-stocks) | Current Ratio, P/B | Graham-style asset bargains | | [Piotroski F-Score](https://www.geminiq.com/screens/piotroski-f-score) | ROA, Operating CF, D/E, Margins | Financial strength within low P/B universe | | [Altman Z-Score Safe](https://www.geminiq.com/screens/altman-z-score-safe) | Altman Z-Score, Debt Ratio | Financial health and stability | | [Low EV/EBITDA](https://www.geminiq.com/screens/low-ev-ebitda) | EV/EBITDA | Cheapest on enterprise value basis | | [High Earnings Yield](https://www.geminiq.com/screens/high-earnings-yield) | EV/EBIT | Highest operating earnings yield | | [Dividend Growth Screen](https://www.geminiq.com/screens/dividend-growth-screen) | Dividend Yield, Payout Ratio, Dividend Growth | Sustainable and growing dividends | | [Shareholder Yield](https://www.geminiq.com/screens/shareholder-yield) | Dividend Yield, Dilution Ratio, Treasury Stock Change | Total return to shareholders | | [Cash Rich Undervalued](https://www.geminiq.com/screens/cash-rich-undervalued) | Net Debt, FCF Yield, Current Ratio | Net cash balance sheets | | [Low Debt High Growth](https://www.geminiq.com/screens/low-debt-high-growth) | D/E, Revenue Growth, Operating Margin | Conservative growth | | [Efficient Asset Turnover](https://www.geminiq.com/screens/efficient-asset-turnover) | Asset Turnover, ROA | Operational efficiency | | [Contrarian Low P/S](https://www.geminiq.com/screens/contrarian-low-ps) | P/S, Gross Margin, Revenue Growth | Revenue-based contrarian value | Every screener result on GeminIQ traces to XBRL-tagged source data. When a company passes your screen, you can verify every input in the original filing. --- ## Why the Data Source Matters for Metrics Every metric in this guide is a formula applied to underlying financial data. If the inputs have been normalized — debt instruments merged, line items reclassified, cash flows combined — the metric inherits those changes. An ROIC calculated from normalized invested capital will differ from one calculated from as-filed data. A free cash flow yield that includes equity settlement taxes in the buyback figure will show a different number than one that separates them. GeminIQ computes every metric from XBRL-tagged inputs, sourced directly from SEC EDGAR. The inputs are the numbers the company filed. The formula is transparent. The result is verifiable. This is what it means to have [auditable metrics](https://www.geminiq.com/features#calculated-metrics). --- ## Frequently Asked Questions **How many total metrics can I screen with on GeminIQ?** The GeminIQ Stock Screener supports 100+ filterable metrics, including the 50+ calculated KPIs described in this guide and the underlying raw financial line items from the XBRL-tagged data. **How often are metrics updated?** Metrics are recalculated whenever new filing data is processed. New 10-K and 10-Q filings are ingested overnight (T+1), so metrics reflect the most recent filing by the next trading day. **Can I build custom metric combinations?** Yes. The [Stock Screener](https://www.geminiq.com/features#screener) supports up to 10 stackable conditions with precise operators (greater than, less than, between). You can combine any metrics from any category to build a custom screening strategy. The [Custom Tables](https://www.geminiq.com/features#custom-tables) feature lets you build reusable data templates that pull specific metrics for comparison. **What happens when a metric can't be calculated?** Some metrics require inputs that not all companies report — for example, inventory turnover requires an inventory figure, which pure-service companies don't have. When an input is missing from the filing, GeminIQ either omits the metric for that company or flags it as not applicable. --- ## The Bottom Line Financial metrics are only as good as the data behind them. A ROIC calculated from normalized data that merged three debt instruments into two will be different from one calculated from as-filed data. A free cash flow yield built on a buyback figure that includes tax payments will overstate the apparent cash return. GeminIQ calculates every metric from XBRL-tagged SEC filing data — no aggregator, no normalization, no proprietary taxonomy. The inputs match the filing. The formulas are transparent. Every number is traceable. Use this guide as your reference. Use the [screeners](https://www.geminiq.com/features#screener) to find opportunities. Use the [financial statements](https://www.geminiq.com/features#financial-statements) to verify the data. And use the [Earnings Market Reaction Heatmap](https://www.geminiq.com/features#price-variance), [insider transactions](https://www.geminiq.com/features#insider-transactions), and [institutional ownership](https://www.geminiq.com/features#institutional-ownership) to layer behavioral signals on top of the fundamentals. --- ## Section 12: The Data Pipeline source: https://www.geminiq.com/blog/Data_Pipeline_What_Gets_Lost ### How Financial Data Flows from the SEC to Your Screen — And What Gets Lost (2026) 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. Here's how the pipeline actually works, stage by stage, with documented examples of what gets lost at each step. --- ## 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 aggregators 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](https://www.geminiq.com/blog/Third_Party_Data_Miss) 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 [50+ calculated metrics](https://www.geminiq.com/features#calculated-metrics), [interactive visualizations](https://www.geminiq.com/features#visualizations), and a [screener](https://www.geminiq.com/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. --- ## 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, free cash flow yield, 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](https://www.geminiq.com/features#screener) lets you find companies worth analyzing. The XBRL-tagged [financial statements](https://www.geminiq.com/features#financial-statements) let you analyze them with data you can trust. And the [Custom Tables](https://www.geminiq.com/features#custom-tables), [Earnings Market Reaction Heatmap](https://www.geminiq.com/features#price-variance), [Insider Transaction Timeline](https://www.geminiq.com/features#insider-transactions), and [Institutional Ownership](https://www.geminiq.com/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](https://www.geminiq.com/blog/Third_Party_Data_Miss) 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. --- ## Section 13: Earnings Reaction Patterns source: https://www.geminiq.com/blog/Earnings_Reaction_Patterns ### Earnings Reaction Patterns: A 17-Year Analysis of How Stocks Behave After SEC Filings (2026) 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? 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](https://www.geminiq.com/features#price-variance) and [XBRL-tagged financial statements](https://www.geminiq.com/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. --- ## 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](https://www.geminiq.com/features#price-variance) exists alongside XBRL-tagged [financial statements](https://www.geminiq.com/features#financial-statements) and [calculated metrics](https://www.geminiq.com/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 | 50% | **+75.5%** | | 2012 | $156.5B | +45% | +59% | 43.9% | +3.4pp | 49% | **-17.0%** | | 2013 | $170.9B | +9% | -10% | 37.6% | -6.2pp | 32% | +37.4% | | 2015 | $233.7B | +28% | +43% | 40.1% | +1.5pp | 43% | -3.5% | | 2016 | $215.6B | -8% | -10% | 39.1% | -1.0pp | 29% | **+33.7%** | | 2019 | $260.2B | -2% | -0.4% | 37.8% | -0.5pp | 32% | **+82.3%** | | 2020 | $274.5B | +6% | +11% | 38.2% | +0.4pp | 40% | +35.8% | | 2021 | $365.8B | +33% | +71% | 41.8% | +3.5pp | 66% | **+1.0%** | | 2023 | $383.3B | -3% | +0.1% | 44.1% | +0.8pp | 69% | +29.6% | | 2024 | $391.0B | +2% | -0.8% | 46.2% | +2.1pp | 69% | +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 49%. 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 40% to 66%. 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](https://www.geminiq.com/demo/research), showing every filing's 1-through-12-month return alongside the [XBRL-tagged financial statements](https://www.geminiq.com/features#financial-statements) and [50+ calculated metrics](https://www.geminiq.com/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% | 19% | **+49.0%** | | 2016 | $38.5B | -13% | -103% (loss) | 26.5% | 3% | **+75.7%** | | 2019 | $53.8B | -2% | +4% | 31.9% | 89% | **+45.5%** | | 2024 | $64.8B | -3% | +10% | 38.0% | 74% | **+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 3%.** 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 48% — 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 improving from 40% to 32% as the business scaled. | FY | Revenue | Rev Growth | EPS Growth | Op Margin | ROIC | 12M Return | |---|---|---|---|---|---|---| | 2016 | $85.3B | -9% | +42% | 23.7% | 14% | +29.8% | | 2019 | $125.8B | +14% | +138% | 34.1% | 22% | **+44.0%** | | 2021 | $168.1B | +18% | +40% | 41.6% | 31% | **-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](https://www.geminiq.com/screeners/dividend-growth-screen), 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 17-25%. 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](https://www.geminiq.com/features#insider-transactions) and the filing's own [risk factors](https://www.geminiq.com/blog/How_to_10-K_Apple) 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](https://www.geminiq.com/blog/How_to_10-K_Apple)) 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](https://www.geminiq.com/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](https://www.geminiq.com/features#financial-statements) and [calculated metrics](https://www.geminiq.com/features#calculated-metrics) to assess the fundamentals: [revenue growth](https://www.geminiq.com/metrics/net_revenue_ttm_growth_1y), [margin trends](https://www.geminiq.com/metrics/gross_profit_margin_ttm), [ROIC](https://www.geminiq.com/metrics/roic_ttm), [free cash flow](https://www.geminiq.com/metrics/free_cash_flow_yield_ttm). 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](https://www.geminiq.com/features#insider-transactions) — are insiders buying the dip? Check [institutional ownership](https://www.geminiq.com/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](https://www.geminiq.com/features#screener) lets you filter for companies with strong underlying quality — high [ROIC](https://www.geminiq.com/metrics/roic_ttm), conservative [leverage](https://www.geminiq.com/metrics/debt_to_equity), growing [free cash flow](https://www.geminiq.com/metrics/free_cash_flow_yield_ttm) — that may be temporarily mispriced after a "weak" filing. The [Buffett-Style Screen](https://www.geminiq.com/screeners/buffett-style-screen) and [Quality Compounder Screen](https://www.geminiq.com/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 50+ 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. --- ## Section 14: GeminIQ in Use — Sector Analysis ### GeminIQ in Use — Defense Sector source: https://www.geminiq.com/blog/Intel_Brief_Defense_Sector ### The GeminIQ Intel Brief: Finding the Signal in the Defense Sector Discover how to use GeminIQ's deep-dive financial and institutional data to cut through the noise and uncover the true fundamental powerhouse among defense sector titans. If you are evaluating high-growth tech or volatile consumer brands, finding a clear winner is usually just a matter of looking at **top-line revenue growth**. The discrepancies between competitors are massive and obvious. But what happens when you need to analyze mature companies that operate in the exact same, highly regulated environment? Welcome to the defense sector. When you look at prime contractors like **Lockheed Martin (LMT)**, **Northrop Grumman (NOC)**, and **General Dynamics (GD)**, their core businesses are almost identical. To find the alpha, you have to run a strict, multi-layered "comps" analysis. You can't just look at high-level ratios; you have to rip open the underlying financial statements. Here is how a real analyst uses GeminIQ to strip away the PR spin, deconstruct the balance sheet, and rank the defense titans. ### Phase 1: The Efficiency Illusion Investing in a vacuum is a massive risk. In GeminIQ, our workflow starts by creating a custom **[Watchlist](https://www.geminiq.com/features#custom-watchlists)** to aggregate LMT, NOC, and GD side-by-side. We start by pulling up the **[Calculated Metrics](https://www.geminiq.com/features#calculated-metrics)** tab to compare fundamental performance. Immediately, a clear hierarchy emerges across multiple key indicators: * **Return on Invested Capital (ROIC):** Lockheed Martin (LMT) looks like a capital efficiency machine. Its ROIC sits at a **massive 25.1%**. Meanwhile, General Dynamics (GD) and Northrop Grumman (NOC) are lagging significantly behind, posting ROIC metrics of 13.5% and 12.7%, respectively. * **Free Cash Flow (FCF):** The cash generation story paints the exact same picture. By the end of 2025, LMT was generating a staggering **$6.9 billion** in Trailing Twelve Month (TTM) Free Cash Flow. GD ($3.96 billion) and NOC ($3.3 billion) are barely producing half of that. * **Dividend Yield:** LMT's massive cash generation is translating directly to investors, boasting a **2.78% yield** that easily outpaces GD (1.76%) and NOC (1.58%). * **Price-to-Earnings (P/E):** Here is the kicker. Despite LMT producing nearly double the cash and capital efficiency of its rivals, the market isn't charging a massive premium for it. All three defense primes are trading in a surprisingly tight P/E band—**LMT at 22.4x, GD at 21.4x, and NOC at 19.6x.** If we only looked at a standard stock screener, the analysis would be over. Lockheed Martin appears to be executing at a vastly superior level, printing cash, and generating massive capital returns—all for roughly the same valuation multiple as its peers. But a good analyst knows that a calculated metric is just a math equation. To know if that 25% ROIC is a sign of operational excellence or a financial mirage, we have to look at the denominator. ### Phase 2: The Balance Sheet Reality Check We pivot our dashboard away from the calculated metrics and pull up the raw **[Balance Sheet](https://www.geminiq.com/features#financial-statements)** data for the end of 2025. This is where Lockheed's "efficiency" narrative falls apart. Lockheed Martin isn't necessarily running a better underlying business; they are just running a **heavily leveraged** one. * **Lockheed Martin (LMT):** LMT is sitting on nearly $60 billion in Total Assets, but they have stacked up **$53.1 billion in Total Liabilities** (including over $20.5 billion in long-term debt). That leaves them with a razor-thin equity base of just **$6.7 billion**. When your equity is that small, any profit makes your returns (like ROIC and ROE) look artificially explosive. * **General Dynamics (GD):** Now we pull up GD’s balance sheet. It is a fortress. Against $57.2 billion in assets, GD holds a massive **$25.6 billion in Total Equity**, weighed against just $7 billion in long-term debt. General Dynamics isn't less efficient than Lockheed; they are just operating with a vastly safer, **de-risked capital structure**. ### Phase 3: Following the Smart Money (Institutions) Now that we have ripped open the balance sheet, we need to see how the market is pricing these two wildly different capital structures. We use GeminIQ’s **[Institutional Ownership](https://www.geminiq.com/features#institutional-ownership)** module to follow the "smart money." The divergence is glaring, but now it makes perfect sense. Wall Street is heavily underweighting the high-ROIC Lockheed Martin, holding just **71.3% of shares**. Meanwhile, the big funds are crowding into General Dynamics, commanding a **massive 84.39% institutional ownership rate**. In an uncertain macroeconomic environment, the massive funds aren't chasing Lockheed's debt-fueled ROIC; they are paying a premium for General Dynamics' pristine, low-leverage balance sheet. ### Phase 4: The Insider Profit Taking We have our thesis: GD is the safest, most structurally sound asset on the board. But a good analyst always checks for red flags. We jump over to GeminIQ’s **[Insider Transactions](https://www.geminiq.com/features#insider-transactions)** data. Throughout 2025, GD's C-suite initiated a staggering sell-off. CEO Phebe Novakovic alone unloaded **over 130,000 shares**, including a massive 129,090-share dump in August. A retail investor sees that insider selling and panics. But by tying our analysis together with GeminIQ’s historical **[Price Variance](https://www.geminiq.com/features#price-variance)** data, we see the real story. At the end of 2024, GD was trading around $257. By Q3 2025, Wall Street's institutional crowding had pushed the stock **past $338**. The executives weren't abandoning a broken company; they were aggressively monetizing a **massive 30% run-up** fueled by their own stellar balance sheet management. ### The Analyst's Verdict By actively jumping from high-level metrics, down into the raw balance sheet, and cross-referencing with institutional sentiment, our comparable company analysis completely shifted the narrative. A surface-level screener will tell you to buy Lockheed Martin for its 25% ROIC. But GeminIQ's deep-dive data reveals that **General Dynamics is the true fundamental powerhouse**, boasting a fortress balance sheet that the smartest money on Wall Street is aggressively accumulating. --- ### GeminIQ in Use — Retail Sector source: https://www.geminiq.com/blog/Intel_Brief_Retail_Sector ### The GeminIQ Intel Brief: The Retail Sector's Inventory Trap and the ROIC Mirage Gross margins are deceiving. Dive into the balance sheets of Home Depot, Lowe's, and Tractor Supply to uncover the retail sector's hidden ROIC mirages and inventory bloat. If you are evaluating the retail sector in 2026, you already know the market is facing a massive "standards reset." With consumers becoming hyper-selective and foot traffic shifting from automatic to deliberate, top-line revenue is rapidly becoming a vanity metric. But how do you spot the real winners when mature companies are all operating in the exact same, highly competitive macroeconomic environment? Welcome to the big-box retail sector. When you look at giants like **Home Depot (HD)**, **Lowe's (LOW)**, and **Tractor Supply Co. (TSCO)**, their core businesses are practically identical. To find the alpha, you have to run a strict, multi-layered "comps" analysis. You can't just look at high-level profit margins; you have to rip open the underlying efficiency metrics and deconstruct the balance sheet. Here is how a real analyst uses GeminIQ to strip away the PR spin, uncover the inventory trap, and rank the retail titans. ### Phase 1: The Top-Line Illusion Investing in a vacuum is a massive risk. In GeminIQ, our workflow starts by creating a custom **[Watchlist](https://www.geminiq.com/features#custom-watchlists)** to aggregate HD, LOW, and TSCO side-by-side. *GeminIQ custom Watchlist displaying Home Depot (HD), Lowe's (LOW), and Tractor Supply Co. (TSCO) side-by-side.* We start by pulling up the **[Calculated Metrics](https://www.geminiq.com/features#calculated-metrics)** tab to compare fundamental performance. Immediately, a clear illusion emerges across their valuation and profit margins: *GeminIQ custom comps view highlighting Gross Profit Margins, Days Inventory Outstanding (DIO), Price-to-Earnings (P/E), and Return on Invested Capital (ROIC) across the retail tickers.* * **Valuation (P/E):** The market is treating these companies as near equals. Home Depot trades at 26.1x, Tractor Supply at 24.1x, and Lowe's at 19.5x. * **Gross Profit Margin:** On the surface, all three retailers appear to be executing perfectly in lockstep. At the end of 2025, Home Depot and Lowe's were practically tied, boasting Gross Profit Margins of **33.3%** and **33.6%**, respectively. Tractor Supply actually leads the pack with a **36.4%** margin. If we only looked at a standard stock screener, the analysis would be over. The sector looks completely commoditized. But a good analyst knows that gross margin only tells you what a product sells for, not what it costs to keep it on the shelf. ### Phase 2: The Inventory Trap We pivot our dashboard away from the gross margins and pull up the **Days Inventory Outstanding (DIO)** and **Inventory Turnover** data for the end of 2025. This is where the retail narrative entirely splits. In retail, inventory is a liability disguised as an asset. If it sits on the shelf, it eats capital. *GeminIQ custom comps view highlighting Gross Profit Margins, Days Inventory Outstanding (DIO), Price-to-Earnings (P/E), and Return on Invested Capital (ROIC) across the retail tickers.* * **Home Depot (HD):** HD is a logistical machine. The data reveals they have a Days Inventory Outstanding (DIO) of just **81.9 days**, turning over their entire inventory base an impressive **4.5 times** a year. * **The Laggards:** Lowe's and Tractor Supply are secretly letting inventory pile up. LOW's DIO sits at a bloated **113.3 days** (turning inventory only 3.2 times a year). TSCO is similarly trapped with a DIO of **109.5 days** (turning inventory 3.3 times a year). Home Depot isn't just selling hardware; they are operating with vastly superior capital velocity, getting cash back into the business over a month faster than their direct competitors. ### Phase 3: The ROIC Mirage Faster inventory turnover should mean better returns. But when we look at **Return on Invested Capital (ROIC)**, the numbers look completely broken. Home Depot posts a massive **68.6% ROIC**. Tractor Supply sits at **27.9%**. But Lowe's models break completely, posting a technically impossible **negative 130.0% ROIC**. Why? To solve this, we use GeminIQ to rip open the **[Balance Sheet](https://www.geminiq.com/features#financial-statements)**. The data reveals a massive financial engineering illusion: *Lowe's raw balance sheet data revealing a massive liability load driving total equity negative.* * **Lowe's:** Lowe's has so aggressively bought back stock and leveraged their balance sheet that they are operating with **negative equity (-$10.4 billion)**. Their total liabilities ($63.8 billion) completely outpace their $53.5 billion in assets. When equity goes negative, ROIC calculation models break. *Home Depot's balance sheet showing a heavily leveraged structure masked by asset size.* * **Home Depot:** HD is playing the same leverage game. They have bought back a staggering **$96.0 billion in treasury stock**, shrinking their equity base down to just $12.8 billion against $105.1 billion in assets. By artificially shrinking their equity denominator, they mathematically inflate their ROIC to a "massive" 68.6%. *Tractor Supply Co.'s clean, traditional balance sheet with positive equity.* * **Tractor Supply:** TSCO is the only retailer operating a traditional, safe balance sheet ($10.9 billion in assets vs. $8.4 billion in liabilities). Their 27.9% ROIC is legitimate, unleveraged operational efficiency. ### Phase 4: Following the Smart Money (Institutions) Now that we have ripped open the balance sheet and exposed the ROIC mirage, we need to see how the market is pricing these differing capital structures. We use GeminIQ’s **[Institutional Ownership](https://www.geminiq.com/features#institutional-ownership)** module to follow the "smart money." When we look at the institutional flows side-by-side, a glaring divergence emerges. *GeminIQ Institutional Holdings view for Tractor Supply Co. showing heavy 93.67% total ownership.* *GeminIQ Institutional Holdings view for Lowe's showing 75.92% total ownership.* *GeminIQ Institutional Holdings view for Home Depot showing just 70.20% total ownership.* Wall Street is playing it aggressively safe. Massive funds are heavily crowding into Tractor Supply, claiming an **93.67%** ownership stake to hide in its clean, unleveraged balance sheet. They are also maintaining a strong **75.92%** position in Lowe's, perhaps blinded by the artificially engineered returns. But incredibly, institutions are entirely underweighting the true operational king. Home Depot has the lowest institutional backing of the group at just **70.20%**. Wall Street is completely missing HD's massive advantage in inventory velocity. ### Phase 5: The Insider Reality We have our thesis: Home Depot is moving inventory the fastest, Tractor Supply has the cleanest balance sheet, and Lowe's is bogging down in inventory while aggressively over-leveraging. We also know institutions are underweighting the best operator. But a good analyst always checks for the ultimate reality check: **What are the people running the company actually doing with their own money?** We jump over to GeminIQ’s **[Insider Transactions](https://www.geminiq.com/features#insider-transactions)** data to see how the executives are playing their hands. When a stock price is being propped up by financial engineering—like Lowe's massive, debt-fueled stock buybacks—the executives know the ceiling is approaching. And the data shows exactly that. Take a look at the sea of "Sale" transactions hitting the tape for Lowe's and Tractor Supply. The C-suites at the slower-moving retailers aren't waiting around for the inventory bloat to hit the bottom line; they are quietly taking heavy chips off the table. *GeminIQ Insider Transactions module highlighting recent share liquidations by Lowe's C-suite executives.* *GeminIQ Insider Transactions module showing Tractor Supply executives taking chips off the table.* Conversely, look at Home Depot. Despite playing a similar buyback game to Lowe's, their underlying operational engine—that lightning-fast 81.9 Day Inventory turn—is real. And the executives know it. The insider selling feed for Home Depot is practically crickets. The operators running the most efficient business are holding their equity tight. *GeminIQ Insider Transactions module showing little selling activity from Home Depot executives.* ### The Analyst's Verdict By actively jumping from high-level margins, down into the operational inventory metrics, ripping open the balance sheet structure, and verifying with institutional and insider flow data, our comparable company analysis completely shifted the narrative. A surface-level screener will tell you these three retailers are identical because their gross margins match. But GeminIQ's deep-dive data reveals that **Home Depot is the true operational powerhouse** dominating inventory velocity. Wall Street funds are underweighting it, but HD's C-suite's absolute refusal to sell shares proves they know their advantage is sustainable. Meanwhile, its peers are relying on massive financial engineering to keep up appearances while insiders rush for the exits. --- ### GeminIQ in Use — Airlines Sector source: https://www.geminiq.com/blog/Intel_Brief_Airlines ### The GeminIQ Intel Brief: The Airline Sector's Altman Stress Test A discounted valuation can be a massive value trap. Dive into the Altman Z-Scores of Delta, United, and American Airlines to expose the sector's hidden debt crisis. If you are evaluating the airline sector in 2026, you already know the market is facing a massive "standards reset." With corporate travel budgets tightening and consumers becoming hyper-selective with their discretionary income, top-line revenue is rapidly becoming a vanity metric. But how do you spot the real winners when mature companies are all operating in the exact same, highly cyclical macroeconomic environment? Welcome to the airline sector. When you look at giants like **Delta Air Lines (DAL)**, **United Airlines (UAL)**, and **American Airlines (AAL)**, their core business models are practically identical. To find the alpha in a capital-heavy industry, you aren't analyzing for growth; you are analyzing for survival. You can't just look at high-level valuations; you have to run a strict stress test on their balance sheets. Here is how a real analyst uses GeminIQ to strip away the PR spin, uncover the debt bloat, and rank the airline titans. ### Phase 1: The Valuation Disconnect Investing in a vacuum is a massive risk. In GeminIQ, our workflow starts by creating a custom **[Watchlist](https://www.geminiq.com/features#custom-watchlists)** to aggregate DAL, UAL, and AAL side-by-side. *GeminIQ custom Watchlist displaying Delta (DAL), United (UAL), and American Airlines (AAL) side-by-side.* We start by pulling up the **[Calculated Metrics](https://www.geminiq.com/features#calculated-metrics)** tab to compare fundamental performance. Immediately, a massive disconnect emerges in how the market is valuing these operations: * **The Leaders:** At the end of 2025, Delta led the pack with a commanding **$44.85 billion market cap**, fueled by a healthy **7.90% net profit margin**. United follows closely with a **$36.33 billion valuation** and a **5.68% margin**. * **The Value Trap:** American Airlines stands out entirely. It is trading at a heavily discounted **$10.12 billion market cap**, barely scraping by with an anemic **0.20% net profit margin**. *GeminIQ custom comps table.* *GeminIQ calculated metrics showing Market Cap across the airline tickers.* *GeminIQ calculated metrics showing Net Profit Margin (TTM) across the airline tickers.* If we only looked at a standard stock screener, a novice investor might assume AAL is a highly discounted "value play" waiting for a rebound. But a good analyst knows that a heavily suppressed market cap usually means the market is pricing in a massive underlying liability. ### Phase 2: The Debt Bloat We pivot our dashboard away from profitability and look at capital structure. In the airline industry, planes are financed with massive amounts of leverage. By looking at the **Net Debt** and **Debt-to-Equity** ratios, the reason for AAL's discounted valuation becomes terrifyingly clear. * **Delta & United:** DAL and UAL are managing their capital responsibly. Delta carries just $8.01 billion in net debt, operating with a manageable **2.90 Debt-to-Equity** ratio. United carries $14.62 billion in net debt (a **4.00 Debt-to-Equity** ratio). * **The Laggard:** American Airlines is operating with a completely broken capital structure. AAL is sitting on a staggering **$24.20 billion in net debt**. Worse, they have completely wiped out their equity base, operating with negative equity. Because their equity is less than zero, their Debt-to-Equity calculation breaks the model entirely, registering at a highly distressed **-17.57**. *GeminIQ custom view comparing Net Debt across the airline tickers.* *GeminIQ custom view comparing Debt-to-Equity ratios across the airline tickers.* American Airlines isn't just flying passengers; they are operating a highly leveraged debt vehicle trying to outrun its interest payments. ### Phase 3: The Altman Stress Test To see exactly how dangerous AAL's debt load is, we use GeminIQ to run an **Altman Z-Score** analysis. The Altman Z-Score is a legendary financial model used to predict corporate distress. Any score above 3.0 is safe. A score between 1.8 and 3.0 is the "gray zone." Anything below 1.8 indicates severe financial distress and high risk. * **Delta and United:** While the entire airline sector is capital intensive, DAL and UAL manage to keep their heads above water, posting Z-Scores of **1.44** and **1.37**, respectively. * **American Airlines:** AAL's model breaks down completely. Dragged down by massive liabilities and negative retained earnings, American Airlines posts an abysmal **0.66 Z-Score**, placing them deeply into the financial distress zone. *GeminIQ calculated metrics showing the Altman Z-Score distress levels for DAL, UAL, and AAL.* ### Phase 4: Following the Smart Money (Institutions) Now that we have exposed the debt mirage and the Z-Score distress, we need to see how the market is pricing these differing capital structures. We use GeminIQ’s **[Institutional Ownership](https://www.geminiq.com/features#institutional-ownership)** module to follow the "smart money." When we look at the institutional flows side-by-side, a glaring divergence emerges. Wall Street is playing it aggressively safe. Massive funds are heavily crowding into United and Delta, claiming **86.55%** and **83.10%** ownership stakes, respectively, to hide in their safer, unleveraged balance sheets. But institutions are actively avoiding the value trap. American Airlines has the lowest institutional backing of the group by a massive margin, sitting at just **69.48%**. Wall Street is completely aware of AAL's fragile Altman score and is refusing to hold the bag. *GeminIQ Institutional Holdings view for United Airlines showing heavy 86.55% total ownership.* *GeminIQ Institutional Holdings view for Delta Air Lines showing 83.10% total ownership.* *GeminIQ Institutional Holdings view for American Airlines showing just 69.48% total ownership.* ### Phase 5: The Insider Reality A good analyst always checks for the ultimate reality check: **What are the people running the company actually doing with their own money?** We jump over to GeminIQ’s **[Insider Transactions](https://www.geminiq.com/features#insider-transactions)** data to see how the executives are playing their hands. The C-suites across the sector aren't taking any chances with this macroeconomic environment. In the early months of 2026, we see a sea of "Sale" transactions hitting the tape. Delta insiders have sold millions of dollars in equity, United executives took heavy chips off the table in late 2025 and early 2026, and American Airlines management continues to steadily liquidate their holdings. When the operators running the businesses are selling into the cycle, investors need to be heavily scrutinizing the balance sheets. *GeminIQ Insider Transactions module highlighting recent share liquidations by Delta executives.* *GeminIQ Insider Transactions module highlighting recent share liquidations by United executives.* *GeminIQ Insider Transactions module highlighting recent share liquidations by American Airlines executives.* ### The Analyst's Verdict By actively jumping from a high-level valuation, down into the balance sheet structure, running a Z-Score distress model, and verifying with institutional flow data, our comparable company analysis completely shifted the narrative. A surface-level screener might show you a heavily discounted market cap for American Airlines, tempting novice value investors. But GeminIQ's deep-dive data reveals that **American Airlines is a financial house of cards** propped up by $24 billion in net debt. Wall Street funds are actively avoiding it, seeking shelter in the mathematically safer operations of Delta and United. --- ## Section 15: GeminIQ in Use — Company Deep-Dives ### Company Deep-Dive — Costco (COST) source: https://www.geminiq.com/blog/COST_2026-04-19 ### Costco ($COST): The 3.8% Margin Business Earning 42% on Capital Costco just filed its Q2 FY26 10-Q. The media obsesses over same-store sales. Value investors see a razor-thin retail margin hiding one of the highest ROIC engines in the S&P 500. **Costco Wholesale Corporation ($COST) just dropped its Q2 FY2026 10-Q (filed March 11, 2026), and the surface-level headlines look identical to every other quarter: thin margins, relentless same-store sales coverage, and another round of debate over whether the stock deserves a 50x P/E. Every financial commentator on TV frames Costco as a "low-margin grocer" and argues the premium valuation is irrational.** But standard financial media is looking at the wrong line. I used GeminIQ to audit the raw SEC data—cross-referencing the Income Statement, the Balance Sheet, Cash Flow, Insider Form 4s, and 13F Institutional Holdings. The real story is that Costco isn't a retailer at all. It is a subscription business wearing a warehouse as a disguise, and the raw filings reveal one of the most capital-efficient business models on the entire S&P 500. Here is the fundamental, data-driven truth behind the ticker. ## The 12.9% Gross Margin "Trap" If you screen Costco against any other major retailer, it looks structurally broken. Walmart operates at roughly 24% gross margin. Target sits in the high 20s. Even commodity grocers like Kroger clear 20%+. Costco, by contrast, posts a **12.87% gross margin TTM**—almost half of its closest competitors. **The Data:** On the Q2 FY26 10-Q, Costco posted **$69.60 Billion** in quarterly Revenues against **$60.72 Billion** in Cost of Goods Sold, leaving just **$6.27 Billion** in SG&A and **$2.61 Billion** in Operating Income for the quarter. On a TTM basis, revenue climbs to **$292.66 Billion**, operating income to **$11.02 Billion**—good for a **3.76% operating margin**. **The GeminIQ Edge:** A standard screener flags this as a red flag. By pulling the raw Income Statement quarter-by-quarter via GeminIQ's Custom Table, we can see Costco is *intentionally* running the thinnest possible gross margin. This isn't weakness—it's the moat. Management prices merchandise at near-breakeven specifically to drive the metric that actually matters: member renewals. The merchandise business is a loss-leader for the real product.
GeminIQ Custom Table pulling raw quarterly Income Statement line items from Costco's recent 10-Q filings. The Q2 FY26 quarter shows $69.6B in Revenue converting to just $2.6B in Operating Income—a structurally thin margin that appears broken until you understand the membership engine behind it.
## The ROIC Paradox (The Real Engine) Here is where the screener lies completely. A 3.76% operating margin business should, mathematically, earn a pedestrian return on capital. Instead, Costco is earning a staggering return that dwarfs nearly every other mega-cap in the market. **The Data:** Using GeminIQ's raw balance sheet and income statement, Costco is operating on roughly **$20 Billion in Invested Capital** while generating a TTM **Return on Invested Capital of 42.68%**. Return on Equity comes in at **29.32%**. For context, that ROIC beats Microsoft, crushes Walmart, and rivals the capital efficiency of software-only businesses. The visualization shows ROIC has been running consistently in the 35-45% range for years, with a pandemic-era spike above 50% in late 2020 when inventory turned at a historic pace. **The GeminIQ Edge:** Standard aggregators show you the 3.76% operating margin and ignore the capital base. By auditing raw NOPAT against Invested Capital in GeminIQ's Interactive Financial Visualizations, we can see exactly how the trick works: Costco doesn't need much capital because *the members are funding the operation*. Suppliers are paid on 30+ day terms using inventory that already sold. Members pay upfront. The capital base stays microscopic relative to the revenue flowing through it.
GeminIQ Interactive Financial Visualizations displaying Costco's ROIC TTM trajectory from 2018 through Q2 FY26. ROIC has run consistently in the high-30s to mid-40s for years, with a COVID-era spike above 50%, settling at 42.68% today—elite capital efficiency the "low-margin grocer" narrative completely ignores.
## The $3.1 Billion Float (Warren Buffett's Favorite Word) So where does the ROIC come from? The balance sheet tells you exactly. Scroll down the Q2 FY26 10-Q liabilities section and you find a line that most retail investors never click on: **Deferred Membership Fees**. This is the annual membership payment members have already handed over—in cash, upfront—that Costco has not yet recognized as revenue. It is, in accounting terms, a liability. In economic terms, it is free capital. **The Data:** Deferred Membership Fees on the balance sheet have grown from roughly **$1.6 Billion** in FY2018 to **$3.13 Billion** in Q2 FY26. That is nearly a **doubling** of the interest-free cash float members are fronting to Costco over the last eight years. Every year, that pile grows. Costco earns interest on it sitting in Treasuries (contributing to the $589M in Interest Income on the TTM Income Statement) while the merchandise business breakeven pays for the staff and the lights. **The GeminIQ Edge:** Most financial sites never surface deferred membership fees as a distinct metric. By auditing the raw Balance Sheet quarter-over-quarter in GeminIQ, you can see the float compound every single quarter for eight straight years. This is the same mechanism Warren Buffett describes when he praises insurance "float"—members are Costco's policyholders, and they just keep sending bigger checks.
GeminIQ Interactive Financial Visualization tracking the Deferred Revenue Current balance sheet line (reported by Costco as "Deferred Membership Fees") from FY18 through Q2 FY26. The liability is actually pre-paid cash from members—a compounding, interest-free float funding the entire operation.
## The Cash Machine (Free Cash Flow) The membership float doesn't just sit pretty on the balance sheet—it flushes through the cash flow statement in ways the GAAP P&L never captures. **The Data:** Costco generated **$11.64 Billion in Free Cash Flow TTM** through Q2 FY26, well above its **$8.68 Billion in reported Net Income**. The cash flow materially exceeds the accounting earnings because of two factors the screeners miss: the growing deferred membership liability and the payables float on inventory. **The GeminIQ Edge:** Pull the raw Operating Cash Flow against Capital Expenditures and the ratio tells the story. Retailers traditionally convert 60-70% of net income to free cash flow because of CapEx burdens and inventory builds. Costco is converting at **134% of Net Income to FCF**. That's software-economics cash conversion on a hard-goods retailer balance sheet.
GeminIQ Free Cash Flow TTM visualization from FY18 through Q2 FY26. The recent vertical spike to $11.6B reflects the combined effect of rising deferred membership fees, disciplined CapEx, and accelerating operating cash flow from the membership engine.
## Timing the Entry (The Q2 10-Q Pattern) So should you buy $COST at an all-time high and a 51.7x P/E? The price tag looks expensive, but the **Earnings Market Reaction Heat Map** reveals a strong historical tailwind specifically for the Q2 filing. **The Data:** Over the last 5 years, Costco's Q2 10-Q has been one of the most consistently positive filings on the calendar. The stock averages **+3.94% in Month 1**, **+6.98% in Month 2**, and **+7.80% in Month 3** after the Q2 filing drops. This current cycle (March 11, 2026 filing) is already tracking the pattern with a **+2.29% move in Month 1**. Strategy suggests the Q2 filing historically acts as a catalyst rather than a "sell the news" event—likely because the data captures holiday-period member renewals, which is the single most important number in the entire Costco thesis. Waiting for a broader market dip is reasonable at 51x earnings, but historical data does not support the "overvalued, wait forever" playbook. The cash machine keeps compounding regardless of the multiple.
GeminIQ Earnings Market Reaction Heat Map for $COST. The Q2 column shows a consistent multi-year positive compounding pattern post-filing, with the current 2026 cycle already tracking a +2.29% M1 move in line with the 5-year average.
## The Insider Exit (The One Red Flag) The thesis is strong, but a good analyst never ignores the reality check. What are the people actually running Costco doing with their own money? **The Data:** GeminIQ's raw Form 4 feed shows that since the stock crossed $900, Costco insiders have executed an uninterrupted stream of sales transactions against zero open-market purchases. EVP-level selling dominates the tape: **Adamo** (multiple sales at $935-$1,003), **Miller** (3,381 shares at $915 and 1,500 more at $916), **Klauer** (1,500 shares at $939), **Wilcox** (2,400 shares at $930), **Rubanenko** (4,000 shares at $975), and **Jones** across multiple filings. **The GeminIQ Edge:** Looking at the 10-year insider history, Costco insiders have always sold more than they buy (standard behavior for a mature mega-cap with heavy RSU compensation). But the *pace* since the stock crossed $900 is notable—zero green "Buy" bars on the chart, unbroken red "Sale" bars every month. At 51.7x earnings, the people with the clearest view of the business are cashing out—not betting against the business, but refusing to add conviction at the price.
GeminIQ Insider Transactions tracker showing an unbroken stream of Sale transactions (red bars) from March 2025 through March 2026 with zero open-market purchases. Every Executive Vice President-level insider listed has sold direct shares at prices between $862 and $1,003.
## The Institutional Accumulation (Smart Money Quietly Crowding In) One final data point that gets ignored by the mainstream narrative: while insiders are selling, institutions are doing the opposite. **The Data:** GeminIQ's 13F Institutional Holdings tracker shows total institutional ownership has climbed from roughly **57% in late 2022 to 67.42% at the December 2025 filing deadline**—a steady, multi-year accumulation into the stock. Over the same window, share count has been essentially flat, meaning this is genuine net buying, not passive index flow from share issuance. **The GeminIQ Edge:** Standard financial sites only display the most recent percentage—they don't show you the trajectory. By auditing the 13F holdings quarter-by-quarter in GeminIQ, we can see the divergence: insider EVPs are taking chips off the table while 13F filers have quietly added 46 million shares over three years. For comparison, mega-cap peers like Delta (83%) and United (86%) carry higher absolute institutional ownership, but very few of them show Costco's sustained *accumulation pattern* at these valuations. Smart money is still buying a 51x P/E grocer. That's worth paying attention to.
GeminIQ 13F Institutional Holdings Tracker showing institutional ownership rising from 57.17% (Dec 2022) to 67.42% (Dec 2025). Despite a stable share count, institutions have net-accumulated roughly 46 million shares—a quiet vote of confidence that offsets the insider selling narrative.
## Research faster. Invest smarter. --- ### Company Deep-Dive — NVIDIA (NVDA) source: https://www.geminiq.com/blog/NVDA_2026-02-26 ### NVIDIA ($NVDA): The $120 Billion Cash Machine No One Is Auditing NVIDIA just dropped its 2026 10-K. While retail is obsessed with revenue, value investors are looking at the 66% ROIC and the massive share buyback engine. **NVIDIA ($NVDA) just dropped its 2026 Annual Report (10-K filed Feb 25, 2026), and the top-line numbers are staggering. While the retail crowd is obsessed with the $215.9B revenue print, value investors are looking at the velocity of the business. I used GeminIQ to audit the raw 10-K. Here is the fundamental truth behind the ticker.** ## The Buyback "Stealth" Engine Most people think NVIDIA is just a growth play. But on GeminIQ, we track the **Capital Return** strategy. Unlike other tech giants that dilute shareholders via stock-based compensation, NVIDIA is actually shrinking the pie to your benefit. **The Purple Bars:** Show the explosive Net Income hitting **$120.1B TTM**. **The Red Line:** Shows the Basic Shares Outstanding dropping from **24.5B** to **24.3B** in just one year. **The GeminIQ Edge:** Seeing the raw share count reduction alongside the income spike proves management is pivoting from "Growth at all costs" to "Capital Return Masterclass." ## Inventory Velocity (The "Bull" Signal) In hardware, "Inventory is Death." If chips sit on shelves, margins collapse. I used the GeminIQ **[Custom Table](https://www.geminiq.com/features#custom-tables)** to audit NVIDIA's operational efficiency. NVIDIA's Inventory Turnover (TTM) is sitting at an elite **3.97**. Management is moving product almost **4 times a year**. Despite doubling revenue, they aren't letting stock pile up—they are shipping it as fast as it's made. This is the hallmark of a dominant moat. ## Verifying the Moat with ROIC Is the capital being used wisely? We used the **[Visualizations Tab](https://www.geminiq.com/features#visualizations)** to check **Return on Invested Capital (ROIC)**. NVIDIA’s ROIC (TTM) is a mind-bending **66.8%**. **GIQ Tip:** Management is turning every $1 of invested capital into nearly **$0.67 of profit**. This is elite-tier efficiency. As long as ROIC stays above 50%, the fundamental machine is working perfectly. ## Timing the Entry (Behavioral Variance) Should you buy the "All-Time High" post-filing? I checked the **[Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** for $NVDA's historical 10-K filings. **The Data:** Historically, $NVDA shows a high "Month 1" volatility following its annual report, often followed by a consolidation window in "Month 2." Strategy suggests that waiting for the "Post-Earnings Drift" often yields a better **Margin of Safety** than chasing the day-of-report pop. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — Coca-Cola (KO) source: https://www.geminiq.com/blog/KO_2026-03-08 ### The Coca-Cola Company ($KO): The 13-Year 'Zero Growth' Illusion Coca-Cola just dropped its 2025 10-K. Standard screeners show 13 years of flat revenue, but value investors are looking at the massive asset dump and the 28.7% operating margin explosion. **The Coca-Cola Company ($KO) just dropped its 2025 Annual Report (10-K filed Feb 20, 2026). If you pull up a standard financial screener, it looks like a dead-money stock: $47.9 Billion in revenue today versus $48.0 Billion in 2012. It looks like 13 years of zero top-line growth. But I used GeminIQ to audit the raw 10-K data, and the real story is one of the greatest corporate "refranchising" pivots in history. Here is the fundamental truth behind the ticker.** ## The Asset Dump (Capital Efficiency) Why did Coca-Cola's revenue stagnate? Because they intentionally executed a massive "refranchising" strategy, selling off their heavy, capital-intensive bottling plants to become a pure-play, capital-light brand licensor and syrup manufacturer. **The Data:** Look at Property, Plant, & Equipment (PP&E) on the Balance Sheet. It dropped from **$14.4 Billion** in 2012 to just **$9.6 Billion** today. They shed nearly $5 Billion in heavy factories and equipment. **The GeminIQ Edge:** By directly auditing the historical Balance Sheet via GeminIQ, you can see they intentionally shrank their asset base to fundamentally restructure the business into a high-margin royalty machine. ## The Margin Explosion If revenue is identical to 2012, what happened to profits? **The Data:** Because they are no longer running low-margin bottling plants, Operating Income exploded from **$10.7 Billion** (2012) to a staggering **$13.7 Billion** (2025). That is a massive jump in Operating Margin from **22.4% to 28.7%**. **The GeminIQ Edge:** Standard aggregators just show flat long-term revenue growth, which triggers basic value traps. By pulling raw Operating Income against Top-Line Revenue, we can prove that while Coca-Cola's total revenue plateaued, their profitability per dollar absolutely skyrocketed. They are making $3 Billion more in pure operating profit on the exact same revenue. Top-line growth is a vanity metric; raw margin data is the truth. ## Timing the Entry (Behavioral Variance) Should you buy the 10-K? I checked the **[Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** for $KO's historical 10-K filings. **The Data:** Historically, $KO's 10-K does not generate massive day-one hype. Over the last several years, the stock averages a slight "flatline" or dip (**-1.0%** in Month 1), typically followed by a steady compounding rebound (**+3.0%** in Month 2). Strategy suggests that $KO is a slow-and-steady compounder. Waiting out the initial 30-day window historically provides a highly stable entry point with a built-in **Margin of Safety**. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — GameStop (GME) source: https://www.geminiq.com/blog/GME_2026-03-31 ### GameStop Corp. ($GME): The $9 Billion SPAC, the Textile Mill, and the 'Next Warren Buffett' GameStop just dropped its 2025 10-K. The media sees a dying retailer. Value investors see $9B in cash, a CEO forced to make acquisitions, and diamond-handed insiders. **GameStop Corp. ($GME) just dropped its 2025 Annual Report (10-K filed March 24, 2026), alongside a flurry of proxy and compensation filings. Every time this company reports earnings, the financial media hyper-focuses on declining physical software sales and mock the company as a dying brick-and-mortar dinosaur kept on life support by internet memes and retail nostalgia.** But standard financial media doesn't read the footnotes. I used GeminIQ to audit the raw SEC data—cross-referencing their 10-K, Cash Flow Statements, Insider Form 4s, and Institutional Holdings. The real story is that GameStop is no longer a video game retailer. It is a heavily armed, institutional holding company actively hunting for a massive acquisition. Here is the fundamental, data-driven truth behind the ticker. ## The $9 Billion War Chest (A Capital-Raising Masterclass) Wall Street views GameStop’s historical stock volatility as a bug; GameStop management viewed it as a feature. While the media was laughing at the stock's wild swings, management quietly used the retail trading frenzy as a live testing ground. They aggressively tested and perfected every mechanism of capital raising, executing At-The-Market (ATM) share offerings at massive premiums, utilizing convertibles, and mastering warrant structures. **The Data:** Look at their Balance Sheet over the last five years. They completely wiped out their legacy, high-interest brick-and-mortar debt. By utilizing their perfected capital-raising mechanics, they have amassed an absolutely staggering war chest. Sitting on the books at the end of FY 2025 is **$6.3 Billion in Cash and Cash Equivalents**, alongside **$2.7 Billion in Marketable Securities**.
GeminIQ custom table and visualization displaying the resulting $9 Billion war chest ($6.3B Cash + $2.7B Marketable Securities) and rising net income.
**The GeminIQ Edge:** Standard screeners blend everything into a negative "GAAP Net Income," completely obscuring this structural pivot. By pulling the raw [balance sheet](https://www.geminiq.com/features#financial-statements) via GeminIQ, you can see the ultimate divergence. GameStop is effectively a **$9 Billion SPAC** (Special Purpose Acquisition Company). They are earning hundreds of millions in pure interest just sitting on Treasury bills while they prepare to deploy their capital. And because they've perfected the art of the offering, they have the proven mechanics to raise even *more* cash instantly if a mega-acquisition requires it. ## The "Convenience" Pivot (Funding the Wait) But what about the core business? In their recent 10-K, management openly acknowledges a harsh truth: modern gamers prefer digital downloads. They aren't in denial. However, the 10-K explicitly outlines their pivot to "convenience", and they don't mean digital games.
Excerpt from GameStop FY 2025 10-K (Item 1: Business) explicitly validating their strategic shift. Management confirms their 'convenience' thesis focused on high-margin physical commerce, collectibles, and professional PSA grading services.
They have confirmed their thesis that customers want high-margin physical convenience in the form of collectibles, trading cards, and professional grading services (like their massive push into PSA card grading). This isn't meant to be the next Amazon; this physical footprint is meant to be their "textile mill." Just as Warren Buffett used the baseline cash flow of a dying textile mill to fund Berkshire Hathaway's early investments, GameStop is using high-margin trading cards to generate **$614.8 Million in Operating Cash Flow** to keep the lights on while the holding company hunts for the whale.
GeminIQ Income Statement highlighting the successful financial mechanics of the retail pivot. While revenue remains under pressure, high-margin collectibles and grading generated $614.8 Million in Operating Cash Flow, providing the holding company with significant firepower.
## The "Berkshire 2.0" Catalyst (Cohen's Milestones) Having $9 Billion in the bank is useless without a visionary capital allocator. This is where the narrative shifts from a retail trade to a serious, institutional value play. **The Context:** For years, CEO Ryan Cohen refused a standard salary, taking exactly $0 in compensation. Now, look at his newly filed compensation package. His proposed financial incentive structure is entirely tied to aggressive, performance-based milestones. He doesn't get a massive base salary just to manage a declining retail footprint. He only unlocks his equity payouts by executing highly accretive acquisitions and transforming the business model. He is structurally, legally, and financially forced to act as a capital allocator.
Excerpt from the FY 2025 Proxy Statement visualizing Ryan Cohen's milestone-based compensation structure. The document confirms his standard base salary of $0 and outlines that all compensation is tied to massive, accretive acquisition milestones and capital allocation targets.
This pivot is so significant that "Big Short" legend Michael Burry, who famously held a massive early stake in GME, has publicly validated the strategy. Wall Street is increasingly comparing GameStop's current state to Warren Buffett's early days. ## Decoding the Volatility (The Heat Map) Standard value investors are horrified by GameStop's stock chart, viewing the constant double-digit price swings as dangerous mania. Retail traders panic during post-earnings drops. But institutions and insiders know the truth: GameStop doesn't trade on its earnings anymore. Traditional valuation models like Price-to-Earnings (P/E) are useless for an entity that is functionally a SPAC. The volatility is not a risk; it is just the engine they use to raise capital.
GeminIQ [Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance) and Volatility Tracker. The data starkly displays extreme post-earnings price variance, reinforcing the narrative that $GME does not trade on standard P/E metrics, but on macro capital flows and acquisition rumors.
## The Unprecedented Conviction (Smart Money Accumulation) Talk is cheap, and Wall Street executives promise "turnarounds" every day. If you want to know what management really believes about this massive acquisition thesis, you have to look at their personal bank accounts. Standard financial sites trigger random "insider selling" alerts on GameStop. But using GeminIQ to audit the raw SEC Form 4 filings reveals that selling is purely administrative—taxes and standard compensation coverage by non-core executives like the General Counsel. The core architects of this turnaround, **Ryan Cohen, Larry Cheng, Alain Attal, and Jim Grube**, have made massive open-market purchases *year after year*. Cohen alone has purchased tens of millions of dollars in stock.
GeminIQ [Insider Tracker](https://www.geminiq.com/features#insider-transactions) filtered specifically for Ryan Cohen, Larry Cheng, Alain Attal, and Jim Grube (2021-2026). The image displayed purely green 'Buy' volume bars with zero red 'Sells,' visualizing unprecedented 5-year conviction.
Furthermore, auditing the [13F Institutional Holdings](https://www.geminiq.com/features#institutional-ownership) data shows that smart money is quietly securing positions. While retail fights over daily price action, institutions are anchoring millions of shares, recognizing that a $9 Billion cash pile with no debt establishes a massive, unbreakable fundamental floor. GameStop is no longer a video game store. **It is Ryan Cohen's acquisition vehicle.**
GeminIQ 13F Institutional Holdings Tracker visualizing steady accumulation. Smart money whales and passive index funds continue to increase their positions, anchoring the float and establishing a fundamental floor based on the $9 Billion war chest.
Research faster. Invest smarter. --- ### Company Deep-Dive — Apple (AAPL) source: https://www.geminiq.com/blog/AAPL_2026-02-19 ### Is Apple ($AAPL) Still a Value Play or a Yield Trap? Is Apple overvalued at 34x? Most analysts are arguing over iPhone units in China. But value investors look at the Capital Machine, not the Gadget. **Is Apple overvalued at 34x? Most analysts are arguing over iPhone units in China, but value investors look at the Capital Machine, not the Gadget. I used GeminIQ to audit Apple's "Capital Efficiency" in their latest 10-Q (filed Jan 30, 2026). Here is the fundamental truth behind the ticker.** ## Standardized Financials vs. Aggregator Lag Wait, why is the buyback value negative on GeminIQ? **Because we don't "massage" the data**. In a raw GAAP filing, a buyback is a **Cash Outflow**. **The Purple Bars (Bottom):** Show the massive cash outflows, **$24.7B** this quarter, as Apple aggressively repurchases its own stock. **The Red Line (Top):** Shows the Basic Shares Outstanding steadily dropping, over **200 million shares retired just since last quarter**. **The GeminIQ Edge:** While aggregators might "clean" this, seeing the raw outflow proves the scale of their Share Cannibal strategy. ## The "Negative" Retained Earnings Alpha On the balance sheet, Apple shows an Accumulated Deficit of **-$2.17B**. Most retail sites show this as a red flag, but on GeminIQ, you see the truth: **A Capital Allocation Masterclass**. Apple generates so much cash ($42.1B in Net Income this quarter) that they've **returned more to shareholders than they've technically "retained" since 2012**. They are a "Self-Liquidating" fortress, mathematically **increasing your ownership stake every quarter**. ## Verifying the Moat with ROIC Take a look at the [Return on Invested Capital (ROIC)](https://www.geminiq.com/features#calculated-metrics), Apple's ROIC (TTM) is sitting at an elite **91.68%**. Management is turning $1 of investment into nearly **$1 of profit**, year after year. **GIQ Tip:** This is a core pillar of Intrinsic Value. As long as ROIC stays elite, the "Apple Machine" is working. ## Timing the Entry (Behavioral Variance) **[GeminIQ's Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** shows that during Q1, $AAPL historically **drifts negatively until Q2**. **The Data:** History suggests waiting for Q2 often yields a better **Margin of Safety** than buying after the release of the Q1 financials. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — Amazon (AMZN) source: https://www.geminiq.com/blog/AMZN_2026-02-20 ### Amazon ($AMZN): Is the $19 Billion Hidden Expense Eating Your Returns? Is Stock-Based Compensation the real value killer? Let’s take a look at Amazon’s latest report. **Amazon ($AMZN) is posting massive operating cash flows, but value investors know that "Cash Flow" doesn't always equal shareholder value. I used GeminIQ to audit Amazon’s cash flow statement in their latest 10-K (filed Feb 2026). If you are looking into identifying hidden stock dilution in SEC filings, you have to look past the top-line revenue and dig into how they pay their employees. Here is the fundamental truth behind the ticker.** ## The Stock-Based Comp Value Killer Wait, why does Amazon’s Operating Cash Flow look so high on popular aggregators? Because **third-party sites often ignore the reality of Non-Cash Add-Backs**. To understand GAAP vs non-GAAP earnings discrepancies, you have to look at **Stock-Based Compensation (SBC)**. **The Purple Bars (Bottom):** Amazon’s Net Cash from Operations is an impressive **$139.5 Billion** for the twelve trailing months (TTM). **The Red Bars (Top):** Their Stock-Based Compensation (SBC) TTM is a massive **$19.5 Billion**. **The GeminIQ Edge:** Mainstream aggregators just show the massive cash flow. **GeminIQ** lets you isolate the SBC line item, proving that nearly **14%** of their operating cash flow is actually just paying employees in stock, a massive, hidden cost to your ownership stake. ## The Dilution Reality (Shares Outstanding) You might think tech giants are buying back enough stock to offset this. However, if you are looking for a reliable stock-based compensation analysis tool, you must track the raw share count. On GeminIQ, we see Amazon’s Basic Shares Outstanding actually **increased from 10.47 Billion (Dec 2024) to 10.66 Billion (Dec 2025)**. They are a **"Dilution Machine”**, while they generate incredible revenue, they are mathematically shrinking your slice of the pie every quarter to fund their talent pool. ## Verifying the Moat with Smart Money If the company is paying out **$19.5 Billion** in stock to employees and executives, what are those insiders doing with it? We use **GeminIQ** [Insider Transactions](https://www.geminiq.com/features#insider-transactions) to track the divergence. **Insider Sentiment:** When executives receive massive SBC grants, tracking their open-market sales becomes critical. The sentiment shows consistent distribution. **GIQ Tip:** Knowing how to calculate true free cash flow means subtracting SBC. When the "Smartest People in the Room" are **aggressively cashing out their stock awards** rather than holding, you need to factor that into your true valuation. ## Timing the Entry (Behavioral Variance) Should you buy the "earnings beat" when they report massive cash flow? For a true margin of safety, we use post-earnings drift historical analysis. **[GeminIQ's Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** shows how the market digests this hidden dilution over time. **The Data:** In Q3 2025, AMZN dropped **9.6%** in the first month (M1) post-earnings, stabilizing by month three (M3). **Strategy:** History suggests that Wall Street initially celebrates the top-line beat, but the stock often drifts lower as analysts factor in the $19.5 Billion SBC dilution reality. Waiting for this drift provides a better **Margin of Safety**. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — Alphabet (GOOGL) source: https://www.geminiq.com/blog/GOOGL_2026-02-22 ### Alphabet ($GOOGL): The $126 Billion Anti-Fragile Fortress YouTube ad slowdown or growing fortress? Let’s take a look at Alphabet’s latest annual report. **Google ($GOOGL) just reported its 2025 annual results. The headlines are arguing about "YouTube Ad Slowdown." But for a value investor, the most important story is on the Balance Sheet. I used GeminIQ to audit Alphabet's "Fortress" in the February 2026 10-K.** ## Visualizing the Safety Margin I used the **[GeminIQ Visualizations Tab](https://www.geminiq.com/features#visualizations)** to plot Total Current Assets vs. Total Current Liabilities. **The Result:** Alphabet has **$206.0B** in Current Assets versus only **$102.7B** in Current Liabilities. **The GeminIQ Edge:** Most sites give you a table of numbers. GeminIQ gives you a visual "Safety Gap." You can see the fortress growing in real-time. ## Retained Earnings Growth Value investors look for **Retained Earnings**, the fuel for future buybacks and R&D. **The Data:** Alphabet’s Retained Earnings have hit **$324B** as of December 2025. **The Insight:** Even with massive AI data center spending, their **internal war chest continues to compound**. This is the definition of Anti-Fragile. ## The "Fear" Window Should you buy during the "AI Panic"? I checked the **[Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** for $GOOGL. **The Fact:** Alphabet has a **60%** probability of recovering its "post-earnings dip" within 60 days. **Strategy:** The map shows that "red" 1-month windows often turn to green by the 3-month mark. The market panics, then realizes the fortress is still standing. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — Palantir (PLTR) source: https://www.geminiq.com/blog/PLTR_2026-03-05 ### Palantir ($PLTR): The Dilution Era Is Over (And the Cash Flow is Exploding) Palantir just dropped its 2025 10-K. While retail is obsessed with AIP revenue, value investors are looking at the 82% Gross Margins, massive FCF, and the stabilized share count. **Palantir ($PLTR) just dropped its 2025 Annual Report (10-K filed Feb 17, 2026), and the top-line numbers are staggering. While the retail crowd is obsessed with the $4.47B revenue print, value investors are looking at the operating leverage. I used GeminIQ to audit the raw 10-K. Here is the fundamental truth behind the ticker.** ## The End of the Dilution Era Most people think Palantir is a dilution trap from its early public days. But on GeminIQ, we track the **Capital Return** and dilution metrics. **The Purple Bars:** Show the explosive GAAP Net Income hitting **$1.63B TTM**. **The Red Bars:** Shows the [Basic Shares Outstanding](https://www.geminiq.com/features#financial-statements) finally stabilizing. **The GeminIQ Edge:** Seeing the raw share count stabilize alongside the income spike proves management is finally increasing your ownership value instead of paying it all out in stock. ## The Software Economics (Gross Margin Expansion) Before looking at the bottom line, you have to look at how much it costs them to deliver their product. **The Data:** Palantir generated **$4.47 Billion** in Net Revenue with a Gross Profit of **$3.68 Billion**. That is a staggering **82.3% Gross Margin**. **The GeminIQ Edge:** Standard screeners give you blended percentages. By pulling the raw COGS against Revenue from the Income Statement, we can track their pricing power. They are scaling revenue without proportionally scaling costs. ## The Free Cash Flow Machine In software, "Free Cash Flow is King." **The Data:** Palantir produced a staggering **$2.13 Billion** in Operating Cash Flow against a tiny **$33 Million** in Capex. That is an incredible **47% FCF margin**. **The GeminIQ Edge:** We pull raw **Operating Cash Flow** directly against Capital Expenditures. The numbers prove Palantir is running an extremely capital-light model. ## Timing the Entry: The "Sell the News" Trap Should you buy the "All-Time High" post-filing? I checked the **[Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** for $PLTR's historical 10-K filings, and the data issues a massive warning. **The Data:** While PLTR historically trends positive after most earnings reports, the annual 10-K is heavily skewed as a "Sell the News" event. Over the last 5 years, the stock averages a **-5.4% drop in Month 1** and a **-5.8% drop in Month 2** following the 10-K. Last year's 10-K triggered a 30% drawdown in the first 30 days. Strategy suggests that aggressively buying the day-of-report hype for the 10-K is a statistical trap. If you are building a position, history favors waiting out the Q4 slump to secure a proper **Margin of Safety**. --- ## Research faster. Invest smarter. --- ### Company Deep-Dive — Exxon Mobil (XOM) source: https://www.geminiq.com/blog/XOM_2026-03-17 ### Exxon Mobil ($XOM): The Ultimate Pandemic Stress Test Exxon just dropped its 2025 10-K. While the media watches the daily price of oil, value investors are looking at their massive $23.6B in Free Cash Flow and insulated dividend. **Exxon Mobil ($XOM) just dropped its 2025 Annual Report (10-K filed Feb 18, 2026). The retail crowd and media treat legacy energy companies purely as daily trades on the price of oil. The mainstream narrative assumes they are highly cyclical and dangerous. But I used GeminIQ to audit the raw 10-K, and the real story is that Exxon has completely engineered the cyclical risk out of its business model. Here is the fundamental truth behind the ticker.** ## From Cash Burn to Cash Cannon To understand Exxon's true moat, you have to look at the ultimate stress test: the 2020 pandemic oil crash. **The Data:** In 2020, as the world locked down, Exxon's Operating Cash Flow plummeted to just **$14.6 Billion**, while their Capital Expenditures (Capex) remained a heavy **$17.2 Billion**. They actually burned $2.6 Billion in Free Cash Flow. Fast forward to 2025: Operating Cash Flow has exploded to **$51.9 Billion**, while Capex remains disciplined at **$28.3 Billion**. **The GeminIQ Edge:** Standard screeners focus on GAAP Net Income, which swings wildly with commodity prices. By directly auditing the [Cash Flow Statement](https://www.geminiq.com/features#financial-statements) via GeminIQ, you can visualize the true spread. Exxon is now generating a staggering **$23.6 Billion** in raw Free Cash Flow. ## The Dividend Fortress Why does that massive Free Cash Flow buffer matter? Because it fundamentally protects the dividend, proving it is a fortress that can survive any crisis. **The Data:** During the 2020 stress test, Exxon paid out $14.8 Billion in dividends while their Free Cash Flow was negative, forcing them to rely heavily on debt. Many thought a dividend cut was inevitable. Today in 2025, they paid out a massive **$17.2 Billion** in dividends—and because their cash engine has recovered so violently, it was effortlessly covered with over $6 Billion in Free Cash Flow to spare. **The GeminIQ Edge:** By pulling raw Dividends Paid against Free Cash Flow, we can prove that Exxon has evolved from a vulnerable wildcatter into a financial utility that prints cash and funds its payouts purely from operations. ## The Macro Illusion (Decoding the Heat Map) If you look at the **[Earnings Market Reaction Heat Map](https://www.geminiq.com/features#price-variance)** for $XOM's historical Q4/10-K filings, it shows an average Month 1 drop of -2.7%. A standard analyst might tell you this is a "post-earnings slump." But if you correlate the filing dates with global macro events, you realize that narrative is completely false. Exxon doesn't trade on its 10-K; it trades on global oil shocks. **The Context:** Look at the specific years driving that negative M_1 average: * **February 2015 (-5.6% M_1):** Driven by OPEC refusing to cut production, crashing the oil market. * **February 2020 (-38.2% M_1):** Driven by the outbreak of the COVID-19 pandemic destroying global oil demand, not the earnings report. * **February 2022 & 2024 (+14% to +15% M_2):** Driven by the Russia-Ukraine conflict and Red Sea shipping attacks adding massive geopolitical risk premiums to crude. Strategy suggests that you cannot trade an oil major's earnings blindly. The historical "average" is skewed by black-swan crashes. Because their business is now an absolute fortress, the true strategy is to ignore the earnings noise and use global macro panics as generational buying opportunities for an insulated dividend. --- ## Research faster. Invest smarter. --- ## Section 16: 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 Founders ($29/mo) vs. Bloomberg Terminal ($2,665/mo). 99% cheaper. GeminIQ requires no contract and includes a 7-day free trial. **Feature Comparison:** | Feature | GeminIQ | Bloomberg Terminal | |---|---|---| | Primary Data Source | Direct SEC EDGAR | Proprietary primary pipelines across every global asset class (350+ exchanges, regulators, market makers) | | XBRL Tag Transparency | ✓ — every data point traceable to its specific XBRL tag | ✗ | | Raw, As-Filed Reporting Structure Preserved | ✓ — filing structure preserved exactly as default view | Partial — as-reported financials available alongside standardized views | | Calculated Financial Metrics | 50+ KPIs from raw XBRL-tagged data | Extensive metrics across all asset classes | | Advanced Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, and between logic | ✓ — EQS equity screening with comprehensive global filters | | Interactive Financial Visualizations | ✓ — line, bar, area charts with log/linear scale, z-score, min-max | ✓ — advanced charting across all asset classes | | Custom Data Tables (saveable templates) | ✓ | ✓ | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — comprehensive comp analysis | | SIC-Based Sector Search | ✓ | ✓ — industry classification screening | | Insider Transaction Tracking | ✓ — visual sentiment timeline from SEC Form 4 | ✓ | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✓ | | Real-Time Market Data (all asset classes) | ✗ | ✓ — equities, fixed income, FX, commodities, derivatives across 350+ exchanges | | Bloomberg IB Chat Messaging | ✗ | ✓ — 325,000+ professional users | | Fixed Income & Bond Data | ✗ | ✓ — industry-leading | | Forex & Commodities Data | ✗ | ✓ | | Integrated News Feed | ✗ | ✓ — Bloomberg News, 2,700+ journalists globally | | Analyst Estimates & Price Targets | ✗ | ✓ | | M&A / Deals Database | ✗ | ✓ | | Portfolio Analytics & Risk Management | ✗ | ✓ — PORT | | Trade Execution | ✗ | ✓ | | Excel BDH/BDP Integration | ✗ | ✓ | | AI Tools | ✗ | ✓ — Bloomberg GPT features | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — global, all asset classes | | Free Trial | ✓ — 7-day full-access | ✗ — personalized demo only, no trial | | Contract Requirement | None (cancel anytime) | 2-year minimum typical | | Individual Pricing Available | ✓ — $29/mo, sign up in minutes | ✗ — $31,980/year single terminal, enterprise sales process | --- ### 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 (annual plans) **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 Founders ($29/mo) is 24% cheaper than TIKR Pro ($37.95/mo annually). GeminIQ is up to 47% cheaper for month-to-month subscribers. **Feature Comparison:** | Feature | GeminIQ | TIKR Terminal | |---|---|---| | Primary Data Source | Direct SEC EDGAR | S&P Capital IQ (aggregated) | | Raw, Unfiltered Financials (as-filed) | ✓ | ✗ — normalized by Capital IQ | | XBRL Tag Transparency | ✓ | ✗ | | Company-Specific Line Item Preservation | ✓ | ✗ — collapsed into generic buckets | | Full Data Auditability to Source Filing | ✓ | ✗ | | Next-Day Filing Availability (T+1) | ✓ | Varies | | Years of Historical Data | 17+ years (all plans) | 3 years (Free), 10 years (Plus), 20 years (Pro) | | Historical Data Paywalled by Tier | ✗ — all data included | ✓ | | Interactive Financial Visualizations | ✓ | ✓ | | Custom Data Tables (saveable templates) | ✓ | ✗ | | Calculated Financial Metrics | 50+ metrics | Valuation ratios and fundamentals available | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing drift | ✗ | | Advanced Screener | ✓ — 100+ metrics, up to 10 stackable filters | ✓ — 300+ filters, saved screens limited by tier | | SIC-Based Sector Search | ✓ | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — watchlists available | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular detail | ✓ — transaction table | | Institutional Ownership Monitoring | ✓ — aggregate ownership trend tracking | ✓ — 10,000+ funds on Pro | | Superinvestor / Hedge Fund Portfolio Tracking | ✗ | ✓ — 10,000+ fund portfolios | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — 100,000+ stocks, 92 countries | | Analyst Estimates & Consensus Forecasts | ✗ | ✓ — up to 4 years forward on Pro | | Earnings Call Transcripts | ✗ | ✓ | | Valuation Model Builder | ✗ | ✓ | | Free Trial | ✓ — 7-day full-access trial | ✗ — 14-day money-back guarantee instead | | Free Plan Available | ✗ | ✓ — US only, 3 years of data | | All Features Included at One Price | ✓ | ✗ — tiered: Free, Plus, Pro | --- ### 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 pre-built 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 **Who Should Switch:** - Analysts who verify numbers against the original SEC filing - US-focused fundamental researchers who need XBRL-level data lineage - Investors frustrated by data that doesn't match the 10-K - Those who want a focused analytical platform without feature overload - Anyone paying for global guru tracking features they don't use **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 Founders ($29/mo) 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 Founders. **Feature Comparison:** | Feature | GeminIQ | GuruFocus | |---|---|---| | Primary Data Source | Direct SEC EDGAR | Third-party data vendor (financial data delivered within 2–4 business days of filing; guru/insider data from SEC filings directly) | | XBRL Tag Transparency | ✓ — every data point traceable to its specific XBRL tag | ✗ | | Raw, As-Filed Reporting Structure Preserved | ✓ | ✗ — normalized into standardized templates by data vendor | | Company-Specific Line Item Preservation | ✓ | ✗ — standardized templates | | Years of Historical Data | 17+ years (all plans) | 10 years (Premium), 20 years (Premium Plus), 30 years (Professional) | | All Historical Data Included at One Price | ✓ | ✗ — depth increases by tier | | Calculated Financial Metrics | 50+ KPIs from raw XBRL-tagged data | Extensive metrics including proprietary GF Score, GF Value, Graham Number, Piotroski F-Score | | Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, between logic, on XBRL-traceable data | ✓ — All-in-One Screener with 500+ filters, pre-built value strategies including Buffett-Munger, Graham Net-Net, Peter Lynch | | Interactive Financial Visualizations | ✓ — line, bar, area with log/linear, z-score, min-max | ✓ — interactive charts and maps | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✗ | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | DCF / WACC Calculators | ✗ | ✓ | | Backtesting | ✗ | ✓ — Premium Plus and above, back to 2006 | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — watchlists and stock comparison table | | SIC-Based Sector Search | ✓ | ✗ | | Guru Portfolio Tracking (Buffett, Icahn, Soros, etc.) | ✗ | ✓ — 8,000+ institutional investors, 15,000+ mutual funds | | Real-Time Guru Picks | ✗ | ✓ — within 1–2 weeks of filing | | Insider Transaction Tracking | ✓ — visual sentiment timeline from SEC Form 4 | ✓ — insider tracker with CEO/CFO buys/sells, clusters, trends, Double/Triple Buys | | Politician Trading Tracker | ✗ | ✓ — Congress and Senate trades under STOCK Act | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✓ — 13F/13D/13G data on Premium Plus+ | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — ~100,000 stocks in ~100 markets; international coverage requires per-region add-on fees | | GuruAI Chatbot | ✗ | ✓ — natural-language research assistant | | Earnings Call Transcripts | ✗ | ✓ | | Model Portfolios | ✗ | ✓ — Buffett-Munger, Graham, Lynch strategies | | Mobile App | ✗ | ✓ — iOS and Android | | Analyst Ratings | ✗ | ✓ | | Free Trial | ✓ — 7-day full-access | ✓ — 7-day free trial + 30-day money-back guarantee | | Free Plan | ✗ | ✓ — limited screener access, guru holdings, news | | All Features at One Price | ✓ | ✗ — tiered: Free, Premium, Premium Plus, Professional + per-region add-ons for international coverage | --- ### 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 **Who Should Switch:** - US-focused analysts who need to trace and audit their numbers - Investors who want insider activity, institutional ownership, and comps in one tool - Screener power users who need precise, multi-condition filtering - Anyone who needs the full analytical toolkit without paying $74/mo - Researchers whose calculated metrics don't match what they'd compute from the 10-K or 10-Q **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 Founders ($29/mo) is 61% cheaper than ROIC.ai Professional ($74/mo). **Feature Comparison:** | Feature | GeminIQ | ROIC.ai | |---|---|---| | Primary Data Source | Direct SEC EDGAR | SEC EDGAR (standardized) | | Raw, As-Filed Line Items Preserved | ✓ | ✗ — reformatted into standard templates | | XBRL Tag Transparency | ✓ — every data point traceable to its XBRL tag | ✗ | | Full Auditability to Source Filing | ✓ — verify any number in under 30 seconds | ✗ | | Data Refresh | Next-day (T+1) | Daily | | Years of Historical Data | 17+ years (all plans) | 30+ years (annual financials free, full financials on paid plans) | | Historical Data Paywalled by Tier | ✗ — all data included | Partial — full financials require Individual plan | | Interactive Multi-Metric Visualizations | ✓ — line, bar, area charts with log/linear scale, z-score, min-max normalization | Partial — limited basic price-to-fundamentals charting | | Custom Data Tables (saveable templates) | ✓ | ✗ | | Calculated Financial Metrics | 50+ KPIs (ROIC, ROE, margins, turnover, growth rates, etc.) | Financial ratios and valuation metrics available | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Advanced Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, and between logic | ✓ — value-focused screener with basic filtering | | SIC-Based Sector Search | ✓ | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✗ | | Comparable Company Analysis (Comps) | ✓ | ✗ | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular detail | ✗ | | Institutional Ownership Monitoring | ✓ — aggregate ownership trend tracking | ✗ | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — worldwide on Individual plan and above | | ChatGPT Integration | ✗ | ✓ | | Earnings Call Transcripts | ✗ | ✓ — Professional plan only, $74/mo | | Free Trial | ✓ — 7-day full-access trial | 3-day trial (Professional plan only) | | Free Plan Available | ✗ | ✓ — US only, annual financials, 5 AI messages | | All Features Included at One Price | ✓ | ✗ — tiered: Free, Individual, Professional, Enterprise | --- ### 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+ pre-built 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 **Who Should Switch:** - Independent analysts and quantitative researchers - Boutique investment firms and family offices - Analysts who need XBRL-level data traceability - Those who can't justify $12K+/year enterprise licenses - US-focused fundamental equity specialists **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 Founders is $348/year — 97% cheaper. **Feature Comparison:** | Feature | GeminIQ | S&P Capital IQ | |---|---|---| | Primary Data Source | Direct SEC EDGAR | Proprietary aggregation from thousands of sources (normalized into standardized templates, with as-reported views also available) | | XBRL Tag Transparency | ✓ — every data point traceable to its specific XBRL tag | ✗ — click-through audit trail to source documents, but no XBRL tag exposure | | Raw, As-Filed Reporting Structure Preserved | ✓ — filing structure preserved exactly | Partial — as-reported financials available alongside templated views, but default workflow is normalized templates | | Company-Specific KPI Preservation | ✓ | Partial — industry supplemental pages for select sectors; Visible Alpha KPI data for 7,300+ companies as an add-on | | Click-Through Auditability | ✓ — XBRL tag links to source filing | ✓ — click-through audit trail to source documents | | Calculated Financial Metrics | 50+ KPIs from raw XBRL-tagged data | Extensive metrics library across all asset classes | | Advanced Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, and between logic | ✓ — comprehensive company, equity, and transaction screening with export to Excel | | Interactive Financial Visualizations | ✓ — line, bar, area charts with log/linear, z-score, min-max | ✓ — charting and analytics | | Custom Data Tables (saveable templates) | ✓ | ✓ — extensive template library | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — comprehensive comp analysis tools | | SIC-Based Sector Search | ✓ | ✓ — industry classification screening | | Insider Transaction Tracking | ✓ — visual sentiment timeline from SEC Form 4 | ✓ — comprehensive insider data | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✓ — extensive institutional ownership data | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — 109,000+ public companies globally | | Private Company Data | ✗ | ✓ — 60M+ private companies | | M&A / Deals Database | ✗ | ✓ — industry-leading deals database | | Credit Ratings | ✗ | ✓ — S&P Global Ratings | | Analyst Estimates & Price Targets | ✗ | ✓ — 140+ metrics, Visible Alpha integration | | Earnings Call Transcripts | ✗ | ✓ | | Fixed Income Data | ✗ | ✓ — 29M+ securities via Markit | | ESG Data | ✗ | ✓ — Trucost | | Excel CIQ Add-In | ✗ | ✓ — 250+ pre-built templates, Formula Builder | | AI Tools | ✗ | ✓ — ChatIQ, Document Intelligence, Chart Explainer | | Free Trial | ✓ — 7-day full-access | ✗ — personalized demo only; free academic access at 500+ universities | | Individual Pricing Available | ✓ — $29/mo, no contract | ✗ — enterprise contracts required, $12,000+/year minimum | --- ### 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 - 50+ 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) **Who Should Switch:** - Analysts spending hours copying filing data into spreadsheets - Investors who need trend visualization across 17+ years, not just documents - Anyone who wants KPIs and screening without manual extraction - Researchers who have outgrown document-only workflows - Budget-conscious analysts comparing $69/mo document search to $29/mo full analytics **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 50 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 Founders: $29/month. 58% cheaper. **Feature Comparison:** | Feature | GeminIQ | BamSEC | |---|---|---| | Automated Financial Data Extraction | ✓ — data parsed and structured automatically from every filing | ✗ — manual table extraction to Excel | | 50+ Calculated Financial KPIs | ✓ — ROIC, ROE, margins, growth rates, turnover, etc. | ✗ | | Interactive Multi-Metric Visualizations | ✓ — line, bar, area charts with log/linear scale, z-score, min-max | ✗ | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Advanced Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, and between logic | ✗ | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✗ — watched list for filing alerts only | | SIC-Based Sector Search | ✓ | ✗ | | Primary Data Source | Direct SEC EDGAR | SEC EDGAR | | XBRL Tag Transparency | ✓ — every data point traceable to its XBRL tag | ✗ — filing text, not structured XBRL data | | Raw, As-Filed Line Items Preserved | ✓ | ✓ — displays original filing documents | | Next-Day Filing Availability (T+1) | ✓ | ✓ | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular detail | ✓ — Form 4 data in table format | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✓ — 13F holdings in table format | | Full-Text Filing Search | ✗ | ✓ — Boolean, phrase, proximity operators across all filings | | Filing Comparison / Diff View | ✗ | ✓ — side-by-side redline comparison | | Similar Tables / Merge Tables | ✗ | ✓ | | Highlighting and Link-to-Text | ✗ | ✓ — shareable links to specific filing text | | Team Collaboration Tools | ✗ | ✓ — highlights, shared links, team annotations | | Earnings and Event Transcripts | ✗ | ✓ — S&P sourced, integrated with search | | Free Trial | ✓ — 7-day full-access | ✓ — 7-day free trial | | Free Browsing Tier | ✗ | ✓ — browse all EDGAR filings free, premium tools require Pro | | Price (billed annually) | $29/mo (Founders Plan) | $69/mo (Pro Plan) | --- ### 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:** - Pre-built 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) **Who Should Switch:** - US-focused fundamental analysts who verify numbers against 10-Ks and 10-Qs - Investors who need insider activity and institutional ownership in one platform - Those frustrated by normalized data that doesn't match the filing - Researchers who want XBRL-traceable source data instead of pre-processed metrics - Anyone who wants the complete analytical toolkit without per-region upsells **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 pre-built DCF models — instead, it provides the raw, verified data foundation that makes any model you build more trustworthy. Finbox for pre-built models on normalized data; GeminIQ for the foundation that makes your own models accurate. **Pricing:** GeminIQ Founders ($29/mo) is 56% cheaper than Finbox Professional ($66/mo annually). **Feature Comparison:** | Feature | GeminIQ | Finbox | |---|---|---| | Primary Data Source | Direct SEC EDGAR | S&P Global Market Intelligence (normalized) | | Raw, As-Filed Financials Preserved | ✓ | ✗ — normalized into standardized templates | | XBRL Tag Transparency | ✓ — every data point traceable to its XBRL tag | ✗ | | Company-Specific Line Item Preservation | ✓ | ✗ — standardized by S&P Global | | Full Data Auditability to Source Filing | ✓ | ✗ | | Years of Historical Data | 17+ years (all plans) | ~10 years of normalized financials | | All Historical Data Included at One Price | ✓ | ✓ — historical depth not paywalled by tier | | Calculated Financial Metrics | 50+ KPIs from raw source data | 1,000+ metrics from S&P Global data | | Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, between logic, on XBRL-traceable data | ✓ — 1,000+ metrics, powerful filtering, export requires paid tier | | Interactive Financial Visualizations | ✓ — line, bar, area charts with log/linear scale, z-score, min-max | ✓ — charting and data explorer | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✗ | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Pre-Built Valuation Models (DCF, DDM, Comps) | ✗ | ✓ | | Fair Value Estimates | ✗ | ✓ — automated for every stock | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — smart watchlists with customizable metric views | | SIC-Based Sector Search | ✓ | ✗ | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular Form 4 detail | ✗ — insider ownership % available as screener metric only | | Institutional Ownership Monitoring | ✓ — aggregate ownership trend tracking | ✗ — institutional ownership % available as screener metric only | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — 100,000+ stocks, 130+ exchanges | | Idea Generator / Investor Portfolios | ✗ | ✓ — popular investor portfolio tracking | | Analyst Estimates / Forecasts | ✗ | ✓ — consensus forecasts via S&P data | | Free Trial | ✓ — 7-day full-access | ✓ — 10-day trial on all plans, plus permanent free tier | | Free Plan Available | ✗ | ✓ — unlimited watchlists, model access, limited screener metrics | | All Features at One Price | ✓ | ✗ — tiered: Free, Starter, Executive, Professional, with per-region add-ons | --- ### 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 **Who Should Switch:** - Independent analysts and researchers who don't need advisor tools - Investors who need XBRL-traceable data, not client presentation features - Anyone paying $300+/month for fundamental research they could do at $29/month - US-focused fundamental equity specialists - Those who need insider activity and institutional ownership in their platform **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 Founders: $348/year. 90% cheaper. **Feature Comparison:** | Feature | GeminIQ | YCharts | |---|---|---| | Primary Data Source | Direct SEC EDGAR | S&P Global (normalized) | | XBRL Tag Transparency | ✓ — every data point traceable to its specific XBRL tag | ✗ | | Raw, As-Filed Reporting Structure Preserved | ✓ | ✗ — normalized by S&P Global | | Company-Specific Line Item Preservation | ✓ | ✗ — standardized templates | | Full Data Auditability to Source Filing | ✓ | ✗ | | Years of Historical Data | 17+ years (all plans) | Extensive (varies by metric and security type) | | All Historical Data Included at One Price | ✓ | ✓ — historical depth not tiered | | Calculated Financial Metrics | 50+ KPIs from raw XBRL-tagged data | 4,500+ financial metrics across 28,000+ equities (from S&P Global data) | | Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, between logic, on XBRL-traceable data | ✓ — 4,500+ metrics, 30+ pre-built templates, custom Scoring Models, NLP-powered | | Fund Screener | ✗ | ✓ — 77,000+ mutual funds, ETFs, CEFs, UITs with 50+ risk metrics | | Interactive Financial Visualizations | ✓ — line, bar, area with log/linear, z-score, min-max | ✓ — industry-leading branded visualizations and charts | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✓ — Comp Tables with 4,000+ metrics | | Scoring Models | ✗ | ✓ — custom weighted multi-factor scoring | | Timeseries Analysis | ✗ | ✓ — Professional plan | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — watchlists integrated with screener and alerts | | SIC-Based Sector Search | ✓ | ✗ | | Insider Transaction Tracking | ✓ — visual sentiment timeline from SEC Form 4 | ✗ | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✗ | | Client-Ready Branded PDF Reports | ✗ | ✓ — custom-branded, compliance-ready | | Proposal Generation | ✗ | ✓ | | Model Portfolio Construction | ✗ | ✓ | | Portfolio Analytics & Comparison | ✗ | ✓ | | Compliance Tools | ✗ | ✓ | | Team Collaboration & Sharing | ✗ | ✓ — Professional plan | | Custom Email Reports | ✗ | ✓ — Professional plan | | Economic Indicators & Macro Data | ✗ | ✓ | | Excel Add-in | ✗ | ✓ — Professional plan, with Quick Extract | | API Access | ✗ | ✓ | | Free Trial | ✓ — 7-day full-access | ✓ — 7-day free trial | | Free Plan | ✗ | ✗ | | Individual Pricing Available | ✓ — $29/mo, sign up online | ✗ — Contact sales required ($300+/mo per user) | --- ### 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 every plan - Proprietary Earnings Market Reaction Heatmap - Visual insider sentiment timeline with granular Form 4 detail - 26% cheaper than Fiscal.ai Pro (annual plans) **Who Should Switch:** - Analysts who need XBRL tag-level data lineage, not just filing links - US-focused fundamental researchers who verify every metric - Investors who need 17+ years of history without paying for a higher tier - Those who want insider transaction timelines and institutional ownership trends - Screener users who need every result traceable to the exact filing data point **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 Founders ($29/mo) is 26% cheaper than Fiscal.ai Pro ($39/mo annually) and 63% cheaper than Fiscal.ai Max ($79/mo). **Feature Comparison:** | Feature | GeminIQ | Fiscal.ai | |---|---|---| | Primary Data Source | Direct SEC EDGAR | S&P Global Market Intelligence (fundamentals) + proprietary Fiscal.ai Data Feed (segments/KPIs, sourced from public filings) | | XBRL Tag Transparency | ✓ — every data point traceable to its specific XBRL tag | ✗ | | Raw, As-Filed Reporting Structure Preserved | ✓ | Partial — segments/KPIs from filings; standardized financials from S&P Global | | Source Filing Auditability | ✓ — via XBRL tag, instant verification to exact data point | ✓ — click-through to source filings | | Company-Specific KPI Preservation | ✓ | ✓ — proprietary segment/KPI data for 2,100+ companies | | Data Update Speed | Next-day (T+1) | Minutes for financials; 15 min–1 hour for segments/KPIs after earnings | | Years of Historical Data | 17+ years (all plans) | 5 years (Free), 10 years (Pro), 10+ years with deeper KPI history (Max) | | All Historical Data Included at One Price | ✓ | ✗ — depth increases by tier | | Calculated Financial Metrics | 50+ KPIs from raw XBRL-tagged data | Comprehensive metrics and ratios from S&P Global data | | Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters on XBRL-traceable data | ✓ — 500+ filters, custom formulas, backtesting | | Interactive Financial Visualizations | ✓ — line, bar, area with log/linear, z-score, min-max | ✓ — interactive charts with ratio and event overlays | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✗ | | Customizable Dashboards | ✓ | ✓ — 1–unlimited depending on tier, with real-time alerts | | DCF Modeling | ✗ | ✓ — Pro and above | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — dashboards and comparison tools | | SIC-Based Sector Search | ✓ | ✗ | | AI Copilot (conversational research) | ✗ | ✓ — 10–500 prompts/month depending on tier, specialized financial AI | | AI Summaries & Reports | ✗ | ✓ | | Earnings Call Transcripts | ✗ | ✓ — with AI-powered search and summarization | | Analyst Estimates & Revisions | ✗ | ✓ — 1–3+ years forward depending on tier | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular Form 4 detail | ✓ — insider trades available in alerts and data | | Institutional Ownership Data | ✓ — aggregate ownership trend tracking | ✓ — major holders data | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — 100,000+ companies globally | | Data API | ✗ | ✓ — REST API with MCP beta | | Data Export | ✗ | ✓ — Max plan, US/Canada/ADRs | | Free Trial | ✓ — 7-day full-access | ✓ — free tier with limited access + 2-week Pro trial | | Free Plan | ✗ | ✓ — 10 AI prompts/month, 5 years of data, 1 dashboard | | All Features at One Price | ✓ | ✗ — tiered: Free, Pro, Max, Enterprise | --- ### GeminIQ vs Koyfin source: https://www.geminiq.com/competitor-comparison/koyfin **Headline:** The Best Koyfin Alternative for Analysts Who Need Auditable Source Data **What Koyfin Does Well:** - Exceptional charting and customizable multi-widget dashboards - Global coverage across equities, ETFs, mutual funds, FX, and macro - Economic data dashboards (FRED, Trading Economics integration) - Insider ownership and transactions (Plus and above) - Analyst estimates, transcripts, and premium news - AI Copilot for conversational research - Generous free plan for getting started **Where GeminIQ Wins:** - Direct SEC EDGAR data — no third-party normalization - XBRL tag traceability on every data point - Raw, as-filed company reporting preserved exactly - Proprietary Earnings Market Reaction Heatmap - Advanced screener with 100+ metrics and up to 10 stackable filters on auditable data - 17+ years of historical data on all plans (vs. 2 years free, 10 years on Plus) - 26% cheaper than Koyfin Plus, 63% cheaper than Koyfin Premium **Who Should Switch:** - US-focused fundamental analysts who verify numbers against 10-Ks - Investors who need XBRL-traceable data, not normalized aggregator data - Those frustrated by calculated metrics that don't match the filing - Screener power users who want every result traceable to source - Anyone who needs 17+ years of history without a paid upgrade **Why GeminIQ Was Built Differently:** Koyfin's strength is dashboard breadth — global equities, ETFs, macro, FX, and a polished interface. That breadth requires data licensing across many providers, which in equities means S&P Capital IQ. We took the opposite approach: scope down to US-listed SEC filers and go directly to the source. The tradeoff is real. GeminIQ won't show you Tokyo-listed equities or German bond yields. But for the analyst whose work involves comparing platform numbers against the underlying 10-K, going direct to EDGAR with XBRL tags intact means the gap between "what the platform shows" and "what the company filed" disappears. If your workflow needs global breadth, Koyfin is the better tool. If your workflow demands US data that exactly matches the filing, GeminIQ is built for exactly that case. **Pricing:** GeminIQ Founders ($29/mo) is 26% cheaper than Koyfin Plus ($39/mo annually) and 63% cheaper than Koyfin Premium ($79/mo annually). GeminIQ includes 17+ years of historical data (vs. 10 years on Koyfin Plus), with XBRL-traceable source data and a 7-day free trial. **Feature Comparison:** | Feature | GeminIQ | Koyfin | |---|---|---| | Primary Data Source | Direct SEC EDGAR | S&P Capital IQ (normalized), Morningstar (funds), FRED/Trading Economics (macro), and other licensed vendors | | Raw, As-Filed Financials Preserved | ✓ | ✗ — normalized by S&P Capital IQ | | XBRL Tag Transparency | ✓ — every data point traceable to its XBRL tag | ✗ | | Company-Specific Line Item Preservation | ✓ | ✗ — standardized into Capital IQ templates | | Full Data Auditability to Source Filing | ✓ | ✗ | | Years of Historical Data | 17+ years (all plans) | 2 years (Free), 10 years (Plus and above) | | All Historical Data Included at One Price | ✓ | ✗ — 2 years on free tier | | Interactive Financial Visualizations | ✓ | ✓ | | Custom Data Tables (saveable templates) | ✓ — build once, apply across tickers | ✓ — custom financial analysis templates, Plus and above | | Calculated Financial Metrics | 50+ KPIs from raw source data | Extensive metrics from S&P Capital IQ data | | Custom Formulas | ✗ | ✓ — limited on Free/Plus, unlimited on Premium | | Advanced Stock Screener | ✓ — 100+ metrics, up to 10 stackable filters with less than, greater than, between logic, on XBRL-traceable data | ✓ — global screener with templates, ETF screening on Plus+ | | Earnings Market Reaction Heatmap | ✓ — 1–12 month post-filing price drift | ✗ | | SIC-Based Sector Search | ✓ | ✗ | | Custom Watchlists with Comps Engine | ✓ — side-by-side data grids and multi-ticker charts | ✓ — smart watchlists with customizable views, shareable | | Insider Transaction Tracking | ✓ — visual sentiment timeline with granular Form 4 detail, 17+ years | ✓ — transaction chart and table with 2 years of history, Plus and above | | Institutional Ownership | ✓ — aggregate ownership trend tracking | ✓ — ownership snapshot | | Global Stock Coverage | ✗ — US-listed SEC filers only | ✓ — global equities, ETFs, mutual funds, FX, crypto | | Analyst Estimates & Consensus | ✗ | ✓ — forward estimates via S&P Capital IQ | | Economic / Macro Data Dashboards | ✗ | ✓ — FRED, Trading Economics, currency, bond data | | Earnings Call Transcripts | ✗ | ✓ — 9,000+ companies back to 2004 | | AI Copilot | ✗ | ✓ — AI-powered conversational research | | Portfolio Analytics | ✗ | ✓ — portfolio tracking, model portfolios | | Premium News Feed | ✗ | ✓ — MT Newswires, Plus and above | | Free Trial | ✓ — 7-day full-access | ✓ — free plan available, no time limit | | Free Plan Available | ✗ | ✓ — 2 years financials, limited features | | All Features at One Price | ✓ | ✗ — tiered: Free, Plus, Premium, Advisor tiers | --- ## 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.