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Code examples, market analysis, and data quality deep-dives.

Which Part of a 13F Is Worth Copying? Top Holdings Against New Buys in Python
How Much of a Ticker History Belongs to Another Company? Entity Resolution in Python
Which Corporate Line Item Turns First? Lead-Lag Analysis of S&P 500 Fundamentals in Python
Financial Data API Licensing: What You Can Redistribute
How to Pick a Benchmark for a Backtest
Are the Market’s Best Days Always Rebounds? Drawdown-State Analysis Across Sectors in Python
How Much of EPS Growth Comes From Share Buybacks? EPS Growth Decomposition in Python
How Long Does an S&P 500 Membership Last? Kaplan-Meier Survival Analysis in Python
How to Build a Stock Database in Python
Does Last Quarter’s Best Sector Stay on Top? Sector Rank Persistence in Python
How Much of the S&P 500’s Margin Expansion Is Index Turnover? Shift-Share Decomposition in Python
Trading Days vs Calendar Days: Why 252 Is Only an Average
How Much S&P 500 Profit Skips the Income Statement? Other Comprehensive Income in Python
How Many Calendar Anomalies Survive Multiple Testing? Bootstrap Reality Check in Python
How Long After Quarter End Do Financials Become Public? Filing Lag Analysis in Python
Does a Bollinger Band Squeeze Predict a Big Move? Band Width Analysis in Python
Do Sector Correlations Spike When the Market Falls? Conditional Beta Analysis in Python
Python Stock Data Libraries: What Each Gives You
Does the Balance Sheet Change Which Stocks Look Cheap? P/E Against EV/EBIT in Python
Can 2x Leveraged Sector ETFs Beat Their Sector? Volatility Drag Analysis in Python
Why Is Quarterly Cash Flow Year-to-Date in SEC Filings?
Are Earnings Harder to Forecast Than Revenue? Quarterly Time-Series Models in Python
Does Revenue Breadth Predict the Stock Market? A Quarterly Diffusion Index in Python
How Much Leverage Maximises Long-Run Growth? Kelly Sizing in Python
How to Run an Event Study in Python
Is a High-Margin Screen Just a Sector Bet? Sector-Neutral Profitability Ranking in Python
Does Proximity to the 52-Week High Beat Momentum? Conditional Quintile Sorts in Python
Does Negative Book Equity Signal Distress? S&P 500 Balance Sheet Screening in Python
How Late Does a Bear Market Signal Arrive? Turning-Point Detection in Python
How Much Historical Stock Data Do You Need?
Does Mean Reversion Survive Trading Costs? Moving-Average Deviations in Python
How Much Does Survivorship Bias Add to a Backtest? Point-in-Time S&P 500 Returns in Python
Does High Profitability Persist? Five-Year Transition Analysis in Python
Log Returns vs Simple Returns: Which to Use
Does Mean-Variance Optimisation Beat Equal Weighting? Out-of-Sample Test in Python
Which Sectors Actually Drive "Sell in May"? Sector Seasonality Analysis in Python
Does Free Cash Flow Coverage Predict Dividend Cuts Better Than the Payout Ratio? Point-in-Time Screening in Python
Bulk Stock Data Download vs API: Which to Use
Does a Stock's Beta Depend on the Benchmark? Cap-Weighted vs Equal-Weighted Markets in Python
How Long Does a Volatility Spike Take to Fade? Half-Life Estimation in Python
How Much Does a DCF Depend on Its Assumptions? Sensitivity Analysis in Python
How to Get a List of All US Stock Tickers
Do High-Idiosyncratic-Volatility Stocks Underperform? Residual Volatility Sorts in Python
Does Foreign Revenue Make a Stock Dollar-Sensitive? Firm-Level FX Beta in Python
Does Company Size Slow Revenue Growth? Gibrat's Law Test in Python
How to Get Stock Data Into Excel With Python
Does a Large Goodwill Balance Predict a Writedown? Impairment Risk Screening in Python
Does Revenue Concentration Explain Earnings Volatility? Segment Herfindahl Analysis in Python
Is Residual Momentum Better Than Raw Momentum? Market-Adjusted Decile Sorts in Python
Financial Data API Rate Limits: How Much Do You Need?
Does Index-Fund Ownership Make a Stock Move With the Market? 13F Ownership and Beta in Python
What Is Look-Ahead Bias in Backtesting?
How Much Drawdown Does Month-End Data Hide? Sampling Frequency and Maximum Drawdown in Python
Do Companies Pay the Tax They Report? Cash vs Book Tax Rates in Python
Does a High Dividend Payout Ratio Slow Earnings Growth? S&P 500 Cross-Section in Python
Web Scraping vs a Financial Data API: What Breaks
Did Earnings or the Multiple Drive the Last Decade of Returns? Return Decomposition in Python
What Does a Trailing Stop Cost? Stop-Loss Backtest in Python
Why Do Stock Prices Differ Between Data Sources?
Does an Inventory Build Predict a Margin Squeeze? Cross-Sectional Test in Python
How Much Revenue Does a Dollar of Acquisitions Buy? Growth Decomposition in Python
Do Companies Buy Back Stock at Good Prices? Dollar-Weighted Analysis in Python
What Data You Need for Comparable Company Analysis
How Much Does a Stock Fall on Its Ex-Dividend Date? Event Study in Python
How Seasonal Is Quarterly Revenue? Fiscal Quarter Share Analysis in Python
Do Reported Financials Follow Benford's Law? First-Digit Analysis in Python
What Is Book Value? Why Price-to-Book Stopped Working
How Far Apart Do S&P 500 Stocks Move? Cross-Sectional Return Dispersion in Python
Fama-French Factor Data: Download or Build Your Own?
How Much Does the Rebalance Date Change a Backtest? 21 Rebalance Days in Python
Does Trading Volume Predict Tomorrow's Volatility? Out-of-Sample Test in Python
Do Company Insiders Predict Their Own Stock's Returns? Form 4 Cross-Section in Python
How Many Independent Bets Are There in the S&P 500? Principal Component Analysis in Python
Can a Company's Revenue Be Forecast From Its Own History? Out-of-Sample Test in Python
What Is EBITDA and Why Do Sources Disagree?
Does the Turn-of-the-Month Effect Still Work? Calendar Anomaly Test in Python
Is the S&P 500 Getting More Capital Intensive? Capex Analysis in Python
Do High-Accrual Companies Underperform? Accruals Screening in Python
What Does a Financial Data API Cost?
Do Price Gaps Get Filled? Gap-Fill Rates Against a Random Walk in Python
What Expected Returns Does the S&P 500 Imply? Reverse Optimization in Python
Which Sectors Are Really Cyclical? Revenue Betas vs Stock Betas in Python
How to Build a Stock Dataset for Machine Learning
Comparing Companies With Different Fiscal Year Ends
How Much Has Corporate Debt Actually Repriced? Effective Interest Rates in Python
Does Deferred Revenue Predict Next Quarter's Sales? Leading Indicator Test in Python
How Much Debt Is Hidden in Operating Leases? Lease-Adjusted Leverage in Python
How Much Do Profits Move When Sales Move? Operating Leverage Regression in Python
How Concentrated Is the S&P 500? Index Weight Analysis in Python
How Long Is Cash Tied Up in a Business? Cash Conversion Cycle Analysis in Python
Broker API vs Data API for Historical Stock Data
Where to Get Free Cash Flow Data for Stocks in Python
Are Stock Returns Skewed? Return Skewness in Python
Do High-Margin Companies Trade at Higher Multiples? EV/Sales in Python
How Much Profit Becomes Cash? Free Cash Flow Conversion in Python
Which Sectors Lead Out of a Market Bottom? Sector Recovery Analysis in Python
Are Buybacks Funded by Cash Flow or by Debt? S&P 500 Payout Analysis in Python
What to Look for in Fundamentals Data
Does Cash on the Balance Sheet Cushion a Crash? Quintile Sorts in Python
Do Corporate Insiders Time the Market? S&P 500 Insider Buying Breadth in Python
Does Unstable Volatility Warn of Deeper Drawdowns? Vol-of-Vol Sorts in Python
Does Fast Asset Growth Predict Weak Stock Returns? Decile Sorts in Python
How to Replace yfinance in a Python Script
Does the Nasdaq-100 Index Effect Still Exist? Event Study in Python
Does the Piotroski F-Score Still Work? Quality Screening in Python
How Many S&P 500 Stocks Beat the Index? Return Breadth Analysis in Python
Why Beta Differs Between Data Sources
Where to Get Historical Dividend Data for Stocks
Does a High Dividend Yield Predict a Dividend Cut? Yield-Trap Screening in Python
Do Old Ticker Symbols Still Point to the Same Company? S&P 500 Ticker Recycling in Python
What Growth Is Priced Into the S&P 500? Reverse DCF in Python
Ticker vs CIK vs FIGI: Which Company ID to Use
Does Illiquidity Still Pay? Amihud Measure in the S&P 500 in Python
Where to Get R&D Spending Data for Public Companies
Does R&D Spending Predict Revenue Growth? Cross-Sectional Test in Python
What Actually Drives Return on Equity? DuPont Decomposition in Python
What Data Do You Need to Measure Portfolio Risk?
Does a 60/40 Portfolio Actually Cut Drawdowns? Stocks and Bonds in Python
Do Steady Margins Mean Calmer Stocks? Cross-Sectional Analysis in Python
Do Sectors Diversify When It Matters? Conditional Correlation in Python
How to Get Historical Market Cap Data in Python
How Much of the S&P 500 Survives 20 Years? Index Turnover Analysis in Python
Does Joining the S&P 500 Bring New Institutional Owners? 13F Event Study in Python
Is Volatility Seasonal? Calendar Month Analysis of Realized Volatility in Python
Does Fast Revenue Growth Force Companies to Borrow? Cash Funding Analysis in Python
How Far Back Does SEC EDGAR Data Go?
Are One-Time Charges Really One-Time? Charge Frequency Analysis in Python
Does Buying the Dip Work? Short-Term Reversal by Volatility Regime in Python
Alpha Vantage vs Massive vs xfinlink for Fundamentals
How Long Does a Stock Take to Recover From a 50% Fall? Drawdown Analysis in Python
Do Companies That Shrink Their Share Count Outperform? Net Buyback Yield in Python
How Much Does the Dow's Price Weighting Distort It? Index Weighting Analysis in Python
How to Get SEC Form 4 Insider Trading Data in Python
Can Anything Predict Next Month's Stock Returns? Out-of-Sample R-Squared Testing in Python
How Much of a Stock's Return Comes From Its Sector? Variance Decomposition in Python
Altman Z-Score: Where To Get It in Python
Do Value Screens Agree on Which Stocks Are Cheap? Multiple Overlap Analysis in Python
Annual vs Quarterly Financial Data: Which to Use
Do High Returns on Capital Persist? ROIC Fade Analysis in Python
Does Past Beta Predict Future Beta? Beta Stability Testing in Python
Do Defensive Sectors Actually Defend? Up and Down Capture in Python
How to Choose a Financial Data API
Do Small Caps Actually Beat Large Caps? Size Premium Test in Python
What If You Miss the Market's Best Days? Extreme-Day Analysis in Python
Does Rebalancing Add Return? Fixed-Weight vs Drift Portfolios in Python
Which S&P 500 Companies Are Closest to Default? Merton Distance-to-Default in Python
What Happens to Stocks Removed From the S&P 500? Replacement Pair Analysis in Python
Does the Golden Cross Work? 50/200 Moving Average Crossover Backtest in Python
Financial Data for Academic Finance Research
Does Skipping the Most Recent Month Improve Momentum? S&P 500 Decile Sorts in Python
Does Cointegration Survive Out of Sample? Pairs Trading Validation in Python
Which Dividends Are Not Covered by Cash? Free-Cash-Flow Coverage Screening in Python
GICS vs SIC vs NAICS: Which Industry Classification to Use
How Many Stocks Does It Take to Diversify? Random Portfolio Simulation in Python
How Many Days of Data Does a Volatility Estimate Need? Range-Based Estimators in Python
How Much of S&P 500 Cash Flow Is Stock Compensation? Cross-Sectional Analysis in Python
What Is a 13F Filing? Institutional Holdings Explained
Does Revenue Growth Explain Profit Growth? Cross-Sectional Decomposition in Python
How Much of the Nasdaq 100 Is Already in the S&P 500? Index Overlap Analysis in Python
How Often Does a 99% Value-at-Risk Limit Actually Break? VaR Backtesting in Python
Real-Time vs End-of-Day Market Data: Which Do You Need?
How Concentrated Are S&P 500 Earnings? Point-in-Time Index Analysis in Python
Does Volatility Scale With the Square Root of Time? Variance Ratio Test in Python
Does Goodwill Distort the Price-to-Book Screen? Goodwill-Adjusted Valuation in Python
How Are Shares Outstanding Reported (and Why They Disagree)
Do Low-Volatility Stocks Deliver Better Risk-Adjusted Returns? S&P 500 Quintile Sorts in Python
Does Trend Following Beat Buy and Hold? Time-Series Momentum in Python
Has the Stock-Bond Correlation Flipped? 60/40 Portfolio Risk in Python
What API to Use for a Stock Screener
Which Assets Hedge Inflation Shocks? Macro Factor Betas in Python
Does Covariance Shrinkage Beat the Sample Covariance? Minimum-Variance Portfolios in Python
Do Faster Inventory Turns Mean Thinner Margins? Gross Margin Return on Inventory in Python
SEC EDGAR API vs Fundamentals API: Which to Use
Does Fast Earnings Growth Persist? Rank Correlation Analysis in Python
Split Adjustment Explained: Adjusted Close vs Close
Which Trading Day of the Month Pays Best? Turn-of-the-Month Analysis in Python
Can You Use Yahoo Finance Data Commercially?
How Many Independent Bets Does a Nine-Sector Portfolio Give You? Eigenvalue Analysis in Python
Which Volatility Forecast Wins One Month Ahead? HAR vs EWMA in Python
How Concentrated Are Institutional Equity Portfolios? Form 13F Concentration Analysis in Python
Do Stocks Earn Their Returns Overnight or Intraday? Return Decomposition in Python
When Do Corporate Insiders Actually Trade? Form 4 Timing Analysis in Python
Data Requirements for Backtesting a Trading Strategy
What Is Survivorship Bias in Backtesting?
Do High Dividend Yields Come From Bigger Payouts or Falling Prices? Yield Decomposition in Python
Do Stocks Fall Harder Than They Rise? Downside Beta vs Upside Beta in Python
Does Volatility Targeting Improve Sharpe Ratios? Seven-Asset Backtest in Python
Free Stock Market Data APIs: What You Actually Get
How to Give an LLM Financial Data With an MCP Server
Does Post-Earnings Announcement Drift Survive Real Filing Dates? PEAD Event Study in Python
Do Insider Buying Clusters Predict Returns? Signal Testing in Python
Does the S&P 500 Index Effect Still Exist? Event Study in Python
Are Companies Leaving the S&P 500 Faster Than They Used To? Index Survival Analysis in Python
Does Gross Profitability Predict Stock Returns? Quintile Factor Test in Python
What Growth Rate Is the Market Pricing In? Reverse DCF in Python
Does a Strong Balance Sheet Cushion Drawdowns? Leverage and Downside Risk in Python
Does Ticker Recycling Corrupt a Mean-Reversion Backtest? Entity-Resolved Z-Scores in Python
How Much of a Growth Screen's Backtested Edge Is Survivorship Bias? Point-in-Time Index Testing in Python
Why Do Leveraged ETFs Decay? Measuring Volatility Drag in Python
Are Consumer Staples Margins Shrinking Under Inflation? Gross Margin Trend Analysis in Python
Do Weak Jobs Reports Predict Market Drawdowns? NFP Surprise Event Study in Python
Is the Rotation From Tech to Industrials Backed by Earnings? Relative EPS Growth Analysis in Python
Is the Semiconductor Rally Broadening Beyond NVIDIA? Return Dispersion Analysis in Python
Which Stocks Benefit Most When Oil Prices Fall? Oil Beta Screening in Python
Do Bond Returns Predict Stock Returns? Granger Causality Test in Python
Which Stocks Actually Drive Portfolio Returns? Shapley Value Attribution in Python
Does "Sell in May" Still Work? Calendar Anomaly Backtest in Python
How to Build Complete Price History Through Ticker Changes? Entity Resolution in Python
Are KO and PEP Cointegrated? Pairs Trading Signal Construction in Python
Which Commodities Have the Strongest Momentum? Rotation Backtest in Python
Which Commodity ETFs Have the Worst Tail Risk? Expected Shortfall in Python
Are Gold Miners Leveraged Gold Bets? Rolling Beta Analysis in Python
Does the Base-Metals-to-Gold Ratio Lead Cyclical Stocks? Signal Test in Python
Can Risk Parity Tame Commodity Volatility? Portfolio Optimization in Python
Are Power Stocks Becoming an AI Infrastructure Trade? Momentum Screening in Python
Which AI Chip Stocks Have Margin Momentum? Profitability Trend Analysis in Python
Which AI Stocks Are Cheapest Relative to Growth? Growth-Adjusted Valuation in Python
Does AI Stock Leadership Persist? Momentum Backtest in Python
Which AI Stocks Have the Cleanest Balance Sheets? Net Cash Screening in Python
Can Risk Parity Reduce Mega-Cap Drawdowns? Portfolio Optimization in Python
Which Growth Stocks Are Self-Funding? Cash-Flow Quality Screening in Python
Which Sectors Struggle When the Dollar Rallies? Sector Rotation Analysis in Python
Do Cheap Stocks Hold Up When Bonds Sell Off? Valuation Rotation in Python
Does the Nasdaq 100 Have Better Growth Quality Than the Dow? Index Constituent Analysis in Python
Do Healthcare Cash-Flow Margins Predict Returns? Signal Evaluation in Python
Which Dividend Stocks Survive a Cash-Flow Stress Test? Dividend Screening in Python
Does Heavy Insider Selling Predict Weak Returns? Insider Flow Test in Python
Can Quality Screens Reduce Small-Cap Balance-Sheet Risk? Russell 2000 Test in Python
Which Retailers Have Positive Operating Leverage? Margin Screening in Python
Is MSTR a Leveraged Bitcoin Proxy? Rolling Beta Analysis in Python
Is Micron's Memory Cycle Recovering? Inventory and Margin Forecasting in Python
Which Sectors Work When Bonds Rally? Rate-Sensitive Rotation in Python
Do One-Month Price Extremes Reverse? Signal Evaluation in Python
Do Low-Volatility S&P 500 Stocks Reduce Drawdowns? Factor Test in Python
Is AI Capex Paying Back Fast Enough? Revenue Hurdle Forecasting in Python
Could Shorter AI Asset Lives Hit Earnings? Depreciation Stress Test in Python
How Much AI Capex Risk Can a Portfolio Remove? Constrained Optimization in Python
Is the AI Capex Trade Crowded? Rolling Volatility and Sector Rotation in Python
Did the AI Boom Come From Existing S&P 500 Members? Point-in-Time Momentum Test in Python
Is AI Revenue Circular? Customer-Vendor Capex Loop Analysis in Python
Is the AI Trade Connected to Private Credit? Rolling Correlation Network in Python
Is Apollo More Balance-Sheet Sensitive Than Peers? Leverage Screen in Python
Are AI Earnings Supported by Cash Flow? Accrual and Capex Screen in Python
Can Defensive Stocks Hedge AI Drawdowns? Basket Regime Test in Python
How Fast Does the Market Price In Fed Decisions? FOMC Event Study in Python
How Much Are Options Sellers Overpaid? The Variance Risk Premium in Python
Which Companies Have the Worst Earnings Quality? Sloan Accrual Screen with Geographic Revenue Data in Python
Does the Oil-to-Gold Ratio Signal Recessions? XLE/GLD Backtest in Python
Is AI Spending Crowding Out Free Cash Flow? Capex Sustainability Across the Mag 7 in Python
Does a Long Energy / Short Bonds Portfolio Capture Inflation Surprises? Factor Construction in Python
Can a Hidden Markov Model Detect Oil Market Regimes? HMM Analysis in Python
Do Grain Prices Predict Food Inflation? Granger Causality Test in Python
Does the Corporate Credit Spread Predict Stock Market Crashes? BAA-AAA Spread Analysis in Python
Do Oil Stocks Hedge Inflation? Rolling Beta Analysis in Python
Which Stocks Are Most Rate-Sensitive? Equity Duration via Bond Beta in Python
Which Companies Have the Highest Accrual Ratios? Earnings Quality Screening in Python
Is Alpha Persistent or Decaying? Rolling Sharpe Ratio Analysis in Python
Are Markets Trending or Mean-Reverting? Hurst Exponent Analysis in Python
Is Consumer Discretionary vs Staples a Leading Indicator? XLY/XLP Ratio Analysis in Python
Does Heavy Capex Predict Future Stock Returns? Capital Expenditure Analysis in Python
How to Estimate Cost of Equity Using CAPM in Python
Is Volatility Predictable? Testing for Volatility Clustering in Python
Which Industrials Are Overleveraged? Net Debt to EBITDA Screening in Python
GM Before and After Bankruptcy: Why Entity Resolution Matters for Financial Data
What Is Adjusted Beta? Merrill Lynch Beta Shrinkage in Python
How Good Is a Stock Pick? Information Ratio and Tracking Error in Python
Do Stock Returns Follow a Normal Distribution? Testing for Fat Tails in Python
Which Large Caps Have the Highest Free Cash Flow Yield? FCF Screening in Python
Which Sectors Won Over 5 Years? Sector Rotation Analysis in Python
How to Forecast Stock Volatility with GARCH Models in Python
Are Stock Prices Mean-Reverting? Augmented Dickey-Fuller Test in Python
How to Calculate CAPM Alpha and Beta with Regression in Python
How to Compare Sector Sharpe Ratios and Sortino Ratios in Python
DELL: Why Stitching Historical Price Data Together Is Wrong
How to Analyze Drawdown and Recovery for Bank Stocks in Python
How to Screen SaaS Stocks by Revenue Growth and Cash Flow in Python
How to Screen REITs by Dividend Yield and Valuation in Python
How Correlated Are the Magnificent 7? Intra-Group Correlation in Python
AAPL vs XOM: Do Individual Stocks Have Seasonal Patterns?
How to Rank Large-Cap Stocks by Momentum in Python
How to Build a Multi-Endpoint Financial Dashboard in Python
How to Compare Volatility Across Energy Stocks in Python
How to Screen Healthcare Stocks by Valuation in Python
How to Build a Sector Correlation Matrix for Portfolio Diversification in Python
How to Find Oversold and Overbought Stocks Using Z-Scores in Python
How to Measure Earnings Quality: Cash Flow vs Net Income in Python
How to Build a Multi-Factor Stock Screen in Python (Value + Momentum + Quality)
How to Build a Simple DCF Model for Any Stock in Python
How to Screen Tech Stocks by Revenue Growth in Python
How to Screen Stocks by Balance Sheet Health in Python
Is "Sell in May" Real? SPY Monthly Seasonality Over 10 Years
How to Compare Sector Performance YTD Using Python
How to Screen Dividend Stocks by Yield and Quality in Python
How to Calculate Max Drawdown and Recovery Time for Any Stock in Python
How to Compare Profitability Across Mega-Cap Tech Stocks in Python
Why Ticker Symbols Are Unreliable: The Recycling Problem Every Quant Should Know
How to Calculate and Compare Stock Volatility in Python
How to Screen Blue-Chip Stocks by P/E Ratio in Python
How to Track Companies Through Ticker Changes, Bankruptcies, and Renames in Python
S&P 500 Turnover: How Much the Index Has Changed Since 2010
How to Calculate Stock Beta and Correlation in Python
← All articles

Why Is Quarterly Cash Flow Year-to-Date in SEC Filings?

Quarterly cash flow arrives year-to-date because the SEC requires it that way. Rule 210.10-01(c)(3) of Regulation S-X states that interim statements of cash flows “shall be provided for the period between the end of the preceding fiscal year and the end of the most recent fiscal quarter” (verified against the eCFR, September 2026). A second-quarter 10-Q therefore reports six months of cash flow, and a third-quarter 10-Q reports nine. To recover a single quarter, subtract the previous cumulative figure from the current one. The fourth quarter takes the annual total from the 10-K minus the nine-month figure, because no filing reports it on its own.

What Does a 10-Q Actually Report?

Two statements inside one document follow different rules, which is why this catches people who have already handled quarterly revenue without trouble. Paragraph (c)(2) of the same rule requires interim statements of comprehensive income “for the most recent fiscal quarter” as well as for the year-to-date period. Paragraph (c)(3), covering cash flows, asks only for the cumulative period. Revenue and net income leave a 10-Q in both shapes; operating cash flow leaves in one.

Apple’s fiscal 2025 shows the pattern without ambiguity. Every fact below carries the same start date, 29 September 2024, and a later end date:

2024-09-29 to 2024-12-28    3 months     29,935m   10-Q
2024-09-29 to 2025-03-29    6 months     53,887m   10-Q
2024-09-29 to 2025-06-28    9 months     81,754m   10-Q
2024-09-29 to 2025-09-27   12 months    111,482m   10-K

Read those four values as quarters and Apple appears to have raised its quarterly operating cash flow from $29.9bn to $111.5bn inside a year. The true quarters are the gaps between consecutive rows: 29,935, then 23,952, then 27,867, then 29,728.

Why Is There No Fourth-Quarter Cash Flow Statement?

Companies file three 10-Qs and one 10-K a year. The 10-K covers twelve months and never isolates the final three. A fourth quarter is a derived figure by construction rather than a reported one, which is also why fourth-quarter figures from different vendors disagree more often than the other three.

Apple’s tagged history makes the point concrete. Of every operating cash flow fact the company has filed under NetCashProvidedByUsedInOperatingActivities, sixteen carry a three-month duration, and all sixteen are first quarters, running from fiscal 2009 through fiscal 2026 (verified against data.sec.gov, September 2026). The other durations are six, nine and twelve months.

Anyone building a quarterly series from EDGAR therefore writes two pieces of logic: the subtraction itself, and a reset at the fiscal year boundary. The reset is where implementations usually break, because subtracting a fiscal first quarter from the prior year’s annual total produces a number that is wrong and looks ordinary.

How Do You Get Standalone Quarters Instead?

The code below pulls the same fiscal year twice. Once from the SEC as filed, once from xfinlink, where quarterly cash flow rows are already de-cumulated to single-quarter values at ingestion. Walmart is included as a second case because its fiscal year ends on 31 January, so its quarters and the calendar quarters never line up.

import json
import urllib.request

import pandas as pd
import xfinlink as xfl

xfl.set_api_key("YOUR_API_KEY")  # free at https://xfinlink.com/signup

TAG = "NetCashProvidedByUsedInOperatingActivities"
HEADERS = {"User-Agent": "your name your.email@example.com"}  # SEC requires this


def as_filed(cik, fiscal_start):
    """Operating cash flow exactly as the company tagged it with the SEC."""
    url = f"https://data.sec.gov/api/xbrl/companyconcept/CIK{cik}/us-gaap/{TAG}.json"
    req = urllib.request.Request(url, headers=HEADERS)
    facts = json.load(urllib.request.urlopen(req))["units"]["USD"]
    return sorted({(f["start"], f["end"], f["val"], f["form"])
                   for f in facts if f["start"] == fiscal_start})


cases = [
    ("Apple fiscal 2025", "AAPL", "0000320193", "2024-09-29", "2024-10-01", "2025-10-01"),
    ("Walmart fiscal 2026", "WMT", "0000104169", "2025-02-01", "2025-02-05", "2026-02-05"),
]

for label, ticker, cik, fiscal_start, start, end in cases:
    print(label)
    print("  as filed with the SEC")
    for s, e, val, form in as_filed(cik, fiscal_start):
        months = round((pd.Timestamp(e) - pd.Timestamp(s)).days / 30.44)
        print(f"    {s} to {e}  {months:2d} months  {val / 1e6:>9,.0f}m  {form}")

    q = xfl.fundamentals(ticker, period_type="quarterly", start=start, end=end,
                         fields=["operating_cash_flow", "capital_expenditures",
                                 "free_cash_flow"])
    a = xfl.fundamentals(ticker, period_type="annual", start=start, end=end,
                         fields=["operating_cash_flow"])
    print("  standalone quarters from xfinlink")
    for _, r in q.iterrows():
        print(f"    {r.fiscal_period} to {r.period_end.date()}  "
              f"ocf {r.operating_cash_flow:>8,.0f}m  "
              f"capex {r.capital_expenditures:>6,.0f}m  "
              f"fcf {r.free_cash_flow:>8,.0f}m")
    print(f"    quarters sum to {q['operating_cash_flow'].sum():>9,.0f}m")
    print(f"    annual row      {a['operating_cash_flow'].iloc[0]:>9,.0f}m
")
Apple fiscal 2025
  as filed with the SEC
    2024-09-29 to 2024-12-28   3 months     29,935m  10-Q
    2024-09-29 to 2025-03-29   6 months     53,887m  10-Q
    2024-09-29 to 2025-06-28   9 months     81,754m  10-Q
    2024-09-29 to 2025-09-27  12 months    111,482m  10-K
  standalone quarters from xfinlink
    Q1 to 2024-12-28  ocf   29,935m  capex  2,940m  fcf   26,995m
    Q2 to 2025-03-29  ocf   23,952m  capex  3,071m  fcf   20,881m
    Q3 to 2025-06-28  ocf   27,867m  capex  3,462m  fcf   24,405m
    Q4 to 2025-09-27  ocf   29,728m  capex  3,242m  fcf   26,486m
    quarters sum to   111,482m
    annual row        111,482m

Walmart fiscal 2026
  as filed with the SEC
    2025-02-01 to 2025-04-30   3 months      5,411m  10-Q
    2025-02-01 to 2025-07-31   6 months     18,352m  10-Q
    2025-02-01 to 2025-10-31   9 months     27,452m  10-Q
    2025-02-01 to 2026-01-31  12 months     41,565m  10-K
  standalone quarters from xfinlink
    Q1 to 2025-04-30  ocf    5,411m  capex  4,986m  fcf      425m
    Q2 to 2025-07-31  ocf   12,941m  capex  6,423m  fcf    6,518m
    Q3 to 2025-10-31  ocf    9,100m  capex  7,218m  fcf    1,882m
    Q4 to 2026-01-31  ocf   14,113m  capex  8,015m  fcf    6,098m
    quarters sum to    41,565m
    annual row         41,565m

Both reconciliations close to the dollar, and capital expenditure sits on the same row as the cash flow it is subtracted from, so free cash flow can be checked rather than trusted. Field definitions are in the docs; the free tier covers a rolling one-year window and paid plans carry full history, which is set out on the pricing page.

Which Sources Return Standalone Quarters?

SourceWhat the quarterly cash flow looks likeFourth quarter
SEC XBRL company concept APIAs filed, so year-to-date durations of 3, 6, 9 and 12 monthsAbsent; derive it from the 10-K
Alpha Vantage CASH_FLOWannualReports and quarterlyReports; IBM’s four fiscal 2025 quarters sum to its annual figurePresent in that response
yfinanceTicker.quarterly_cashflow returns a DataFrame; the reference gives no further detailCheck it yourself
xfinlinkSingle-quarter values, de-cumulated at ingestionPresent, and it foots to the annual row

Alpha Vantage deserves credit here. Its demo response for IBM returned 20 annual and 81 quarterly cash flow reports, and the four fiscal 2025 quarterly operatingCashflow values add up exactly to the annual figure alongside them, so those quarters are standalone rather than cumulative (verified against the Alpha Vantage demo endpoint, September 2026). The constraint is throughput rather than shape: a free Alpha Vantage key is capped at 25 API requests per day, stated on the company’s own premium page as of September 2026, which is roughly twelve companies if each needs a cash flow call and a price call.

What Breaks When the Quarters Stay Cumulative?

Walmart is the clearest illustration, because retail cash flow is violently seasonal. Its true fiscal 2026 quarters run 5,411, 12,941, 9,100 and 14,113. A pipeline that reads the year-to-date figures as quarters reports the fourth quarter as 41,565, which is 2.9 times the real number, and the first quarter correctly, which is what makes the fault so hard to see.

What fails afterwards fails quietly. Seasonality disappears, because a cumulative series rises monotonically inside every fiscal year whatever the business actually did, and quarter-on-quarter growth then measures the calendar rather than the company. Coverage ratios built on a quarter, such as dividends against operating cash flow, come out understated in the first quarter and overstated by the fourth.

None of this throws an error. The series looks smooth, which is precisely the problem: a smooth, rising, four-point series per year is what a cumulative series looks like, and it is also what a healthy company looks like.

FAQ

Is quarterly revenue year-to-date as well? No. Regulation S-X requires interim income statements for the most recent fiscal quarter alongside the year-to-date period, so a 10-Q carries revenue and net income in both shapes. Only the cash flow statement is cumulative-only, and that asymmetry is why a pipeline can look correct on the income statement and be wrong on cash flow.

How do I check whether my quarters are already standalone? Sum four consecutive fiscal quarters and compare the result against the annual figure for that fiscal year. Standalone quarters foot to the annual total; cumulative ones overshoot it badly, by 2.5 times for Apple’s fiscal 2025 and 2.2 times for Walmart’s fiscal 2026. Run the check on a company whose fiscal year does not end in December, which will also catch calendar-alignment mistakes.

Do fiscal quarters match calendar quarters? Often not. Apple’s fiscal 2025 ended on 27 September 2025 and Walmart’s fiscal 2026 ended on 31 January 2026, so grouping either company by calendar quarter mixes periods that the company never reported together. More on that in comparing companies with different fiscal year ends.

Where to Go Next

The check worth building into any pipeline is the reconciliation above: four quarters against the annual row, per company, per fiscal year. It costs one extra call and it catches cumulative quarters, a missed fiscal-year reset, and a mislabelled fourth quarter in the same test. xfinlink returns both period types from the same endpoint with the same field names, so the comparison is two lines. Related reading: where to get free cash flow data and annual vs quarterly financial data.

Built with xfinlink — free financial data API for Python. pip install -U xfinlink

Built with xfinlink — free financial data API for Python. pip install -U xfinlink
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