Gross Margin
How much profit remains after subtracting the direct cost of goods sold.
Gross Margin = (Revenue − COGS) / Revenue × 100
Fundamental accounting, core to DuPont analysis since the 1920s.
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Interactive Financial Concepts
Every metric, score, and model used in fffinstill is grounded in peer-reviewed academic research. Explore each concept below — with interactive calculators, quizzes, and visual explainers.
47 Concepts
11 Categories
Interactive
Profitability & Margins
5 concepts
Return Metrics & Capital Efficiency
4 concepts
Balance Sheet Safety
5 concepts
Cash Flow Quality & Earnings
4 concepts
Academic Scoring Models
3 concepts
Growth Analysis
3 concepts
Macro Regime & Sensitivity
3 concepts
Insider Signals & Behavioral
2 concepts
Labor Efficiency & Operations
2 concepts
Conviction Scoring Engine
2 concepts
Statistical & Quantitative Methods
14 concepts
Complete Concept Reference
This reference covers all 50 financial analysis concepts used in fffinstill, organized across 11 categories. Each concept includes its academic origin, formula, interpretation guidelines, and how fffinstill applies it to real-world stock analysis.
Profitability & Margins5 concepts
Operating Margin (EBIT Margin)
Profitability after all operating expenses — the core earning power of the business.
Operating Margin = EBIT / Revenue × 100
Core income-statement metric used by Graham & Dodd (1934) in Security Analysis.
Net Profit Margin
The ultimate bottom line — what percentage of revenue becomes actual profit for shareholders.
Net Margin = Net Income / Revenue × 100
Standard financial reporting metric, mandated by GAAP/IFRS.
EBITDA Margin
Cash-proxy profitability that strips out non-cash charges and financing decisions.
EBITDA Margin = (EBIT + D&A) / Revenue × 100
Popularized in leveraged buyouts (1980s) to approximate operating cash flow.
FCF Margin (Free Cash Flow Margin)
What fraction of revenue converts to actual free cash that the company can deploy.
FCF Margin = (Operating CF − CapEx) / Revenue × 100
Developed by Jensen (1986) in the free cash flow theory of the firm.
Return Metrics & Capital Efficiency4 concepts
Return on Equity (ROE)
How efficiently a company generates profit from shareholders' invested capital.
ROE = Net Income / Shareholders' Equity × 100
Central to the DuPont decomposition framework (1920s, E.I. du Pont de Nemours).
Return on Assets (ROA)
How well a company uses ALL its assets to generate earnings, regardless of how they're financed.
ROA = Net Income / Total Assets × 100
Part of the DuPont decomposition and used in Piotroski F-Score.
Return on Invested Capital (ROIC)
The gold standard return metric — measures how well a company generates returns on ALL capital (debt + equity).
ROIC = NOPAT / Invested Capital × 100
McKinsey & Co. popularized ROIC in "Valuation" (1990). Central to economic profit theory.
Asset Turnover
How efficiently assets generate revenue — the "velocity" in the DuPont framework.
Asset Turnover = Revenue / Total Assets
DuPont decomposition: ROE = Margin × Turnover × Leverage.
Balance Sheet Safety5 concepts
Altman Z-Score
A statistical model that predicts the probability of corporate bankruptcy within 2 years.
Z = 1.2(WC/TA) + 1.4(RE/TA) + 3.3(EBIT/TA) + 0.6(MV Equity/TL) + 1.0(Revenue/TA)
Developed by Edward Altman at NYU Stern (1968). One of the most validated models in finance.
Debt-to-Equity Ratio
How much of the company is financed by debt versus equity — the leverage thermostat.
D/E = Total Debt / Shareholders' Equity
Modigliani & Miller (1958) established the theoretical foundation for capital structure.
Current Ratio
Can the company pay its bills due within the next 12 months?
Current Ratio = Current Assets / Current Liabilities
Benjamin Graham emphasized this in "The Intelligent Investor" (1949) as a safety screen.
Interest Coverage Ratio
How many times over can the company cover its interest payments from operating income.
Interest Coverage = EBIT / Interest Expense
Credit analysis fundamental, used by Moody's and S&P since the 1920s.
Net Debt / EBITDA
How many years of EBITDA would it take to pay off all net debt.
Net Debt / EBITDA = (Total Debt − Cash) / EBITDA
Standard credit metric used by rating agencies and leveraged buyout firms.
Cash Flow Quality & Earnings4 concepts
Operating Cash Flow / Net Income (Earnings Quality)
Tests whether reported earnings are backed by real cash — the #1 red flag detector.
OCF / NI = Operating Cash Flow / Net Income × 100
Sloan (1996) demonstrated that the accrual component of earnings predicts future stock returns.
Accruals Ratio
The portion of earnings that exists only on paper — a measure of accounting aggressiveness.
Accruals Ratio = (Net Income − Operating Cash Flow) / Total Assets × 100
Richardson et al. (2005) showed high accruals predict future earnings declines.
Free Cash Flow (FCF)
The real cash left after keeping the business running — what can be returned to shareholders or reinvested.
FCF = Operating Cash Flow − Capital Expenditures
Jensen (1986) FCF hypothesis; core to DCF valuation models.
CapEx / OCF (Capital Intensity)
What fraction of operating cash flow is consumed by capital expenditures.
CapEx / OCF = |Capital Expenditures| / Operating Cash Flow × 100
Maintenance vs. growth CapEx distinction emphasized by Buffett.
Academic Scoring Models6 concepts
Piotroski F-Score
A 9-point checklist scoring financial strength — originally designed for value stocks.
9 binary tests across Profitability (4 pts), Leverage/Liquidity (3 pts), Efficiency (2 pts)
Developed by Joseph Piotroski at Stanford (2000). Demonstrated that high F-Score value stocks outperform low F-Score stocks by 7.5% annually.
Fama-French Quality Factor
Academic quality metric combining profitability, growth, and safety attributes.
Multi-factor composite of profitability, growth, safety, and payout
Based on Fama & French five-factor model (2015) and Asness, Frazzini & Pedersen "Quality Minus Junk" (2019).
Composite Health Score
fffinstill's proprietary multi-factor score combining quality, safety, capital efficiency, durability, and shareholder value.
Weighted average of Quality Focus, Safety, Capital Efficiency, Durability, and Shareholder Value sub-scores
Built from academic literature: blends Piotroski, Altman, DuPont, and Fama-French into a 0–100 score.
Mohanram G-Score
An 8-point scoring model designed specifically for growth stocks — identifies which high-growth companies are likely to sustain their trajectory.
8 binary signals across Profitability (G1–G3), Naïve Extrapolation (G4–G5), and Earnings Stability (G6–G8)
Developed by Partha Mohanram at Columbia Business School (2005). Separates future winners from losers among high book-to-market (growth) stocks.
Fundamental Beta (BKS)
A purely accounting-based estimate of systematic risk — predicts market sensitivity without using any stock price data.
β = 1.0 + Σ(wᵢ × zᵢ) — weights: Earnings Variability 20%, Financial Leverage 18%, Operating Leverage 15%, Size 12%, Dividend 10%, Growth 10%, Liquidity 8%, Cyclicality 7%
Beaver, Kettler & Scholes (1970) showed 7 accounting variables predict market beta. Extended by Rosenberg & McKibben (1973). Fundamental Beta uses 8 z-scored risk dimensions.
Beneish M-Score
A statistical model that detects whether a company is likely manipulating its reported earnings.
M = −4.84 + 0.92(DSRI) + 0.528(GMI) + 0.404(AQI) + 0.892(SGI) + 0.115(DEPI) − 0.172(SGAI) + 4.679(TATA) − 0.327(LVGI)
Developed by Messod Beneish at Indiana University (1999). Successfully flagged Enron before its collapse.
Growth Analysis3 concepts
CAGR (Compound Annual Growth Rate)
The smoothed annual growth rate between two points — eliminates year-to-year noise.
CAGR = (End Value / Start Value)^(1/Years) − 1
Standard compound interest formula, foundation of time-value-of-money analysis.
Revenue Growth (YoY)
Year-over-year revenue change — the simplest measure of business momentum.
YoY Growth = (Current Revenue − Prior Revenue) / Prior Revenue × 100
Fundamental accounting comparison.
EPS (Earnings Per Share)
Net income distributed across each share — the metric most watched by Wall Street.
EPS (Diluted) = Net Income / Diluted Shares Outstanding
Required by GAAP (ASC 260). Ball & Brown (1968) showed EPS drives stock prices.
Macro Regime & Sensitivity3 concepts
Macro Regime Detection
Classifying the current economic environment to understand which stocks benefit or suffer.
Regime classification from FRED indicators: GDP, unemployment, yield curve, credit spreads, Fed Funds, PMI
Based on Hamilton (1989) regime-switching models and NBER business cycle research.
Rate Shock EPS Impact
How much a 100bps interest rate increase would impact a company's earnings.
Based on floating-rate debt exposure, debt maturity schedule, and interest coverage headroom.
Derived from duration analysis and fixed-income sensitivity concepts (Macaulay, 1938).
Pricing Power Score
A company's ability to raise prices without losing customers — the ultimate competitive moat signal.
Composite of gross margin stability, revenue growth during high-CPI periods, and sector-relative margin trends.
Conceptualized by Buffett; quantified through margin stability during inflationary periods.
Insider Signals & Behavioral2 concepts
Insider Conviction Signal
When executives buy their own stock with personal money, it's one of the strongest bullish signals.
Aggregation of Form 4 SEC filings: net shares transacted, net dollar value, distinct buyers vs. sellers, cluster buying detection
Lakonishok & Lee (2001) showed insider purchases predict positive abnormal returns of 4–7% annually.
Shareholder Dilution
When a company issues new shares, existing shareholders own a smaller piece of the pie.
Dilution = Change in Diluted Shares Outstanding over time
Agency cost theory (Jensen & Meckling, 1976).
Labor Efficiency & Operations2 concepts
Revenue per Employee
How much revenue each employee generates — a proxy for operational efficiency.
Revenue / Employee = Annual Revenue / Total Employees
Peter Drucker's management theory emphasized productivity per worker.
Operating Profit per Employee
How much profit each employee generates — combines productivity with cost management.
Op Profit / Employee = Operating Income / Total Employees
Extension of Drucker's productivity metrics, enhanced with BLS labor data.
Conviction Scoring Engine2 concepts
Conviction Score (0–100)
fffinstill's headline metric — a multi-factor score aggregating all available data signals into a single investment conviction number.
Starting point: Overall Health Score, then adjusted for ROIC, Piotroski, Z-Score, Earnings Quality, Insider Activity, Regime Fit, Labor Alpha, and Sector Position
Proprietary synthesis of Piotroski, Altman, Fama-French, insider signals, macro regime fit, labor efficiency, and sector-relative positioning.
Sector-Relative Positioning
Comparing a company against its sector and industry peers rather than absolute thresholds.
Percentile rank within sector/industry for Health Score, ROIC, and margins
Industry-relative valuation is standard in institutional equity research.
Statistical & Quantitative Methods14 concepts
Percentile Rank & Normalisation
Ranking every company within its sector on a 0–100 scale so metrics become directly comparable across industries.
Percentile = (# of values below x / total # of values) × 100
Foundational non-parametric statistic dating to Francis Galton (1885).
Weighted Average & Composite Scoring
Combining multiple metrics using assigned weights to produce a single summary score.
Composite = Σ(wᵢ × percentileᵢ) / Σwᵢ
Weighted means are foundational in portfolio theory (Markowitz, 1952).
Year-over-Year (YoY) Change
Measuring the percentage change in a metric between the same period in consecutive years.
YoY Change = ((Current Period − Prior Year Same Period) / |Prior Year Same Period|) × 100
Standard time-series analysis technique.
Compound Annual Growth Rate (CAGR)
The smoothed annual rate of return over a multi-year period.
CAGR = (Ending Value / Beginning Value)^(1/n) − 1
Standard financial mathematics.
Standard Deviation & Volatility
Measuring the dispersion of data points around the mean — the foundation of financial risk measurement.
σ = √(Σ(xᵢ − x̄)² / (n − 1))
Karl Pearson (1894). Harry Markowitz (1952) applied it as the primary measure of portfolio risk.
Coefficient of Variation (CV)
Standardised volatility — allows comparing risk across metrics with different scales.
CV = (σ / μ) × 100
Karl Pearson (1896).
Z-Score (Standardisation)
How many standard deviations a value is from the mean — universal comparison tool.
Z = (x − μ) / σ
Carl Friedrich Gauss (normal distribution). Not to be confused with Altman Z-Score.
Linear Regression & Trend Lines
Fitting a straight line through data points to identify trends and make projections.
y = mx + b where m = slope (trend), b = intercept
Legendre (1805), Gauss (1809).
Moving Averages & Smoothing
Averaging data over a rolling window to reveal underlying trends.
SMA(n) = Σ(last n values) / n
Used in signal processing and time-series analysis since the 1900s.
Ratio Analysis & Cross-Sectional Comparison
Expressing financial data as ratios for comparison across companies of different sizes.
Ratio = Metric A / Metric B (e.g., P/E, D/E, Current Ratio, ROE)
Benjamin Graham, "Security Analysis" (1934).
Logarithmic Scaling
Compressing wide-range data to make proportional changes visible.
log scale: equal distances represent equal percentage changes
John Napier (1614).
Correlation & Multi-Factor Analysis
Measuring how two variables move together — essential for diversification and factor analysis.
r = Σ((xᵢ−x̄)(yᵢ−ȳ)) / √(Σ(xᵢ−x̄)² × Σ(yᵢ−ȳ)²)
Pearson correlation (1895). Factor analysis: Spearman (1904), Fama & French (1992).
Winsorisation & Outlier Treatment
Capping extreme values to prevent outliers from distorting statistical summaries.
Values below 5th percentile → set to 5th percentile value; above 95th → set to 95th
Named after Charles P. Winsor.
Non-Parametric Methods
Statistical techniques that make no assumptions about the underlying data distribution.
Percentile rank, Median, Spearman rank correlation, Sign test
Frank Wilcoxon (1945), Henry Mann & Donald Whitney (1947).
See These Concepts in Action
Fundamentals Dashboard
Acceleration Matrix, Sector Analysis, and 6 more screening tools
Factors DashboardPiotroski F-Score, Fama-French, Z-Score, Beneish M-Score, G-Score, Fundamental Beta, and more
Foresight DashboardInsider signals, macro regime, refinancing risk, and sector rotation
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