QSI

Adjusts the numerator for debt and cash so heavily-levered or cash-rich companies become comparable on a revenue-multiple basis. Particularly useful for cross-industry valuation work where some firms run net cash and others carry meaningful debt loads. Same caveats as P/S: best read alongside gross margin to translate the multiple into expected steady-state earnings power.

Capital-structure-agnostic earnings yield. Pairs with Greenblatt ROC to compute the famous Magic Formula rank (the universe-rank of earnings yield plus universe-rank of return on capital). Pre-tax operating earnings divided by the full claim on the firm gives a cleaner cross-firm valuation comparison than P/E or earnings yield alone, because it strips out the distortions from leverage, cash, and tax structure.

An ABSOLUTE intrinsic-value signal, distinct from the relative multiples (PE, EV/EBITDA) which only compare a stock to its industry peers. Intrinsic value comes from the Residual Income Model: book value plus the present value of the residual income (earnings above a charge for the cost of equity) the firm is forecast to generate. This is the best-VALIDATED absolute value signal in the academic literature (Frankel & Lee 1998, replicated through 2026): the value-to-price ratio robustly predicts 1-3 year cross-sectional returns, survives every major factor model, and subsumes book-to-market. Because it is scored across the WHOLE universe (not within-industry), it complements the relative multiples rather than double-counting them. Pair it with a quality screen (Piotroski) to avoid value traps, and read the EPV decomposition to see whether a discount is unpriced earnings power or just speculative growth coming out of the price. One caveat: the model anchors on book equity, so for low-book, buyback-heavy, or asset-light firms (think Apple or Coca-Cola) book is a poor floor and the model can read durable franchises as wildly overvalued. Readings are clamped, and the metric is currently shadow-scored — shown for context, with zero weight in the fundamentals grade — pending validation.

Useful when earnings are negative, noisy, or one-time-distorted (early-stage growth, restructurings, cyclical troughs). Works best within an industry, not across — gross margin profiles vary so wildly that 1x P/S for a software company means something completely different from 1x P/S for a grocery chain.

Productivity of the asset base — how efficiently the firm converts assets into sales. Combined with net margin, this is the core of the DuPont decomposition: ROA = net margin × asset turnover. Two businesses can land at the same ROA via opposite paths: thin-margin / high-turnover (Costco, supermarkets) vs. fat-margin / low-turnover (luxury, software).

Lower is generally better for shareholder cash returns — less of every dollar of revenue gets reinvested in maintaining the asset base. But very low values can flag under-investment in a capital-intensive business, which catches up later via deteriorating capacity or competitiveness. Pairs with FCF margin to separate 'thin operating margin' from 'fat operating margin offset by heavy capex'.

Easier to compare than operating margin across firms with very different leverage and depreciation profiles, because it adds D&A back. Software platforms commonly run above 30%; capital-light service businesses cluster around 20%; capital-intensive industrials sit below 15%. The weakness: ignores the cash needed to maintain the asset base — pair with FCF margin for a complete profitability picture.

End-to-end conversion ratio: of every dollar of revenue, how much falls through to genuine free cash flow available to all capital providers? More honest than net margin because it accounts for the capex needed to maintain (and grow) the business. The single best indicator of whether the business is a quality compounder or a GAAP-earnings illusion.

Free cash flow the business throws off, divided by what the market currently charges for the equity. Treats the equity claim as a perpetual stream of free cash. More honest than earnings yield because it reflects the cash actually available to shareholders after all reinvestment. Cyclicals can swing below zero in a downturn — read with the trailing-cycle range.

Joel Greenblatt's reformulation of return-on-capital, designed to filter for businesses that earn high pre-tax returns on the tangible operating capital that actually generates EBIT. Excludes goodwill and acquired intangibles so that two firms with the same operating economics rank similarly regardless of acquisition history. Pairs with Greenblatt's Earnings Yield (EBIT/EV) to produce the famous 'Magic Formula' rank — quality stocks at value prices.

First-line profitability measure — how much revenue is left after the direct cost of producing it. Stable or rising gross margin signals pricing power and low input-cost exposure; falling gross margin is one of the earliest reliable signals of competitive pressure or commodity-input squeeze. Industry context is everything: 30% gross margin is excellent for a grocery chain and disastrous for a software company.

Operating margin minus interest, tax, and below-the-line items. Useful but noisier than operating margin: tax rate changes, debt-service shifts, and one-time items can move net margin year-over-year even when the operating business is unchanged. Always pair with operating margin and FCF margin — divergence between them is a tell about leverage, tax structure, or earnings quality.

Captures the leverage between revenue and operating profit — the core test of whether a business converts sales into income at the operating level. Independent of capital structure (excludes interest) and tax-jurisdiction noise. Trend matters as much as level: an improving operating margin indicates pricing power or operational efficiency gains; a falling margin signals input-cost pressure, wage inflation, or competitive erosion.

Capital-efficiency measure that ignores how the assets are financed. Useful for comparing within a sector but heavily biased by industry — banks and utilities run low ROA by design (huge balance sheets), software and franchise businesses run high ROA (asset-light). The DuPont decomposition links it to ROE: ROE = ROA × (assets / equity), so leverage inflates the gap between ROA and ROE.

Pre-tax cousin of ROIC using operating capital employed (long-term debt plus equity, approximately equal to total assets minus current liabilities). Damodaran publishes ROCE by industry annually, so it benchmarks cleanly against sector norms. Particularly useful for capital-intensive businesses where you want to see pre-tax returns on the long-term capital base.

The headline profitability metric. Net income divided by average book equity tells you how productive each dollar of shareholders' capital is. High sustained ROE compounds book value when the business can reinvest at a similar return. Two warnings: ROE rises mechanically with leverage (high D/E inflates ROE without making the business better), and aggressive buybacks can shrink the equity denominator faster than they shrink earnings, artificially boosting ROE even as fundamental returns are flat.

Top-line growth — the cleanest way to see whether the franchise is expanding. Best read alongside margin trend: revenue rising while margin compresses is often discount-driven volume rather than real growth, and can mask underlying weakness. Compare to industry peers — what looks weak in absolute terms can be best-in-sector if the industry is contracting.

How long the average sale sits as a receivable before becoming cash. Earnings-quality flag: receivables growing faster than revenue is one of the cleanest tells for revenue recognition stretching — Beneish flagged exactly this pattern as a primary fraud indicator. Industry context matters: B2B / project businesses run longer DSO than retail, but the trend is more important than the level.

DuPont productivity measure. Combined with margin, it tells the asset-light vs. asset-heavy story: low turnover with high margin is the luxury / branded model, high turnover with thin margin is the supermarket / discount model. Very high turnover in retail can also flag stockouts (lost sales) — the metric reads best industry-relative, not absolute.

The Coppock Curve is a weighted moving average of the sum of two rate-of-change measures, originally designed as a long-horizon, buy-only bottom indicator for equity indices. This screener applies it to daily bars and adds a bearish state for symmetry: a cross up through zero is the classic long-term buy tell, a cross down through zero flags a bearish momentum cycle.

+1 while the Coppock Curve is above zero; -1 while it is below zero; 0 only at exactly zero.

+1 = bullish zero-line cross (classic long-term buy), -1 = bearish zero-line cross.

Fires on the bar where the MACD line (EMA12 minus EMA26) crosses through the signal line (EMA9 of MACD). Bullish when MACD crosses up through signal, bearish when it crosses down. Far more commonly used as a trade trigger than divergence — see macd_divergence for the slower confirmatory tell. Whipsaws in chop; cleanest when combined with a trend-regime filter.

+1 on bullish cross (MACD crosses up through signal); -1 on bearish cross (MACD crosses down through signal); 0 otherwise.

+1 = bullish MACD-signal cross, -1 = bearish MACD-signal cross.

ROC is the simplest momentum oscillator: (close − close_N_ago) / close_N_ago × 100. It's unbounded, sign-bearing, and reads as 'how much price has moved in absolute % terms over the lookback'. A configurable threshold (default 5%) separates ordinary fluctuation from strong directional thrusts. Useful as a coarse momentum cross when you want a less smoothed signal than RSI or MACD.

+1 while ROC is above +threshold (strong bullish thrust); -1 while ROC is below −threshold (strong bearish thrust); 0 inside the ±threshold band.

+1 = ROC above +threshold (bullish thrust), -1 = ROC below −threshold (bearish thrust), 0 = ROC within ±threshold.