SCL

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.

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.

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.

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.

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.

MFI is essentially RSI computed on (typical price × volume) instead of close alone, so high-volume bars push the oscillator harder than low-volume bars. It's 0-100 bounded and uses the same 20/80 OB-OS convention as a slower RSI. Because it folds in volume, MFI can flag distribution / accumulation underneath a flat price tape that RSI would miss.

+1 while MFI is below 20 (oversold); -1 while MFI is above 80 (overbought); 0 in between.

+1 = oversold (bullish, volume-weighted), -1 = overbought (bearish), 0 = mid-range.

The 14-period Relative Strength Index is the canonical Wilder momentum oscillator, bounded 0-100. Readings below 30 mark oversold conditions and above 70 mark overbought. This signal flags time spent at those extremes: bullish while RSI is at or below 30 (a mean-reversion bounce bias), bearish while it is at or above 70. The 30/70 thresholds are standard practice layered on top of the TA-Lib primitive.

+1 while RSI(14) is at or below the oversold threshold (default 30); -1 while it is at or above the overbought threshold (default 70); 0 in between.

+1 = oversold (bullish mean-reversion bias), -1 = overbought (bearish), 0 = RSI in its mid-range.

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.