Quality#16tier 1live in production

`bab`

cadence: Dailydata: medium

Mechanism

For a single stock, "BAB strategy" can be expressed as: scale exposure inversely to rolling beta vs SPY. Lower-beta moments → bigger position; high-beta moments → reduced. The stock-level analog of the BAB

Signal rule

long low-β stocks levered to β=1; short high-β stocks deleveraged

Data dependencies

daily_bars
Daily OHLCV bars used by all price-based generators.
factor_returns
Worker data table — see services/worker schema.

Expected edge

~0.7 Sharpe in Frazzini-Pedersen 2014; ~0.4 in recent OOS

Illustrative pattern only

NOT a backtest

Illustrative pattern only — see /app for live backtests and the actual current equity curve.

Example tickers where this is likely to fire

JNJ PG KO

Illustrative only — the signal fires based on the live data, not a fixed list.

Related families

qmjQuality

Combine quality (gross profit / assets, ROE) with momentum: long when both are in their respective top buckets relative to their own history. Stock-level adaptation; the cross-sectional implementation would rank across the universe but we approximate with self-relative

speculative betaRisk-Premium

Distinct from BAB (#16): Hong-Sraer 2016 (JF) show that the underperformance of high-beta stocks is concentrated in periods of high disagreement (proxied by analyst forecast dispersion OR by realized vol dispersion across estimation windows). Low-disagreement high-beta is fine; high-disagreement high-beta

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bab