The Fallacy of Additive Condition Logic
Analysts frequently build screener scripts under an intuitive assumption of linear independence. They presume that if Rule A weeds out 20% of symbols and Rule B weeds out another 15%, the joint filter retains roughly two-thirds of the starting database. In practice, market structures carry tight statistical collinearity. Price levels correlate with daily trading volumes, momentum metrics link directly to volatility expansions, and moving average tests echo one another across consecutive horizons.
When multiple rules tap into shared underlying mechanics, the resulting intersection removes candidates irregularly. Instead of a refined sub-segment, the screener yields either severe over-pruning or an unintended concentration in a single asset profile. The outcome mimics high selectivity while merely exposing an uncontrolled interaction effect.
Coupling two moderate conditions does not simply double the precision of a research pass; it introduces an entirely new topological boundary across the data set.
Primary Vectors of Cross-Condition Friction
Isolating why a multi-parameter screen suddenly contracts begins with classifying how parameters cross-fire. Empirical screening records reveal three recurrent interaction profiles:
- Turnover and Volatility Binding: Imposing a strict minimum dollar volume alongside a narrow daily range floor routinely strips away emerging mid-capitalization leaders, favoring slow institutional instruments without signaling higher quality.
- Multi-Period Indicator Clashing: Pairing a daily oscillator oversold requirement with a weekly moving-average trend test often yields zero matches during broad market rotations, freezing output precisely when comparative study is most needed.
- Threshold Cannibalization: When one criterion demands a breakout above the prior high and another requires a pullback below a short-term benchmark, the logical conjunction excludes everything except rare contradictory price bars.
Stepwise testing provides the sole reliable remedy. By running each rule against the raw baseline universe and noting the solitary survivor count, researchers can measure mutual overlap and pinpoint which interaction triggers unexpected universe contraction.