SML-KNN Entropy Sentinel

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Equities, Crypto, Forex · Timeframes: 1H, 4H

Thesis

Markets rotate between high-entropy noise and structural order. By using an S/R Matrix (SML) to identify structural order and a KNN-refined Volume SuperTrend to confirm momentum, we can capitalize on price bounces at liquidity clusters. The 'unsupported' diagnostic indicators act as a sentinel; when market structure becomes too complex for simple classification (high label count), the strategy assumes a breakdown in predictability and stands aside. Risk is uniquely mitigated by Alpha factors (238, 51, 262) which identify the 'real' volatility floor beneath the noise.

Components

Known failure conditions

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