KNN-HA Structural Momentum Navigator

Family: hybrid · Regime: trending · Complexity: high · Asset classes: FX, Indices, Equities · Timeframes: H1, H4

Thesis

This strategy hypothesizes that market trends are best captured by identifying 'local memory' patterns via KNN, then validating the strength of that pattern using Heikin-Ashi momentum and institutional price levels. By only entering when volatility is expanding (ATM logic) near documented support/resistance (Q-Levels), we filter out noise and capture the meat of the move.

Components

Known failure conditions

Explore the full interactive blueprint with parameter ranges and evidence on WOBR StrategyVerse, or generate this strategy as an MT4/MT5 Expert Advisor with QuantMogul AI Engine (free download).


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