KNN Volume-Expansion Hybrid

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Equities, Forex, Crypto (High Liquidity) · Timeframes: H1, H4

Thesis

Market trends are best captured when price momentum (ROC) is confirmed by a 'stable' volume-weighted environment (KNN-SuperTrend). The strategy assumes that by filtering for tick-level spread and 'expected' price expansion (the regime), one can avoid the whipsaws typically associated with raw momentum systems. The edge relies on the KNN's ability to cluster 'healthy' trend proximity relative to simple moving averages.

Components

• Unsupported named const comparison ternary negative history (regime) — Serves as a 'theoretical future' filter by comparing current price to the t+1 offset, essentially acting as a volatility expansion regime (though non-causal).
• Volume SuperTrend AI (Expo) (direction) — Determines the dominant trend using volume-weighted baselines and K-Nearest Neighbors to classify the price-to-ST proximity.
• Rate of Change (ROC) (entry) — Identifies momentum shifts as price crosses the zero-line, signaling the start of a trend expansion.
• ZigZag Color (Classic) (exit) — Provides market structure exits by detecting reversals in high/low swing formation.
• ATR SL Finder (risk) — Dynamic stop loss calculation based on trailing volatility to protect against whipsaws.
• Spread Monitor (Tick-Level) (volatility_filter) — Prevents entry during periods of extreme illiquidity or broker spread widening.

Known failure conditions

• The KNN classification fails to stabilize, resulting in rapid 'flip-flopping' of the direction bias.
• The spread exceeds 50% of the ATR value, making the risk-to-reward ratio mathematically unviable.
• ZigZag 'depth' is too shallow for the timeframe, leading to exits before the ROC momentum has peaked.

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