McNicholl KNN-Volume Darvas Hybrid
Family: trend_following · Regime: trending · Complexity: high · Asset classes: Equities, FX Major Pairs, Crypto (High Liquidity) · Timeframes: H1, H4
Thesis
The hypothesis is that low-lag trend indicators (McNicholl EMA) combined with historical volume-price classification (KNN) can identify higher-probability breakouts than standard indicators. By using Darvas Boxes for risk, we align entry with structural market phases (consolidation to expansion), and the Heiken Ashi ATR smoothing provides an exit that is less reactive to minor noise while remaining disciplined to volatility shifts.
Components
- Indicator Sample (Bar Count Logger) (regime) — Acts as a data-sufficiency filter, ensuring the platform has loaded enough historical bars for the KNN algorithm and the 6-stage EMA to stabilize before signals are valid.
- McNicholl EMA (MCNMA) (direction) — The primary trend filter. Its 6-stage cascaded TEMA structure provides a low-lag directional bias, ensuring we only trade in the direction of high-order momentum.
- Volume SuperTrend AI (Expo) (entry) — The entry trigger. It merges volume-weighted trends with K-Nearest Neighbors pattern classification, filtering out trend signals that do not align with historical volume/price clusters.
- ATR Heiken Ashi (exit) — Uses smoothed Heiken Ashi TR to define trailing exits, reducing noise-induced premature stops compared to standard ATR-based trailing.
- Darvas Boxes MetaTrader 5 (risk) — Provides structural support/resistance levels for stop-loss placement and position sizing. Uses Darvas's non-penetration logic to define risk zones.
- Relative Strength Index (Standard) (confirmation) — Confirming momentum. Ensures the trade is entered as velocity increases but before the trend reaches statistical exhaustion.
Known failure conditions
- Successive Darvas Box violations without Volume SuperTrend signals (indicating a range regime).
- MCNMA frequently crossing price in a sawtooth pattern (low-volatility chop).
- KNN signals flipping every 5 bars, indicating a lack of historical pattern persistence.
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