KNN-Liquidity Gap Regime Strategy

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Equities, Forex, Crypto · Timeframes: H1, H4, D1

Thesis

Price breakouts are most likely to sustain when they occur after a volatility expansion (Boxline) and are subsequently supported by historical price-action patterns (KNN). By entering only when price retraces to 'liquidity gaps' (low-volume Supply/Demand zones), the strategy enters at points where price discovery is most efficient, using Darvas Boxes to define structural invalidation points.

Components

• Boxline (Dynamic Range Breakout) (regime) — Defines the current volatility regime; a trade is only valid in the direction of the most recent 'Box' breakout close.
• AI Trend Navigator [K-Neighbor] (direction) — Filters the regime by ensuring the local price 'neighborhood' is statistically aligned with the breakout direction.
• Dynamic Supply and Demand Zones [AlgoAlpha] (entry) — Used to identify 'liquidity gaps' (low volume bins) within the new range for high-probability entry on retracements.
• HiLo Activator 02 (exit) — Provides a trailing stop-loss and final exit signal when price crosses the staircase MA of highs/lows.
• Darvas Boxes (Multi-Mode) (risk) — Determines the structural floor/ceiling for stop-loss placement and position sizing.

Known failure conditions

• The AI Trend Navigator shows a 'flat' prediction while Boxline is shifting rapidly, indicating a lack of local pattern consistency.
• Price trades through a Demand zone with high volume (invalidating the 'liquidity gap' hypothesis).
• The Darvas Box range is wider than the Boxline range, creating a negative reward-to-risk ratio.

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.