Categorical Regime Volume Gap Hybrid

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

Thesis

Price movement is most efficient through areas of low historical volume (liquidity gaps). By identifying these zones through dynamic volume profiling and entering only when momentum (QQE) and trend consensus (String Mode Regime) are aligned, the strategy exploits the tendency for price to 'fill' or 'reject' these zones rapidly, providing high R:R opportunities.

Components

• Mode of String Array (Compatibility Test) (regime) — Aggregates categorical market states (e.g., 'BULL', 'BEAR', 'FLAT') over a window to determine the most stable current regime, filtering out transient noise.
• QQE (Qualitative Quantitative Estimation) (direction) — Provides a filtered momentum bias by comparing smoothed RSI to a volatility-adjusted trailing band.
• Dynamic Supply and Demand Zones [AlgoAlpha] (entry) — Identifies 'liquidity gaps' via volume profile; entries are triggered when price enters these zones of low volume intensity.
• Ichimoku Kinko Hyo (exit) — The Kijun-sen (base line) serves as a dynamic trailing stop and trend exhaustion exit.
• Average True Range (ATR) (risk) — Calculates volatility-adjusted stop-loss distances and position sizing.
• MACD (confirmation) — Confirms that momentum is actively accelerating in the direction of the trade during the demand/supply zone touch.

Known failure conditions

• Market enters a 'churn' phase where Supply and Demand zones are frequently created and immediately invalidated.
• Extreme low volume periods where the Volume Profile bins become indistinguishable.
• String conversion failures or NaN returns from the compatibility-test regime indicator.

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.