LVN-Fractal Darvas Reversal Strategy

Family: hybrid · Regime: mixed · Complexity: high · Asset classes: Forex Majors, US Equities (Indices), Gold · Timeframes: H1, H4

Thesis

The hypothesis is that price exhibits structural 'memory' at Low Volume Nodes (LVNs) within supply and demand zones. By waiting for a momentum shift (Williams %R) and structural confirmation (Fractals) at these points, we capture the high-velocity rejection from 'value' areas. Darvas Boxes provide the volatility-adjusted risk floor to protect against failed rejections.

Components

• Dynamic Supply and Demand Zones [AlgoAlpha] (regime) — Provides the high-level regime context; identifies Low Volume Nodes (LVNs) as price magnets or rejection points where price is likely to pivot.
• CCI / Connectable [Azullian] (direction) — Filters for momentum direction, ensuring the entry is not fighting a strong counter-trend move.
• Williams %R (entry) — Provides the specific timing trigger for entries when price recovers from local overextended conditions within a zone.
• Pivot Point S&R with GMT Correction (exit) — Sets objective price targets based on standard floor pivots, adjusted for global session starts.
• Darvas Boxes (Multi-Mode) (risk) — Calculates the risk boundary based on local price consolidation; provides a structural stop-loss level.
• FractalScanner (confirmation) — Confirms that a local swing high or low has formed, adding structural validation to the volume-based regime.

Known failure conditions

• Price oscillates indefinitely within the supply/demand zone, leading to multiple Darvas box breaks and W%R triggers.
• Darvas Box boundaries are too wide (high volatility), resulting in an R:R ratio below 1:1 against the nearest Pivot level.

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).