Neural-Darvas Force Breakout Strategy
Family: hybrid · Regime: trending · Complexity: high · Asset classes: FX Major Pairs, Equity Indices (DAX, S&P 500) · Timeframes: H1, H4
Thesis
This strategy operates on the hypothesis that non-linear momentum signals (Neural Network) are more reliable when confirmed by traditional smoothed force calculations (Average Force) within a macro-momentum regime (GFRMa). By filtering for expanding volatility (GOM BB) and using structural price floors/ceilings (Darvas Boxes) for risk, the strategy aims to capture the 'meat' of a breakout while filtering for the naive linear failures often seen in momentum-only systems. The edge exists in the synergy between machine-learning price-action classification and structural consolidation breakouts.
Components
- GFRMa Pivot HTF3 Dashboard (regime) — Defines the macro environment (Bullish/Bearish) by aggregating RSI and CCI thresholds to ensure trades align with higher-order momentum.
- Neural Network Indicator (NNind) (direction) — Provides a non-linear momentum score (0-100) to identify high-probability directionality that standard oscillators might miss.
- Average Force (entry) — Acts as the precision trigger; ensures that momentum is actually shifting across the zero-line before entry, reducing the impact of NNind noise.
- ATR SL Finder (exit) — Provides dynamic, volatility-adjusted exit levels to capture trend extensions while protecting against spikes.
- Darvas Boxes Modern/Classic (risk) — Provides structural support/resistance levels for hard stop-loss placement and risk-to-reward position sizing.
- GOM BB Prediction (300 bars) (volatility_filter) — Filters out entries when the volatility slope is contracting or predicted to flatten, avoiding 'trap' breakouts.
Known failure conditions
- Failure of the Neural Network to maintain signal efficacy across different market cycles due to hardcoded weights.
- Consistently hitting Darvas Box boundaries in range-bound markets where the GOM BB Prediction fails to identify the contraction.
- Graphical object errors in GFRMa Dashboard preventing data extraction for automated execution.
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