Fractal RMSE Cyclical Pivot Long Strategy
Family: hybrid · Regime: trending · Complexity: medium · Asset classes: Equities, Forex, Crypto · Timeframes: H1, H4, D1
Thesis
Market cycles often bottom with a 'chaos' phase that transitions into a structural breakout. By combining a detrended oscillator to find the cycle bottom with a fractal filter to ensure noise reduction, we can isolate the Bullish Pivot signals that represent high-probability trend reversals. The use of RMSE for risk ensures the strategy adapts its stop-loss to the current prediction error of the market mean.
Components
- MQL4 Indicator Skeleton Sample (regime) — Acts as a data-integrity filter, ensuring the strategy only operates once sufficient historical bars (iBars) exist for statistical significance of the RMSE and FCB components.
- Detrended Price Oscillator (DPO) (direction) — Used to identify the cyclical state; entries are prioritized when the short-term cycle is potentially bottoming (DPO < 0).
- Bullish Pivot Detector (entry) — Provides the specific execution trigger by identifying a 'Red Sequence' followed by a 'Green' candle and a subsequent breach of local resistance.
- Sherif Hilo (exit) — Acts as a trailing stop-loss mechanism by defining a trend-following floor (LineUp) based on the lowest low of the lookback period.
- Root Mean Squared Error (RMSE) (risk) — Quantifies current market 'uncertainty' or volatility around the mean; used to scale the Stop-Loss distance and position size.
- Fractal Chaos Bands (FCB) (volatility_filter) — Filters out 'chaotic' noise; entry is only permitted if price is breaking out of the upper band, suggesting a non-random directional move.
Known failure conditions
- If the Bullish Pivot Detector produces no signals during a 20% drawdown, the sequence logic is too restrictive.
- If RMSE stays below 0.0001 for extended periods (flat market), the stop-loss logic collapses.
- Persistent cycle inversion where DPO < 0 consistently leads to further price drops rather than mean-reversion.
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