Autocorrelated Fractal Liquidity Engine

Family: hybrid · Regime: trending · Complexity: high · Asset classes: FX, Equities, Indices · Timeframes: H4, D1

Thesis

Market trends are driven by institutional liquidity cycles that exhibit self-similarity (autocorrelation). By identifying periods of high autocorrelation and waiting for liquidity sweeps at DRT levels, we can enter via Order Blocks. The Bandpass Filter provides a timing edge by ensuring entry occurs during the expansive phase of a price cycle, while Fractal S/R provides structural 'safe havens' for risk placement.

Components

• Autocorrelation Function (ACF) (regime) — Used as a regime filter to ensure the market is in a trend-persistent state (positive autocorrelation) rather than a mean-reverting or noisy state.
• SNAP HTF_LTF Indicator (direction) — Establishes the directional bias by identifying institutional liquidity pools and Daily Range Transfer (DRT) levels.
• Order Block & FVG Detector (entry) — Provides the high-probability entry trigger when price reacts to institutional supply/demand zones.
• SuperTrend (exit) — Acts as the dynamic trailing exit and trend-invalidation signal.
• Support and Resistance (Fractal-based) (risk) — Defines the hard stop-loss placement and calculates position sizing based on established structural pivots.
• Bandpass Filter (BPF) (confirmation) — Confirms the entry by ensuring the price cycle momentum is aligned with the trade direction, filtering out high-frequency noise.

Known failure conditions

• ACF remains consistently negative or near zero for >10 bars, indicating a breakdown in trend persistence.
• Average trade duration falls below the BPF cycle period, suggesting the strategy is chasing noise.
• The distance to the Fractal Stop Loss exceeds 3x the ATR, making the Reward-to-Risk ratio mathematically unviable.

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.