Kalman-Ichimoku Hybrid Statistical Arbitrage

Family: hybrid · Regime: mixed · Complexity: high · Asset classes: Crypto-Assets (ETH/BTC pairs), Equities (Sector ETFs) · Timeframes: 15m, 1h, 4h

Thesis

Mean reversion is more likely to succeed when the asset's internal momentum (CCI/Ichimoku) aligns with a statistical return-to-fair-value (Kalman Filter) relative to a benchmark pair. The edge comes from filtering out weak statistical signals that lack momentum backing.

Components

• AI Pair Trading System v1.0 (regime) — Establishes the mean-reversion regime by identifying when Asset A is statistically over/undervalued relative to Asset B using a Kalman Filter.
• Modern Ichimoku Cloud [GBB] (direction) — Ensures that momentum is trending in favor of the trade direction and that volatility (Cloud Grade) is sufficient to move price.
• CCI Arrows (entry) — Provides a precise momentum trigger for entry once the higher-timeframe regime and trend are aligned.
• Chandelier Exit (exit) — Dynamic trailing stop that accounts for volatility contraction and expansion to maximize run-up capture.
• Williams Fractals (risk) — Provides structural support/resistance levels for hard stop-loss placement, respecting a 2-bar confirmation lag.
• Spread Monitor (Tick-Level) (volatility_filter) — Filters out entries during periods of low liquidity or high volatility spikes to prevent slippage erosion.

Known failure conditions

• The spread between assets A and B enters a 'random walk' without mean reversion for >100 periods.
• ATR levels fall below transaction costs (spread + commissions), making the strategy unprofitable due to friction.
• Williams Fractal extremes are consistently broken within 3 bars of formation, indicating chaotic market structure.

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).