KNN-Kalman Volatility Arbitrage

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Forex, Crypto · Timeframes: H1, H4

Thesis

The hypothesis is that an asset's price is driven by its relative value to a correlated benchmark, but this statistical edge is only tradable when confirmed by a volume-weighted trend and a volatility breakout. By using a Kalman Filter for spread detection and KNN for historical trend classification, we can identify high-probability entries that coincide with institutional liquidity zones (Round Levels) while avoiding the noise of economic news.

Components

• Volume SuperTrend AI (Expo) (regime) — Acts as the primary regime filter, ensuring entries only occur when the volume-weighted trend and KNN historical classification align.
• Arnaud Legoux Moving Average (ALMA) (direction) — Provides a smoothed directional bias with minimal lag compared to traditional MAs, filtering out noise within the regime.
• AI Pair Trading System v1.0 (entry) — Generates mean-reversion signals based on the statistical spread between the traded asset and a benchmark (e.g., ETH relative to BTC).
• Round Levels Zone Shading (exit) — Provides objective take-profit targets based on psychological institutional levels where order flow typically clusters.
• Auto Fibonacci (risk) — Automatically identifies recent structural swing points to define the invalidation level (Stop Loss).
• NNFX Squeeze (Volatility Breakout) (confirmation) — Confirms the trade by ensuring the entry occurs during a volatility expansion (squeeze release), preventing entries in low-liquidity ranges.
• News Indicator NMNNFX (volatility_filter) — Filters out high-volatility events that invalidate statistical mean-reversion models.

Known failure conditions

• The correlation between the base asset and the pairSymbol breaks down permanently (cointegration failure).
• Market enters a 'low-volatility grind' where the NNFX Squeeze never triggers despite price movement.
• KNN historical labels become stuck in a feedback loop due to high 'n' and 'k' settings in a trending market.

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.