Non-Normal Lorentzian Structure Trader

Family: hybrid · Regime: high_vol · Complexity: high · Asset classes: Forex, Crypto, Indices · Timeframes: 15m, 1h, 4h

Thesis

This strategy hypothesizes that significant market moves are preceded by a shift from Gaussian to non-normal price return distributions (identified by Jarque-Bera). In these high-conviction regimes, historical similarities (Lorentzian Classification) and institutional structural breaks (TradeEase) converge to provide high-probability entry points, while smoothed ATR-HA volatility accounts for the noise inherent in such volatile states.

Components

Jarque-Bera Test (JB) (regime) — Acts as a volatility regime filter; entry is only permitted when returns deviate from a normal distribution (JB > 5.991), identifying periods of institutional momentum or panic.
Lorentzian Classification (direction) — Uses non-Euclidean distance to classify current price action against historical analogs to determine the probability of a bullish or bearish continuation.
TradeEase (entry) — Provides the structural trigger via Market Structure Breaks (BOS) or Change of Character (CHoCH) to ensure entries align with institutional order flow.
Bollinger Bands (Standard) (exit) — Used as a mean-reversion target; exiting when price reaches the outer bands ensures profit-taking during volatility expansion.
ATR Heiken Ashi (risk) — Calculates volatility using smoothed Heiken Ashi candles to provide a noise-filtered stop-loss distance.

Known failure conditions

The Jarque-Bera value remains consistently below 5.99 for extended periods, indicating a Gaussian 'noise' regime.
High correlation between TradeEase pivot points and Lorentzian feature sets leading to redundant signals.
Price repeatedly hits ATR-HA stops due to the inherent lag in Heiken Ashi smoothing during high-velocity reversals.

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).