The Book:
Theory That Becomes Working Code
7 Chapters — What you'll learn
Each chapter maps directly to a working notebook in the code pack.
The Code Pack:
88 Strategies. Zero Filler.
Every file is a complete, runnable Python script. Load your data, set your parameters, run. No babysitting required.
Hurst Exponent EMA Cross
Filters trending vs mean-reverting regimes via Hurst exponent; activates EMA crossover signals only in trending conditions.
HMM Regime SL/TP
Hidden Markov Model classifies market state and dynamically adjusts stop-loss and take-profit targets per regime.
GMM Regime Adaptive
Gaussian Mixture Model identifies volatility regimes and adapts position sizing and signal thresholds to each state.
Decision Tree EMA
Scikit-learn decision tree classifies market conditions and gates EMA trend signals with trained predictions.
Isolation Forest Anomaly
Detects unusual price action and market anomalies using unsupervised isolation forest — avoids noise spike entries.
Guppy MMA + Pullback
Full Guppy Multiple Moving Average system with pullback entry timing and structured exit logic.
Triple EMA Crossover
Three-MA system using fast/medium/slow crossover confirmation to filter false breakouts in trending markets.
ADX Trend Filter
ADX gates EMA crossover signals — only enters when trend strength exceeds threshold, reducing whipsaw losses.
Bollinger RSI Filter
Bollinger Band mean-reversion gated by RSI extremes — long on lower band oversold, short on upper band overbought.
Quantile Regression SL/TP
Quantile regression channels define dynamic mean-reversion zones with adaptive stop-loss and take-profit levels.
Adaptive Fourier Cycle
Fourier transform identifies dominant market cycles and adapts signal periods dynamically to the current frequency regime.
Hilbert RSI
Hilbert Transform extracts instantaneous phase of the market cycle; RSI entries are synchronized to the dominant cycle.
6 Categories:
Every Edge Covered
Regime Detection
HMM, GMM, Hurst exponent, dual-regime, and BBands regime-adaptive strategies.
Machine Learning
Decision tree EMA, isolation forest, and IVM BTC regime classification systems.
Trend Following
EMA crosses, ADX filters, Guppy MMA pullback, DEMA, TRIX, triple EMA, MA ribbon.
Mean Reversion
Bollinger RSI, quantile regression channels, enhanced BB, RSI MR with ADX filters.
Volatility & Cycles
Adaptive Fourier, Hilbert RSI, ATR breakouts, vol clustering, vol cooling gridsearch.
Optimization & Portfolio
Walk-forward notebooks, grid search, equal/dynamic allocation, ensemble weights.
What Traders Say
"The regime detection strategies alone are worth 10x the price. The HMM + GMM implementations saved me weeks of research. Immediately plugged into my live bot."
"The book explains the 'why' and the code pack gives you the 'how'. I got more from this in a weekend than 6 months building my own VBT strategies from scratch."
"Clean, well-structured code that actually runs. The walk-forward optimization notebook alone justified the purchase. Already running 8 of these in my portfolio framework."
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