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Algorithmic Gold: Building ML-Powered Trading Systems with MQL5 and Python
Most trading bots fail. Not because the code is bad, but because the methodology is broken. Overfitting, look-ahead bias, and untested assumptions kill more systems than bad entries ever will.
Algorithmic Gold is a complete, code-first guide to building machine learning trading systems that survive contact with live markets. You'll go from raw OHLCV data to a walk-forward validated XGBoost model running as a production Expert Advisor on MetaTrader 5 — with no external DLLs, no black boxes, and no hand-waving about "edge."
Every line of code in this book has been tested. Every performance number is reproducible. The system's out-of-sample results on XAUUSD H1 across six walk-forward profit factor 1.94, AUC 0.6518, Monte Carlo p-value 0.003.
WHAT YOU'LL
A complete feature engineering pipeline (63 features including ICT/SMC order blocks, fair value gaps, liquidity sweeps, market structure)A properly validated XGBoost classifier with purged cross-validation and Optuna hyperparameter tuningA walk-forward testing framework that proves your edge is real — not curve-fittedA production MQL5 Expert Advisor with ONNX model integration, ATR-based risk management, and full broker compatibilityMonitoring, retraining, and multi-asset scaling infrastructureWHAT MAKES THIS BOOK Unlike academic quant books (López de Prado, Jansen), this book targets retail traders using MetaTrader 5 — not institutional desks with Bloomberg terminals. Unlike MQL5 tutorials, it goes far beyond indicators into proper ML validation methodology. Unlike trading course material, every claim is backed by reproducible, walk-forward tested results.
The code runs on a standard Windows PC with Anaconda Python and MT5. No institutional data feeds. No expensive subscriptions. No DLL imports.
WHO THIS BOOK IS
Traders who know ICT/SMC concepts and want to systematize and validate themDevelopers who can code but haven't built ML trading systems beforeAnyone who's tired of curve-fitted backtests that collapse in live tradingWHAT YOU
Intermediate Python (pandas, numpy) or willingness to learnMetaTrader 5 installed with a demo or live accountBasic understanding of forex/CFD trading mechanics20 chapters. 7 appendices. ~70,000 words. Complete source code included.
From data preprocessing to live deployment — no steps skipped, no results faked, no magic promised.
Algorithmic Gold is a complete, code-first guide to building machine learning trading systems that survive contact with live markets. You'll go from raw OHLCV data to a walk-forward validated XGBoost model running as a production Expert Advisor on MetaTrader 5 — with no external DLLs, no black boxes, and no hand-waving about "edge."
Every line of code in this book has been tested. Every performance number is reproducible. The system's out-of-sample results on XAUUSD H1 across six walk-forward profit factor 1.94, AUC 0.6518, Monte Carlo p-value 0.003.
WHAT YOU'LL
A complete feature engineering pipeline (63 features including ICT/SMC order blocks, fair value gaps, liquidity sweeps, market structure)A properly validated XGBoost classifier with purged cross-validation and Optuna hyperparameter tuningA walk-forward testing framework that proves your edge is real — not curve-fittedA production MQL5 Expert Advisor with ONNX model integration, ATR-based risk management, and full broker compatibilityMonitoring, retraining, and multi-asset scaling infrastructureWHAT MAKES THIS BOOK Unlike academic quant books (López de Prado, Jansen), this book targets retail traders using MetaTrader 5 — not institutional desks with Bloomberg terminals. Unlike MQL5 tutorials, it goes far beyond indicators into proper ML validation methodology. Unlike trading course material, every claim is backed by reproducible, walk-forward tested results.
The code runs on a standard Windows PC with Anaconda Python and MT5. No institutional data feeds. No expensive subscriptions. No DLL imports.
WHO THIS BOOK IS
Traders who know ICT/SMC concepts and want to systematize and validate themDevelopers who can code but haven't built ML trading systems beforeAnyone who's tired of curve-fitted backtests that collapse in live tradingWHAT YOU
Intermediate Python (pandas, numpy) or willingness to learnMetaTrader 5 installed with a demo or live accountBasic understanding of forex/CFD trading mechanics20 chapters. 7 appendices. ~70,000 words. Complete source code included.
From data preprocessing to live deployment — no steps skipped, no results faked, no magic promised.
241 pages, Kindle Edition
Published February 25, 2026
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