High-performance Algorithmic Trading using Machine Learning: Building automated trading strategies with AutoML and feature engineering (English Edition) by Franck Bardol ISBN 9789365892949, 9365892945 instant download

High-performance Algorithmic Trading using Machine Learning: Building automated trading strategies with AutoML and feature engineering (English Edition) by Franck Bardol ISBN 9789365892949, 9365892945 instant download

This book is a practitioner’s blueprint for building production-grade ML trading systems from scratch. It goes far beyond basic return-sign classification tasks, which often fail in live markets, and delivers field-tested techniques used inside elite quant desks. It covers everything from the fundamentals of systematic trading and ML’s role in detecting patterns to data preparation, backtesting, and model lifecycle management using Python libraries. You will learn to implement supervised learning for advanced feature engineering and sophisticated ML models. You will also learn to use unsupervised learning for pattern detection, apply ultra-fast pattern matching to chartist strategies, and extract crucial trading signals from unstructured news and financial reports. Finally, you will be able to implement anomaly detection and association rules for comprehensive insights.

By the end of this book, you will be ready to design, test, and deploy intelligent trading strategies to institutional standards.

What you will learn

Build end-to-end machine learning pipelines for trading systems.

Apply unsupervised learning to detect anomalies and regime shifts.

Extract alpha signals from financial text using modern NLP.

Use AutoML to optimize features, models, and parameters.

Design fast pattern detectors from signal processing techniques.

Backtest event-driven strategies using professional-grade tools.

Interpret ML results with clear visualizations and plots.