Деталі електронної книги

Machine Learning for Trading. Integrate GenAI, Causal Inference, and Reinforcement Learning into Real World Trading Systems - Third Edition

Machine Learning for Trading. Integrate GenAI, Causal Inference, and Reinforcement Learning into Real World Trading Systems - Third Edition

Stefan Jansen

EЛЕКТРОННА КНИГА
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The rapid rise of AI and the growing complexity of financial markets have transformed quantitative trading into a data-driven, process-oriented discipline. This third edition provides a comprehensive blueprint for designing, validating, and deploying systematic trading strategies powered by modern machine learning.

It introduces the 7 stage ML4T Workflow, a professional framework that unites data engineering, model development, validation, and live deployment into one cohesive process. It demonstrates how to turn raw market, fundamental, and alternative data into predictive signals and robust, production-ready trading systems.

You’ll learn to build advanced pipelines for feature engineering, model evaluation, and portfolio optimization using libraries such as Polars, LightGBM, PyTorch, and Optuna.

Practical notebooks illustrate every stage of the workflow, from factor testing and backtesting with zipline reloaded to live deployment with MLOps tools such as MLflow, Feast, and Prometheus. Additional coverage of synthetic data generation, Graph Neural Networks, and Reinforcement Learning extends the toolkit for building resilient, adaptive strategies that thrive in dynamic markets.

By the end of this book, you’ll be proficient to build your own industrial-grade “alpha factory.
  • 1. Machine Learning for Trading – From Idea to Execution
  • 2. ML4T Workflow: End-to-end strategy development and evaluation
  • 3. Market and Fundamental Data
  • 4. Alternative Data for Finance
  • 5. Alpha Factor Research
  • 6. Portfolio Management & Strategy Evaluation
  • 7. Linear Models
  • 8. Linear Time Series Models
  • 9. Bayesian Machine Learning
  • 10. Tree-Based Ensembles
  • 11. Intro to Deep Learning & Feedforward NN
  • 12. Linear & Non-linear Time Series Models
  • 13. Text Data: Sentiment Analysis & Topic Models
  • 14. Text Data: Word2Ved & Transformers
  • 15. Convolutional Neural Networks
  • 16. Autoencoders
  • 17. Generative Adversarial Nets
  • 18. Reinforcement Learning
  • 19. Live Trading
  • 20. Next Steps
  • 21. Appendix
  • Назва:Machine Learning for Trading. Integrate GenAI, Causal Inference, and Reinforcement Learning into Real World Trading Systems - Third Edition
  • Автор:Stefan Jansen
  • Оригінальна назва:Machine Learning for Trading. Integrate GenAI, Causal Inference, and Reinforcement Learning into Real World Trading Systems - Third Edition
  • ISBN:9781803231686, 9781803231686
  • Дата видання:2026-09-04
  • Формат:Eлектронна книга - EPUB
  • Ідентифікатор видання: e_4q6h
  • Видавець: Packt Publishing