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Hands-On Machine Learning for Algorithmic Trading

You're reading from   Hands-On Machine Learning for Algorithmic Trading Design and implement investment strategies based on smart algorithms that learn from data using Python

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789346411
Length 684 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Jeffrey Yau Jeffrey Yau
Author Profile Icon Jeffrey Yau
Jeffrey Yau
Stefan Jansen Stefan Jansen
Author Profile Icon Stefan Jansen
Stefan Jansen
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Table of Contents (23) Chapters Close

Preface 1. Machine Learning for Trading 2. Market and Fundamental Data FREE CHAPTER 3. Alternative Data for Finance 4. Alpha Factor Research 5. Strategy Evaluation 6. The Machine Learning Process 7. Linear Models 8. Time Series Models 9. Bayesian Machine Learning 10. Decision Trees and Random Forests 11. Gradient Boosting Machines 12. Unsupervised Learning 13. Working with Text Data 14. Topic Modeling 15. Word Embeddings 16. Deep Learning 17. Convolutional Neural Networks 18. Recurrent Neural Networks 19. Autoencoders and Generative Adversarial Nets 20. Reinforcement Learning 21. Next Steps 22. Other Books You May Enjoy

ML for trading in practice

As you proceed to integrate the numerous tools and techniques into your investment and trading process, there are numerous things you could focus your efforts on. If your goal is to make better decisions, you should select projects that are realistic yet ambitious given your current skill set. This will help you to develop an efficient workflow underpinned by productive tools and gain practical experience.

We will briefly list some of the tools that are useful to expand on the Python ecosystem covered in this book and refer to the links listed on GitHub to dive deeper. These include big data technologies that will eventually be necessary to implement ML for trading strategies at scale. We will also list some of the platforms that allow you to implement trading strategies using Python, often with access to data sources and ML algorithms and libraries...

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