Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789346411
Length 684 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Authors (2):
Arrow left icon
Jeffrey Yau Jeffrey Yau
Author Profile Icon Jeffrey Yau
Jeffrey Yau
Stefan Jansen Stefan Jansen
Author Profile Icon Stefan Jansen
Stefan Jansen
Arrow right icon
View More author details
Toc

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

Separating signal and noise – how to use alphalens

Quantopian has open sourced the Python library, alphalens, for the performance analysis of predictive stock factors that integrates well with the backtesting library zipline and the portfolio performance and risk analysis library pyfolio that we will explore in the next chapter.

alphalens facilitates the analysis of the predictive power of alpha factors concerning the:

  • Correlation of the signals with subsequent returns
  • Profitability of an equal or factor-weighted portfolio based on a (subset of) the signals
  • Turnover of factors to indicate the potential trading costs
  • Factor-performance during specific events
  • Breakdowns of the preceding by sector

The analysis can be conducted using tearsheets or individual computations and plots. The tearsheets are illustrated in the online repo to save some space.

...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime