Machine Learning for Factor Investing: Python Version

by Guillaume Coqueret, Tony Guida

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon, as the jargon and coding requirements may seem out-of-reach. Machine learning for factor Python version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that rely on firm characteristics.



The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Common supervised learning algorithms such as tree models and neural networks are explained in the context of style investing and the reader can also dig into more complex techniques like autoencoder asset returns, Bayesian additive trees and causal models.



All topics are illustrated with self-contained Python code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material is available online so that readers can reproduce and enhance the examples at their convenience. If you have even a basic knowledge of quantitative finance, this combination of theoretical concepts and practical illustrations will help you learn quickly and deepen your financial and technical expertise.

Kindle Edition

Published August 8, 2023

Reviews

[Kem Bong · Rating 5 out of 5]

my god, this book is good!!! it is so good that i use it as the backbone for my teaching (dont worry, i dont use any code or example in the book, so no copyright issue here :D), my students dont love it though :)) it is heavy on math, you will have to be pretty comfortable with all the greek letters to read through this ;) this is not a cookbook, you cant copy the code and make money with it, you will learn about the thoery/math behind each model, from Linear regression, Random forests... to SVM, Neural network... the codes and exercises are very helpful, it is not always correct but easy enough to fix. Highly recommend this book to anyone serious about machine learning and stock market analysis. Factor investing is a great way to begin your trading career ;)

[Firefox · Rating 4 out of 5]

Good for referencing, you'll have to develop your own code tho.