Machine Learning for Factor Investing: Python Version - Rilegato

Coqueret, Guillaume; Guida, Tony

 
9780367639747: Machine Learning for Factor Investing: Python Version
Rilegato
ISBN 10: 0367639742 ISBN 13: 9780367639747
Casa editrice: Chapman and Hall/CRC, 2023

Sinossi

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 investing: 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.

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Informazioni sull?autore

Guillaume Coqueret is associate professor of finance and data science at EMLYON Business School. His recent research revolves around applications of machine learning tools in financial economics.

Tony Guida is co-head of Systematic Macro at RAM Active Investments. He is the editor and co-author of Big Data and Machine Learning in Quantitative Investment.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Chapman and Hall/CRC
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
0367639742
ISBN 13 
9780367639747
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
340
Contatto del produttore
non disponibile
Persona responsabile
non disponibile

Altre edizioni note dello stesso titolo

9780367639723: Machine Learning for Factor Investing: Python Version

Edizione in evidenza

ISBN 10:  0367639726 ISBN 13:  9780367639723
Casa editrice: Chapman and Hall/CRC, 2023
Brossura