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Machine Learning for Factor Investing: R Version: R Version (Chapman and Hall/CRC Financial Mathematics Series) - Softcover
Synopsis
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: R 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 R code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material, along with the content of the book, 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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About the Author
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 executive director at RAM Active Investments. He serves as chair of the machineByte think tank and is the author of Big Data and Machine Learning in Quantitative Investment.
"About this title" may belong to another edition of this title.
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Machine Learning for Factor Investing: R Version: R Version (Chapman and Hall/CRC Financial Mathematics Series)
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Machine Learning for Factor Investing: R Version: R Version (Chapman and Hall/CRC Financial Mathematics Series)
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Chapman and Hall/CRC; 1st edition, 2020
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Machine Learning for Factor Investing: R Version: R Version
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 executive dir. Seller Inventory # 395500148
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Machine Learning for Factor Investing: R Version
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Taschenbuch. Condition: Neu. Neuware - The aim of the book is to give an interpretation of ML tools through the lens of factor investing. Concepts illustrated with examples on the same (public) dataset throughout the book. Provides code samples and the corresponding results so that anybody can reproduce the steps. Seller Inventory # 9780367545864
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