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Machine Learning for Factor Investing: R Version - R Version (Hardcover) Loot Price: R5,546
Discovery Miles 55 460
Machine Learning for Factor Investing: R Version - R Version (Hardcover): Guillaume Coqueret, Tony Guida

Machine Learning for Factor Investing: R Version - R Version (Hardcover)

Guillaume Coqueret, Tony Guida

Series: Chapman and Hall/CRC Financial Mathematics Series

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Loot Price R5,546 Discovery Miles 55 460 | Repayment Terms: R520 pm x 12*

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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.

General

Imprint: Crc Press
Country of origin: United Kingdom
Series: Chapman and Hall/CRC Financial Mathematics Series
Release date: September 2020
First published: 2021
Authors: Guillaume Coqueret • Tony Guida
Dimensions: 254 x 178mm (L x W)
Format: Hardcover
Pages: 321
ISBN-13: 978-0-367-47322-8
Categories: Books > Business & Economics > Economics > Econometrics > Economic statistics
Books > Science & Mathematics > Mathematics > Applied mathematics > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Business & Economics > Finance & accounting > Finance > Investment & securities > General
Books > Money & Finance > Investment & securities > General
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LSN: 0-367-47322-4
Barcode: 9780367473228

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