Guillaume Coqueret's Books

Machine Learning for Factor Investing

Python Version

By: Guillaume Coqueret,Tony Guida

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Machine Learning for Factor Investing

Python Version

By: Guillaume Coqueret,Tony Guida

a detailed presentation of the key machine learning tools use in finance a large scale coding tutorial with easily reproducible examples realistic applications on a large publicly available dataset all the key ingredients to perform a full portfolio backtest

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Page Count

358

Publisher

CRC Press

Published Date

ISBN 10

1000912809

ISBN 13

9781000912807

Perspectives in Sustainable Equity Investing

By: Guillaume Coqueret

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Perspectives in Sustainable Equity Investing

By: Guillaume Coqueret

Sustainable investing has recently gained traction throughout the world. This trend has multiple sources, which span from genuine ethical concerns to hopes of performance boosting, and also encompass risk mitigation. The resulting appetite for green assets is impacting the decisions of many investors. Perspectives in Sustainable Equity Investing is an up-to-date review of the academic literature on sustainable equity investing. It covers more than 800 academic sources grouped into six thematic chapters. Designed for corporate sustainability and financial management professionals, this is an ideal reference for ESG-driven financiers (both retail and institutional). Students majoring in finance or economics with some background or interest in ESG concerns would also find this compact overview useful. Key Features: Introduces the reader to terms and nomenclature used in the field. Surveys the link between sustainability and performance (including risk). Details the integration of sustainable criteria in complex portfolio optimization. Reviews the financial liabilities induced by climate change.

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Page Count

205

Publisher

CRC Press

Published Date

ISBN 10

1000536483

ISBN 13

9781000536485

Perspectives in Sustainable Equity Investing

By: Guillaume Coqueret

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Perspectives in Sustainable Equity Investing

By: Guillaume Coqueret

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Page Count

135

Publisher

CRC Press

Published Date

ISBN 10

100053653X

ISBN 13

9781000536539

Machine Learning for Factor Investing

Python Version

By: Guillaume Coqueret,Tony Guida

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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 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, 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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Page Count

498

Publisher

CRC Press

Published Date

ISBN 10

1000912825

ISBN 13

9781000912821

Machine Learning for Factor Investing: R Version

By: Guillaume Coqueret,Tony Guida

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Machine Learning for Factor Investing: R 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 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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Page Count

321

Publisher

CRC Press

Published Date

ISBN 10

1000176762

ISBN 13

9781000176766

Book's by Guillaume Coqueret

Machine Learning for Factor Investing

Machine Learning for Factor Investing

Perspectives in Sustainable Equity Investing

Perspectives in Sustainable Equity Investing

Perspectives in Sustainable Equity Investing

Perspectives in Sustainable Equity Investing

Machine Learning for Factor Investing

Machine Learning for Factor Investing

Machine Learning for Factor Investing: R Version

Machine Learning for Factor Investing: R Version

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