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Machine Learning for Factor Investing: R Version
Taschenbuch von Guillaume Coqueret (u. a.)
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor

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.

Inhaltsverzeichnis

1. Preface 2. Notations and data 3. Introduction 4. Factor investing and asset pricing anomalies 5. Data preprocessing 6. Penalized regressions and sparse hedging for minimum variance portfolios 8. Neural networks 7. Tree-based methods 9. Support vector machines 10. Bayesian methods 11. Validating and tuning 12. Ensemble models 13. Portfolio backtesting 14. Interpretability 15. Two key concepts: causality and non-stationarity 16. Unsupervised learning 17. Reinforcement learning

Details
Erscheinungsjahr: 2020
Fachbereich: Allgemeines
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367545864
ISBN-10: 0367545861
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Coqueret, Guillaume
Guida, Tony
Hersteller: Taylor & Francis Ltd
Maße: 178 x 254 x 22 mm
Von/Mit: Guillaume Coqueret (u. a.)
Erscheinungsdatum: 01.09.2020
Gewicht: 0,702 kg
Artikel-ID: 126500361
Über den Autor

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.

Inhaltsverzeichnis

1. Preface 2. Notations and data 3. Introduction 4. Factor investing and asset pricing anomalies 5. Data preprocessing 6. Penalized regressions and sparse hedging for minimum variance portfolios 8. Neural networks 7. Tree-based methods 9. Support vector machines 10. Bayesian methods 11. Validating and tuning 12. Ensemble models 13. Portfolio backtesting 14. Interpretability 15. Two key concepts: causality and non-stationarity 16. Unsupervised learning 17. Reinforcement learning

Details
Erscheinungsjahr: 2020
Fachbereich: Allgemeines
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367545864
ISBN-10: 0367545861
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Coqueret, Guillaume
Guida, Tony
Hersteller: Taylor & Francis Ltd
Maße: 178 x 254 x 22 mm
Von/Mit: Guillaume Coqueret (u. a.)
Erscheinungsdatum: 01.09.2020
Gewicht: 0,702 kg
Artikel-ID: 126500361
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