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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.
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
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Importe, 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 |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 178 x 254 x 22 mm |
| Von/Mit: | Guillaume Coqueret (u. a.) |
| Erscheinungsdatum: | 01.09.2020 |
| Gewicht: | 0,702 kg |
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.
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
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Importe, 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 |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 178 x 254 x 22 mm |
| Von/Mit: | Guillaume Coqueret (u. a.) |
| Erscheinungsdatum: | 01.09.2020 |
| Gewicht: | 0,702 kg |
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