ISBN 13 : 978-0-367-54586-4

Sommaire :

I Introduction
1. Preface
2. Notations and data
3. Introduction
4. Factor investing and asset pricing anomalies
5. Data preprocessing

II Common supervised algorithms
6. Penalized regressions and sparse hedging for minimum variance portfolios
7. Tree-based methods
8. Neural networks
9. Support vector machines
10. Bayesian methods
12. Ensemble models
13. Portfolio backtesting

IV Further important topics
14. Interpretability
15. Two key concepts: causality and non-stationarity
16. Unsupervised learning
17. Reinforcement learning

V Appendix
Data Description

Solution to exercises

Langue : Anglais

Collection : CHAPMAN AND HALL / CRC FINANCIAL MATHEMATICS SERIES

Localisation : Bibliothèque Campus de Nice

Support : Papier

Etat : Présent

Propriétaire : Bibliothèque