ISBN 13 : 978-1786305442

Sommaire :
Contributors: David E. Rapach , Guofu Zhou, Kris Boudt, Muzafer Cela, Majeed Simaan, Daniele Bianchi, Andrea Tamoni, Riccardo Borghi, Giuliano De Rossi, Georgios V. Papaioannou, Daniel Giamouridis, Yin Luo, Alexei Jourovski, Vladyslav Dubikovskyy, Pere Adell, Ravi Ramakrishnan, Robert Kosowski, Sarah Perrin, Thierry Roncalli, Harald Lohre, Carsten Rother, Kilian Axel Schäefer, Ryan Brown, Harindra De Silva, Patrick D. Neal, Marie Brière, Charles-Albert Lehalle, Tamara Nefedova, Amine Raboun.

1. Time-series and Cross-sectional Stock Return Forecasting: New Machine Learning Methods,
2. In Search of Return Predictability: Application of Machine Learning Algorithms in Tactical Allocation,
3. Sparse Predictive Regressions: Statistical Performance and Economic Significance,
4. The Artificial Intelligence Approach to Picking Stocks,
5. Enhancing Alpha Signals from Trade Ideas Data Using Supervised Learning,
6. Natural Language Process and Machine Learning in Global Stock Selection,
7. Forecasting Beta Using Machine Learning and Equity Sentiment Variables,
8. Machine Learning Optimization Algorithms & Portfolio Allocation,
9. Hierarchical Risk Parity: Accounting for Tail Dependencies in Multi-asset Multi-factor Allocations,
10. Portfolio Performance Attribution: A Machine Learning-Based Approach,
11. Modeling Transaction Costs When Trades May Be Crowded: A Bayesian Network Using Partially Observable Orders Imbalance.

Nbre volumes : 0

Langue : Anglais

Collection : INNOVATION, ENTREPRENEURSHIP AND MANAGEMENT SERIES

Lieu d'édition : TORONTO

Localisation : Bibliothèque Campus de Nice

Support : Papier

Etat : Présent

Professeur EDHEC : Oui

Propriétaire : Bibliothèque