Deep Learning in Quantitative Trading - Couverture souple

Zhang, Zihao

Couverture souple

ISBN 10 : 1009707116 ISBN 13 : 9781009707114

Editeur : Cambridge University Press, 2025

Synopsis

This Element provides a comprehensive guide to deep learning in quantitative trading, merging foundational theory with hands-on applications. It is organized into two parts. The first part introduces the fundamentals of financial time-series and supervised learning, exploring various network architectures, from feedforward to state-of-the-art. To ensure robustness and mitigate overfitting on complex real-world data, a complete workflow is presented, from initial data analysis to cross-validation techniques tailored to financial data. Building on this, the second part applies deep learning methods to a range of financial tasks. The authors demonstrate how deep learning models can enhance both time-series and cross-sectional momentum trading strategies, generate predictive signals, and be formulated as an end-to-end framework for portfolio optimization. Applications include a mixture of data from daily data to high-frequency microstructure data for a variety of asset classes. Throughout, they include illustrative code examples and provide a dedicated GitHub repository with detailed implementations.

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 1009707116
• ISBN 13: 9781009707114
• Reliure: Broché
• Nombre de pages: 184
• Coordonnées du fabricant: non disponible
• Personne responsable: Avery; https://www.avery.fr/; ; chemin des peupliers 27; Dardilly; France