Deep Learning in Quantitative Trading (Elements in Quantitative Finance) - Softcover

Zhang, Zihao

Softcover

ISBN 10: 1009707116 ISBN 13: 9781009707114

Publisher: 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.

Edition details

• Publisher: Cambridge University Press
• Publication date: 2025
• Language: English
• ISBN 10: 1009707116
• ISBN 13: 9781009707114
• Binding: Paperback
• Number of pages: 184