Isbn: 9781009707114 - deep learning in quantitative trading (elements in quantitative finance) (5 Ergebnisse)

paperback. Zustand: Very Good. In stock ready to dispatch from the UK.

Paperback. Zustand: Brand New. 75 pages. 6.00x0.39x9.00 inches. In Stock.

Paperback. Zustand: Brand New. 75 pages. 6.00x0.39x9.00 inches. In Stock.

Zustand: New. 2025. paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…