Deep Learning in Quantitative Trading
€ 28,90
Informação do Produto
| ISBN | 9781009707114 |
|---|---|
| Autores | Stefan Zohren, Zihao Zhang |
| Editora | Cambridge University Press |
| Formato | Capa mole |
| Número de páginas | 75 |
| Peso (kg) | 0,278 |
| Data de Publicação | 30/10/2025 |
| Preço (iva excl.) | € 27,26 |
| Imposto | € 1,64 |
| Preço (iva inc.) | € 28,90 |
| Disponibilidade | 1 unidade em armazém externo |
Descrição do Produto
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.