{"product_id":"deep-learning-in-quantitative-trading-9781009707114","title":"Deep Learning in Quantitative Trading","description":"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.\u003cbr\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51806105174290,"sku":"9781009707114","price":22.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_b3a5bb51-8868-4818-9a2e-9ba0786773c8.jpg?v=1765976474","url":"https:\/\/surprise-castle.myshopify.com\/products\/deep-learning-in-quantitative-trading-9781009707114","provider":"Surprise Castle","version":"1.0","type":"link"}