Overview
Deep Learning in Quantitative Trading is a book by Zihao Zhang and Stefan Zohren, first published in 2025. In this catalogue it is classified mainly under Quantitative Finance and Deep Learning for Finance, with secondary coverage of Algorithmic Trading.
Audience and depth. The rule-based model places its mathematical difficulty at advanced level (7/10); readers are typically expected to know calculus, linear algebra, machine learning, probability theory, statistics and stochastic processes.
Orientation. The theory-versus-practice balance could not be determined from metadata. The archive holds 6 papers whose topics and vocabulary overlap with this book; those links are inferred (see the research connections below).
How to read this page. Topics, difficulty, prerequisites and orientation are model-derived (rule-based, rule_based_v1) from bibliographic metadata such as title, subject headings and edition data. They were not produced by reading the book and are not a review. Relevance confidence is 92% and difficulty confidence is 66%; the catalogue lists no ratings or awards.