Overview
Quantitative Trading Strategies Using Python is a book by Peng Liu, first published in 2023. In this catalogue it is classified mainly under Algorithmic Trading, with secondary coverage of Quantitative Finance and Financial Machine Learning.
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 metadata points to an implementation-oriented, applied treatment. 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 96% and difficulty confidence is 66%; the catalogue lists no ratings or awards.