Quantitative Trading

Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Second Edition) by Dr. Ernest P. Chan is a comprehensive and practical handbook for mastering the disciplined and data-driven world of quantitative trading. Written by one of the most respected practitioners in the field, the book offers a clear roadmap for designing, testing, and deploying algorithmic trading strategies in real financial markets.

In this newly revised second edition, Dr. Chan blends time-tested quantitative methods with modern innovations, including machine learning–based approaches, to reflect today’s rapidly evolving trading environment. Rather than focusing on abstract theory, the book emphasizes real-world implementation, helping readers understand what actually works, why it works, and how to adapt strategies as markets change.

Readers gain access to:

• Updated backtests across a wide range of asset classes and trading strategies

• Practical Python and R code examples for strategy development and evaluation

• New techniques for parameter optimization under changing market regimes using machine learning

• Clear guidance on risk management, execution, and performance evaluation

Beyond strategy design, the book also explores the business side of quantitative trading. It provides valuable insights into building and managing a trading operation, evaluating fund managers, and selecting the right traders or advisors to handle investment capital.

Written in a clear and accessible style, Quantitative Trading is ideal for independent retail traders aiming to start their own algorithmic trading business, as well as investors seeking to understand or allocate capital to quantitative strategies. It is equally valuable for professionals and students interested in pursuing a career in quantitative finance, hedge funds, or institutional trading.

Overall, this book serves as both a technical guide and strategic blueprint, equipping readers with the tools, mindset, and practical knowledge needed to succeed in the competitive world of quantitative trading.