Ernest Chan

Ernest Chan is a quantitative trader, hedge fund manager, and author known for his work in algorithmic trading and statistical arbitrage strategies. He has written multiple influential books on quantitative trading including "Quantitative Trading: How to Build Your Own Algorithmic Trading Business" and "Algorithmic Trading: Winning Strategies and Their Rationale." Chan holds a PhD in physics from Cornell University and has worked at major financial institutions including IBM's T.J. Watson Research Center, Morgan Stanley, and Credit Suisse. He founded QTS Capital Management, LLC and has managed various quantitative hedge funds focused on statistical arbitrage strategies. His written work and teachings focus on practical applications of statistical methods in financial markets, with particular emphasis on mean reversion strategies and pairs trading. Chan maintains an active blog called "Quantitative Trading" where he shares insights about algorithmic trading strategies and market analysis. Chan is recognized for making complex quantitative trading concepts accessible to individual traders while maintaining technical rigor. His work spans both institutional-grade strategies and approaches suitable for independent retail traders.

Readers respect Chan's technical expertise in quantitative trading but note his books require advanced mathematics and programming knowledge. Many reviewers have finance or engineering backgrounds. Likes: - Clear explanations of complex statistical concepts - Practical code examples in MATLAB/Python - Balanced perspective on automated trading risks - Real trading examples with performance metrics - Emphasis on backtesting and risk management Dislikes: - Too advanced for beginners - Dated technical references in older books - Limited coverage of modern machine learning - Some strategies no longer profitable - Code samples need updating Ratings: Amazon: Algorithmic Trading (4.3/5 from 178 reviews) Goodreads: Quantitative Trading (4.1/5 from 447 reviews) Common reader comment: "Not for novices but valuable for those with quantitative backgrounds seeking to apply their skills to trading." Several reviewers noted Chan's blog posts and newer articles provide more current strategy examples than his books.

Quantitative Trading: How to Build Your Own Algorithmic Trading Business (2009) A technical guide covering the creation of automated trading systems, risk management, and establishing a quantitative trading business.

Algorithmic Trading: Winning Strategies and Their Rationale (2013) An examination of specific trading algorithms with mathematical and statistical foundations, including mean reversion and momentum strategies.

Machine Trading: Deploying Computer Algorithms to Conquer the Markets (2017) A practical manual focusing on implementing machine learning techniques in trading, including detailed Python and MATLAB code examples.

Artificial Intelligence in Asset Management (2020) A technical overview of AI applications in portfolio management, covering topics from trading strategies to risk assessment.

Quantitative Trading Systems: Practical Methods for Design, Testing, and Validation (2021) A systematic approach to designing and validating trading systems using statistical and mathematical methods.