Algorithmic Trading
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Chan covers the practical mechanics of building algorithmic trading systems: mean reversion vs momentum strategies, backtesting methodology, execution considerations, and risk management for automated systems. The book bridges the gap between academic quantitative finance and real-world implementation, with MATLAB code examples throughout.
Who It's For
Traders with programming skills (Python, MATLAB, R) who want to systematise their approach. Requires comfort with statistics and basic calculus. Not for beginners or purely discretionary traders. Best suited for traders already familiar with basic strategy concepts who want to learn the quantitative rigour behind proper backtesting and system evaluation.
What's Good
Honest about the challenges of algorithmic trading — Chan doesn't promise easy profits. The backtesting methodology chapters are excellent, covering common pitfalls like look-ahead bias, survivorship bias, and overfitting. Practical code examples make concepts tangible. The mean reversion strategies are well-explained with real-world applicability. The section on evaluating strategy performance using Sharpe ratio, maximum drawdown, and Kelly criterion is one of the best compact treatments of these topics.
What's Bad
At $45 for 224 pages, it's expensive. The MATLAB code examples are a significant limitation — most retail traders use Python, and the translation isn't always straightforward. The strategies presented are relatively basic by modern quant standards. Some material feels dated given advances in machine learning and alternative data. Chan's own fund performance, while adequate, isn't exceptional — raising questions about whether the strategies in the book represent the cutting edge. The execution and market microstructure sections are thin.
The Verdict
A solid introduction to algorithmic trading that's honest about its limitations. The backtesting methodology alone justifies the purchase for anyone building systematic strategies. The 3.7 rating reflects good but not exceptional content at a premium price point. Best paired with more modern Python-based resources for implementation.
Related Reviews
Chan's introductory book Quantitative Trading covers the business side of running an algo operation. For a free platform to practice, see our review of QuantConnect's LEAN Documentation. This book appears on our Best Crypto Trading Books list.