I have been meaning to read this Quantitative Trading book for quite sometime however I didn’t see the point until I got Matlab up and running. The book is a lot shorter then I expected yet still manages to cover some important topics. The table of contents is shown below:

Quantitative Trading How to Build Your Own Algorithmic Trading Business by Ernest Chan

Table of Contents 

Chapter 1 – The Whats, Whos, and Whys of Quantitative Trading

Who Can Become a Quantitative Trader?

The Business Case for Quantitative Trading

• Scalability
• Demand on Time
• The Nonnecessity of Marketing

The Way Forward

Chapter 2 – Fishing for Ideas

How to Identify a Strategy That Suits You

• Your Working Hours
• Your Programming Skills
• Your Trading Capital
• Your Goal

A Taste for Plausible Strategies and Their Pitfalls

• How Does It Compare with a Benchmark and How Consistent Are Its Returns?
• How Deep and Long Is the Drawdown?
• How Will Transaction Costs Affect the Strategy?
• Does the Data Suffer from Survivorship Bias?
• How Did the Performance of the Strategy Change over the Years?
• Does the Strategy Suffer from Data-Snooping Bias?
• Does the Strategy “Fly under the Radar" of Institutional Money Managers?

Chapter 3 – Back Testing

Common Back testing Platforms

• Excel
• MATLAB
• TradeStation
• High-End Back testing Platforms

Finding and Using Historical Databases

• Are the Data Split and Dividend Adjusted?
• Are the Data Survivorship Bias Free?
• Does Your Strategy Use High and Low Data?

Performance Measurement-Common Back testing Pitfalls to Avoid

• Look-Ahead Bias
• Data-Snooping Bias

Transaction Costs

Strategy Refinement

Chapter 4 – Setting Up Your Business

Business Structure: Retail or Proprietary?

Choosing a Brokerage or Proprietary Trading Firm

Physical Infrastructure

Chapter 5 – Execution Systems

What an Automated Trading System Can Do for You

• Building a Semi automated Trading System
• Building a Fully Automated Trading System

Minimizing Transaction Costs

Testing Your System by Paper Trading

Why Does Actual Performance Diverge from Expectations?

Chapter 6 – Money and Risk Management

Optimal Capital Allocation and Leverage

Risk Management

Psychological Preparedness

Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian

Chapter 7 – Special Topics in Quantitative Trading

Mean-Reverting versus Momentum Strategies

Regime Switching

Stationarity and Cointegration

Factor Models

What Is Your Exit Strategy?

Seasonal Trading Strategies

High-Frequency Trading Strategies

Is It Better to Have a High-Leverage versus a High-Beta Portfolio?

Chapter 8 – Next Steps Conclusion: Can Independent Traders Succeed?

Appendix A Quick Survey of MATLAB

As you can see from the table of contents the book does a good job of covering a broad range of topics. Chan has an excellent ability to break down some high level concepts into very easy to understand concise definitions.From the preface it is clear that this book is written with the beginner in mind.

Do I need Matlab before I read this book?

After reading the book and going through the sample code I have come to the conclusion that Matlab is not required, however I think it is definitely an advantage if you have access to a copy of Matlab. Most of the code in the book is written with Matlab in mind however it is a trivial task to port it to Octave or implement it in python. Most of the concepts presented can also be implemented in Excel, however you may run into to some scale problems with large datasets.  

Will this book give me a license to print money?

Quantitative Trading:How to Build Your Own Algorithmic Trading Business book forms a solid foundation to build upon for the aspiring Quant trader. You will need to do more then just read this book, you will have to download the sample code and go through the examples. You will also need to know how to code or be willing to learn.

Bottom Line

This book is an excellent easy to read concise introduction to Quantitative Algorithmic trading. The concepts are presented in such a way that any high school graduate would be able to pick up the book and not get lost. If you have a higher level of mathematical understanding you will still derive benefit from reading this book. This book should be compulsory reading for anyone wanting to start algorithmic trading. It would have been nice if some areas could have been looked at in more detail however Chan’s blog goes into more detail.