Introduction

The book "Quantitative Trading: How to Build Your Own Algorithmic Trading Business" is written by Ernest P. Chan. It aims to guide independent traders and individuals who are interested in engaging in quantitative trading in financial institutions on how to build their own algorithmic trading business. The book introduces the core concepts and practical methods of quantitative trading in detail, emphasizing the importance of applying theoretical knowledge to practical operations.

This book covers the key mathematical techniques needed to build algorithmic trading systems and their applications in finance. Content includes but is not limited to: how to identify and develop a trading strategy that suits you, which involves consideration of trading time, programming skills, and trading capital. The book deeply discusses the importance of backtesting and introduces common platforms such as Excel, MATLAB, Python and R. It also points out common pitfalls in backtesting, such as future data bias (Look-Ahead Bias) and data snooping bias (Data-Snooping Bias).

In addition, this book also explains in detail fund management and risk management, including optimal capital allocation and leverage use, as well as risk control strategies. The book also covers the construction of execution systems, including semi-automated and fully automated trading systems, and how to minimize transaction costs. Special topic sections explore mean reversion and momentum strategies, market mechanism transitions, stationarity and cointegration, factor models, and exit strategies. This book aims to provide a comprehensive guide to help readers combine technical expertise with business acumen to successfully build and operate a profitable algorithmic trading business.

Main features

• Solid theoretical foundation
• Rich practical cases
• Clear operating instructions
• Suitable for practical applications

Suitable for the crowd

• Quantitative Analyst
• Algorithmic Trader
• Financial Engineer
• Data Scientist