Algorithmic Trading: Winning Strategies and Their Rationale

Praise for Algorithmic Trading

"Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers."

DAREN SMITH, CFA, CAIA, FSA, Managing Director, Manager Selection & Portfolio Construction, University of Toronto Asset Management

"Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses."

Roger Hunter, Mathematician and Algorithmic Trader

Preface ix

CHAPTER 1 Backtesting and Automated Execution 1

CHAPTER 2 The Basics of Mean Reversion 39

CHAPTER 3 Implementing Mean Reversion Strategies 63

CHAPTER 4 Mean Reversion of Stocks and ETFs 87

CHAPTER 5 Mean Reversion of Currencies and Futures 107

CHAPTER 6 Interday Momentum Strategies 133

CHAPTER 7 Intraday Momentum Strategies 155

CHAPTER 8 Risk Management 169

Conclusion 187

Bibliography 191

About the Author 197

About the Website 199

Index 201

ERNEST P. CHAN is the Managing Member of QTS Capital Management, LLC. He has worked for various investment banks (Morgan Stanley, Credit Suisse, Maple) and hedge funds (Mapleridge, Millennium Partners, MANE) since 1997. Chan received his PhD in physics from Cornell University and was a member of IBM′s Human Language Technologies group before joining the financial industry. He was a cofounder and principal of EXP Capital Management, LLC, a Chicago–based investment firm. Chan is also the author of Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley) and a popular financial blogger at http://epchan.blogspot.com. Find out more about him at www.epchan.com.