Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field
In the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, quant trading expert Dr. Ernest P. Chan shows you how to apply both time-tested and novel quantitative trading strategies to develop or improve your own trading firm.
You'll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as:
Updated back tests on a variety of trading strategies, with included Python and R code examples A new technique on optimizing parameters with changing market regimes using machine learning. A guide to selecting the best traders and advisors to manage your money
Perfect for independent retail traders seeking to start their own quantitative trading business, or investors looking to invest in such traders, this new edition of Quantitative Trading will also earn a place in the libraries of individual investors interested in exploring a career at a major financial institution.
By:
Ernest P. Chan (Cornell University)
Foreword by:
Rishi K. Narang
Imprint: John Wiley & Sons Inc
Country of Publication: United States
Edition: 2nd edition
Dimensions:
Height: 226mm,
Width: 150mm,
Spine: 20mm
Weight: 295g
ISBN: 9781394378043
ISBN 10: 1394378041
Series: Wiley Trading
Pages: 256
Publication Date: 23 February 2026
Audience:
General/trade
,
Professional and scholarly
,
ELT Advanced
,
Undergraduate
Format: Paperback
Publisher's Status: Active
Foreword by Rishi K. Narang xi Preface to the 2nd Edition xv Preface xix Acknowledgments xxv CHAPTER 1: The Whats, Whos, and Whys of Quantitative Trading 1 Who Can Become a Quantitative Trader? 2 The Business Case for Quantitative Trading 4 The Way Forward 8 CHAPTER 2: Fishing for Ideas 11 How to Identify a Strategy that Suits You 14 A Taste for Plausible Strategies and Their Pitfalls 20 CHAPTER 3: Backtesting 33 Common Backtesting Platforms 34 Finding and Using Historical Databases 40 Performance Measurement 47 Common Backtesting Pitfalls to Avoid 57 Transaction Costs 72 Strategy Refinement 77 CHAPTER 4: Setting Up Your Business 81 Business Structure: Retail or Proprietary? 81 Choosing a Brokerage or Proprietary Trading Firm 85 Physical Infrastructure 87 CHAPTER 5: Execution Systems 93 What an Automated Trading System Can Do for You 93 Minimizing Transaction Costs 101 Testing Your System by Paper Trading 103 Why Does Actual Performance Diverge from Expectations? 104 Summary 107 CHAPTER 6: Money and Risk Management 109 Optimal Capital Allocation and Leverage 109 Risk Management 120 Psychological Preparedness 125 Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian 131 CHAPTER 7: Special Topics in Quantitative Trading 133 Mean-Reverting versus Momentum Strategies 134 Regime Change and Conditional Parameter Optimization 137 Stationarity and Cointegration 147 Factor Models 160 What Is Your Exit Strategy? 169 Seasonal Trading Strategies 174 High-Frequency Trading Strategies 186 Is it Better to Have a High-Leverage versus a High-Beta Portfolio? 188 CHAPTER 8: Conclusion 193 Next Steps 197 References 198 Appendix: A Quick Survey of MATLAB 199 Bibliography 205 About the Author 209 Index 211
ERNEST P. CHAN, PhD, is an expert in the application of statistical models and software for trading currencies, futures, and stocks. He holds a doctorate in theoretical physics from Cornell University and is Managing Member of investment management firm QTS Capital Management and founder of financial machine learning firm Predictnow.ai.
