Description

Book Synopsis


Table of Contents

Preface to the 2nd Edition xi

Preface xv

Acknowledgments xxi

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

Scalability 5

Demand on Time 5

The Nonnecessity of Marketing 7

The Way Forward 8

Chapter 2: Fishing for Ideas 11

How to Identify a Strategy that Suits You 14

Your Working Hours 14

Your Programming Skills 15

Your Trading Capital 15

Your Goal 19

A Taste for Plausible Strategies and Their Pitfalls 20

How Does It Compare with a Benchmark, and How Consistent Are Its Returns? 20

How Deep and Long Is the Drawdown? 23

How Will Transaction Costs Affect the Strategy? 24

Does the Data Suffer from Survivorship Bias? 26

How Did the Performance of the Strategy Change over the Years? 27

Does the Strategy Suffer from Data-Snooping Bias? 28

Does the Strategy “Fly under the Radar” of Institutional Money Managers? 30

Summary 30

References 31

Chapter 3: Backtesting 33

Common Backtesting Platforms 34

Excel 34

MATLAB 34

Python 36

R 38

QuantConnect 40

Blueshift 40

Finding and Using Historical Databases 40

Are the Data Split and Dividend Adjusted? 41

Are the Data Survivorship-Bias Free? 44

Does Your Strategy Use High and Low Data? 46

Performance Measurement 47

Common Backtesting Pitfalls to Avoid 57

Look-Ahead Bias 58

Data-Snooping Bias 59

Transaction Costs 72

Strategy Refinement 77

Summary 78

References 79

Chapter 4: Setting Up Your Business 81

Business Structure: Retail or Proprietary? 81

Choosing a Brokerage or Proprietary Trading Firm 85

Physical Infrastructure 87

Summary 89

References 91

Chapter 5: Execution Systems 93

What an Automated Trading System Can Do for You 93

Building a Semiautomated Trading System 95

Building a Fully Automated Trading System 98

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

Model Risk 124

Software Risk 125

Natural Disaster Risk 125

Psychological Preparedness 125

Summary 130

Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian 131

References 132

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

Summary 190

References 192

Chapter 8: Conclusion 193

Next Steps 197

References 198

Appendix: A Quick Survey of MATLAB 199

Bibliography 205

About the Author 209

Index 211

Quantitative Trading

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    Order before 4pm today for delivery by Fri 26 Jun 2026.

    A Hardback by Ernest P. Chan

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      Publisher: John Wiley & Sons Inc
      Publication Date: 16/09/2021
      ISBN13: 9781119800064, 978-1119800064
      ISBN10: 1119800064

      Description

      Book Synopsis


      Table of Contents

      Preface to the 2nd Edition xi

      Preface xv

      Acknowledgments xxi

      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

      Scalability 5

      Demand on Time 5

      The Nonnecessity of Marketing 7

      The Way Forward 8

      Chapter 2: Fishing for Ideas 11

      How to Identify a Strategy that Suits You 14

      Your Working Hours 14

      Your Programming Skills 15

      Your Trading Capital 15

      Your Goal 19

      A Taste for Plausible Strategies and Their Pitfalls 20

      How Does It Compare with a Benchmark, and How Consistent Are Its Returns? 20

      How Deep and Long Is the Drawdown? 23

      How Will Transaction Costs Affect the Strategy? 24

      Does the Data Suffer from Survivorship Bias? 26

      How Did the Performance of the Strategy Change over the Years? 27

      Does the Strategy Suffer from Data-Snooping Bias? 28

      Does the Strategy “Fly under the Radar” of Institutional Money Managers? 30

      Summary 30

      References 31

      Chapter 3: Backtesting 33

      Common Backtesting Platforms 34

      Excel 34

      MATLAB 34

      Python 36

      R 38

      QuantConnect 40

      Blueshift 40

      Finding and Using Historical Databases 40

      Are the Data Split and Dividend Adjusted? 41

      Are the Data Survivorship-Bias Free? 44

      Does Your Strategy Use High and Low Data? 46

      Performance Measurement 47

      Common Backtesting Pitfalls to Avoid 57

      Look-Ahead Bias 58

      Data-Snooping Bias 59

      Transaction Costs 72

      Strategy Refinement 77

      Summary 78

      References 79

      Chapter 4: Setting Up Your Business 81

      Business Structure: Retail or Proprietary? 81

      Choosing a Brokerage or Proprietary Trading Firm 85

      Physical Infrastructure 87

      Summary 89

      References 91

      Chapter 5: Execution Systems 93

      What an Automated Trading System Can Do for You 93

      Building a Semiautomated Trading System 95

      Building a Fully Automated Trading System 98

      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

      Model Risk 124

      Software Risk 125

      Natural Disaster Risk 125

      Psychological Preparedness 125

      Summary 130

      Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian 131

      References 132

      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

      Summary 190

      References 192

      Chapter 8: Conclusion 193

      Next Steps 197

      References 198

      Appendix: A Quick Survey of MATLAB 199

      Bibliography 205

      About the Author 209

      Index 211

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