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| Preface to the Second Edition | |
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| Acknowledgments | |
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| The Quant Universe | |
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| Why Does Quant Trading Matter? | |
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| The Benefit of Deep Thought | |
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| The Measurement and Mismeasurement of Risk | |
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| Disciplined Implementation | |
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| Summary | |
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| Notes | |
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| An Introduction to Quantitative Trading | |
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| What Is a Quant? | |
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| What Is the Typical Structure of a Quantitative Trading System? | |
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| Summary | |
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| Notes | |
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| Inside the Black Box | |
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| Alpha Models: How Quants Make Money | |
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| Types of Alpha Models: Theory-Driven and Data-Driven | |
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| Theory-Driven Alpha Models | |
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| Data-Driven Alpha Models | |
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| Implementing the Strategies | |
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| Blending Alpha Models | |
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| Summary | |
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| Notes | |
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| Risk Models | |
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| Limiting the Amount of Risk | |
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| Limiting the Types of Risk | |
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| Summary | |
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| Notes | |
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| Transaction Cost Models | |
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| Defining Transaction Costs | |
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| Types of Transaction Cost Models | |
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| Summary | |
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| Note | |
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| Portfolio Construction Models | |
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| Rule-Based Portfolio Construction Models | |
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| Portfolio Optimizers | |
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| Output of Portfolio Construction Models | |
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| How Quants Choose a Portfolio Construction Model | |
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| Summary | |
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| Notes | |
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| Execution | |
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| Order Execution Algorithms | |
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| Trading Infrastructure | |
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| Summary | |
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| Notes | |
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| Data | |
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| The Importance of Data | |
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| Types of Data | |
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| Sources of Data | |
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| Cleaning Data | |
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| Storing Data | |
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| Summary | |
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| Notes | |
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| Research | |
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| Blueprint for Research: The Scientific Method | |
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| Idea Generation | |
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| Testing | |
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| Summary | |
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| Note | |
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| A Practical Guide fop Investors in Quantitative Strategies | |
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| Risks Inherent to Quant Strategies | |
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| Model Risk | |
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| Regime Change Risk | |
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| Exogenous Shock Risk | |
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| Contagion, or Common Investor, Risk | |
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| How Quants Monitor Risk | |
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| Summary | |
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| Notes | |
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| Criticisms of Quant Trading | |
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| Trading Is an Art, Not a Science | |
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| Quants Cause More Market Volatility by Underestimating Risk | |
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| Quants Cannot Handle Unusual Events or Rapid Changes in Market Conditions | |
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| Quants Are All the Same | |
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| Only a Few Large Quants Can Thrive in the Long Run | |
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| Quants Are Guilty of Data Mining | |
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| Summary | |
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| Notes | |
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| Evaluating Quants and Quant Strategies | |
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| Gathering Information | |
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| Evaluating a Quantitative Trading Strategy | |
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| Evaluating the Acumen of Quantitative Traders | |
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| The Edge | |
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| Evaluating Integrity | |
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| How Quants Fit into a Portfolio | |
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| Summary | |
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| Note | |
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| High-Speed and High-Frequency Trading | |
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| An Introduction to High-Speed and High-Frequency Trading* | |
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| Notes | |
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| High-Speed Trading | |
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| Why Speed Matters | |
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| Sources of Latency | |
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| Summary | |
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| Notes | |
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| High-Frequency Trading | |
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| Contractual Market Making | |
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| Noncontractual Market Making | |
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| Arbitrage | |
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| Fast Alpha | |
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| HFT Risk Management and Portfolio Construction | |
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| Summary | |
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| Note | |
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| Controversy Regarding High-Frequency Trading | |
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| Does HFT Create Unfair Competition? | |
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| Does HFT Lead to Front-Running or Market Manipulation? | |
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| Does HFT Lead to Greater Volatility or Structural Instability? | |
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| Does HFT Lack Social Value? | |
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| Regulatory Considerations | |
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| Summary | |
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| Notes | |
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| Looking to the Future of Quant Trading | |
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| About the Author | |
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| Index | |