Includes bibliographical references and index.

Inside the Black Box; Contents; Preface to the Second Edition; Acknowledgments; Part One The Quant Universe; Chapter 1 Why Does Quant Trading Matter?; The Benefit of Deep Thought; The Measurement and Mismeasurement of Risk; Disciplined Implementation; Summary; Notes; Chapter 2 An Introduction to Quantitative Trading; What Is a Quant?; What Is the Typical Structure of a Quantitative Trading System?; Summary; Notes; Part Two Inside the Black Box; Chapter 3 Alpha Models: How Quants Make Money; Types of Alph a Models: Theory-Driven and Data-Driven; Theory-Driven Alpha Models.

Strategies Utilizing Price-Related DataStrategies Utilizing Fundamental Data; Data-Driven Alph a Models; Implementing the Strategies; Forecast Target; Time Horizon; Bet Structure; Investment Universe; Model Definition; Conditioning Variables; Run Frequency; An Explosion of Diversity; Blending Alpha Models; Summary; Notes; Chapter 4 Risk Models; Limiting the Amount of Risk; Limiting by Constraint or Penalty; Measuring the Amount of Risk; Where Limits Can Be Applied; Limiting the Types of Risk; Theory-Driven Risk Models; Empirical Risk Models; How Quants Choose a Risk Model; Summary; Notes.

Chapter 5 Transaction Cost ModelsDefining Transaction Costs; Commissions and Fees; Slippage; Market Impact; Types of Transaction Cost Models; Flat Transaction Cost Models; Linear Transaction Cost Models; Piecewise-Linear Transaction Cost Models; Quadratic Transaction Cost Models; Summary; Note; Chapter 6 Portfolio Construction Models; Rule-Based Portfolio Construction Models; Equal Position Weighting; Equal Risk Weighting; Alpha-Driven Weighting; Summary of Rule-Based Portfolio Construction Models; Portfolio Optimizers; Inputs to Optimization; Optimization Techniques.

Final Thoughts on OptimizationOutput of Portfolio Construction Models; How Quants Choose a Portfolio Construction Model; Summary; Notes; Chapter 7 Execution; Order Execution Algorithms; Aggressive versus Passive; Other Order Types; Large Order versus Small Order; Where to Send an Order; Trading Infrastructure; Summary; Notes; Chapter 8 Data; The Importance of Data; Types of Data; Sources of Data; Cleaning Data; Storing Data; Summary; Notes; Chapter 9 Research; Blueprint for Research: The Scientific Method; Idea Generation; Testing; In-Sample Testing, a.k.a. Training.

What Constitutes a "Good" Model?Overfitting; Out-of-Sample Testing; Assumptions of Testing; Summary; Note; Part Three A Practical Guide for Investors in Quantitative Strategies; Chapter 10 Risks Inherent to Quant Strategies; Model Risk; Inapplicability of Modeling; Model Misspecification; Implementation Errors; Regime Change Risk; Exogenous Shock Risk; Contagion, or Common Investor, Risk; How Quants Monitor Risk; Summary; Notes; Chapter 11 Criticisms of Quant Trading; Trading Is an Art, Not a Science; Quants Cause More Market Volatility by Underestimating Risk; The Market Turmoil of 2008.

New edition of book that demystifies quant and algo trading In this updated edition of his bestselling book, Rishi K Narang offers in a straightforward, nontechnical style-supplemented by real-world examples and informative anecdotes-a reliable resource takes you on a detailed tour through the black box. He skillfully sheds light upon the work that quants do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. This new edition includes information on High Frequency Trading. Offers an updat.

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