Inside the Black Box (eBook)

rishi k narang is the Founding Principal of T2AM LLC, which invests in quantitative strategies. He has been involved in the hedge fund industry variously as an investor in and practitioner of quantitative trading strategies since 1996. When he isn't working, Rishi enjoys playing his guitar, writing essays and poems, making pencil sketches, arguing with people, playing tennis, doing yoga, and hiking. Rishi completed his undergraduate degree in economics at the University of California at Berkeley. He lives in Los Angeles with his wife, Dr. Carolyn Wong, and their son, Solomon.

Foreword

Preface to the Second Edition

Acknowledgments

Part I: The Quant Universe

Chapter 1: Why Does Quant Trading Matter?

The Benefit of Deep Thought

The Measurement and Mis-measurement 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 II: Inside the Black Box

Chapter 3: Alpha Models: How Quants Make Money

Types of Alpha Models: Theory Driven and Data Driven

Theory-Driven Alpha Models

Data-Driven Alpha Models

Implementing the Strategies

Blending Alpha Models

Summary

Notes

Chapter 4: Risk Models

Limiting the Amount of Risk

Limiting the Types of Risk

Summary

Notes

Chapter 5: Transaction Cost Models

Defining Transaction Costs

Types of Transaction Cost Models

Summary

Notes

Chapter 6: Portfolio Construction Models

Rule-Based Portfolio Construction Models

Portfolio Optimizers

Output of Portfolio Construction Models

How Quants Choose a Portfolio Construction Model

Summary

Notes

Chapter 7: Execution

Order Execution Algorithms

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

Summary

Notes

Part III: A Practical Guide for Investors in Quantitative Strategies

Chapter 10: Risks Inherent to Quant Strategies

Model Risk

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

Quants Cannot Handle Unusual Events or Rapid Changes in Market Conditions

Quants Are All the Same

Only a Few Large Quants Can Thrive in the Long Run

Quants Are Guilty of Data Mining

Summary

Notes

Chapter 12: Evaluating Quants and Quant Strategies

Gathering Information

Evaluating a Quantitative Trading Strategy

Evaluating the Acumen of Quantitative Traders

The Edge

Evaluating Integrity

How Quants Fit into a Portfolio

Summary

Notes

Part IV: High Speed and High Frequency Trading

Chapter 13: An Introduction to High Speed and High Frequency Trading* Notes

Chapter 14: High Speed Trading

Why Speed Matters

Sources of Latency

Summary

Notes

Chapter 15: High Frequency Trading

Contractual Market Making

Non-Contractual Market Making

Arbitrage

Fast Alpha

HFT Risk Management and Portfolio Construction

Summary

Notes

Chapter 16: Controversy Regarding High Frequency Trading

Does HFT Create Unfair Competition?

Does HFT Lead to Front-running or Market Manipulation?

Does HFT Lead to Greater Volatility or Structural Instability?

Does HFT Lack Social Value?

Regulatory Considerations

Summary

Notes

Chapter 17: Looking to the Future of Quant Trading

About the Author

Index