[eBook Code] Inside the Black Box (eBook Code, 1st)

Preface.

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.

Chapter 2 An Introduction to Quantitative Trading.

What is a Quant?

What is the Typical Structure of a Quantitative Trading System?

Summary.

Part Two Inside the Black Box.

Chapter 3 How Do Quants Make Money?

Answer: Alpha Models.

Types of Alpha Models: Theory-driven and Data-driven.

Theory-Driven Alpha Models.

Data-Driven Alpha Models.

Implementing the Strategies.

Blending Alpha Models.

Summary.

Chapter 4 Risk Models.

Limiting the Amount of Risk.

Limiting the Types of Risk.

Summary.

Chapter 5 Transaction Cost Models.

Defining Transaction Costs.

Types of Transaction Cost Models.

Summary.

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.

Chapter 7 Execution.

Order Execution Algorithms.

High Frequency Trading: Blurring the Line between Alpha and Execution.

Trading Infrastructure.

Summary.

Chapter 8 Data.

The Importance of Data.

Types of Data.

Sources of Data..

Cleaning Data

Storing Data.

Summary.

Chapter 9 Research.

Blueprint for Research: The Scientific Method.

Idea Generation.

Testing.

Summary.

Part Three 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.

Chapter 11 Criticisms of Quant Trading:  Setting the Record Straight.

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.

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.

Chapter 13 Looking to the Future of Quant Trading.

Notes.

About the Author.

Index.