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Pairs Trading: Quantitative Methods and Analysis

توضیحات

Comprised of three information-packed parts, Pairs Trading presents an in-depth look at the various aspects of these strategies and provides quantitative tools to assist in their analysis. The first part of this comprehensive resource sets the context for the rest of the book by introducing preliminary material on some key topics, including time series, factor models, and Kalman filtering.

After presenting the broad ideas and concepts of this trading method, Pairs Trading delves into two different versions of pairs trading in the equity markets–statistical arbitrage pairs trading and risk arbitrage. Part II of this book details statistical arbitrage pairs trading, which is a relative value arbitrage on two securities based on the premise that there is a long-run equilibrium between the prices of the stocks comprising the pair. Part III moves on to illustrate the trading techniques and strategies associated with risk arbitrage–the widely practiced arbitrage technique that involves pairs trading arising in the context of corporate events, especially mergers and acquisitions.

Written in a straightforward and accessible style, Pairs Trading provides a framework that will allow you to boost the bottom line of any portfolio.


Ganapathy Vidyamurthy has been working in the financial markets for nearly a decade. During this time, he created the entire risk management software infrastructure for RBC Dominion Securities in New York, and built valuation models and automated execution strategies for UBS Warburg and JP Morgan Fleming. He is currently the principal of Himalaya Consulting. Beyond finance, Mr. Vidyamurthy's interests range from discrete optimization to algorithmic music composition–a field in which he is often cited. Mr. Vidyamurthy has a master's degree in electrical communication engineering from the Indian Institute of Science and a master's degree from the Courant Institute of Mathematical Sciences of New York University.
Preface.

Acknowledgments.

PART ONE: BACKGROUND MATERIAL.

Chapter 1. Introduction.

The CAPM Model.

Market Neutral Strategy.

Pairs Trading.

Outline.

Audience.

Chapter 2. Time Series.

Overview.

Autocorrelation.

Time Series Models.

Forecasting.

Goodness of Fit versus Bias.

Model Choice.

Modeling Stock Prices.

Chapter 3. Factor Models.

Introduction.

Arbitrage Pricing Theory.

The Covariance Matrix.

Application: Calculating the Risk on a Portfolio.

Application: Calculation of Portfolio Beta.

Application: Tracking Basket Design.

Sensitivity Analysis.

Chapter 4. Kalman Filtering.

Introduction.

The Kalman Filter.

The Scalar Kalman Filter.

Filtering the Random Walk.

Application: Example with the Standard & Poor Index.

PART TWO: STATISTICAL ARBITRAGE.

Chapter 5. Overview.

History.

Motivation.

Cointegration.

Applying the Model.

A Trading Strategy.

Road Map for Strategy Design.

Chapter 6. Pairs Selection in Equity Markets.

Introduction.

Common Trends Cointegration Model.

Common Trends Model and APT.

The Distance Measure.

Interpreting the Distance Measure.

Reconciling Theory and Practice.

Chapter 7. Testing for Tradability.

Introduction.

The Linear Relationship.

Estimating the Linear Relationship: The Multifactor Approach.

Estimating the Linear Relationship: The Regression Approach.

Testing Residual for Tradability.

Chapter 8. Trading Design.

Introduction.

Band Design for White Noise.

Spread Dynamics.

Nonparametric Approach.

Regularization.

Tying Up Loose Ends.

PART THREE: RISK ARBITRAGE PAIRS.

Chapter 9. Risk Arbitrage Mechanics.

Introduction.

History.

The Deal Process.

Transaction Terms.

The Deal Spread.

Trading Strategy.

Quantitative Aspects.

Chapter 10. Trade Execution.

Introduction.

Specifying the Order.

Verifying the Execution.

Execution During the Pricing Period.

Short Selling.

Chapter 11. The Market Implied Merger Probability.

Introduction.

Implied Probabilities and Arrow-Debreu Theory.

The Single-Step Model.

The Multistep Model.

Reconciling Theory and Practice.

Risk Management.

Chapter 12. Spread Inversion.

Introduction.

The Prediction Equation.

The Observation Equation.

Applying the Kalman Filter.

Model Selection.

Applications to Trading.

Index.