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Pairs Trading: Quantitative Methods and Analysis
Ganapathy Vidyamurthy
DESCRIPTION
The first comprehensive examination of trading pairings
The most basic type of market-neutral technique is pairs trading. One asset is long (or bullish) and another is short (or bearish) as part of the strategy. If done correctly, the investor will profit whether the market rises or falls. The secrets of this exacting quantitative analysis program are revealed by Pairs Trading, which gives people and investment firms the resources they need to properly apply and profit from this tried-and-true trading strategy. In addition to providing precise and tried-and-true methods for finding and investing in pairs, Pairs Trading also provides solutions to crucial queries like which ratio to employ when building pairs.
Currently employed at a significant hedge fund in New York City, Ganapathy Vidyamurthy (Stamford, CT) works as a quantitative software analyst and developer.
ABOUT THE AUTHOR
GANAPATHY VIDYAMURTHY has almost ten years of experience in the financial markets. He developed valuation models and automated execution techniques for UBS Warburg and JP Morgan Fleming during this time, as well as the whole risk management software infrastructure for RBC Dominion Securities in New York. He is Himalaya Consulting’s principal at the moment.
Mr. Vidyamurthy’s interests extend beyond finance; he is frequently recognized in the fields of algorithmic music creation and discrete optimization.
Mr. Vidyamurthy holds master’s degrees from the Courant Institute of Mathematical Sciences at New York University and the Indian Institute of Science in electrical communication engineering.
TABLE OF CONTENTS
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.
