Details

Preface. <p>Foreword.</p> <p>Acknowledgments.</p> <p>Chapter 1. Monte Carlo or Bust.</p> <p>Beginning.</p> <p>Whither? And Allusions.</p> <p>Chapter 2. Statistical Arbitrage.</p> <p>Introduction.</p> <p>Noise Models.</p> <p>Reverse Bets.</p> <p>Multiple Bets.</p> <p>Rule Calibration.</p> <p>Spread Margins for Trade Rules.</p> <p>Popcorn Process.</p> <p>Identifying Pairs.</p> <p>Refining Pair Selection.</p> <p>Event Analysis.</p> <p>Correlation Search in the Twenty-First Century.</p> <p>Portfolio Configuration and Risk Control.</p> <p>Exposure to Market Factors.</p> <p>Market Impact.</p> <p>Risk Control Using Event Correlations.</p> <p>Dynamics and Calibration.</p> <p>Evolutionary Operation: Single Parameter Illustration.</p> <p>Chapter 3. Structural Models.</p> <p>Introduction.</p> <p>Formal Forecast Functions.</p> <p>Exponentially Weighted Moving Average.</p> <p>Classical Time Series Models.</p> <p>Autoregression and Cointegration.</p> <p>Dynamic Linear Model.</p> <p>Volatility Modeling.</p> <p>Pattern Finding Techniques.</p> <p>Fractal Analysis.</p> <p>Which Return?</p> <p>A Factor Model.</p> <p>Factor Analysis.</p> <p>Defactored Returns.</p> <p>Prediction Model.</p> <p>Stochastic Resonance.</p> <p>Practical Matters.</p> <p>Doubling: A Deeper Perspective.</p> <p>Factor Analysis Primer.</p> <p>Prediction Model for Defactored Returns.</p> <p>Chapter 4. Law of Reversion.</p> <p>Introduction.</p> <p>Model and Result.</p> <p>The 75 percent Rule.</p> <p>Proof of the 75 percent Rule.</p> <p>Analytic Proof of the 75 percent Rule.</p> <p>Discrete Counter.</p> <p>Generalizations.</p> <p>Inhomogeneous Variances.</p> <p>Volatility Bursts.</p> <p>Numerical Illustration.</p> <p>First-Order Serial Correlation.</p> <p>Analytic Proof.</p> <p>Examples.</p> <p>Nonconstant Distributions.</p> <p>Applicability of the Result.</p> <p>Application to U.S. Bond Futures.</p> <p>Summary.</p> <p>Appendix 4.1: Looking Several Days Ahead.</p> <p>Chapter 5. Gauss is Not the God of Reversion.</p> <p>Introduction.</p> <p>Camels and Dromedaries.</p> <p>Dry River Flow.</p> <p>Some Bells Clang.</p> <p>Chapter 6. Interstock Volatility.</p> <p>Introduction.</p> <p>Theoretical Explanation.</p> <p>Theory versus Practice.</p> <p>Finish the Theory.</p> <p>Finish the Examples.</p> <p>Primer on Measuring Spread Volatility.</p> <p>Chapter 7. Quantifying Reversion Opportunities.</p> <p>Introduction.</p> <p>Reversion in a Stationary Random Process.</p> <p>Frequency of Reversionary Moves.</p> <p>Amount of Reversion.</p> <p>Movements from Quantiles Other Than the Median.</p> <p>Nonstationary Processes: Inhomogeneous Variance.</p> <p>Sequentially Structured Variances.</p> <p>Sequentially Unstructured Variances.</p> <p>Serial Correlation.</p> <p>Appendix 7.1: Details of the Lognormal Case in Example.</p> <p>Chapter 8. Nobel Difficulties.</p> <p>Introduction.</p> <p>Event Risk.</p> <p>Will Narrowing Spreads Guarantee Profits?</p> <p>Rise of a New Risk Factor.</p> <p>Redemption Tension.</p> <p>Supercharged Destruction.</p> <p>The Story of Regulation Fair Disclosure (FD).</p> <p>Correlation During Loss Episodes.</p> <p>Chapter 9. Trinity Troubles.</p> <p>Introduction.</p> <p>Decimalization.</p> <p>European Experience.</p> <p>Advocating the Devil.</p> <p>Stat. Arb. Arbed Away.</p> <p>Competition.</p> <p>Institutional Investors.</p> <p>Volatility Is the Key.</p> <p>Interest Rates and Volatility.</p> <p>Temporal Considerations.</p> <p>Truth in Fiction.</p> <p>A Litany of Bad Behavior.</p> <p>A Perspective on 2003.</p> <p>Realities of Structural Change.</p> <p>Recap.</p> <p>Chapter 10. Arise Black Boxes.</p> <p>Introduction.</p> <p>Modeling Expected Transaction Volume and Market Impact.</p> <p>Dynamic Updating.</p> <p>More Black Boxes.</p> <p>Market Deflation.</p> <p>Chapter 11. Statistical Arbitrage Rising.</p> <p>Catastrophe Process.</p> <p>Catastrophic Forecasts.</p> <p>Trend Change Identification.</p> <p>Using the Cuscore to Identify a Catastrophe.</p> <p>Is It Over?</p> <p>Catastrophe Theoretic Interpretation.</p> <p>Implications for Risk Management.</p> <p>Appendix 11.1: Understanding the Cuscore.</p> <p>Bibliography.</p> <p>Index.</p>

"Over time, anything that creates an edge for a particular group of bettors—including the most astute observers of horse flesh—gets factored into the odds and becomes unreliable as a system. That's the classic argument of random walk theorists, and the equally classic response is that there's a lot of money to be made before that factoring is complete. This book is a contribution to that never-ending debate." (Hedgeworld.com)

<p>Andrew Pole is a Managing Director at TIG Advisors, LLC, a registered investment advisor in New York. He specializes in quantitative trading strategies and risk management. This book is the result of his own research and experience running a statistical arbitrage hedge fund for eight years. Pole is also the coauthor of Applied Bayesian Forecasting and Time Series Analysis.</p>

<p>Praise for Statistical Arbitrage</p> <p>"In this lucid, intelligent, and highly readable book, Andrew Pole presents the insights of an experienced and successful exponent of statistical arbitrage, with an uncommon mixture of flair, accessibility, and academic precision. Anyone with an interest—professional or otherwise—in what goes on inside the black boxes of mathematical trading strategies will enjoy the book."<br /> —Nick Macleod, Head of Quantitative Research and Risk Management Ermitage Asset Management Jersey Limited</p> <p>"What a find! Andy Pole provides a remarkable look at the history and evolution of what is frequently considered to be the most opaque of the myriad hedge fund strategies. His detailed focus on and clever examples of the underlying drivers of stat arb are an invaluable resource for anyone investigating the strategy for the first time. Even we old-timers will learn something."<br /> —Judith Posnikoff, PhD, Managing Director Pacific Alternative Asset Management Company</p> <p>"Andy Pole delivers a readable and comprehensive history of statistical arbitrage. Using real-life examples and accounts from his decades of experience, this book chronicles the rise in popularity of stat arb, explains its recent struggle for profitability, as well as provides novices with insights into the art and science of building their own models."<br /> —Susan Kaderabek, Portfolio Manager, Franklin Street Partners</p> <p>"Statistical Arbitrage offers a rare glimpse of insights into the otherwise opaque world of short-term trading strategies. The book provides an excellent balance conceptualizing the mathematics of short-term technical trading strategies with more practical discussions on the recent performance of such strategies. Statistical arbitrage remains for many outsiders, including hedge fund professionals, a 'black box' strategy. Andy Pole has managed to turn black into, if not white, then a lighter shade of gray."<br /> —Christian Thygesen, Managing Director, Investcorp International Inc.</p> <p>"Andy Pole has extensive practical experience of statistical arbitrage trading together with an ability to explain the underlying theory with great clarity. This book is therefore highly recommended for those looking to master the subject matter."<br /> —Bruce Lockwood, Financial Risk Management</p>

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