Statistical Arbitrage / Wiley Finance Editions (ePub)

Preface. Foreword. Acknowledgments. Chapter 1. Monte Carlo or Bust. Beginning. Whither? And Allusions. Chapter 2. Statistical Arbitrage. Introduction. Noise Models. Reverse Bets. Multiple Bets. Rule Calibration. Spread Margins for Trade Rules. Popcorn Process. Identifying Pairs. Refining Pair Selection. Event Analysis. Correlation Search in the Twenty-First Century. Portfolio Configuration and Risk Control. Exposure to Market Factors. Market Impact. Risk Control Using Event Correlations. Dynamics and Calibration. Evolutionary Operation: Single Parameter Illustration. Chapter 3. Structural Models. Introduction. Formal Forecast Functions. Exponentially Weighted Moving Average. Classical Time Series Models. Autoregression and Cointegration. Dynamic Linear Model. Volatility Modeling. Pattern Finding Techniques. Fractal Analysis. Which Return? A Factor Model. Factor Analysis. Defactored Returns. Prediction Model. Stochastic Resonance. Practical Matters. Doubling: A Deeper Perspective. Factor Analysis Primer. Prediction Model for Defactored Returns. Chapter 4. Law of Reversion. Introduction. Model and Result. The 75 percent Rule. Proof of the 75 percent Rule. Analytic Proof of the 75 percent Rule. Discrete Counter. Generalizations. Inhomogeneous Variances. Volatility Bursts. Numerical Illustration. First-Order Serial Correlation. Analytic Proof. Examples. Nonconstant Distributions. Applicability of the Result. Application to U.S. Bond Futures. Summary. Appendix 4.1: Looking Several Days Ahead. Chapter 5. Gauss is Not the God of Reversion. Introduction. Camels and Dromedaries. Dry River Flow. Some Bells Clang. Chapter 6. Interstock Volatility. Introduction. Theoretical Explanation. Theory versus Practice. Finish the Theory. Finish the Examples. Primer on Measuring Spread Volatility. Chapter 7. Quantifying Reversion Opportunities. Introduction. Reversion in a Stationary Random Process. Frequency of Reversionary Moves. Amount of Reversion. Movements from Quantiles Other Than

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.

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