Statistical Arbitrage Algorithmic Trading Insights and Techniques

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ISBN: 9780470138441 | 0470138440
Cover: Hardcover
Copyright: 10/5/2007

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While statistical arbitrage has faced some tough timesas markets experienced dramatic changes in dynamics beginning in 2000new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Poles own research and experience running a statistical arbitrage hedge fund for eight yearsin partnership with a group whose own history stretches back to the dawn of what was first called pairs tradingthis unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.

Preface	p. xiii
Foreword	p. xix
Acknowledgments	p. xxiii
Monte Carlo or Bust	p. 1
Beginning	p. 1
Whither? And Allusions	p. 4
Statistical Arbitrage	p. 9
Introduction	p. 9
Noise Models	p. 10
Reverse Bets	p. 11
Multiple Bets	p. 11
Rule Calibration	p. 12
Spread Margins for Trade Rules	p. 16
Popcorn Process	p. 18
Identifying Pairs	p. 20
Refining Pair Selection	p. 21
Event Analysis	p. 22
Correlation Search in the Twenty-First Century	p. 26
Portfolio Configuration and Risk Control	p. 26
Exposure to Market Factors	p. 29
Market Impact	p. 30
Risk Control Using Event Correlations	p. 31
Dynamics and Calibration	p. 32
Evolutionary Operation: Single Parameter Illustration	p. 34
Structural Models	p. 37
Introduction	p. 37
Formal Forecast Functions	p. 39
Exponentially Weighted Moving Average	p. 40
Classical Time Series Models	p. 47
Autoregression and Cointegration	p. 47
Dynamic Linear Model	p. 49
Volatility Modeling	p. 50
Pattern Finding Techniques	p. 51
Fractal Analysis	p. 52
Which Return?	p. 52
A Factor Model	p. 53
Factor Analysis	p. 54
Defactored Returns	p. 55
Prediction Model	p. 57
Stochastic Resonance	p. 58
Practical Matters	p. 59
Doubling: A Deeper Perspective	p. 61
Factor Analysis Primer	p. 63
Prediction Model for Defactored Returns	p. 65
Law of Reversion	p. 67
Introduction	p. 67
Model and Result	p. 68
The 75 percent Rule	p. 68
Proof of the 75 percent Rule	p. 69
Analytic Proof of the 75 percent Rule	p. 71
Discrete Counter	p. 73
Generalizations	p. 73
Inhomogeneous Variances	p. 74
Volatility Bursts	p. 75
Numerical Illustration	p. 76
First-Order Serial Correlation	p. 77
Analytic Proof	p. 79
Examples	p. 82
Nonconstant Distributions	p. 82
Applicability of the Result	p. 84
Application to U.S. Bond Futures	p. 85
Summary	p. 87
Looking Several Days Ahead	p. 87
Gauss Is Not the God of Reversion	p. 91
Introduction	p. 91
Camels and Dromedaries	p. 92
Dry River Flow	p. 95
Some Bells Clang	p. 98
Interstock Volatility	p. 99
Introduction	p. 99
Theoretical Explanation	p. 103
Theory versus Practice	p. 105
Finish the Theory	p. 105
Finish the Examples	p. 106
Primer on Measuring Spread Volatility	p. 108
Quantifying Reversion Opportunities	p. 113
Introduction	p. 113
Reversion in a Stationary Random Process	p. 114
Frequency of Reversionary Moves	p. 117
Amount of Reversion	p. 118
Movements from Quantiles Other Than the Median	p. 135
Nonstationary Processes: Inhomogeneous Variance	p. 136
Sequentially Structured Variances	p. 136
Sequentially Unstructured Variances	p. 137
Serial Correlation	p. 138
Details of the Lognormal Case in Example 6	p. 139
Nobel Difficulties	p. 141
Introduction	p. 141
Event Risk	p. 142
Will Narrowing Spreads Guarantee Profits?	p. 144
Rise of a New Risk Factor	p. 145
Redemption Tension	p. 148
Supercharged Destruction	p. 150
The Story of Regulation Fair Disclosure (FD)	p. 150
Correlation During Loss Episodes	p. 151
Trinity Troubles	p. 155
Introduction	p. 155
Decimalization	p. 156
European Experience	p. 157
Advocating the Devil	p. 158
Stat. Arb. Arbed Away	p. 159
Competition	p. 160
Institutional Investors	p. 163
Volatility Is the Key	p. 163
Interest Rates and Volatility	p. 165
Temporal Considerations	p. 166
Truth in Fiction	p. 174
A Litany of Bad Behavior	p. 174
A Perspective on 2003	p. 178
Realities of Structural Change	p. 179
Recap	p. 180
Arise Black Boxes	p. 183
Introduction	p. 183
Modeling Expected Transaction Volume and Market Impact	p. 185
Dynamic Updating	p. 188
More Black Boxes	p. 189
Market Deflation	p. 189
Statistical Arbitrage Rising	p. 191
Catastrophe Process	p. 194
Catastrophic Forecasts	p. 198
Trend Change Identification	p. 200
Using the Cuscore to Identify a Catastrophe	p. 202
Is It Over?	p. 204
Catastrophe Theoretic Interpretation	p. 205
Implications for Risk Management	p. 209
Sign Off	p. 211
Understanding the Cuscore	p. 211
Bibliography	p. 223
Index	p. 225
Table of Contents provided by Ingram. All Rights Reserved.

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Statistical Arbitrage Algorithmic Trading Insights and Techniques

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