Statistical Arbitrage Algorithmic Trading Insights and Techniques
by Pole, AndrewEdition: 1st
Format: Hardcover
Pub. Date: 2007-10-05
Publisher(s): Wiley
Other versions by this Author
-
This Item Qualifies for Free Shipping!*
*Excludes marketplace orders.
List Price: $120.75
Buy New
Arriving Soon. Will ship when available.
$115.00
Rent Book
Select for Price
Used Book
We're Sorry
Sold Out
eBook
We're Sorry
Not Available
How Marketplace Works:
- This item is offered by an independent seller and not shipped from our warehouse
- Item details like edition and cover design may differ from our description; see seller's comments before ordering.
- Sellers much confirm and ship within two business days; otherwise, the order will be cancelled and refunded.
- Marketplace purchases cannot be returned to eCampus.com. Contact the seller directly for inquiries; if no response within two days, contact customer service.
- Additional shipping costs apply to Marketplace purchases. Review shipping costs at checkout.
Summary
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.
Author Biography
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.
Table of Contents
| 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. |
An electronic version of this book is available through VitalSource.
This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.
By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.
Digital License
You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.
More details can be found here.
A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.
Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.
Please view the compatibility matrix prior to purchase.