Anticipating correlations : a new paradigm for risk management

著者

書誌事項

Anticipating correlations : a new paradigm for risk management

Robert Engle

Princeton University Press, c2009

  • : hbk

大学図書館所蔵 件 / 全25件

この図書・雑誌をさがす

注記

"The Econometric Institute lectures"--Jacket

Includes bibliographical references (p. [141]-149) and index

内容説明・目次

内容説明

Financial markets respond to information virtually instantaneously. Each new piece of information influences the prices of assets and their correlations with each other, and as the system rapidly changes, so too do correlation forecasts. This fast-evolving environment presents econometricians with the challenge of forecasting dynamic correlations, which are essential inputs to risk measurement, portfolio allocation, derivative pricing, and many other critical financial activities. In Anticipating Correlations, Nobel Prize-winning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included. Based on the Econometric and Tinbergen Institutes Lectures, Anticipating Correlations puts powerful new forecasting tools into the hands of researchers, financial analysts, risk managers, derivative quants, and graduate students.

目次

Introduction vii Chapter 1: Correlation Economics 1 1.1 Introduction 1 1.2 How Big Are Correlations? 3 1.3 The Economics of Correlations 6 1.4 An Economic Model of Correlations 9 1.5 Additional Influences on Correlations 13 Chapter 2: Correlations in Theory 15 2.1 Conditional Correlations 15 2.2 Copulas 17 2.3 Dependence Measures 21 2.4 On the Value of Accurate Correlations 25 Chapter 3: Models for Correlation 29 3.1 The Moving Average and the Exponential Smoother 30 3.2 Vector GARCH 32 3.3 Matrix Formulations and Results for Vector GARCH 33 3.4 Constant Conditional Correlation 37 3.5 Orthogonal GARCH 37 3.6 Dynamic Conditional Correlation 39 3.7 Alternative Approaches and Expanded Data Sets 41 Chapter 4: Dynamic Conditional Correlation 43 4.1 DE-GARCHING 43 4.2 Estimating the Quasi-Correlations 45 4.3 Rescaling in DCC 48 4.4 Estimation of the DCC Model 55 Chapter 5: DCC Performance 59 5.1 Monte Carlo Performance of DCC 59 5.2 Empirical Performance 61 Chapter 6: The MacGyver Method 74 Chapter 7: Generalized DCC Models 80 7.1 Theoretical Specification 80 7.2 Estimating Correlations for Global Stock and Bond Returns 83 Chapter 8: FACTOR DCC 88 8.1 Formulation of Factor Versions of DCC 88 8.2 Estimation of Factor Models 93 Chapter 9: Anticipating Correlations 103 9.1 Forecasting 103 9.2 Long-Run Forecasting 108 9.3 Hedging Performance In-Sample 111 9.4 Out-of-Sample Hedging 112 9.5 Forecasting Risk in the Summer of 2007 117 Chapter 10: Credit Risk and Correlations 122 Chapter 11: Econometric Analysis of the DCC Model 130 11.1 Variance Targeting 130 11.2 Correlation Targeting 131 11.3 Asymptotic Distribution of DCC 134 Chapter 12: Conclusions 137 References 141 Index 151

「Nielsen BookData」 より

詳細情報

ページトップへ