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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.

Correlation (Statistics). --- Economic forecasting --Mathematical models. --- Finance --Econometrics models. --- Risk management --Mathematical models. --- Finance --- Risk management --- Economic forecasting --- Correlation (Statistics) --- Business & Economics --- Finance - General --- Investment & Speculation --- Econometric models --- Mathematical models --- Econometric models. --- Mathematical models. --- Funding --- Funds --- Economics --- Currency question --- Least squares --- Mathematical statistics --- Probabilities --- Regression analysis --- Statistics --- Instrumental variables (Statistics) --- Econometrics models. --- Graphic methods

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Mathematical statistics --- Quantitative methods (economics) --- Econometric models --- Economics --- Time-series analysis --- Modèles économétriques --- Economie politique --- Série chronologique --- Statistical methods --- Méthodes statistiques --- Econometric models. --- Time-series analysis. --- Cointegration. --- Statistical methods. --- 330.115 --- Econometrics models --- -Time-series analysis --- Cointegration --- 330.015195 --- Econometrics --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities --- Economic theory --- Political economy --- Social sciences --- Economic man --- Econometrie --- 330.115 Econometrie --- Modèles économétriques --- Série chronologique --- Méthodes statistiques --- Economic statistics --- Mathematical models --- Economics - Statistical methods.

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

International financial management --- Finance --- Risk management --- Economic forecasting --- Correlation (Statistics) --- Econometrics models --- Mathematical models --- AA / International- internationaal --- 305.970 --- 303.5 --- -336.76 --- -Risk management --- -Correlation (Statistics) --- 332.015195 --- Least squares --- Mathematical statistics --- Probabilities --- Regression analysis --- Statistics --- Instrumental variables (Statistics) --- Insurance --- Management --- Economics --- Forecasting --- Economic indicators --- Funding --- Funds --- Currency question --- Algemeenheden: Autoregression and moving average representation. ARIMA. ARMAX. Lagrange multiplier. Wald. Function (mis) specification. Autocorrelation. Homoscedasticity. Heteroscedasticity. ARCH. GARCH. Integration and co-integration. Unit roots. --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek). --- Econometric models --- Geldmarkt. Kapitaalmarkt --- Graphic methods --- 336.76 --- Theorie van correlatie en regressie. (OLS, adjusted LS, weighted LS, restricted LS, GLS, SLS, LIML, FIML, maximum likelihood). Parametric and non-parametric methods and theory (wiskundige statistiek) --- Algemeenheden: Autoregression and moving average representation. ARIMA. ARMAX. Lagrange multiplier. Wald. Function (mis) specification. Autocorrelation. Homoscedasticity. Heteroscedasticity. ARCH. GARCH. Integration and co-integration. Unit roots --- Finance - Econometrics models --- Risk management - Mathematical models --- Economic forecasting - Mathematical models --- Econometric models. --- Mathematical models.