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Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH Author info | Abstract | Publisher info | Download info | Related research | Statistics Robert F. Engle
Kevin Sheppard
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In this paper, we develop the theoretical and empirical properties of a new class of multivariate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need be modified. We use the model to estimate the conditional covariance of up to 100 assets using S&P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator.
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Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number
2001-15.
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Date of creation: Sep 2001Date of revision:
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988.
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[Downloadable!]
Other versions:
Robert Engle & Simone Manganelli, 2000.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles ,"
Econometric Society World Congress 2000 Contributed Papers
0841, Econometric Society.
[Downloadable!] Robert F. Engle & Simone Manganelli, 1999.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles ,"
University of California at San Diego, Economics Working Paper Series
99-20, Department of Economics, UC San Diego.
[Downloadable!] Robert F. Engle & Simone Manganelli, 2004.
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repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
Demos, Antonis & Sentana, Enrique, 1998.
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Tse, Y. K., 2000.
"A test for constant correlations in a multivariate GARCH model ,"
Journal of Econometrics ,
Elsevier, vol. 98(1), pages 107-127, September.
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Harvey, Andrew & Ruiz, Esther & Shephard, Neil, 1994.
"Multivariate Stochastic Variance Models ,"
Review of Economic Studies ,
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