FIN-02-038

Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models

January 2002

Robert Engle

ABSTRACT
Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.

Robert F. Engle
Institution: Stern School of Business, New York University, 44 West 4th Street, New York, NY 10012
Telephone: (212) 998-0710
Fax: (212) 995-4220
Email: rengle@stern.nyu.edu
Homepage:http://www.stern.nyu.edu/~rengle

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