Dynamic Conditional Correlation - a Simple Class of Multivariate GARCH Models
UCSD Economics Discussion Paper No. 2000-09
28 Pages Posted: 1 Dec 2000
Date Written: May 2000
Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of returns. 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 give sensible empirical results.
Keywords: ARCH, GARCH, Correlation, Time Series, Value at Risk
JEL Classification: C1
Suggested Citation: Suggested Citation