Transcription of DYNAMIC CONDITIONAL CORRELATION – A SIMPLE CLASS …
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DYNAMIC CONDITIONAL CORRELATION – A SIMPLE CLASS …
1 DYNAMIC CONDITIONAL CORRELATION A SIMPLE CLASS OF MULTIVARIATE GARCH MODELS Robert Engle1 July 1999 Revised Jan 2002 Forthcoming Journal of Business and Economic Statistics 2002 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.
An analysis of the performance of Dynamic Conditional Correlation methods for large covariance matrices is considered in Engle and Sheppard(2001). The next section of the paper will give a brief overview of various models for estimating correlations. Section 3 will introduce the new method and compare it with some of the other cited approaches.
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