Template-Type: ReDIF-Paper 1.0
Author-Name: Caporin, M.
Author-Name-Last: Caporin
Author-Name-First: Massimiliano
Author-Person: pca441
Author-Name: McAleer, M.J.
Author-Name-Last: McAleer
Author-Name-First: Michael
Author-Person: pmc90
Title: Ten Things You Should Know About the Dynamic Conditional Correlation Representation
Abstract: The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for caution about the use of DCC include the following: DCC represents the dynamic conditional covariances of the standardized residuals, and hence does not yield dynamic conditional correlations; DCC is stated rather than derived; DCC has no moments; DCC does not have testable regularity conditions; DCC yields inconsistent two step estimators; DCC has no asymptotic properties; DCC is not a special case of GARCC, which has testable regularity conditions and standard asymptotic properties; DCC is not dynamic empirically as the effect of news is typically extremely small; DCC cannot be distinguished empirically from diagonal BEKK in small systems; and DCC may be a useful filter or a diagnostic check, but it is not a model.
Creation-Date: 2013-06-18
File-URL: https://repub.eur.nl/pub/40377/EI2013-21.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2013-21
Classification-JEL: C19, C32, C59, G17
Keywords: BEKK, DCC representation, GARCC, assumed properties, asymptotic properties, conditional correlations, conditional covariances, derived model, diagnostic check, filter, financial econometrics, moments, regularity conditions, stated representation, two step estimators
Handle: RePEc:ems:eureir:40377