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Ten Things You Should Know About DCC



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Caporin, Massimiliano and McAleer, Michael (2013) Ten Things You Should Know About DCC. [ Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE); nº 12, 2013, ] (Unpublished)

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Official URL: http://eprints.ucm.es/20494/



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.

Item Type:Working Paper or Technical Report
Uncontrolled Keywords:DCC, BEKK, GARCC, Stated representation, Derived model, Conditional covariances, Conditional correlations, Regularity conditions, Moments, Two step estimators, Assumed properties, Asymptotic properties, Filter, Diagnostic check.
Subjects:Social sciences > Economics > Econometrics
JEL:C18, C32, C58, G17
Series Name:Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
ID Code:20494
Deposited On:19 Mar 2013 12:52
Last Modified:23 Feb 2016 10:10

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