Caporin, MassimilianoMcAleer, Michael2023-06-192023-06-192013-03https://hdl.handle.net/20.500.14352/41466The 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.engAtribución-NoComercial 3.0 Españahttps://creativecommons.org/licenses/by-nc/3.0/es/technical reporthttps://www.ucm.es/icaeopen accessC18C32C58G17DCCBEKKGARCCStated representationDerived modelConditional covariancesConditional correlationsRegularity conditionsMomentsTwo step estimatorsAssumed propertiesAsymptotic propertiesFilterDiagnostic check.Econometría (Economía)5302 Econometría