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Ten Things You Should Know About the Dynamic Conditional Correlation Representation

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dc.contributor.authorCaporin, Massimiliano
dc.contributor.authorMcAleer, Michael
dc.date.accessioned2023-06-19T23:53:11Z
dc.date.available2023-06-19T23:53:11Z
dc.date.issued2013-06
dc.descriptionRevised: June 2013 The authors most are grateful to two referees for very helpful comments and suggestions. For financial support, the second author wishes to acknowledge the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science. An earlier version of this paper was distributed as “Ten Things You Should Know About DCC”.
dc.description.abstractThe 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.
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.facultyInstituto Complutense de Análisis Económico (ICAE)
dc.description.refereedFALSE
dc.description.statusunpub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/22109
dc.identifier.relatedurlhttps://www.ucm.es/icae
dc.identifier.urihttps://hdl.handle.net/20.500.14352/41489
dc.issue.number21
dc.language.isoeng
dc.page.total20
dc.relation.ispartofseriesDocumentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
dc.rightsAtribución-NoComercial 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/es/
dc.subject.jelC18
dc.subject.jelC32
dc.subject.jelC58
dc.subject.jelG17
dc.subject.keywordDCC representation
dc.subject.keywordBEKK
dc.subject.keywordGARCC
dc.subject.keywordStated representation
dc.subject.keywordDerived model
dc.subject.keywordConditional covariances
dc.subject.keywordConditional correlations
dc.subject.keywordregularity conditions
dc.subject.keywordmoments
dc.subject.keywordtwo step estimators
dc.subject.keywordAssumed properties
dc.subject.keywordAsymptotic properties
dc.subject.keywordfilter
dc.subject.keywordDiagnostic check.
dc.subject.ucmEconometría (Economía)
dc.subject.unesco5302 Econometría
dc.titleTen Things You Should Know About the Dynamic Conditional Correlation Representation
dc.typetechnical report
dc.volume.number2013
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