Ten Things You Should Know About the Dynamic Conditional Correlation Representation
dc.contributor.author | Caporin, M. | |
dc.contributor.author | McAleer, M. | |
dc.date.accessioned | 2015-10-19T01:14:16Z | |
dc.date.available | 2015-10-19T01:14:16Z | |
dc.date.issued | 2013 | en |
dc.description.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 fore-casting 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 stand-ardized 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 prop-erties; 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. | en |
dc.identifier.citation | Caporin, M., McAleer, M. (2013) Ten Things You Should Know About the Dynamic Conditional Correlation Representation. Department of Economics and Finance College of Business and Economics University of Canterbury.. | en |
dc.identifier.uri | http://hdl.handle.net/10092/11245 | |
dc.language.iso | en | |
dc.publisher | University of Canterbury. Department of Economics and Finance | en |
dc.rights.uri | https://hdl.handle.net/10092/17651 | en |
dc.subject | DCC representation | en |
dc.subject | BEKK | en |
dc.subject | GARCC | en |
dc.subject | stated representation | en |
dc.subject | derived model | en |
dc.subject | condi-tional covariances | en |
dc.subject | conditional correlations | en |
dc.subject | regularity conditions | en |
dc.subject | moments | en |
dc.subject | two step estimators | en |
dc.subject | assumed properties | en |
dc.subject | asymptotic properties | en |
dc.subject | filter | en |
dc.subject | diagnostic check | en |
dc.subject.anzsrc | Field of Research::14 - Economics | en |
dc.title | Ten Things You Should Know About the Dynamic Conditional Correlation Representation | en |
dc.type | Discussion / Working Papers |
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