Ten Things You Should Know About DCC

Massimiliano Caporin and Michael McAleer

No EI 2013-13, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

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.

Keywords: BEKK; DCC; GARCC; assumed properties; asymptotic properties; conditional correlations; conditional covariances; derived model; diagnostic check; filter; moments; regularity conditions; stated representation; two step estimators (search for similar items in EconPapers)
Date: 2013-03-01
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Citations: View citations in EconPapers (66)

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Working Paper: Ten Things You Should Know About DCC (2013)
Working Paper: Ten Things You Should Know About DCC (2013)
Working Paper: Ten Things you should know about DCC (2013)
Working Paper: Ten Things You Should Know About DCC (2013)
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