Ten Things you should know about DCC

Massimiliano Caporin and Michael McAleer

No 13-048/III, Tinbergen Institute Discussion Papers from Tinbergen 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: DCC; BEKK; GARCC; Stated representation; Derived model; Conditional covariances; Conditional correlations; Regularity conditions; Moments; Two step estimators; Assumed properties; Asymptotic properties; Filter; Diagnostic check (search for similar items in EconPapers)
JEL-codes: C18 C32 C58 G17 (search for similar items in EconPapers)
Date: 2013-03-21
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
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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