Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87262
Authors: 
Caporin, Massimiliano
McAleer, Michael
Year of Publication: 
2013
Series/Report no.: 
Tinbergen Institute Discussion Paper 13-048/III
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.
Subjects: 
DCC
BEKK
GARCC
Stated representation
Derived model
Conditional covariances
Conditional correlations
Regularity conditions
Moments
Two step estimators
Assumed properties
Asymptotic properties
Filter
Diagnostic check
JEL: 
C18
C32
C58
G17
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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