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Econometrics 2013, 1(1), 115-126; doi:10.3390/econometrics1010115

Ten Things You Should Know about the Dynamic Conditional Correlation Representation

1
Department of Economics and Management "Marco Fanno", University of Padova, Via del Santo 33, 35123 Padova, Italy
2
Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, 3000 DR Rotterdam, Netherlands
3
Department of Quantitative Economics, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain
4
Institute of Economic Research, Kyoto University, Kyoto 606-8501, Japan
*
Author to whom correspondence should be addressed.
Received: 13 May 2013 / Revised: 7 June 2013 / Accepted: 14 June 2013 / Published: 21 June 2013
View Full-Text   |   Download PDF [1106 KB, 24 June 2013; original version 21 June 2013]

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 Generalized Autoregressive Conditional Correlation (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 Baba, Engle, Kraft and Kroner (BEKK) in small systems; and DCC may be a useful filter or a diagnostic check, but it is not a model. View Full-Text
Keywords: DCC representation; BEKK; GARCC; stated representation; derived model; conditional correlations; two step estimators; assumed asymptotic properties; filter DCC representation; BEKK; GARCC; stated representation; derived model; conditional correlations; two step estimators; assumed asymptotic properties; filter
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Caporin, M.; McAleer, M. Ten Things You Should Know about the Dynamic Conditional Correlation Representation. Econometrics 2013, 1, 115-126.

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