文章基本信息

标题：Ten Things You Should Know about the Dynamic Conditional Correlation Representation
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作者：Caporin, Massimiliano ; McAleer, Michael
期刊名称：Econometrics
印刷版ISSN：2225-1146
出版年度：2013
卷号：1
期号：1
页码：115-126
出版社：MDPI, Open Access Journal
摘要：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.
关键词：DCC representation; BEKK; GARCC; stated representation; derived model; conditional correlations; two step estimators; assumed asymptotic properties; filter