ダウンロード数: 71
タイトル: | Ten Things You Should Know About DCC |
著者: | Caporin, Massimiliano McAleer, Michael |
キーワード: | DCC BEKK GARCC Stated representation Derived model Conditional covariances Conditional correlations Regularity conditions Moments Two step estimators Assumed properties Asymptotic properties Filter Diagnostic check |
発行日: | Mar-2013 |
出版者: | Institute of Economic Research, Kyoto University |
誌名: | KIER Discussion Paper |
巻: | 854 |
抄録: | 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. |
URI: | http://hdl.handle.net/2433/172696 |
出現コレクション: | KIER Discussion Paper (英文版) |
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