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Ten Things You Should Know About DCC

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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.

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Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico in its series Documentos de Trabajo del ICAE with number 2013-12.

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Length: 18 pages
Date of creation: Mar 2013
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Handle: RePEc:ucm:doicae:1312

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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.;

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References

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  1. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.
  2. Hammoudeh, Shawkat & Liu, Tengdong & Chang, Chia-Lin & McAleer, Michael, 2013. "Risk spillovers in oil-related CDS, stock and credit markets," Energy Economics, Elsevier, Elsevier, vol. 36(C), pages 526-535.
  3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  4. Massimiliano Caporin & Michael McAleer, 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," CIRJE F-Series, CIRJE, Faculty of Economics, University of Tokyo CIRJE-F-713, CIRJE, Faculty of Economics, University of Tokyo.
  5. Matteo Manera & Alessandro Lanza & Michael McAleer, 2004. "Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns," Working Papers, Fondazione Eni Enrico Mattei 2004.72, Fondazione Eni Enrico Mattei.
  6. McAleer, Michael & Chan, Felix & Hoti, Suhejla & Lieberman, Offer, 2008. "Generalized Autoregressive Conditional Correlation," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 24(06), pages 1554-1583, December.
  7. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, . "Multivariate GARCH models: a survey," CORE Discussion Papers RP -1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, Econometric Society, vol. 50(4), pages 987-1007, July.
  9. Sheppard, Kevin & Cappiello, Lorenzo & Engle, Robert F., 2003. "Asymmetric dynamics in the correlations of global equity and bond returns," Working Paper Series, European Central Bank 0204, European Central Bank.
  10. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
  11. Tansuchat, R. & Chang, C-L. & McAleer, M.J., 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Econometric Institute Research Papers EI 2010-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  12. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 28(6), pages 612-631.
  13. Monica Billio & Massimiliano Caporin & Michele Gobbo, 2006. "Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation," Applied Financial Economics Letters, Taylor and Francis Journals, Taylor and Francis Journals, vol. 2(2), pages 123-130, March.
  14. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, Elsevier, vol. 164(1), pages 45-59, September.
  15. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(3), pages 339-50, July.
  16. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
  17. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 21(01), pages 232-261, February.
  18. Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Multivariate GARCH models," CREATES Research Papers 2008-06, School of Economics and Management, University of Aarhus.
  19. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 11(01), pages 122-150, February.
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Cited by:
  1. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  2. Carlos Castro & Nini Johana Marin, 2014. "Stock return comovements and integration within the Latin American integrated market," BORRADORES DE INVESTIGACIÓN 011041, UNIVERSIDAD DEL ROSARIO.
  3. Carlos Castro & Nini Johana Marin, 2014. "Stock return comovements and integration within the Latin American integrated market," DOCUMENTOS DE TRABAJO 011082, UNIVERSIDAD DEL ROSARIO.

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