An Extended Constant Conditional Correlation GARCH Model and Its Fourth-Moment Structure
AbstractThe constant conditional correlation GARCH model is probably the most frequently applied multivariate GARCH model. In this paper we consider an extension to this model and examine its fourth-moment structure. The extension, first considered by Jeantheau (1998), is motivated by the result found and discussed in the paper that the squared observations from the extended model have a rich autocorrelation structure. This means that already the first-order model is capable of reproducing a whole variety of autocorrelation structures observed in financial return series. These autocorrelations are derived for the first and the second-order constant conditional correlation GARCH model. The usefulness of the theoretical results of the paper is demonstrated by reconsidering an empirical example that appeared in the original paper on the constant conditional correlation GARCH model.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 509.
Length: 28 pages
Date of creation: 01 Sep 2002
Date of revision:
Publication status: Published in Econometric Theory, 2004, pages 904-926.
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More information through EDIRC
Autoregressive conditional heteroskedasticity; moment structure of GARCH; multivariate conditional heteroskedasticity; volatility dynamics;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-09-21 (All new papers)
- NEP-ECM-2002-09-21 (Econometrics)
- NEP-ETS-2002-09-21 (Econometric Time Series)
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