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Asymmetric multivariate normal mixture GARCH


Haas, Markus; Mittnik, Stefan; Paolella, Marc S (2009). Asymmetric multivariate normal mixture GARCH. Computational Statistics and Data Analysis, 53(6):2129-2154.

Abstract

An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic correlation structure of the process are provided. In an application to stock market returns, it is shown that the disaggregation of the conditional (co)variance process generated by the model provides substantial intuition. Moreover, the model exhibits a strong performance in calculating out–of–sample Value–at–Risk measures.

An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic correlation structure of the process are provided. In an application to stock market returns, it is shown that the disaggregation of the conditional (co)variance process generated by the model provides substantial intuition. Moreover, the model exhibits a strong performance in calculating out–of–sample Value–at–Risk measures.

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17 citations in Web of Science®
20 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Language:English
Date:9 January 2009
Deposited On:14 Nov 2008 11:38
Last Modified:05 Apr 2016 12:30
Publisher:Elsevier
ISSN:0167-9473
Publisher DOI:10.1016/j.csda.2007.12.018
Permanent URL: http://doi.org/10.5167/uzh-4386

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