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Asymmetric multivariate normal mixture GARCH

Listed author(s):
  • Haas, Markus
  • Mittnik, Stefan
  • Paolella, Marc S.

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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File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(07)00486-0
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Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 53 (2009)
Issue (Month): 6 (April)
Pages: 2129-2154

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Handle: RePEc:eee:csdana:v:53:y:2009:i:6:p:2129-2154
Contact details of provider: Web page: http://www.elsevier.com/locate/csda

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