Asymmetric multivariate normal mixture GARCH

Markus Haas (), Stefan Mittnik and Marc S. Paolella

Computational Statistics & Data Analysis, 2009, vol. 53, issue 6, pages 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.

Date: 2009

Downloads: (external link)
http://www.sciencedirect.com/science/article/B6V8V ... bc235cb4d31014c4030f
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:eee:csdana:v:53:y:2009:i:6:p:2129-2154

Access Statistics for this article

Computational Statistics & Data Analysis is edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Series data maintained by Heidi Boesdal ().