Asymmetric multivariate normal mixture GARCH

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
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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Metadaten
Author:Markus Haas, Stefan Mittnik, Marc S. Paolella
URN:urn:nbn:de:hebis:30-53240
Parent Title (German):Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2008,07
Series (Serial Number):CFS working paper series (2008, 07)
Document Type:Working Paper
Language:English
Year of Completion:2008
Year of first Publication:2008
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2008/03/03
Tag:Conditional Volatility; Finite Normal Mixtures; Leverage Effect; Multivariate GARCH
SWD-Keyword:GARCH-Prozess
Issue:January 18, 2008
Pagenumber:44
HeBIS PPN:195435443
Institutes:Center for Financial Studies (CFS)
Dewey Decimal Classification:330 Wirtschaft
JEL-Classification:C32 Time-Series Models; Dynamic Quantile Regressions (Updated!)
C51 Model Construction and Estimation
G10 General
G11 Portfolio Choice; Investment Decisions
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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