Feasible generalized least squares estimation of multivariate GARCH(1, 1) models

We provide a feasible generalized least squares estimator for (unrestricted) multivariate GARCH(1, 1) models. We show that the estimator is consistent and asymptotically normally distributed under mild assumptions. Unlike the (quasi) maximum likelihood method, the feasible GLS is considerably fast to implement and does not require any complex optimization routine.

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Year of publication:	2014
Authors:	Poloni, Federico ; Sbrana, Giacomo
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 129.2014, C, p. 151-159
Publisher:	Elsevier
Subject:	Multivariate GARCH(1 \| 1) models \| Feasible generalized least squares estimation \| Maximum likelihood estimation

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010786420