Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

Christian Francq, Guillaume Lepage and Jean-Michel Zakoian

Journal of Econometrics, 2011, vol. 165, issue 2, 246-257

Abstract: In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that the variance of the iid process is equal to 1 can be replaced by an alternative moment assumption. We show that, for estimating the original specification based on the standard identifiability assumption, efficiency gains can be expected from using a quasi-maximum likelihood (QML) estimator based on a non Gaussian density and a reparameterization based on an alternative identifiability assumption. A test allowing to determine whether a reparameterization is needed, that is, whether the more efficient QMLE is obtained with a non Gaussian density, is proposed.

Keywords: Conditional heteroskedasticity; Efficiency of estimators; Quasi maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:165:y:2011:i:2:p:246-257

DOI: 10.1016/j.jeconom.2011.08.001

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