Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models

In this article, consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) in the class of polynomial augmented generalized autoregressive conditional heteroscedasticity models (GARCH) is proven. The result extends the results of the standard GARCH model to the class of polynomial augmented GARCH models which contains many commonly employed GARCH models as special cases. The results are obtained under mild conditions.

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Year of publication:	2013
Authors:	Tinkl, Fabian
Publisher:	Nürnberg : Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
Subject:	asymptotic normality \| consistency \| polynomial augmented GARCH models \| quasi-maximum likelihood estimation

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Series:	IWQW Discussion Papers ; 03/2013
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	745263119 [GVK] hdl:10419/73143 [Handle] RePEc:zbw:iwqwdp:032013 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010312004