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
Institutions:	Wirtschafts- und Sozialwissenschaftliche Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg
Subject:	asymptotic normality \| consistency \| polynomial augmented GARCH models \| quasi-maximum likelihood estimation

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Extent:	application/pdf
Series:	IWQW Discussion Paper Series. - ISSN 1867-6707.
Type of publication:	Book / Working Paper
Notes:	Number 03/2013
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010954427