Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models - Fabian Tinkl (Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW), 2013)
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.
Keywords: 330; asymptotic normality; consistency; polynomial augmented GARCH models; quasi-maximum likelihood estimation