Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/71187
Title: 

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

Authors: 
Tinkl, Fabian
Year of Publication: 
2013
Series/Report no.: 
IWQW Discussion Paper Series 03/2013
Abstract: 
In this article consistency and asymptotic normality of the quasi-maximum likelihood esti- mator (QMLE) in the class of polynomial augmented generalized autoregressive conditional heteroscedasticity models (GARCH) is proven. The result extend the results of (Berkes et al., 2003) and (Francq and Zaköian, 2004) of the standard GARCH model to augmented GARCH models introduced by (Duan, 1997) which contains many commonly employed GARCH models as special cases. The conditions for consistency and asymptotic normality are more tractable than the ones discussed in (Straumann and Mikosch, 2006).
Subjects: 
asymptotic normality
consistency
polynomial augmented GARCH models
quasi-maximum likelihood estimation
Is replaced by the following version: 
Document Type: 
Working Paper

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