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

Fabian Tinkl

No 03/2013, FAU Discussion Papers in Economics from Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics

Abstract: 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: asymptotic normality; consistency; polynomial augmented GARCH models; quasi-maximum likelihood estimation (search for similar items in EconPapers)
Date: 2013, Revised 2013
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:iwqwdp:032013

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