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

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  • Tinkl, Fabian

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.

Suggested Citation

  • Tinkl, Fabian, 2013. "Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models," FAU Discussion Papers in Economics 03/2013, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  • Handle: RePEc:zbw:iwqwdp:032013
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    Cited by:

    1. Leucht, Anne & Neumann, Michael H. & Kreiss, Jens-Peter, 2013. "A model specification test for GARCH(1,1) processes," Working Papers 13-11, University of Mannheim, Department of Economics.

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    Keywords

    asymptotic normality; consistency; polynomial augmented GARCH models; quasi-maximum likelihood estimation;

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