Arbeitspapier
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: IWQW Discussion Papers ; No. 03/2013
- Klassifikation
-
Wirtschaft
- Thema
-
asymptotic normality
consistency
polynomial augmented GARCH models
quasi-maximum likelihood estimation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Tinkl, Fabian
- Ereignis
-
Veröffentlichung
- (wer)
-
Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
- (wo)
-
Nürnberg
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Tinkl, Fabian
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
Entstanden
- 2013
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