The impacts of outliers on different estimators for GARCH processes: an empirical study

The Maximum likelihood estimation (MLE) is the most widely used method to estimate the parameters of a GARCH(p,q) process. This is owed to the fact that the MLE, among other properties, is asymptotically efficient. Even though the MLE is sensitive to outliers, which can occur in time series. In order to abate the influence of outliers, robust estimators are introduced. Afterwards an Monte Carlo study compares the introduced estimators.

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Year of publication:	2009
Authors:	Ardelean, Vlad
Publisher:	Nürnberg : Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
Subject:	ARCH-Modell \| Maximum-Likelihood-Methode \| Robustes Verfahren \| Theorie \| GARCH \| Robust-Estimates \| M-Estimates

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Series:	IWQW Discussion Papers ; 06/2009
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	612504670 [GVK] hdl:10419/29561 [Handle] RePEc:zbw:iwqwdp:062009 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010299759