The impacts of outliers on different estimators for GARCH processes: an empirical study
AbstractThe 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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Bibliographic InfoPaper provided by Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW) in its series IWQW Discussion Paper Series with number 06/2009.
Date of creation: 2009
Date of revision:
GARCH; Robust-Estimates; M-Estimates;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-01-23 (All new papers)
- NEP-ECM-2010-01-23 (Econometrics)
- NEP-ETS-2010-01-23 (Econometric Time Series)
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