Estimating GARCH volatility in the presence of outliers

GARCH volatilities depend on the unconditional variance, which is a non-linear function of the parameters. Consequently, they can have larger biases than estimated parameters. Using robust methods to estimate both parameters and volatilities is shown to outperform Maximum Likelihood procedures. ► Th...

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Bibliographic Details
Published in:Economics letters 2012, Vol.114 (1), p.86-90
Main Authors: Carnero, M. Angeles, Peña, Daniel, Ruiz, Esther
Format: Article
Language:English
Subjects:
Capital market
Estimation bias
Financial markets
GARCH models
Heteroscedasticity
Maximum likelihood method
Parameter estimation
QML estimator
Robustness
Stochastic models
Studies
Volatility
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Summary:GARCH volatilities depend on the unconditional variance, which is a non-linear function of the parameters. Consequently, they can have larger biases than estimated parameters. Using robust methods to estimate both parameters and volatilities is shown to outperform Maximum Likelihood procedures. ► This research analyses the effects of outliers on estimated GARCH volatilities. ► Volatilities can be overestimated even when only one large outlier is present. ► Overestimation affects not only the instant when the outlier appears but all periods. ► Robust methods reduce the biases associated with estimated volatilities.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2011.09.023