Extreme observations and non-normality in ARCH and GARCH |
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| Affiliation: | 1. Department of Applied Economics, Universitat de les Illes Balears, Ctra. Valldemossa, km 7.5, 07122 Palma de Mallorca, Spain;2. Montpellier Business School, 2300 Avenue des Moulins, 34080 Montpellier, France;3. Department of Business Economics, Universitat de les Illes Balears, Ctra. Valldemossa, km 7.5, 07122 Palma de Mallorca, Spain;1. Universidad de Vigo and rede, Spain;2. Departamento de Fundamentos del Análisis Económico I and ICAE, Universidad Complutense de Madrid, Spain;3. Departamento de Fundamentos del Análisis Económico II and ICAE, Universidad Complutense de Madrid, Spain |
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| Abstract: | Most studies employing ARCH and GARCH models document the existence of severe excess kurtosis in the estimated residuals. This non-normality may be due to model misspecifications, structural changes, or outliers. We conduct simulation experiments to examine the impact of extreme observations on the estimated parameters and residuals in the ARCH models. Then, we propose an iterative algorithm to detect and correct for the non-normality generated by extreme observations and additive outliers. Results for the simulated data, US equity returns and $/£ exchange rates are presented. Correcting outliers dramatically reduces the non-normality and bias in the estimated coefficients for small samples. |
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