Teräsvirta, Timo () (Dept. of Economic Statistics, Stockholm School of Economics) Zhao, Zhenfang () (Dept. of Economic Statistics, Stockholm School of Economics)
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Financial return series of sufficiently high frequency display stylized facts such as volatility clustering, high kurtosis, low starting and slow-decaying autocorrelation function of squared returns and the so-called Taylor effect. In order to evaluate the capacity of volatility models to reproduce these facts, we apply both standard and robust measures of kurtosis and autocorrelation of squares to first-order GARCH, EGARCH and ARSV models. Robust measures provide a fresh view of stylized facts which is useful because many financial time series can be viewed as being contaminated with outliers.
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Length: 51 pages Date of creation: 01 Jun 2007 Date of revision:
05 Jun 2007 Handle: RePEc:hhs:hastef:0662
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