Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility

Timo Teräsvirta and Zhenfang Zhao ()
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Zhenfang Zhao: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, SE-113 83 Stockholm, Sweden

No 662, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

Abstract: 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.

Keywords: GARCH; EGARCH; ARSV; extreme observations; autocorrelation function; kurtosis; robust measure; confidence region. (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2007-06-01, Revised 2007-08-01
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (4)

Published as Teräsvirta, Timo and Zhenfang Zhao, 'Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility' in Applied Financial Economics, 2011, pages 67-94.

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Persistent link: https://EconPapers.repec.org/RePEc:hhs:hastef:0662

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