SSE/EFI Working Paper Series in Economics and Finance
No 96:
Two Stylized Facts and the Garch (1,1) Model
Timo Teräsvirta ()
Abstract: Many high frequency economic or financial time series
display two empirical characteristics: high kurtosis and positive
autocorrelation in the centred and squared observations. The first- order
autocorrelation is typically low, and the autocorrelation function decays
slowly. These series are often modelled with a GARCH (1,1) model. In this
paper it is shown why such a model with normal errors cannot adequately
characterize these stylized facts. The same seems true for the IGARCH
(1,1)model. It is also shown why one can improve the situation by replacing
the normal error distribution by a leptokurtic one, although this may not
provide a complete remedy.
Keywords: Conditional heteroskedasticity; moment condition; IGARCH; t-distribution; high frequency economic data; (follow links to similar papers)
JEL-Codes: C22; C52; (follow links to similar papers)
27 pages, January 1996
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