Fourth Moment Structure of a Family of First-Order Exponential GARCH Models
Timo Teräsvirta () and
No 29, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney
In this paper we consider the fourth moment structure of a class of first-order Exponential GARCH models. This class contains as special cases both the standard Exponential GARCH model and the symmetric and asymmetric Logarithmic GARCH one. Conditions for the existence of any arbitrary moment are given. Furthermore, the expressions for the kurtosis and the autocorrelations of squared observations are derived. The properties of the autocorrelations of squared observations are derived. The properties of the autocorrelation structure are discussed and compared to those of the standard first-order GARCH process. In particular, it is seen that, contrary to the standard GARCH case, the decay rate of the autocorrelations is not constant and that the rate can be quite rapid in the beginning, depending on the parameters of the model.
Keywords: autocorrelation function of squared observations; conditional variance model; heavy tails; exponential GARCH; logarithmic GARCH (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed
Published as: He, C., Terasvirta, T. and Malmstein, H., 2002, "Moment Structure Of A Family Of First-Order Exponential Garch Models", Economic Theory, 18(4), 868-885.
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Journal Article: MOMENT STRUCTURE OF A FAMILY OF FIRST-ORDER EXPONENTIAL GARCH MODELS (2002)
Working Paper: Fourth Moment Structure of a Family of First-Order Exponential GARCH Models (1999)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:uts:rpaper:29
Access Statistics for this paper
More papers in Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney PO Box 123, Broadway, NSW 2007, Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Duncan Ford ().