EGARCH models with fat tails, skewness and leverage


Type
Working Paper
Change log
Authors
Harvey, Andrew 
Sucarrat, Genaro 
Abstract

An EGARCH model in which the conditional distribution is heavy-tailed and skewed is proposed. The properties of the model, including unconditional moments, autocorrelations and the asymptotic distribution of the maximum likelihood estimator, are obtained. Evidence for skewness in conditional t-distribution is found for a range of returns series and the model is shown to give a better .t than the corresponding skewed-t GARCH model.

Description
Keywords
General error distribution, heteroskedasticity, leverage, score, Student's t, two components
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