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Faculty of Economics

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Harvey, A. C. and Sucarrat, G.

EGARCH models with fat tails, skewness and leverage


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.

Keywords: General error distribution, heteroskedasticity, leverage, score, Student?s t, two components

JEL Codes: C22 G17

Author links: Andrew Harvey  


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Published Version of Paper: EGARCH models with fat tails, skewness and leverage, Harvey, A. C. and Sucarrat, G., Computational Statistics & Data Analysis (2014)

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