Genaro Sucarrat har publisert en fagartikkel med Andrew Harvey i Computational Statistics and Data Analysis

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 distribu- tion 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 correspond- ing skewed-t GARCH model.

Harvey, Andrew and Genaro Sucarrat. 2014. “EGARCH models with fat tails, skewness and leverage.” Computational Statistics and Data Analysis, 76:320-338

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