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EGARCH models with fat tails, skewness and leverage

Harvey, Andrew; Sucarrat, Genaro
Journal article
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URI
http://hdl.handle.net/11250/2349731
Date
2015
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Original version
Computational Statistics and Data Analysis, 76(2014): 320-338   10.1016/j.csda.2013.09.022
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.
Description
This is the manuscript to the article first published in Cambridge Working Papers in Economics: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe1236.pdf
Publisher
Elsevier
Journal
Computational Statistics and Data Analysis

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