Publication:
Unbiased QML Estimation of Log-GARCH Models in the Presence of Zero Returns

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dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorSucarrat, Genaro
dc.contributor.authorEscribano, Álvaro
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Economíaes
dc.date.accessioned2013-11-11T14:30:40Z
dc.date.available2013-11-11T14:30:40Z
dc.date.issued2013-09-01
dc.description.abstractA critique that has been directed towards the log-GARCH model is that its logvolatility specification does not exist in the presence of zero returns. A common "remedy" is to replace the zeros with a small (in the absolute sense) non-zero value. However, this renders Quasi Maximum Likelihood (QML) estimation asymptotically biased. Here, we propose a solution to the case where actual returns are equal to zero with probability zero, but zeros nevertheless are observed because of measurement error (due to missing values, discreteness approximisation error, etc.). The solution treats zeros as missing values and handles these by combining QML estimation via the ARMA representation with the Expectation-maximisation (EM) algorithm. Monte Carlo simulations confirm that the solution corrects the bias, and several empirical applications illustrate that the biascorrecting estimator can make a substantial difference.es
dc.format.mimetypeapplication/pdf
dc.identifier.issn2340-5031
dc.identifier.repecwe1321
dc.identifier.urihttps://hdl.handle.net/10016/17909
dc.identifier.uxxiDT/0000001136es
dc.language.isoenges
dc.relation.ispartofseriesWorking Papers. Economics. WEes
dc.relation.ispartofseries13-21es
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaEconomíaes
dc.subject.jelC22es
dc.subject.jelC58es
dc.subject.otherARCHes
dc.subject.otherExponential GARCHes
dc.subject.otherLog-GARCHes
dc.subject.otherARMAes
dc.subject.otherExpectation-Maximization (EM)es
dc.titleUnbiased QML Estimation of Log-GARCH Models in the Presence of Zero Returnses
dc.typeworking paper*
dc.type.hasVersionSMUR*
dspace.entity.typePublication
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