Publication:
Bootstrap prediction for returns and volatilities in GARCH models

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorPascual, Lorenzo
dc.contributor.authorRomo, Juan
dc.contributor.authorRuiz Ortega, Esther
dc.date.accessioned2009-07-14T11:04:52Z
dc.date.available2009-07-14T11:04:52Z
dc.date.issued2006
dc.description.abstractA new bootstrap procedure to obtain prediction densities of returns and volatilities of GARCH processes is proposed. Financial market participants have shown an increasing interest in prediction intervals as measures of uncertainty. Furthermore, accurate predictions of volatilities are critical for many financial models. The advantages of the proposed method are that it allows incorporation of parameter uncertainty and does not rely on distributional assumptions. The finite sample properties are analyzed by an extensive Monte Carlo simulation. Finally, the technique is applied to the Madrid Stock Market index, IBEX-35.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationComputational Statistics & Data Analysis, 2006, vol. 50, n. 9, p. 2293-2312
dc.identifier.doi10.1016/j.csda.2004.12.008
dc.identifier.issn0167-9473
dc.identifier.urihttps://hdl.handle.net/10016/4739
dc.language.isoeng
dc.publisherElsevier
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.csda.2004.12.008
dc.rights©Elsevier
dc.rights.accessRightsopen access
dc.subject.ecienciaEstadística
dc.subject.otherTime series
dc.subject.otherNon-Gaussian distributions
dc.subject.otherNonlinear models
dc.subject.otherResampling methods
dc.titleBootstrap prediction for returns and volatilities in GARCH models
dc.typeresearch article*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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