Bootstrap prediction intervals for VaR and ES in the context of GARCH models

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dc.contributor.author Nieto, María Rosa
dc.contributor.author Ruiz, Esther
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2010-05-27T10:02:34Z
dc.date.available 2010-05-27T10:02:34Z
dc.date.issued 2010-05
dc.identifier.uri http://hdl.handle.net/10016/8524
dc.description.abstract In this paper, we propose a new bootstrap procedure to obtain prediction intervals of future Value at Risk (VaR) and Expected Shortfall (ES) in the context of univariate GARCH models. These intervals incorporate the parameter uncertainty associated with the estimation of the conditional variance of returns. Furthermore, they do not depend on any particular assumption on the error distribution. Alternative bootstrap intervals previously proposed in the literature incorporate the first but not the second source of uncertainty when computing the VaR and ES. We also consider an iterated smoothed bootstrap with better properties than traditional ones when computing prediction intervals for quantiles. However, this latter procedure depends on parameters that have to be arbitrarily chosen and is very complicated computationally. We analyze the finite sample performance of the proposed procedure and show that the coverage of our proposed procedure is closer to the nominal than that of the alternatives. All the results are illustrated by obtaining one-step-ahead prediction intervals of the VaR and ES of several real time series of financial returns.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 10-14
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Expected Shortfall
dc.subject.other Feasible Historical Simulation
dc.subject.other Hill estimator
dc.subject.other Parameter uncertainty
dc.subject.other Quantile intervals
dc.subject.other Value at Risk
dc.title Bootstrap prediction intervals for VaR and ES in the context of GARCH models
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws102814
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