Outliers in Garch models and the estimation of risk measures

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dc.contributor.author Grané, Aurea
dc.contributor.author Veiga, Helena
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2010-02-01T16:20:53Z
dc.date.available 2010-02-01T16:20:53Z
dc.date.issued 2010-01
dc.identifier.uri http://hdl.handle.net/10016/6699
dc.description.abstract In this paper we focus on the impact of additive level outliers on the calculation of risk measures, such as minimum capital risk requirements, and compare four alternatives of reducing these measures' estimation biases. The first three proposals proceed by detecting and correcting outliers before estimating these risk measures with the GARCH(1,1) model, while the fourth procedure fits a Student’s t-distributed GARCH(1,1) model directly to the data. The former group includes the proposal of Grané and Veiga (2010), a detection procedure based on wavelets with hard- or soft-thresholding filtering, and the well known method of Franses and Ghijsels (1999). The first results, based on Monte Carlo experiments, reveal that the presence of outliers can bias severely the minimum capital risk requirement estimates calculated using the GARCH(1,1) model. The message driven from the second results, both empirical and simulations, is that outlier detection and filtering generate more accurate minimum capital risk requirements than the fourth alternative. Moreover, the detection procedure based on wavelets with hard-thresholding filtering gathers a very good performance in attenuating the effects of outliers and generating accurate minimum capital risk requirements out-of-sample, even in pretty volatile periods
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 10-02
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Minimum capital risk requirements
dc.subject.other Outliers
dc.subject.other Wavelets
dc.title Outliers in Garch models and the estimation of risk measures
dc.type workingPaper
dc.subject.jel C22
dc.subject.jel C5
dc.subject.jel G13
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws100502
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