Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk

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Show simple item record Hotta, Luiz Trucíos, Carlos Ruiz, Esther
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2015-11-19T16:26:47Z 2015-11-19T16:26:47Z 2015-11
dc.identifier.issn 2387-0303
dc.description.abstract Bootstrap procedures are useful in GARCH models to obtain forecast densities for returns and volatilities.In this paper, we analyze the effect of outliers on the finite sample properties of these densities when they are based on standard maximum likelihood and robust procedures. We show that when the former procedure is implemented, the bootstrap densities are badly affected by the presence of outliers. However,the robust estimator based on variance targeting with an adequate modification of the volatility filter has the best performance when compared with alternative robust procedures. The results are illustrated withboth simulated and real data
dc.description.sponsorship The second author also acknowledges financial support from CAPES while the third author is grateful for financial support from the Spanish Ministry of Education and Science, research project ECO2012-32401
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers Statistics and Econometrics
dc.relation.ispartofseries 15-23
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other BM estimator
dc.subject.other Outliers
dc.subject.other Smooth bootstrap
dc.subject.other Variance targeting
dc.subject.other Winsorized bootstrap
dc.title Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk
dc.type workingPaper
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. ECO2012-32401
dc.identifier.uxxi DT/0000001411
dc.identifier.repec ws1523
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