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dc.contributor.authorFranke, Jürgenen_US
dc.contributor.authorStockis, Jean-Pierreen_US
dc.contributor.authorTadjuidje, Josephen_US
dc.date.accessioned2007-03-07en_US
dc.date.accessioned2009-07-23T14:44:31Z-
dc.date.available2009-07-23T14:44:31Z-
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10419/25177-
dc.description.abstractWe consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series available at time t - 1. We discuss sieve estimates which are a nonparametric versions of the Koenker-Bassett regression quantiles and do not require the specification of the innovation law. We prove consistency of those estimates and illustrate their good performance for light- and heavy-tailed distributions of the innovations with a small simulation study. As an economic application, we use the estimates for calculating the value at risk of some stock price series.en_US
dc.language.isoengen_US
dc.publisherSFB 649, Economic Risk Berlinen_US
dc.relation.ispartofseriesSFB 649 discussion paper 2007,005en_US
dc.subject.jelC14en_US
dc.subject.jelC45en_US
dc.subject.ddc330en_US
dc.subject.keywordconditional quantileen_US
dc.subject.keywordtime seriesen_US
dc.subject.keywordsieve estimateen_US
dc.subject.keywordneural networken_US
dc.subject.keywordqualitative threshold modelen_US
dc.subject.keyworduniform consistencyen_US
dc.subject.keywordvalue at risken_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwMaßzahlen_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwValue at Risken_US
dc.subject.stwBörsenkursen_US
dc.subject.stwTheorieen_US
dc.titleQuantile sieve estimates for time seriesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn525376372en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

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