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2015-07-20Buch DOI: 10.18452/4591
Factorisable Sparse Tail Event Curves
dc.contributor.authorChao, Shih-Kang
dc.contributor.authorHärdle, Wolfgang Karl
dc.contributor.authorYuan, Ming
dc.date.accessioned2017-06-16T01:17:08Z
dc.date.available2017-06-16T01:17:08Z
dc.date.created2016-07-27
dc.date.issued2015-07-20
dc.date.submitted2015-07-20
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/5243
dc.description.abstractIn this paper, we propose a multivariate quantile regression method which enables localized analysis on conditional quantiles and global comovement analysis on conditional ranges for high-dimensional data. The proposed method, hereafter referred to as FActorisable Sparse Tail Event Curves, or FASTEC for short, exploits the potential factor structure of multivariate conditional quantiles through nuclear norm regularization and is particularly suitable for dealing with extreme quantiles. We study both theoretical properties and computational aspects of the estimating procedure for FASTEC. In particular, we derive nonasymptotic oracle bounds for the estimation error, and develope an efficient proximal gradient algorithm for the non-smooth optimization problem incurred in our estimating procedure. Merits of the proposed methodology are further demonstrated through applications to Conditional Autoregressive Value-at-Risk (CAViaR) (Engle and Manganelli; 2004), and a Chinese temperature dataset.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectvalue-at-riskeng
dc.subjectquantile regressioneng
dc.subjecthigh-dimensional data analysiseng
dc.subjectmultivariate quantile regressioneng
dc.subjectnuclear normeng
dc.subjectmulti-task learningeng
dc.subject.ddc310 Statistik
dc.subject.ddc330 Wirtschaft
dc.titleFactorisable Sparse Tail Event Curves
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100239300
dc.identifier.doihttp://dx.doi.org/10.18452/4591
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages63
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2015
local.edoc.container-issue34
local.edoc.container-year2015
local.edoc.container-erstkatid2195055-6

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