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2017-11-06Diskussionspapier DOI: 10.18452/18747
Dynamic semi-parametric factor model for functional expectiles
dc.contributor.authorBurdejová, Petra
dc.contributor.authorHärdle, Wolfgang Karl
dc.date.accessioned2018-01-24T15:08:51Z
dc.date.available2018-01-24T15:08:51Z
dc.date.issued2017-11-06
dc.identifier.urihttp://edoc.hu-berlin.de/18452/19460
dc.description.abstractHigh-frequency data can provide us with a quantity of informa- tion for forecasting, help to calculate and prevent the future risk based on extremes. This tail behaviour is very often driven by ex- ogenous components and may be modelled conditional on other vari- ables. However, many of these phenomena are observed over time, exhibiting non-trivial dynamics and dependencies. We propose a func- tional dynamic factor model to study the dynamics of expectile curves. The complexity of the model and the number of dependent variables are reduced by lasso penalization. The functional factors serve as a low-dimensional representation of the conditional tail event, while the time-variation is captured by factor loadings. We illustrate the model with an application to climatology, where daily data over years on temperature, rainfalls or strength of wind are available.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectfactor modeleng
dc.subjectfunctional dataeng
dc.subjectexpectileseng
dc.subjectextremeseng
dc.subject.ddc330 Wirtschaft
dc.titleDynamic semi-parametric factor model for functional expectiles
dc.typeworkingPaper
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/19460-6
dc.identifier.doihttp://dx.doi.org/10.18452/18747
local.edoc.pages22
local.edoc.type-nameDiskussionspapier
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
dc.identifier.zdb2195055-6
bua.series.nameSonderforschungsbereich 649: Ökonomisches Risiko
bua.series.issuenumber2017,27
bua.departmentWirtschaftswissenschaftliche Fakultät

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