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2007-06-01Diskussionspapier DOI: 10.18452/4054
Estimating Probabilities of Default With Support Vector Machines
dc.contributor.authorHärdle, Wolfgang Karl
dc.contributor.authorMoro, Rouslan
dc.contributor.authorSchäfer, Dorothea
dc.date.accessioned2017-06-15T23:27:46Z
dc.date.available2017-06-15T23:27:46Z
dc.date.created2007-07-13
dc.date.issued2007-06-01
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4706
dc.description.abstractThis paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on German Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectBankruptcyeng
dc.subjectCompany ratingeng
dc.subjectDefault probabilityeng
dc.subjectSupport vector machineseng
dc.subject.ddc330 Wirtschaft
dc.titleEstimating Probabilities of Default With Support Vector Machines
dc.typeworkingPaper
dc.identifier.urnurn:nbn:de:kobv:11-10078445
dc.identifier.doihttp://dx.doi.org/10.18452/4054
local.edoc.pages24
local.edoc.type-nameDiskussionspapier
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2007
dc.identifier.zdb2195055-6
bua.series.nameSonderforschungsbereich 649: Ökonomisches Risiko
bua.series.issuenumber2007,35

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