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dc.contributor.authorZhang, Junni L.en_US
dc.contributor.authorHärdle, Wolfgang Karlen_US
dc.date.accessioned2008-02-20en_US
dc.date.accessioned2009-07-23T15:03:29Z-
dc.date.available2009-07-23T15:03:29Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10419/25245-
dc.description.abstractWe propose a new nonlinear classification method based on a Bayesian sum-of-trees model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric additive model specified by a prior and a likelihood in which the additive components are trees, and it is fitted by an iterative MCMC algorithm. Each of the trees learns a different part of the underlying function relating the dependent variable to the input variable, but the sum of the trees offers a flexible and robust model. Through several benchmark examples, we show that the BACT has excellent performance. This practical example is very important for banks to construct their risk profile and operate successfully. We use the German Creditreform database and classify the solvency status of German firms based on financial statement information. We show that the BACT outperforms the logit model, CART and the Support Vector Machine in identifying insolvent firms.en_US
dc.language.isoengen_US
dc.publisherSFB 649, Economic Risk Berlinen_US
dc.relation.ispartofseriesSFB 649 discussion paper 2008,003en_US
dc.subject.jelC14en_US
dc.subject.jelC11en_US
dc.subject.jelC45en_US
dc.subject.jelC01en_US
dc.subject.ddc330en_US
dc.subject.keywordClassification and Regression Treeen_US
dc.subject.keywordFinancial Ratioen_US
dc.subject.keywordMisclassification Rateen_US
dc.subject.keywordAccuracy Ratioen_US
dc.subject.stwClusteranalyseen_US
dc.subject.stwBayes-Statistiken_US
dc.subject.stwKreditwürdigkeiten_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwTheorieen_US
dc.subject.stwDeutschlanden_US
dc.titleThe bayesian additive classification tree applied to credit risk modellingen_US
dc.typeWorking Paperen_US
dc.identifier.ppn558748309en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

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