Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/25245 
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dc.contributor.authorZhang, Junni L.en
dc.contributor.authorHärdle, Wolfgang Karlen
dc.date.accessioned2008-02-20-
dc.date.accessioned2009-07-23T15:03:29Z-
dc.date.available2009-07-23T15:03:29Z-
dc.date.issued2008-
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
dc.language.isoengen
dc.publisher|aHumboldt University of Berlin, Collaborative Research Center 649 - Economic Risk |cBerlinen
dc.relation.ispartofseries|aSFB 649 Discussion Paper |x2008,003en
dc.subject.jelC14en
dc.subject.jelC11en
dc.subject.jelC45en
dc.subject.jelC01en
dc.subject.ddc330en
dc.subject.keywordClassification and Regression Treeen
dc.subject.keywordFinancial Ratioen
dc.subject.keywordMisclassification Rateen
dc.subject.keywordAccuracy Ratioen
dc.subject.stwClusteranalyseen
dc.subject.stwBayes-Statistiken
dc.subject.stwKreditwürdigkeiten
dc.subject.stwPrognoseverfahrenen
dc.subject.stwTheorieen
dc.subject.stwDeutschlanden
dc.titleThe bayesian additive classification tree applied to credit risk modelling-
dc.type|aWorking Paperen
dc.identifier.ppn558748309en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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