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dc.contributor.authorOoghe, Hubert
dc.contributor.authorSpaenjers, Christophe
dc.contributor.authorVandermoere, Pieter
dc.date.accessioned2017-12-02T14:23:20Z
dc.date.available2017-12-02T14:23:20Z
dc.date.issued2005
dc.identifier.urihttp://hdl.handle.net/20.500.12127/1872
dc.description.abstractWe give an overview of the shortcomings of the most frequently used statistical techniques in failure prediction modelling. The statistical procedures that underpin the selection of variables and the determination of coefficients often lead to ‘overfitting'. We also see that the ‘expected signs' of variables are sometimes neglected and that an underlying theoretical framework mostly does not exist. Based on the current knowledge of failing firms, we construct a new type of failure prediction models, namely ‘simple-intuitive models'. In these models, eight variables are first logit-transformed and then equally weighted. These models are tested on two broad validation samples (1 year prior to failure and 3 years prior to failure) of Belgian companies. The performance results of the best simple-intuitive model are comparable to those of less transparent and more complex statistical models.
dc.language.isoen
dc.publisherVlerick Business School
dc.subjectCorporate Finance
dc.titleBusiness failure prediction: simple-intuitive models versus statistical models
refterms.dateFOA2019-10-14T12:44:42Z
dc.source.issue22
dc.source.numberofpages55
vlerick.knowledgedomainAccounting & Finance
vlerick.supervisor
vlerick.typecommWorking paper
vlerick.vlerickdepartmentA&F
dc.relation.urlhttp://public.vlerick.com/Publications/16522f07-6aa9-e011-8a89-005056a635ed.pdf
dc.identifier.vperid35891
dc.identifier.vperid84587
dc.identifier.vperid50360
dc.identifier.vpubid2108


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