Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorOuenniche, Jamal
dc.contributor.authorBouslah, Kais
dc.contributor.authorCabello, Jose Manuel
dc.contributor.authorRuiz, Francisco
dc.date.accessioned2018-06-21T23:32:24Z
dc.date.available2018-06-21T23:32:24Z
dc.date.issued2018-01-12
dc.identifier.citationOuenniche , J , Bouslah , K , Cabello , J M & Ruiz , F 2018 , ' A new classifier based on the reference point method with application in bankruptcy prediction ' , Journal of the Operational Research Society , vol. 69 , no. 10 , pp. 1653-1660 . https://doi.org/10.1057/s41274-017-0254-zen
dc.identifier.issn0160-5682
dc.identifier.otherPURE: 250454776
dc.identifier.otherPURE UUID: 8e6d1286-8701-4be0-b9f8-3116c6f01a85
dc.identifier.otherWOS: 000452046800011
dc.identifier.otherScopus: 85021082530
dc.identifier.otherORCID: /0000-0001-8407-8929/work/82179585
dc.identifier.urihttp://hdl.handle.net/10023/14433
dc.description.abstractThe finance industry relies heavily on the risk modelling and analysis toolbox to assess the risk profiles of entities such as individual and corporate borrowers and investment vehicles. Such toolbox includes a variety of parametric and nonparametric methods for predicting risk class belonging. In this paper, we expand such toolbox by proposing an integrated framework for implementing a full classification analysis based on a reference point method, namely in-sample classification and out-of-sample classification. The empirical performance of the proposed reference point method-based classifier is tested on a UK data set of bankrupt and nonbankrupt firms. Our findings conclude that the proposed classifier can deliver a very high predictive performance, which makes it a real contender in industry applications in banking and investment. Three main features of the proposed classifier drive its outstanding performance, namely its nonparametric nature, the design of our RPM score-based cut-off point procedure for in-sample classification, and the choice of a k-nearest neighbour as an out-of-sample classifier which is trained on the in-sample classification provided by the reference point method-based classifier.
dc.format.extent8
dc.language.isoeng
dc.relation.ispartofJournal of the Operational Research Societyen
dc.rights© The Operational Research Society 2017. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1057/s41274-017-0254-zen
dc.subjectBankruptcyen
dc.subjectIn-sample predictionen
dc.subjectk-nearest neighbour classifieren
dc.subjectOut-of-sample predictionen
dc.subjectReference point method classifieren
dc.subjectRisk class predictionen
dc.subjectHD28 Management. Industrial Managementen
dc.subjectFinanceen
dc.subjectEconomics, Econometrics and Finance (miscellaneous)en
dc.subjectManagement Science and Operations Researchen
dc.subjectNDASen
dc.subjectBDCen
dc.subjectR2Cen
dc.subject.lccHD28en
dc.titleA new classifier based on the reference point method with application in bankruptcy predictionen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Managementen
dc.contributor.institutionUniversity of St Andrews.Centre for the Study of Philanthropy & Public Gooden
dc.contributor.institutionUniversity of St Andrews.Centre for Responsible Banking and Financeen
dc.identifier.doihttps://doi.org/10.1057/s41274-017-0254-z
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-06-21


This item appears in the following Collection(s)

Show simple item record