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dc.contributor.authorSánchez-Monedero, J.
dc.contributor.authorCampoy-Muñoz, Pilar
dc.contributor.authorGutiérrez, P.A.
dc.contributor.authorHervás-Martínez, César
dc.date.accessioned2017-01-20T12:05:29Z
dc.date.available2017-01-20T12:05:29Z
dc.date.issued2017-01-20
dc.identifier.urihttp://hdl.handle.net/10396/14349
dc.description.abstractSovereign rating has had an increasing importance since the beginning of the nancial crisis. However, credit rating agencies opacity has been criticised by several authors highlighting the suitability of designing more objective alternative methods. This paper tackles the sovereign credit rating classi cation problem within an ordinal classi cation perspective by employing a pairwise class distances projection to build a classi cation model based on standard regression techniques. In this work the -SVR is selected as the regressor tool. The quality of the projection is validated through the classi cation results obtained for four performance metrics when applied to Standard & Poors, Moody's and Fitch sovereign rating data of U27 countries during the period 2007-2010. This validated projection is later used for ranking visualization which might be suitable to build a decision support systemes_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.subjectOrdinal regressiones_ES
dc.subjectOrdinal classificationes_ES
dc.subjectCountry riskes_ES
dc.subjectRating agencieses_ES
dc.subjectFinancial crisises_ES
dc.titleA guided data projection technique for classi cation of sovereign ratings: the case of European Union 27es_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.relation.projectIDGobierno de España. TIN2011-22794es_ES
dc.relation.projectIDJunta de Andalucía. P2011-TIC-7508es_ES
dc.relation.projectIDJunta de Andalucía Ph.D. Student Program.es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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