DC FieldValueLanguage
dc.contributor.authorLoukeris, Nikolaos-
dc.contributor.authorEleftheriadis, Iordanis-
dc.date.accessioned2024-04-22T10:32:41Z-
dc.date.available2024-04-22T10:32:41Z-
dc.date.issued2015-10-01-
dc.identifierscopus-84943452729-
dc.identifier.issn1099-1158-
dc.identifier.issn1076-9307-
dc.identifier.other84943452729-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2196-
dc.description.abstractA novel approach on the portfolio selection theory is given with regard to advanced utility performance that incorporates more accurate investor patterns up to the fifth moment. Bankruptcy detection, a priori, on an investment portfolio of stocks is a significant process that can eliminate potential losses. Even in case of corporate fraud, efficient funds can maximize their net present value by reforming the assets. Multi-layer perceptron neural networks are compared with hybrids of neuro-genetic multi-layer perceptrons and the voted-perceptron algorithm to define the most efficient classification method into the perceptrons family, implementing extensive network topologies.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of International Finance and Economicsen_US
dc.subjectCorporate financeen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMulti-layer perceptronen_US
dc.subjectPortfolio managementen_US
dc.titleFurther Higher Moments in Portfolio Selection and A Priori Detection of Bankruptcy, Under Multi-layer Perceptron Neural Networks, Hybrid Neuro-genetic MLPs, and the Voted Perceptronen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/ijfe.1521en_US
dc.identifier.scopus2-s2.0-84943452729-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume20en_US
dc.relation.issue4en_US
dc.identifier.spage341en_US
dc.identifier.epage361en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-1891-8245-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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