DC FieldValueLanguage
dc.contributor.authorLoukeris, Nikolaos-
dc.contributor.authorEleftheriadis, Iordanis-
dc.date.accessioned2024-04-22T10:43:04Z-
dc.date.available2024-04-22T10:43:04Z-
dc.date.issued2015-09-
dc.identifiergoogle_scholar-XlKYe28AAAAJ:WF5omc3nYNoC-
dc.identifier.issn1099-1158-
dc.identifier.issn1076-9307-
dc.identifier.otherXlKYe28AAAAJ:WF5omc3nYNoC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2198-
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.sourceInternational Journal of Finance & Economics 20 (4), 341-361, 2015-
dc.titleFurther Higher Moments in Portfolio Selection and A Priori Detection of Bankruptcy, Under Multi‐layer Perceptron Neural Networks, Hybrid Neuro‐genetic MLPs …en_US
dc.typeArticleen_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.linkhttps://onlinelibrary.wiley.com/doi/abs/10.1002/ijfe.1521en_US
dc.collaborationUniversity of West Attica (UNIWA)en_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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