DC FieldValueLanguage
dc.contributor.authorLoukeris, Nikolaos-
dc.contributor.authorMaltoudoglou, Lysimachos-
dc.contributor.authorBoutalis, Yannis-
dc.contributor.authorArampatzis, Avi-
dc.contributor.authorLivanis, Efstratios-
dc.date.accessioned2024-04-23T09:58:51Z-
dc.date.available2024-04-23T09:58:51Z-
dc.date.issued2016-01-20-
dc.identifierscopus-84963861087-
dc.identifier.isbn9781467393119-
dc.identifier.other84963861087-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2222-
dc.description.abstractWe introduce a new methodology, that incorporates advanced higher moments evaluation in a new approach of the Portfolio Selection problem, supported by effective Computational Intelligence models. The Portfolio Intelligence (PI) model extracts hidden patterns out of the numerous accounting data and financial statements filtering misguiding effects such as noise or fraud, offering an optimal portfolio selection method.en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 6th International Conference on Information, Intelligence, Systems and Applications (IISA)en_US
dc.subjectFinancial analysisen_US
dc.subjectGenetic algorithmsen_US
dc.subjectIntegrated systemsen_US
dc.subjectNonlinear regressionsen_US
dc.subjectSVM & RBF neural networksen_US
dc.titleComputational intelligence in optimal portfolio selection - The PI modelen_US
dc.typeConference Paperen_US
dc.relation.conference6th International Conference on Information, Intelligence, Systems and Applications (IISA), 6-8 July 2015, Corfu, Greeceen_US
dc.identifier.doi10.1109/IISA.2015.7388004en_US
dc.identifier.scopus2-s2.0-84963861087-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_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.openairetypeConference Paper-
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-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
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