DC FieldValueLanguage
dc.contributor.authorLoukeris, Nikolaos-
dc.contributor.authorEleftheriadis, Iordanis-
dc.date.accessioned2024-04-23T09:01:48Z-
dc.date.available2024-04-23T09:01:48Z-
dc.date.issued2010-12-01-
dc.identifierscopus-79958702254-
dc.identifier.isbn978-960-474-199-1-
dc.identifier.other79958702254-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2218-
dc.description.abstractFund managers, and portfolio administrators must secure the net present value of their invested capital, providing an increasing return to investors. Regression models from the domain of Econometrics are used successfully in financial analysis, whilst Artificial Neural Networks and Genetic Algorithms in the field of Artificial Intelligence may offer significant results. A thorough comparison of additive model AdaBoost M1 regression, to various Logistic regression models such as: Logistic, Logit Boost, Simple Logistic, and hybrids of Recurrent neural networks optimized by Genetic Algorithms gives valuable information on the efficiency of these methods in Corporate Financial Analysis. Simple Logistic regression and Logistic Model Trees performed optimally.en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconferenceen_US
dc.subjectAdditive regressionen_US
dc.subjectFinanceen_US
dc.subjectGenetic algorithmsen_US
dc.subjectHybrid systemsen_US
dc.subjectLogistic regressionsen_US
dc.subjectRecurrent neural networksen_US
dc.titleDefault prediction and bankruptcy hazard analysis into recurent neuro-genetic hybrid networks to AdaBoost M1 regression and Logistic regression models in financeen_US
dc.typeConference Paperen_US
dc.relation.conference14th WSEAS International Conference on Systems: part of the 14th WSEAS CSCC multiconference, 22-24 July 2010, Corfu Island, Greeceen_US
dc.identifier.doi10.5555/1984140.1984154en_US
dc.identifier.scopus2-s2.0-79958702254-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume1en_US
dc.identifier.spage35en_US
dc.identifier.epage41en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsSubscriptionen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeConference Paper-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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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