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Decision Support Using Machine Learning Indication for Financial Investment

dc.contributor.authorOliveira, Ariel Vieira deen_US
dc.contributor.authorDazzi, Márcia Cristina Schiavien_US
dc.contributor.authorFernandes, Anita
dc.contributor.authorDazzi, Rudimar Luis Scaranto
dc.contributor.authorFerreira, Paulo
dc.contributor.authorLEITHARDT, VALDERI
dc.date.accessioned2023-02-01T18:12:32ZPT
dc.date.available2023-02-01T18:12:32ZPT
dc.date.issued2022-10-25en_US
dc.date.updated2022-10-26T16:28:49Z
dc.description.abstractTo support the decision-making process of new investors, this paper aims to implement Machine Learning algorithms to generate investment indications, considering the Brazilian scenario. Three artificial intelligence techniqueswere implemented, namely: Multilayer Perceptron, Logistic Regression and Decision Tree, which performed the classification of investments. The database used was the one provided by the website Oceans14, containing the history of Fundamental Indicators and the history of Quotations, considering BOVESPA (São Paulo State Stock Exchange). The results of the different algorithms were compared to each other using the following metrics: accuracy, precision, recall, and F1-score. The Decision Tree was the algorithm that obtained the best classification metrics and an accuracy of 77%.PT
dc.description.versionN/A
dc.identifier.doi10.3390/fi14110304en_US
dc.identifier.issn1999-5903en_US
dc.identifier.slugcv-prod-3065603
dc.identifier.urihttp://hdl.handle.net/10400.26/43553PT
dc.language.isoengpor
dc.titleDecision Support Using Machine Learning Indication for Financial Investmenten_US
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue11en_US
oaire.citation.startPage304
oaire.citation.titleFuture Interneten_US
oaire.citation.volume14en_US
person.familyNameFernandes
person.familyNameDazzi
person.familyNameFerreira
person.familyNameREIS QUIETINHO LEITHARDT
person.givenNameAnita
person.givenNameRudimar Luis Scaranto
person.givenNamePaulo
person.givenNameVALDERI
person.identifierJsOq45sAAAAJ&hl=pt-PT
person.identifier.ciencia-idB513-B46A-E5F3
person.identifier.ciencia-id0614-5834-E7F3
person.identifier.orcid0000-0002-2986-5353
person.identifier.orcid0000-0003-4183-4098
person.identifier.orcid0000-0003-1951-889X
person.identifier.orcid0000-0003-0446-9271
person.identifier.ridP-9622-2016
person.identifier.scopus-author-id42861207900
person.identifier.scopus-author-id35745865300
person.identifier.scopus-author-id35303109600
rcaap.cv.cienciaid0614-5834-E7F3 | Valderi Reis Quietinho Leithardt
rcaap.rightsopenAccessen_US
rcaap.typearticleen_US
relation.isAuthorOfPublication4e0e3a69-c788-455a-81a0-679da835632e
relation.isAuthorOfPublication4b02215d-82d2-4b40-8160-93c1ad420186
relation.isAuthorOfPublicationcef169d9-c594-4505-ab57-7c6f92868cb6
relation.isAuthorOfPublicationab15f7c6-e882-406e-813d-2629e9cec5c8
relation.isAuthorOfPublication.latestForDiscovery4b02215d-82d2-4b40-8160-93c1ad420186

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