Stocks classification using fuzzy clustering

dc.contributor.advisorOrcidhttps://orcid.org/0000-0002-4413-3847
dc.contributor.authorRenato Aguiar
dc.contributor.authorSALES, R. M.
dc.contributor.authorDE SOUSA, L. A.
dc.contributor.authorIMONIANA, J. O.
dc.date.accessioned2023-08-26T23:50:57Z
dc.date.available2023-08-26T23:50:57Z
dc.date.issued2004-06-21
dc.description.abstractThe main objective of this paper is to investigate the application of a pattern recognition technique as a supporting tool for stock investment decision taking by the public companies in the Brazilian Stock Market. The technique, known as fuzzy clustering means is applied to a set of indexes extracted from the quarterly financial statements relating to the 4 th quarter of 1994 through the 2nd quarter of 2002 belonging to oil/petrochemical and textile companies. The technique separates a group of companies into two sets. Having a set with higher potential returns than the other. And besides that, the set of stocks of the companies produced a higher potential yields and an average financial returns closer to the Bovespa index.
dc.description.firstpage249
dc.description.lastpage255
dc.description.volume1
dc.identifier.citationAGUIAR, R.; SALAES, R. M.; DE SOUSA, L. A.; IMONIANA, J. O. Stocks classification using fuzzy clustering. Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, v. 1, p. 249-255, jun. 2004.
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/5068
dc.relation.ispartofProceedings of the International Conference on Artificial Intelligence, IC-AI'04
dc.rightsAcesso Restrito
dc.subject.otherlanguageFinancial index
dc.subject.otherlanguageFuzzy clustering means
dc.subject.otherlanguagePartitional clustering
dc.subject.otherlanguagePattern recognition
dc.subject.otherlanguageStock classification
dc.titleStocks classification using fuzzy clustering
dc.typeArtigo de evento
fei.scopus.citations1
fei.scopus.eid2-s2.0-12744269965
fei.scopus.subjectFinancial index
fei.scopus.subjectFuzzy clustering means
fei.scopus.subjectPartitional clustering
fei.scopus.subjectStock classification
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=12744269965&origin=inward
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