Please use this identifier to cite or link to this item: http://repositorio.ufc.br/handle/riufc/68324
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dc.contributor.authorCarmo, Breno Barros Telles do-
dc.contributor.authorMedeiros, Pablo Picasso Morais de-
dc.contributor.authorGonçalo, Thomas Edson Espíndola-
dc.contributor.authorCorreia, Gabriela Colaço-
dc.date.accessioned2022-09-16T19:15:06Z-
dc.date.available2022-09-16T19:15:06Z-
dc.date.issued2021-
dc.identifier.citationCARMO, B. B. T. et al. Framework to assist investment portfolio generation for finantial sector. Exacta, 2021. DOI: 10.5585/exactaep.2021.18687pt_BR
dc.identifier.issn1983-9308-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/68324-
dc.description.abstractSeveral variables are influencing the financial performance of listed companies in the stock exchange, making the choice of an ideal investment portfolio complex. Multicriteria decision support methods emerge as a potential tool to support the investor in the asset selection process. Thus, this paper proposes a framework to assist investors in generating an investment portfolio in financial sector companies considering the fundamentalist analysis approach. Based on selected investors, the study defined the appropriate minimum performance filters, criteria, and weights for stock selection in the financial sector. The portfolio was established based on investor constraints using the PROMETHEE V method. As a subsequent step, an entire linear programming model was implemented to define, given the available budget, the amount of capital to be allocated to each asset of the portfolio. The research provides investors with a clear and accurate method for selecting a stock portfolio and allowing customization of the model.pt_BR
dc.language.isoenpt_BR
dc.publisherExactapt_BR
dc.subjectStockspt_BR
dc.subjectFundamentalist analysispt_BR
dc.subjectMulticriteria methodspt_BR
dc.subjectPROMETHEE Vpt_BR
dc.titleFramework to assist investment portfolio generation for finantial sectorpt_BR
dc.typeArtigo de Periódicopt_BR
Appears in Collections:DEPR - Artigos publicados em revistas científicas

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