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Veuillez utiliser cette adresse pour citer ce document : https://hdl.handle.net/20.500.12177/7727
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dc.contributor.advisorFono, louis aimé-
dc.contributor.advisorAndjiga, Nicolas Gabriel-
dc.contributor.authorTassak Deffo, Christian-
dc.date.accessioned2022-03-14T14:52:19Z-
dc.date.available2022-03-14T14:52:19Z-
dc.date.issued2017-
dc.identifier.urihttps://hdl.handle.net/20.500.12177/7727-
dc.description.abstractIn the literature, three measures were proposed to deal with imprecision and uncertainty in phenomenons. Zadeh [40] proposed the two first measures, namely possibility and necessity measures, and they enable to determine and study fuzzy variable’s parameters and to apply theoretical results in some research areas (medical diagnosis, robot control, strategic decision, games,...). The third measure, namely credibility measure and proposed by Liu [20], is a dual measure and the average of the two first measures. Following that, scholars (Liu [20], Huang [11], Li et al. [16]) determined the three first moments (mean, variance, skewness) and the first semi-moment (semi-variance) of a fuzzy variable. They used the obtained results to solve portfolio selection problem with fuzzy returns by means of the mean-semi-variance model and the mean-variance-skewness model. Furthermore, Peng et al. [27] introduced two dominance relations on fuzzy variables, namely the first and the second order dominances, and they used them to analyze risk in fuzzy context. In this thesis, we introduce moments and semi-moments of order k (k ∈ N) of a fuzzy variable and we study their properties. We introduce a new dominance relation on fuzzy variables, we characterize three dominance relations (the two previous ones and the new one) and determine their properties. TASSAK DEFFO CHRISTIAN PhD. Thesis 1 The obtained theoretical results are applied to solve the main problem of portfolio selection with fuzzy returns described by triangular fuzzy numbers by means of two approaches: the first approach based on four first moments (mean, variance, skewness, kurtosis) and the second approach based on the core of portfolios of a finite family of assets, that is, the subset of non dominated portfoliosfr_FR
dc.format.extent159p.fr_FR
dc.publisherUniversity of Doualafr_FR
dc.publisherUniversity of Yaounde Ifr_FR
dc.subjectFuzzy variablefr_FR
dc.subjectCredibility measurefr_FR
dc.subjectDominance relationfr_FR
dc.subjectPortfolio selectionfr_FR
dc.titleDecision criteria on fuzzy variables for portfolio selection with fuzzy returns.fr_FR
dc.typeThesis-
Collection(s) :Thèses soutenues

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