GDL

Journal from gdlhub / 2021-08-27 17:07:52
Oleh : Mahdi Pourrafiee, AmirHossein Nafei, Shokoufe Banihashemi & S. Pourmohammad Azizi, Fuzzy Information and Engineering
Dibuat : 2021-08-27, dengan 0 file

Keyword : value at risk;space multi-objective portfolio model, scredibility fuzzy membership function, higher-order moments, entropy, genetic algorithm
Url : http://www.tandfonline.com/doi/full/10.1080/16168658.2020.1811481
Sumber pengambilan dokumen : Web

Credibility fuzzy value at risk in portfolio models is a reasonable solution when investors may face ambiguity, lack of historical data, and when avoiding normally or symmetrically distributed assumptions is needed. Credibility fuzzy membership function because having a self-duality axiom is analogous to measurable function on a probability space for the random variable. The primary aim of this paper is to solve the portfolio problem by using the third and fourth credibility moments in multi-objective higher-order moment portfolio models with different entropies. Firstly, Minkowski, Shannon, Yager, Renyi, and Gini-Simpson entropies are presented as new objective functions to solve corner solutions of conventional fuzzy multi-objective weighted credibility higher-order moment portfolio selection models. Secondly, because of the non-linearity nature of multi-objective models, a genetic algorithm is used to solve the models. Finally, proposed models are tested – using the data of Tehran Stock Exchange – and then evaluated – applying adjusted Sharpe Ratio as a portfolio performance technique.

Deskripsi Alternatif :

Credibility fuzzy value at risk in portfolio models is a reasonable solution when investors may face ambiguity, lack of historical data, and when avoiding normally or symmetrically distributed assumptions is needed. Credibility fuzzy membership function because having a self-duality axiom is analogous to measurable function on a probability space for the random variable. The primary aim of this paper is to solve the portfolio problem by using the third and fourth credibility moments in multi-objective higher-order moment portfolio models with different entropies. Firstly, Minkowski, Shannon, Yager, Renyi, and Gini-Simpson entropies are presented as new objective functions to solve corner solutions of conventional fuzzy multi-objective weighted credibility higher-order moment portfolio selection models. Secondly, because of the non-linearity nature of multi-objective models, a genetic algorithm is used to solve the models. Finally, proposed models are tested – using the data of Tehran Stock Exchange – and then evaluated – applying adjusted Sharpe Ratio as a portfolio performance technique.

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