Using Fuzzy Possibilistic Mean and Variance in Portfolio Selection Model

Conference PaperinLecture Notes in Computer Science · December 2005with4 Reads
Impact Factor: 0.51 · DOI: 10.1007/11596448_42 · Source: DBLP
Conference: Computational Intelligence and Security, International Conference, CIS 2005, Xi'an, China, December 15-19, 2005, Proceedings, Part I


    There are many non-probabilistic factors that affect the financial markets such that the returns of risky assets may be regarded
    as fuzzy numbers. This paper discusses the portfolio selection problem based on the possibilistic mean and variance of fuzzy
    numbers, which can better described an uncertain environment with vagueness and ambiguity to compare with conventional probabilistic
    mean-variance methodology. Markowitz’s mean-variance model is simplified a linear programming when returns of assets are symmetric
    triangular fuzzy numbers, so the possibilistic efficient portfolios can be easily obtained by some related algorithms.