Computation of mean-semivariance efficient sets by the Critical Line Algorithm
Annals of Operations Research
Portfolio selection based on fuzzy probabilities and possibility distributions
Fuzzy Sets and Systems
A possibilistic approach to selecting portfolios with highest utility score
Fuzzy Sets and Systems - Special issue: Soft decision analysis
Portfolio selection with fuzzy returns
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Mean-semivariance models for fuzzy portfolio selection
Journal of Computational and Applied Mathematics
Constructing investment strategy portfolios by combination genetic algorithms
Expert Systems with Applications: An International Journal
Portfolio optimization of equity mutual funds with fuzzy return rates and risks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Portfolio selection based on fuzzy cross-entropy
Journal of Computational and Applied Mathematics
Portfolio algorithm based on portfolio beta using genetic algorithm
Expert Systems with Applications: An International Journal
Portfolio adjusting optimization under credibility measures
Journal of Computational and Applied Mathematics
Existence and uniqueness theorem for uncertain differential equations
Fuzzy Optimization and Decision Making
UNCERTAIN OPTIMAL CONTROL WITH APPLICATION TO A PORTFOLIO SELECTION MODEL
Cybernetics and Systems
Mean-risk model for uncertain portfolio selection
Fuzzy Optimization and Decision Making
On the convergence of uncertain sequences
Mathematical and Computer Modelling: An International Journal
A risk index model for multi-period uncertain portfolio selection
Information Sciences: an International Journal
A risk index model for portfolio selection with returns subject to experts' estimations
Fuzzy Optimization and Decision Making
Hi-index | 12.05 |
Since the security market is complex, sometimes the future security returns are available mainly based on experts judgements. This paper discusses a portfolio selection problem in which security returns are given subject to experts' estimations. The use of uncertain measure is justified, and two new mean-variance and mean-semivariance models are proposed. In addition, a hybrid intelligent algorithm for solving the optimization models is given. To illustrate the application of the new models, the method to obtain the uncertainty distributions of the security returns based on experts' evaluations is given, and two selection examples are provided.