The mean value of a fuzzy number
Fuzzy Sets and Systems - Fuzzy Numbers
Fuzzy and semi-infinite mathematical programming
Information Sciences: an International Journal
Analytical linear inequality systems and optimization
Journal of Optimization Theory and Applications
Portfolio selection under independent possibilistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
Fuzzy Optimization: Recent Advances
Fuzzy Optimization: Recent Advances
Nearest interval approximation of a fuzzy number
Fuzzy Sets and Systems - Fuzzy intervals
A possibilistic approach to selecting portfolios with highest utility score
Fuzzy Sets and Systems - Special issue: Soft decision analysis
On weighted possibilistic mean and variance of fuzzy numbers
Fuzzy Sets and Systems - Theme: Basic concepts
Fuzzy portfolio optimization under downside risk measures
Fuzzy Sets and Systems
A hybrid approach to asset allocation with simultaneous consideration of suitability and optimality
Information Sciences: an International Journal
Portfolio optimization of equity mutual funds: Malaysian case study
Advances in Fuzzy Systems
A hybrid approach for constructing suitable and optimal portfolios
Expert Systems with Applications: An International Journal
Solving portfolio optimization problem based on extension principle
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Fuzzy measures for profit maximization with fuzzy parameters
Journal of Computational and Applied Mathematics
A multi-objective genetic algorithm for cardinality constrained fuzzy portfolio selection
Fuzzy Sets and Systems
A portfolio selection model with borrowing constraint based on possibility theory
Applied Soft Computing
| Hi-index | 7.30 |
This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.