Multiobjective credibilistic portfolio selection model with fuzzy chance-constraints

In this paper, we propose a multiobjective credibilistic model with fuzzy chance constraints of the portfolio selection problem. The key financial criteria used are short-term return, long-term return, risk and liquidity. The model generates portfolios which are optimal to the extent of achieving the highest credibility values for the objective functions. The problem is solved using a hybrid intelligent algorithm that integrates fuzzy simulation with a real-coded genetic algorithm. The approach adopted here has advantage of handling the multiobjective portfolio selection problem where fuzzy parameters are characterized by general functional forms. Numerical examples are provided to demonstrate effectiveness of the solution approach and efficiency of the model.

► We propose a new multiobjective portfolio selection model in fuzzy environment.
► We model fuzziness using credibility measure of fuzzy events.
► We use fuzzy-chance constraints for measuring portfolio risk.
► A hybrid intelligent algorithm is designed to solve the mathematical model.
► The approach is useful when the fuzzy parameters take any general functional form.