Portfolio selection based on fuzzy probabilities and possibility distributions
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A class of linear interval programming problems and its application to portfolio selection
IEEE Transactions on Fuzzy Systems
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The business environment is fully characterized with uncertainties. In order to minimize risk and maximize future returns proper portfolio model must be designed. In this paper the application of fuzzy theory to portfolio selection is presented. Fuzzy logic is utilized in the estimation of expected return and risk. Using fuzzy logic, managers can extract useful information and estimate expected return by using not only statistical data, but also economical and financial behaviours of the companies and business strategies. In the formulated fuzzy portfolio model, fuzzy set theory gives chance of possibility trade-off between risk and return. This is obtained by assigning satisfaction degree between criteria and constraints and defining tolerance for the constraints in order to obtain goal value in objective risk function. Using the formulated fuzzy portfolio model, a Genetic Algorithm (GA) is applied to find optimal values of risky securities. The obtained results satisfy the efficiency of the proposed method.