Abstract
Due to the complexity of the financial market, security returns are sometimes expressed by expert estimates rather than historical data. In this paper, we deal with a multiobjective multiperiod portfolio selection problem based on uncertainty theory. We propose a new uncertain multiobjective multiperiod mean-semisentropy-skewness portfolio optimization model, in which uncertain semi-entropy is used to quantify the downside risk. To be more realistic, several constraints are also considered, such as the transaction costs, cardinality, liquidity, budget, and bound constraint. Moreover, a novel hybrid technique, called the MFA-SOS algorithm, which combines the features of the firefly algorithm (FA) and symbiotic organism search algorithm (SOS) is designed to solve the proposed model. Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.
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