A multiobjective multiperiod mean-semientropy-skewness model for uncertain portfolio selection

摘要

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.