Fuzzy multi-objective portfolio selection model with transaction costs

Within the framework of credibility theory, several fuzzy portfolio selection models have been researched such as mean-variance model, chance constrained programming model, entropy optimization model and so on. However, all of them are proposed in the forms of single-objective programming, and there is no investigation on the transaction costs between the new portfolio and the existing one. In this paper, a fuzzy multi-objective mean-variance-skewness model with transaction costs is presented. In order to solve this model, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, relevance vector machine and fuzzy simulation techniques, where the relevance vector machine is used to approximate the expected value, variance and skewness of portfolio returns and the fuzzy simulation is used to generate the training data for relevance vector machine.