A prospect theory-based group decision approach considering consensus for portfolio selection with hesitant fuzzy information

The problem that firms usually face with is how to allocate limited funds to available projects. In this study, we develop a group decision-making approach to help managers to select optimal portfolio in which the group contains several experts who are invited to express their personal evaluations on candidate projects. The proposed approach considers not only the group intelligence, but also the consensus process of group decision making. Because of the uncertain environment of portfolio selection, especially when investing newly-established projects, the hesitant fuzzy information is considered in evaluating the performance of projects. Furthermore, the score function and deviation function of hesitant fuzzy numbers are used to depict the return and risk of the projects, respectively. In addition, the prospect theory is employed to reflect the psychological behavior of experts because they evaluate the projects relying heavily on their intuition under risk. A numerical example is given to demonstrate the applicability of the proposed method and comparisons are conducted to show the advantages of the method.