Portfolio selection models based on Cross-entropy of uncertain variables

This paper researches the uncertain portfolio selection problem when security returns are hard to be well reflected by previous data. We take security returns as uncertain variables. Firstly, three new portfolio selection models are presented based on the cross-entropy of uncertain variables. Secondly, the crisp form of the new model is also provided when security returns are linear uncertain variables. In addition, the gravitation search algorithm and numerical integration are introduced to solve the proposed models. Finally, several numerical examples are presented to illustrate the effectiveness of the algorithm and the application of the mathematical models.