Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practi- cal investment decision-making problem. However, the existing literature on this field is almost undertaken by regard- ing security returns as random variables in the framework of probability theory. Different from these works, we as- sume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncer- tain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold con- straints into account, which an optimal investment policy can be generated to help investors not only achieve an opti- mal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dy- namic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.
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