Multi-period investment portfolio selection of interval programming based on quantum optimization algorithm

Considering the portfolio selection problem in emerging markets which constantly face a serious shortage of information, the single-stage method of interval analysis can estimate assets income, assets risk, and approximate ranges of assets liquidity. However, it is difficult to evaluate flexibly and accurately assets income, assets risk, and approximate ranges of assets liquidity for multi-stage investment portfolio. In this paper, a novel quantum optimization model was applied to interval analysis method for multi-stage investment portfolio. Firstly, the multi-period investment portfolio selection models are designed by using inequalities equations of interval coefficients. Secondly, to solve the multi-stage investment portfolio constraint, the quantum mechanics is used along with an adaptive strategy designed to determine the best particle`s positions for a better global position. Finally, the proposed constrained linear programming is validated by a practical example. Also, various decision-making factors were analysed for multi-period investment portfolio strategies which are compared with existing fuzzy portfolio selection models.