Portfolio optimization model with uncertain returns based on prospect theory

Abstract When investing in new stocks, it is difficult to predict returns and risks a general way without the support of historical data. Therefore, portfolio optimization model with an uncertain rate return proposed. On this basis, prospect theory used for reference, then established from perspective expected utility maximization. An improved gray wolf (GWO) algorithm designed because complex nonsmooth nonconcave characteristics model. The results show that GWO superior traditional particle swarm genetic algorithm.