The study of distributionally robust reward-risk optimization models with moment-based ambiguity set
This article studies the reward-risk optimization model under the uncer-tain distribution of random variables.In view of the three typical problems of traditional reward-risk and the background of uncertainty of distributions,a new model of distri-butionally robust reward-risk optimization is proposed under more general conditions.Based on moment ambiguity set and optimal duality theory,the complex new optimiza-tion model is simplified to a nonlinear optimization problem of conventional structure.The equivalence of efficient frontier of three types of distributionally robust reward-risk optimization models is proved theoretically.Numerical example verifies the effectiveness of the theoretical analysis.
万方数据
维普
