Portfolio Problems under the Convex Risk Measure of Distribution Uncertainty

Modern portfolio theory uses variance and standard deviation to assess risk, but it is less applicable in complex market situations, and it is difficult for investors to accurately predict asset returns. Based on this, this paper uses the convex risk measure suitable for non-normal distribution to measure risk, establishes a portfolio model under the uncertainty of return distribution, and uses the geometric solution method to discuss the existence of feasible sets and optimal solutions in different scenarios.