Frontiers of Stochastically Nondominated Portfolios
提出用线性规划求解均值风险模型，生成二阶随机占优意义下的非支配投资组合，并开发参数化方法恢复整个有效前沿，适用于数千资产的大数据集。
We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution. We propose mean-risk models which are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second-order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean-risk efficient frontiers of these models and we illustrate its operation on a large data set involving thousands of assets and realizations.