Risk Modeling Using Direct Solution of Nonlinear Approximations of the Utility Function
开发了一个风险模型，通过非线性规划直接求解期望效用最大化问题，支持递增、恒定和递减绝对风险规避的效用函数，并在正态、均匀和三角数据集上进行了演示。
Abstract A risk model is developed which involves direct solution of the expected utility maximization problem utilizing nonlinear programming. The model permits the use of utility functions exhibiting increasing, constant, and decreasing absolute risk aversion. Demonstrations are done using functions exhibiting such properties over normal, uniform, and triangular data sets.