Abstract
AbstractA 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.
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