
The paper refers to a model regarding the investment of a number of capital assets in order to obtain under the random returns of assets some desirable characteristics of the total return on the investment. The model is a stochastic optimization problem involving stochastic dominance constraints. Necessary and sufficient conditions of optimality and duality theory for these models are developed and it is shown that the Lagrange multipliers corresponding to dominance constraints are concave nondecreasing utility functions. Numerical results to illustrate the feature of the new models on a problem of investing eight assets in 22 years is given.
Programming in abstract spaces, stochastic programming, partial orders, optimality conditions, Applications of functional analysis in optimization, convex analysis, mathematical programming, economics, Stochastic programming, duality, Optimality conditions and duality in mathematical programming, stochastic dominance
Programming in abstract spaces, stochastic programming, partial orders, optimality conditions, Applications of functional analysis in optimization, convex analysis, mathematical programming, economics, Stochastic programming, duality, Optimality conditions and duality in mathematical programming, stochastic dominance
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 277 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
