Decision Sciences · 1978 · 42 citations · 12 references
BusinessDecision SciencesOptimizationPortfolio ManagementUncertainty QuantificationInteger ProgrammingOptimization Under UncertaintyPortfolio OptimizationPortfolio SelectionStochastic OptimizationStochastic ProgrammingMultiobjective Portfolio OptimizationPortfolio PlanningPortfolio Value At RiskProject Evaluation Under UncertaintyStochastic Integer ProgrammingStochastic Multi-criteria Optimization
Abstract There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse. The method involves the use of a time‐based decision tree structure called a “project tree.” Using this basic format, an illustrative six‐project example is presented and analyzed. Various forms of objectives are discussed, ranging from the maximization of expected portfolio value to the maximization of the minimum weighted portfolio deviation from two goals. In each case, formulated numerical problems are given, and the solutions derived are presented. The approach is shown to be very flexible and capable of handling a variety of situations and objectives.
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