Stochastic programming has been proposed to be used to cope with the uncertainty inherent in financial planning problems, e.g. asset allocation, asset and liability management and goal saving. Among the advantages of stochastic programming is the flexibility in tailoring the program to closely reflect the opportunities and constraints of reality. We take a look at different aspects that need to be addressed when approaching financial decision making with stochastic programming. These include representation of the uncertainty in a scenario tree, specification of the objective, and the incorporation of the decision maker's attitute towards risk. In addition, some simple examples are considered.
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