| Summary: | Portfolio Management is the process of allocating an investor's wealth to in
vestment opportunities over a given planning period. Not only should Portfolio
Management be treated within a multi-period framework, but one should also take into consideration
the stochastic nature of related parameters.
After a short review of key concepts from Finance Theory, e.g. utility function, risk attitude,
Value-at-rusk estimation methods, a.nd mean-variance efficiency, this work describes a framework
for the formulation of the Portfolio Management problem in a Stochastic Programming setting.
Classical solution techniques for the resolution of the resulting Stochastic Programs (e.g.
L-shaped Decompo sition, Approximation of the probability function) are presented. These are
discussed within both the two-stage and the multi-stage case with a special em phasis on the
former. A description of how Importance Sampling and EVPI are used to improve the efficiency of
classical methods is presented. Postoptimality Analysis, a sensitivity analysis method, is also
described. === Statistics === M. Sc. (Operations Research)
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