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Conditional Stochastic Dominance in Project Portfolio Selection

  • Samuel B. Graves
  • Jeffrey L. Ringuest
  • Andrés L. Medaglia
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 58)

Abstract

In Chapter 5 we described a method for deciding which projects to add to or remove from an existing portfolio. That treatment was restrictive in that it required knowledge of the decision maker’s utility function. This chapter moves toward a more practical methodology for the selection of projects to add to or remove from an existing portfolio. The analysis uses the criterion of conditional stochastic dominance to make selection recommendations. This criterion takes into account the effect of a given project on the risk and return of the existing portfolio. We use a methodology previously employed to analyze stock portfolios, however, we apply it using simulation, in an R&D portfolio context. We apply the methodology to the portfolios of two actual companies and find that it generates priorities very close to those developed by internal company heuristics. We show that this methodology can be applied appropriately in these circumstances and that its recommendations are consistent with observed decision maker behavior. These results provide further evidence that a manager should not consider project selection decisions in isolation, but, following the methodology recommended here, should take into account the context of the existing portfolio.

Keywords

Portfolio Return Project Selection Cumulative Probability Distribution Project Portfolio Stock Portfolio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Samuel B. Graves
    • 1
  • Jeffrey L. Ringuest
    • 1
  • Andrés L. Medaglia
  1. 1.Boston CollegeUSA

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