Stochastic Network Programming for Financial Planning Problems

John M. Mulvey and Hercules Vladimirou
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John M. Mulvey: Department of Civil Engineering and Operations Research, School of Engineering and Applied Science, Princeton University, Princeton, New Jersey 08544
Hercules Vladimirou: IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, New York 10598

Management Science, 1992, vol. 38, issue 11, 1642-1664

Abstract: Several financial planning problems are posed as dynamic generalized network models with stochastic parameters. Examples include: asset allocation for portfolio selection, international cash management, and programmed-trading arbitrage. Despite the large size of the resulting stochastic programs, the network structure can be exploited within the solution strategy giving rise to efficient implementations. Empirical results are presented indicating the benefits of the stochastic network approach for the asset allocation case.

Keywords: financial planning; stochastic programming; generalized networks; scenario analysis (search for similar items in EconPapers)
Date: 1992
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