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Implementation of Large-Scale Financial Planning Models: Solution Efficient Transformations

Published online by Cambridge University Press:  06 April 2009

Roy L. Crum ,
Darwin D. Klingman  and
Lee A. Tavis
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Extract

It has long been recognized in the literature of finance that the robustness and analytical potential of mathematical programming procedures can be utilized to structure highly complex decision environments and to ascertain quickly and efficiently the dominant set(s) of actions for achieving an explicit objective(s). Although some formulations involve nonlinear relationships (for instance [13] [15]), the vast majority of the models appearing in the finance literature are variants of linear programming, including such identifiable methodologies as linear programming, goal programming, networks, integer programming, mixed integer programming, and chance-constrained programming. The decision processes for capital budgeting ([25] [1] [2] [4] [14] [16] [24]), working capital management ([20] [18] [21] [6]), cash management ([17] [23]), and portfolio selection ([22] [24]), have been structured as linear programs and have contributed significantly to understanding the dynamics of financial systems. Given the potential of these mathematical approaches, the limited industrial use of financial optimization models is disturbing.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 14 , Issue 1 , March 1979 , pp. 137 - 152
Copyright
Copyright © School of Business Administration, University of Washington 1979

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References

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