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Capital Budgeting with Uncertain Future Opportunities: A Markovian Approach

Published online by Cambridge University Press:  19 October 2009

Shelby L. Brumelle  and
Bernhard Schwab
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Extract

The importance of an explicit consideration of uncertainty in evaluating the economic desirability of investment propositions is generally recognized in contemporary literature on capital budgeting. The emphasis has been on analyzing the effects of uncertainty of future cash-flows which result from an investment on the economic desirability of that investment. However, although future cash-flows are one important source of uncertainty, it should be recognized that other factors may contribute to uncertainty in a significant way. Uncertainty regarding alternate future investment opportunities is of obvious importance in the capital budgeting context. Thus, an investor who makes the best possible investment decision at a given point in time may deplore such a decision a short time afterward simply because his commitment prevents him from exploiting a better opportunity. While it might be assumed implicitly that an investor, in considering his alternatives, ought to include in such deliberations all the courses of action that may become available in the future, this aspect seems important enough to warrant explicit attention.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 8 , Issue 1 , January 1973 , pp. 111 - 122
Copyright
Copyright © School of Business Administration, University of Washington 1973

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References

[1]Blackwell, David. “Discounted Dynamic Programming.” Annals, Mathematics Statistics, vol. 36 (1965), pp. 226–235.CrossRefGoogle Scholar
[2]Breiman, Leo. “Stopping Rule Problems.” Applied Combinatorial Mathematics, edited by Beckenbach, E.F.. New York: John Wiley and Sons, 1964.Google Scholar
[3]Denardo, E.V. “Contraction Mappings in the Theory Underlying Dynamic Programming.” SIAM Review, vol. 9 (April 1967).CrossRefGoogle Scholar
[4]Howard, R.A.Dynamic Programming and Markov Processes. Cambridge, Mass.: Technology Press of MIT, 1960.Google Scholar
[5]Kushner, Harold. Introduction to Stochastic Control. New York: Holt, Rinehart and Winston, 1971.Google Scholar
[6]MacQueen, J., and Miller, R.G. Jr. “Optimal Persistence Policies.” Operations Research, vol. 8 (1962).Google Scholar
[7]Manne, A. “Linear Programming and Sequential Decisions.” Management Science, vol. 6 (1960).CrossRefGoogle Scholar
[8]Robichek, A., and Van Horne, J.. “Abandonment Value and Capital Budgeting.” Journal of Finance, vol. 22 (December 1967).Google Scholar
[9]Ross, Sheldon M.Applied Probability Models with Optimization Applications. San Francisco: Holden-Day, 1970.Google Scholar
[10]Schwab, B., and Lusztig, P.. “A Note on Abandonment Value and Capital Budgeting.” Journal of Financial and Quantitative Analysis, vol. 5 (September 1970)CrossRefGoogle Scholar
[11]Van Horne, J.Financial Management and Policy. 2nd ed.Englewood Cliffs, N.J.: Prentice Hall, 1971.Google Scholar