Capital Budgeting Under Uncertainty - An Integrated Approach Using Contingent Claims Analysis and Integer Programming

Recently the application of contingent claims analysis and dynamic programming to project evaluation has attracted a lot of attention. These techniques are required, for example, if the value of a project develops stochastically over time and the decision to invest into this project can be postponed. Yet, so far there are no considerations regarding how this perception of projects reflects on a capital budgeting situation. We propose two approaches that integrate these methods with traditional capital budgeting models. A simple capital budgeting model can be formulated as the problem of finding the portfolio of options that has maximal value and fulfils the capital expenditure constraint. However, this model has some shortcomings regarding its applicability in traditional budgeting situations. Therefore, we define an alternative optimisation model that uses scenarios to depict a set of possible future states. The optimal portfolio is then equivalent to a dynamic investment strategy that determines a number of state-dependent optimal portfolios.

[1]  Samuel Karlin,et al.  A First Course on Stochastic Processes , 1968 .

[2]  Stewart C. Myers,et al.  A Programming Approach to Corporate Financial Management , 1974 .

[3]  S. Karlin,et al.  A second course in stochastic processes , 1981 .

[4]  L. Trigeorgis.  Real Options: Managerial Flexibility and Strategy in Resource Allocation , 1996 .

[5]  David E. Stout,et al.  A Framework for Integrating Capital Budgeting Analysis with Strategy , 1992 .

[6]  Sherwood C. Frey,et al.  Equivalent Mathematical Programming Models of Pure Capital Rationing , 1978 .

[7]  E. Thanassoulis.  SELECTING A SUITABLE SOLUTION METHOD FOR A MULTI OBJECTIVE PROGRAMMING CAPITAL BUDGETING PROBLEM , 1985 .

[8]  Martin R. Holmer,et al.  A stochastic programming model for money management , 1995 .

[9]  Nalin Kulatilaka,et al.  PROJECT VALUATION UNDER UNCERTAINTY: WHEN DOES DCF FAIL? , 1992 .

[10]  S. Ross,et al.  Option pricing: A simplified approach☆ , 1979 .

[11]  Raj Aggarwal,et al.  Capital budgeting under uncertainty , 1994 .

[12]  Eduardo S. Schwartz,et al.  Evaluating Natural Resource Investments , 1985 .

[13]  J. Hull.  Options, futures, and other derivative securities , 1989 .

[14]  Lenos Trigeorgis,et al.  A Log-Transformed Binomial Numerical Analysis Method for Valuing Complex Multi-Option Investments , 1991, Journal of Financial and Quantitative Analysis.

[15]  E. H. Bowman,et al.  Strategy through the Option Lens: An Integrated View of Resource Investments and the Incremental-Choice Process , 1993 .

[16]  Ji Soo Kim,et al.  Equivalent mathematical programming models of the capital budgeting problem , 1991 .

[17]  John M. Mulvey,et al.  Solving multistage stochastic networks: An application of scenario aggregation , 1991, Networks.

[18]  John M. Mulvey,et al.  A New Scenario Decomposition Method for Large-Scale Stochastic Optimization , 1995, Oper. Res..

[19]  Eduardo S. Schwartz,et al.  Investment Under Uncertainty. , 1994 .