There are several different methodologies for finding the value of assets or projects that have both underlying uncertainty and the managerial flexibility to optimize decision making. This has led to questions about the differences between approaches to these so-called real option valuation problems; the assumptions, mechanics, and applicability of the various methods for different problems.

In this paper, we show that traditional decision analysis methods can provide an intuitive generalized approach to valuing real options. The first characteristic of our approach is a departure from the binomial lattice framework with replicating portfolios that is typically implemented in the discrete-time approach in the Finance literature to a binomial decision tree with risk-neutral probabilities. This gives an equivalent but more intuitive framework for approximating the uncertainty associated with the changes in the value of a project over time. The second characteristic is a methodology for combining uncertainties for a project into a single underlying uncertain variable; the present value of the project itself. This approach provides greater flexibility in modeling of real problems, including the ability to include multiple underlying uncertainties and multiple options with complex payoff characteristics.

We apply this method to an example acquisition valuation problem, showing the specification of project uncertainties, cash flows, and decisions, and demonstrate how solutions can be obtained with commercially available decision tree software.

You can access this article if you purchase or spend a download.