Using Real Options Analytics to Improve the Capital Budgeting Process under Uncertainty

Abstract

Capital allocation processes are complex and time consuming in large organizations because of the diverse choices from projects proposed by various departments within the organization. Invariably these projects reveal various types of uncertainties in the amounts of investment needed, timing over which such investments are made, and technical and regulatory risks as well as ultimate benefits accruing to the firm. In practice, companies utilize basic financial evaluation tools such as the expected Net Present Value (NPV), what-if scenarios, and risk simulation along with qualitative judgments to judiciously allocate the limited resources and capital available to them. However, these basic tools have shortcomings of ignoring investment flexibility embedded in the investment projects. Many attempts have been made to remedy these shortcomings, but these attempts have created more methodology confusions. On the other hand, these also have perpetuated the practice of using the expected value criterion under the assumption that things will work out as expected over the long-run. However, it is important to recognize that real investments are not single decisions without future flexibility, but rather a basket of interacting options driven by many different uncertainties. At a single project level, real options thinking has been proposed in aiding this important evaluation process. That is, investments into products, systems or technologies, have a changing economic value showing downside risk and upside potential over the project life. However, this option framework has not been explicitly considered in allocating the limited capital among competing risky projects. This research is to address these needs and attempt to improve capital budgeting processes by developing a decision criterion which iii explicitly considers both the changing option values associated with each project and other financial analytics.