An Integrated Approach to Solve Resource-Constrained Real Options Problem under Multiple Risks

Zhu Xuejing

Abstract

Decision tree analysis is widely used to solve problems involving real options. It is more intuitive and has less restrictive assumptions compared to conventional option pricing techniques. However, due to the risk-neutral limitation, traditional decision tree analysis rarely considers decision makers’ risk attitude. Moreover, it only deals with unconstrained real options problem; while in practice most projects are constrained by different types of resources. Lastly decision tree analysis discount risks holistically by using a single discount rate, ignoring the impact of different risk types on project valuation.

This thesis reviews real option valuation methods, with the focus on decision tree analysis; from which derive an integrated approach to address the limitations of decision tree analysis in solving real options problems. The proposed approach is able to solve resource-constrained real options problem, taking into consideration the decision makers’ risk preferences and the impact of different risk types. The integrated approach consists of four steps. Step 1 is Problem Formulation, where project options are identified and project complexities are represented using a decision tree. Step 2 is Risk-based Adjustment, where project cash flows are discounted according to different risk types. Step 3 is where constraints are tackled through separate mathematical optimization models. In the last step, optimization models are integrated with decision tree to derive an optimal decision set.

Finally, a case study is used to illustrate the proposed methodology. The results show that the proposed approach can generate feasible strategy that maximizes the utilities based on decision maker’s risk preference while fulfilling budget constraints. In addition, the modularity of the optimization models allows the approach to solve any other real options problems with different constraint settings. Furthermore, the proposed approach can be readily implemented using Excel TreePlan or currently available decision analysis software, such as DPL.