Real option methods for improving economic risk management in infrastructure project finance

Effective risk management is essential for success in infrastructure project financing arrangements such as Build-Operate-Transfer (BOT). Both Sponsors and Lenders consider the revenue risk an extremely important factor when they assess a BOT project's feasibility. One potential strategy for mitigating the revenue risk is a revenue guarantee, where a guarantor secures a minimum amount of revenue for a project, and such guarantees take the form of a put option. Current valuation techniques: (a) lack the flexibility to structure these options in a manner that is affordable to the Government and attractive to the Private Sector, and (b) presume that a single guarantor, i.e. the Government, will underwrite the guarantee. These shortcomings open a research opportunity to explore the development of methods to value more flexible and affordable revenue risk mitigation contracts. This research presents a novel valuation framework that supports developing new types of revenue risk mitigation contracts. The approach provides BOT project participants with far more flexibility than prevailing methods. In the framework, the contracts are modeled as multiple-exercise real options and valued by two new valuation methods, the Multi-Least Squares Monte Carlo method (MLSM) and the Multi-Exercise Boundary method (MEB), which were derived by extending option theory. These two methods successfully combine Monte Carlo simulation and dynamic programming techniques to price multiple-exercise real options. A hypothetical case study illustrates the application and the potential of the two methods to serve as tools for risk mitigation in BOT projects. In addition, the general nature of the framework increases the scope of its applicability beyond the area of infrastructure project finance. It is flexible enough to assess any type of contract with multiple-exercise option characteristics.