Real Options Methods Illustrated

Abstract

In this chapter we will discuss different approaches to real options pricing. We will start with the analytical solution of the Black-Scholes equation, which will be applied to the case of Netscape. Subsequently, we will present the Cox-Ross-Rubinstein Approach to option pricing, a numerical method for solving dynamic programming problems. Dynamic programming problems are often solved by partial differential equations, which can become very complex and their analytical solutions are even more complex. Therefore, analytical dynamic programming is beyond the scope of this book. But, we will elaborate on numerical dynamic programming using the numerical method of Copeland and Antikarov (2001), which is applied to the case of Portes. This method is a combination of dynamic programming, contingent claims and Monte Carlo simulation. Furthermore, the case of Boeing is used to demonstrate an application of the Monte Carlo simulation approach by Datar and Mathews (2007). We will conclude the discussion on real options approaches with the spreadsheet approach of de Neufville et al. (2006), which includes the use of Monte Carlo simulation in Excel®, and optimizes the decision regarding the design of a parking garage. This final method is more known to the field of engineering, however, it’s a very interesting method to use, because it demonstrates the impact and importance of probability distributions on real options value. We will discuss this in more detail in Chap. 4. The concluding part of this chapter is the evaluation of the real options approaches by discussing the pros and cons of each approach.