A new methodology to evaluate the real options of an investment using binomial trees and Monte Carlo simulation

This paper deals with a new methodology to evaluate the real operating options embedded in a manufacturing system investment. In a single product framework, the demand is assumed as the main source of uncertainty, therefore as a stochastic variable following a Geometric Brownian Motion (GBM). Then, focusing on the real option to expand the capacity at a certain time in the future, we have developed a new approach for the option payoff, looking forward in the time interval from the expansion date to the end of the planning horizon. The payoff function is the expected Net Present Value (NPV), at the expansion date, of the additional investment to increase the capacity, and it is calculated using Monte Carlo simulation. The option value is computed with a binomial tree algorithm. A numerical example and a sensitivity analysis of the option value as a function of some parameters are finally presented.