Valuing Real Options in the Volatile Real World - A Generalized Implied Binomial Tree Approach

Abstract

Motivated by the real-world challenges of real options evaluation faced by many companies when commodity prices exhibit dramatic volatility and project values can become negative, this paper presents a generalized framework for solving a multifactor real options problem by approximating the underlying stochastic process of project value with a displaced implied binomial tree. The proposed approach allows a flexible structure for stochastic processes with fat tail distributions such as jump diffusion or regime switch, and provides a more accurate estimate of the extreme downside risk by allowing negative values for the underlying project values. The value of a real option by the proposed approach is more accurate and stable than the alternative lattice-based approaches in the literature regardless of the underlying commodity process, which makes this a general and robust approach for valuing complex real options under multiple sources of uncertainty in the volatile real world.

Keywords: Extreme Downside Risk, Multifactor Real Options; Implied Binomial Trees; Simulation

JEL Classification: G10; G13