Monte Carlo Estimation of Project Volatility for Real Options Analysis

Abstract

Volatility is a fundamental parameter for option valuation. In particular, real options models require project volatility, which is very hard to estimate accurately because there is usually no historical data for the underlying asset. Several authors have used a method based on Monte Carlo simulation for estimating project volatility. In this paper we analyse the existing procedures for applying the method, concluding that they will lead to an upward bias in the volatility estimate. We propose different procedures that will provide better results, and we also discuss the business consequences of using upwardly biased volatility estimates in real options analysis.