A Hedged Monte Carlo Approach to Real Option Pricing

TL;DR

This paper introduces a Hedged Monte Carlo method for valuing real options in projects, especially in incomplete markets with simulated cash flows, subjective views, and stochastic costs, enhancing valuation accuracy.

Contribution

It adapts the Hedged Monte Carlo strategy for real option valuation, accommodating subjective views, incomplete markets, and nonlinear cash flows, which are common in commodity projects.

Findings

Effective valuation of real options using simulated data

Incorporates subjective views and stochastic costs

Suitable for commodity-related project evaluation

Abstract

In this work we are concerned with valuing optionalities associated to invest or to delay investment in a project when the available information provided to the manager comes from simulated data of cash flows under historical (or subjective) measure in a possibly incomplete market. Our approach is suitable also to incorporating subjective views from management or market experts and to stochastic investment costs. It is based on the Hedged Monte Carlo strategy proposed by Potters et al (2001) where options are priced simultaneously with the determination of the corresponding hedging. The approach is particularly well-suited to the evaluation of commodity related projects whereby the availability of pricing formulae is very rare, the scenario simulations are usually available only in the historical measure, and the cash flows can be highly nonlinear functions of the prices.