However, when the project involved is linked to commodities, mean-reverting assumptions are more meaningful. Previous works on stochastic project and investment cost concentrate on geometric Brownian motions (GBMs) for driving the factors.

In this work we are concerned with valuing the option to invest in a project when the project value and the investment cost are both mean-reverting. We derive the holding cost that optimizes the landowner's combined value of the option premium, holding costs and eventual royalties. Not only does the holding cost mediate between these two poles, but it provides the option seller (usually a landowner or a government) with a policy instrument for influencing the extraction timing and thus the extraction profit of the option buyer. Moreover, variations in the holding cost give rise to a host of investment decisions ranging from the standard real option solution for a zero-holding cost to a net present value solution for an infinite-holding cost. We claim that the combination of a convenience yield and an option-holding cost produces a more satisfying representation. His model pioneered the application of risk neutrality to uncertain investments, but his originality of introducing an option-holding cost albeit to overcome the extraction paradox is rarely imitated. PhD thesis View all references work as one of the earliest contributors to the real options literature. “ The valuation of reserves of natural resources: an option pricing approach ”.

This article evaluates Tourinho's (1979b)17. In each case, we use an example problem to show how a revised estimation methodology can be applied. We then generalize this development for the cases of levered cash flows and non-constant volatility. In this article, we extend that work by showing analytically the source of the overestimation bias and the adjustment necessary to remove it. Examples that illustrate this issue numerically have appeared in several recent papers, along with revised estimation methods that address this problem. Nonetheless, the simulation estimation method originally suggested for this purpose systematically overstates the project volatility, which can result in incorrect option values and non-optimal investment decisions. A common approach to estimating the project volatility in such instances is to use a Monte Carlo simulation where one or more sources of uncertainty are consolidated into a single stochastic process for the project cash flows, from which the volatility parameter can be determined. Most often, however, there is no market or historical data available to provide an accurate estimate for this parameter. One of the key parameters in modeling capital budgeting decisions for investments with embedded options is the project volatility.

Real options valuation risk case study