The Impact of Real Option Valuation in the African Gold Mining Industry: A Least-Squares Monte Carlo Approach

Dario Ravaglioli & Nils Maximilian Bachmann

Student thesis: Master thesis

Abstract

Enterprises in the mining industry operate in unpredictable environments, which exposes them to highly volatile cash flows. Simultaneously, they must spend significant upfront capital expenditures to finance their investments. Because of these factors, traditional valuation techniques might fail to accurately assess a project’s value. This study strives to appraise, how ROV in the mining industry can be used to improve the capital-budgeting decision process. Further, we combine an ROV-based explanation with a strategic assessment, why international companies have started to divest their holdings in South African gold mines in favor of Ghanaian ones. We do so by comparing hypothetical investment opportunities in a South African underground mine with a Ghanaian open-pit mine. To simulate each project’s volatility, we incorporate stochastic gold prices, exchange rate, and operating costs via Geometric Brownian Motions. We use the All-In Sustaining Costs calculated from a basket of companies to obtain the starting value of the operating costs and the mining Producer Price Index of each respective country to approximate its volatility and drift. Next, we use the Least-Squares Monte Carlo method to deduct the value of flexibility inherent in each mine design. We find that the Ghanaian mine has a higher NPV without the option inclusion, which reinforces our qualitative assessment. Further, we find that the options add significant value for both projects, making the overall project value difference smaller. Furthermore, the inclusion of a stochastic exchange rate parameter has a considerable impact on both mine designs, and yet seems to be underutilized in the mining ROV literature. Most importantly, we deduct that ROV is highly valuable for volatile industries to improve the decision-making process of capital budgeting problems.

EducationsMSc in Finance and Investments, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2020
Number of pages156