Journal of the Southern African Institute of Mining and Metallurgy
On-line version ISSN 2411-9717
ABDEL SABOUR, S.A. and WOOD, G.. Modelling financial risk in open pit mine projects: Implications for strategic decision-making. J. S. Afr. Inst. Min. Metall. [online]. 2009, vol.109, n.3, pp. 169-175. ISSN 2411-9717.
Strategic decisions in the mining industry are made under multiple technical and market uncertainties. Therefore, to reach the best possible decision, based on information available, it is necessary to integrate uncertainty about the input variables and model financial risk of the project's merit measures. However, this rovides few useful insights to decision-makers unless accompanied by modeling management responses to uncertainty resolutions. It is widely acknowledged that conventional decision-support methods based on static, no-change, discounted cash flow (DCF) techniques such as net present value (NPV) and internal rate of return (IRR) tend to provide inaccurate value estimates. This could mislead the strategic decision-making process and result in significant value losses. This paper aims to model financial risk related to uncertainty about market variables such as metal prices and foreign exchange rates. Other sources of risk that are related, for example, to geology and production costs are not considered in this work. The article outlines a flexible financial model that integrates uncertainty about market variables and management flexibility to react to uncertainty resolutions into mine project valuation using a real-options valuation technique based on Monte Carlo simulation. Significance of information generated from this simulation-based flexible valuation model to the strategic decision-making process is tested using an illustrative case study of a Canadian mining project. The project is a typical multi-metal, open pit mine that produces copper and gold. In this case, there are three uncertain market variables, which are: copper and gold prices and US$/CAN$ exchange rate. Financial valuations are carried out using both the conventional static DCF method and a flexible real-options model. In the flexible model, management flexibility to decide whether to go ahead with the next expansion or terminate production operations is integrated. Results show how the flexible financial model can enhance the decision-making process.