Journal of the Southern African Institute of Mining and Metallurgy
On-line version ISSN 2411-9717
LANE, G.R; TERBLANCHE, M; MEYER, G and SASTO, N. Case study on quantitative risk modelling to obtain a realistic risk-adjusted project valuation. J. S. Afr. Inst. Min. Metall. [online]. 2013, vol.113, n.3, pp. 00-00. ISSN 2411-9717.
A large opencast gold mining company in Africa had just completed a feasibility study for an expansion of the operations. A traditional net present value project valuation methodology had been used that showed a very positive net present value (NPV). The project team had conducted a qualitative risk assessment that identified and logged all potential project risks and had subjectively incorporated 'risk' via the discount rate and other assumption contingencies around gold price expectations, operating parameters, etc. Management requested that an independent quantitative risk modelling approach be adopted to obtain a better understanding of the impact of risk on the overall project valuation and confidence level in the final valuation. A detailed project valuation model was configured in the Cyest Carbon Modelling Technology platform, and the stochastic modelling module used to perform the Monte Carlo simulations. Analysis of historical operational performance data relating to actual achievements versus planned and budget determined the historical variability of the underlying parameters as well as variance to budget. This was done at a detailed level for mining rates and costs, processing rate, costs and recovery, and other operational efficiency measures. External market assumptions relating to gold price, exchange rate, and inflation were modelled and the dependency between them modelled using a copula. This case study will demonstrate the approach taken to building and populating the quantitative risk model and the overall results of the Monte Carlo simulation. The final valuation demonstrated that the project had a 44 percent probability of an NPV less than zero i.e. a 44 percent chance of project finance loss.
Keywords : risk modelling; project valuation; NPV.