The financial valuation of mining assets has a number of fundamental differences to the valuation of many other asset groupings. One such difference is that typically, the greater proportion of both the cost and revenue sides of the cash flow are inherently governed by systemic market forces.
As a result, the range of outcomes for the valuation of each mining asset is more unpredictable, with higher levels of risk and uncertainty. In contrast, the management function of many other non-mining businesses or industry groups can control at least a portion of the cash flow by maintaining the margin or controlling the sales price. The management teams of mining businesses and operations typically have limited options, and are thus price-takers for both costs and revenues. As mining is an inherently cyclical industry, large, long-life operations can exist through several price cycles, making valuation both subjective and challenging.
The outcomes of both static- and stochastic-based valuations, as well as the internal probabilities of the associated cash flow statements, are significantly impacted when the correlations between the appropriate parameters are quantified, modelled and incorporated into the valuation framework. The appropriate parameters for correlation modelling primarily include those that are governed by systemic market forces. Applying this process results in a different risk profile for the asset by allowing the risks resulting from systemic market movements to be more accurately quantified and then objectively minimised. This process also reduces the level of residual uncertainty in the valuation outcome.
This paper presents a valuation methodology to pragmatically incorporate this level of valuation sophistication and statistically quantify the associated increase in the level of confidence of the valuation outcomes reported.
Holloway, E C, 2016. Correlated valuation methodology, in Proceedings Project Evaluation 2016, pp 181–200 (The Australasian Institute of Mining and Metallurgy: Melbourne).