Cut-off grade: A real options analysis

• The Cut-off definition of what constitutes ore is investigated.
• A stochastic dynamic optimal control based real options model is developed.
• Results show that optimal cut-off grades are lower in the presence of uncertainty as compared to those determined using industry standard deterministic models.
• The high cut-off levels that result from a failure to incorporate price, may be leading to greater resource waste than is optimal.

In this paper we examine the impact of forward price uncertainty on the optimal cut-off policy of mines. We employ a new real options model for determining the optimal cut-off grade of ore under stochastic prices. The economic insights and consequences of incorporating uncertainty into the cut-off decision making process are shown to be in opposition to that of traditional deterministic cut-off theory. Key among the new insights is that when prices are stochastic, optimal cut-off grades are much lower than those determined using traditional deterministic models that are currently used in practice. This implies that the traditional techniques may lead to greater resource waste than is optimal. This effect is most pronounced for higher volatility metals, marginal mines, higher discount rates and longer valuation time horizons. In addition to the important insights, the new model produces valuations, sensitivities and optimal cut-off strategies that can be used to enhance project valuation, mine operation, hedging strategy determination, mine design and risk management decisions.