Portfolio risk reduction: Optimising selection of resources projects by application of financial industry techniques

Abstract

We seek to forecast accurately the likely outcome of an exploration program - in particular minimum and maximum and average size of a success; also the chance of achieving a success. Commonly such predictions are employed in the resource industry, but only on a project-by-project basis. When a group of projects are combined in a portfolio, a higher level of evaluation is possible by quantifying the correlation coefficients among the projects. The outcome is that the result is not necessarily the sum of the parts. The approach in this paper draws on financial portfolio theory, and is routinely employed in the financial industry. It faces a similar challenge of forecasting outcomes (from investments). Analysing projects within a portfolio structure has the advantage of reducing the uncertainty for the resultantrange of deposit sizes that may be encountered after asuccess. It allows selection of the most efficient group of projects that maximises the expected NPV value for the total portfolio, while at the same time minimising the uncertainty in the range of NPVs that could be expected. Furthermore, if projects are selected with low correlation coefficients with each other (?diversification?), then the chance of obtaining one success is increased, compared to projects that are more positively correlated.