Mine Investment Analysis By The Generation Of Profitability Moments

In this paper, the authors present a typical mine profitability model. The method of generating system moments is used to examine the sensitivity of the profitability function to changes in the dependent variables, and to express the expected risk associated with undertaking the project in a predicted economic and technical environment. Profitability of a mining venture is a function of many variables ore grade, capital and operating costs, milling efficiency, ore reserve tonnage and annual tonnage, equity - loan structure, tax regime, etc. Estimates of the expected value and the variance of the profitability function are obtained by calculating the partial derivatives of the function with respect to the dependent variables, using the Taylor series expansion method to the second order. Sensitivity analysis is carried out by examining the effects of each variable on the profitability function, which is determined by the magnitude of the product of its partial derivative and variance. An appropriate probability density function, based on the expected value and the variance of the profitability function, is assumed to estimate the expected risk associated with the project. This expected risk is a measure of the area under the profitability density function below the appropriate, selected discount rate or the cut-off net present value (NPV). The results are compared with those obtained by using the Monte Carlo simulation technique, and they show that either of the two methods could be used to evaluate the probability of project failure or success with no significant difference.