Cash flow at risk valuation of mining project using Monte Carlo simulations with stochastic processes calibrated on historical data

Abstract

ABSTRACT Mining projects are subject to multiple sources of market uncertainties such as metal price, exchange rates, and their volatilities. Assessing a mining project's exposure to market risk usually requires Monte Carlo simulations to capture a range of probable outcomes. The probability of a major loss is extracted from the probability density function of simulated prices at a given time into the future. This article proposes an approach to calibrate the stochastic process to be used in Monte Carlo simulations. The simulations are then used for measuring the cash flow at risk of a mining project. To assess the performance of the proposed approach, a case study is conducted on a mining project. The results show that the calibration approach is robust and apt at fitting various stochastic processes to historical observations.