Forecasting Coal Price Using Static and Dynamic Stochastic Model as Based for Indonesia’s Mining Project Valuation with Real Option Method

Abstract

Indonesia's coal mining company is not only a capital-incentive business that needs high investment at the start of the project but also a cost-incentive business that needs high operational costs along the project. The most important parameter needed to determine the project value is assuming uncertainty of coal price in the future. This condition forces mining entrepreneurs to forecast future coal prices with the assumption. One of the approaches is using the Stochastic Model to predict price fluctuation in the future. There are two models: the static model, which uses 50 percentiles of historical data, and the dynamic model, which uses Monte Carlo simulation with normal distribution as the fluctuation of the percentile. Using the Real Options Method, this approach could make a difference in project valuation. This difference could give insight into the mining project valuation.