Discounted Cash Flow (DCF) analysis is the most common form of evaluation of coal mining projects. However, DCF models suffer from a number of deficiencies. Firstly, they assume a project time horizon based on an assumption of extraction rates and current measured and indicated reserves. Secondly, they assume that discount rates will be constant over this time period. They frequently assume that coal prices and mining costs remain constant over the life of a project. Lastly, they do not explicitly allow for flexibility in changing the productive capacity of the mine as a consequence of adapting to changing market conditions or costs. Real Option Valuation (ROV) methods have been promoted in recent years as a means of incorporating flexibility within mining project evaluation. This flexibility relates to changes in mine productive capacity, specifically options to permanently or temporarily close, restrict or expand production. A common means of Real Options calculation is via Binomial Options Pricing (BOP) developed by Brennan and Schwartz. This research advances a number of innovative econometrics models for predicting: fossil fuel depletion times and, by inference, estimated coal mine lives; coal prices and mining costs in Australian surface coal mines. These econometrics models were then integrated into the BOP algorithm for calculating the value of coal mines when considering flexible options regarding productive capacity. These econometric models address many of the shortcomings of traditional DCF valuation approaches and recent ROV frameworks. The new econometrics model for fossil fuel depletion adapts the dynamic Klass formula, which utilises a continuous compound rate, and is a function of production rate and coal reserves. The model indicates that, at current consumption rates, coal will be the only fossil fuel available after 2042, and that coal will be available until at least 2112. The model can assist project managers in identifying policies to expand/shrink/close mining projects, increase exports, invest in additional connectivity to shipping facilities, or to estimate government policy and tax systems of the future. The new econometrics model for forecasting coal prices introduces a new version of the classical mean reverting model. The key characteristic of this new model is the addition of jump and dip in the model, measured on the basis of an extrapolation of the historical sinusoidal trend and upon the size of the historical jump/dip. This model was applied to the forecasting of nominal and real coal prices for the period from 2009 to 2018. An econometrics model for the cost of surface mining in Australia was developed using the Sherpa cost guide, Apex project valuation software and an InfoMine data set. The model uses operating and capital cost estimates derived from multiple variables such as the average seam thickness, the stripping ratio, the daily production rate etc. The cost model is also useful in estimating temporary closure costs, as re-opening costs used in the real option valuation method. The new econometrics models were incorporated into a revised BOP algorithm in order to restrict the search space of the algorithm according to expected mine life, and price and cost trends. The new Real Options Valuation algorithm was applied to a hypothetical coal project, demonstrating how hidden, extra value can be obtained in comparison to the use of traditional DCF evaluation techniques.
