Stratified state aggregation (SSA) approach in real option valuation: combining price and grade uncertainties in tin mining projects

The only source of revenue for mining is the sale of its reserves. Therefore, a particular quantity of reserves and a specific selling price will generate a certain income. However, these income determinants are very unpredictable. Theoretically, real options (RO) substitute the discounted cash flow (DCF) approach to account for this uncertainty. Generally, RO quantify the uncertainty particularly related to price volatility. However, owing to its mathematical intricacy and application, the utility of RO is minimal. In addition, historical data analysis cannot be applied for spatial uncertainty related to grade uncertainty. Conventional RO approaches, such as the Black–Scholes method and lattice valuation technique, cannot measure a project with multiple uncertainties. In addition, these methods are mathematically complex and not sufficiently flexible for practical adaptation. This study proposes originality on simulation technique called stratified state aggregation (SSA) development that combined price and grade uncertainties in estimating the value of mining projects. For case study, a tin mining project of PT Timah Tbk in Indonesia was undertaken, specifically for short-term mine planning in underwater mining operations at two mining locations. We utilized the historical data natural logarithmic analysis to determine price uncertainty and conditional simulation to evaluate grade uncertainty. Our results indicated that mining uncertainties might be modeled using RO and value-added through SSA can be used to assess multi-uncertainty and multi-stage mining (rainbow option). The SSA decision aligned with the DCF method with improvement in uncertainty assessment. In addition, incorporating management flexibility may aid in alleviating concerns regarding the continuation or termination of a project.