A Technical Framework for Monte Carlo-Based Coal Mining Valuation
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Abstract
Coal mining valuation must represent uncertainty from price cycles, output and cost variability, policy constraints, exchange rates, and capital market risk. Deterministic discounted cash flow remains a useful baseline but yields false precision for cyclical commodity businesses. A desk-based framework for Monte Carlo simulation in coal mining valuation is developed by synthesising valuation theory, mining risk literature, commodity price modelling, and simulation-based decision analysis across five stages: problem identification, free cash flow to firm mapping, input classification, distribution assignment, and output interpretation. Four blocks are integrated (operating assumptions, financial assumptions, simulation design, output interpretation) with seven stochastic drivers under lognormal, triangular, or truncated normal distributions: coal benchmark price, selling price realisation, production volume, operating margin, weighted average cost of capital, terminal multiple, and exchange rate. Interpretation rests on P10, P50, and P90 percentiles with sensitivity ranking rather than a single point estimate, supported by eleven matrices. Application is demonstrated on an export-oriented producer on the Indonesia Stock Exchange. Seaborne benchmark prices for 2001 to 2024 calibrate to a reversion speed of 0.328 and a 2.12 year shock half-life. Across ten thousand trials, value per share spans IDR 30,356 (P10) to IDR 75,048 (P90), median IDR 45,879, with the deterministic estimate 3.5% above the median and benchmark price years accounting for 72.5% of output variance. The approach supports mining economics teaching, preliminary investment risk screening, and empirical research.
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