Scenario-Based Financial Planning in Gold Mining Under Commodity Price Uncertainty

Gold mining firms operate in an environment characterized by substantial commodity price volatility, capital intensity, and long investment horizons. Traditional deterministic financial planning frameworks are insufficient to capture the nonlinear and asymmetric risks associated with gold price fluctuations. This study develops a simulation-based scenario planning framework for gold mining firms, integrating deterministic scenario analysis with stochastic price modeling. Using a stylized and benchmark-calibrated financial model intended for methodological illustration rather than firm-specific forecasting, the study evaluates the impact of gold price uncertainty on key financial indicators, including EBITDA, free cash flow, and net present value. Monte Carlo simulations indicate substantial dispersion in financial outcomes, with approximately 28% of simulated realizations producing negative Net Present Value outcomes under baseline assumptions. The results further demonstrate that volatility significantly amplifies downside exposure despite positive expected returns, thereby highlighting the limitations of deterministic planning approaches. The findings suggest that probabilistic scenario-based financial planning provides a more comprehensive framework for evaluating financial resilience and tail-risk exposure in commodity-dependent industries.