SUSTAINABILITY UNDER EXTREME RISK: AN INTEGRAL PROBABILISTIC ASSESSMENT OF CASH COST AND NPV IN GOLD MINING WITH ADVANCED MONTECARLO SIMULATION F.E. Valdez 1Mining Management Institute, National University of Engineering, Peru, Presenting author: fvaldezn@mminstitute.net 2Mining Technology Lima, Peru ABSTRACT The financial evaluation of gold mining projects has traditionally relied on univariate sensitivity analyses or deterministic, optimistic, base case, and pessimistic scenarios that fail to adequately capture the inherent uncertainty of the industry. Given that critical variables such as the price of gold, metallurgical recovery, and operating costs exhibit simultaneous volatility and interdependent relationships, this approach is insufficient to estimate the true risk affecting project profitability. This study proposes the application of Monte Carlo simulation as the central methodology for analyzing operational financial risk in gold mining projects. To this end, historical and projected data for the main variables that determine economic performance are collected and processed. Based on this information, empirical or theoretical probability distributions such as Normal, Lognormal, or Triangular are fitted, and correlations between variables are incorporated. The execution of thousands of iterations allows for obtaining a probabilistic distribution of the Net Present Value (NPV), providing a comprehensive view of the risk. The results allow for the identification of key metrics for decision-making, such as Value at Risk (VaR), the probability of achieving a positive NPV, and variance contribution analysis, which reveals which variables have the greatest influence on the overall project risk. The study concludes that incorporating Monte Carlo Simulation transforms risk management from a limited qualitative process to a quantitative and predictive one, strengthening the strategic decisionmaking process and enhancing financial sustainability in gold mining operations. KEYWORDS Simulation, Risk Analysis, NPV, Cash cost, probability distributions. 1. INTRODUCCION Monte Carlo simulation is a widely used approach for modeling systems with multiple sources of uncertainty and dependencies, allowing for the estimation not only of expected values but also the full distribution of possible outcomes. In the mining sector, its application has proven
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