2099 From the results obtained we can conclude that: 1. Risk-return trade-off. The project, as shown, does not exceed the classic threshold of expected NPV > 0, nor P(NPV>0) >= 50%. The negative median and the mode near - 60MM indicate that most scenarios resulted in a loss. 2. What improvement would we need for a probabilistic "go" decision? • For P (NPV >0) ≅ 50%, the median would have to be shifted by +- US $ 33MM (Approx.). • For P(NPV>0) ≅ 60%, it is to improve the NPV by ≅ U $ 55MM (Through CAPEX/OPEX reduction, metallurgical recovery improvements, price optimization (hedging) or discount rate. • Upside exists, but with low probability: only 10.8% of runs exceed US$100 million, and above US$150 million it is 5.3%. 3. High risk of loss: 63.3% of simulations give an NPV < 0; only 36.7% are positive. 4. The recommendation to the board was that the project presented a lot of risk and that it was not advisable to make an investment. 8. CONCLUSIONS 1. Monte Carlo simulation allows replacing “a single outcome” with a “complete distribution of outcomes”. Monte Carlo simulation, on the other hand, produces thousands of possible NPV values, showing: • The entire distribution of results • Probabilities of loss or gain. • Extremes in queues (Successes or Failures) Making the evaluation probabilistic, not deterministic, which is much more realistic in mining where the variability of prices, grades, recoveries, costs and CAPEX is high. 2. It allows for the explicit quantification of project risk, enabling the following questions to be answered: • What is the probability that the NPV is negative? • What is the probability of losing more than US$100 million? • What is the likely range of the NPV? This ability to quantify transforms analysis into a decision-making tool, not just simple calculations. 3. Monte Carlo captures the correlations of the variables. Since mining projects are complex, the variables are not dependent. • The price of gold and silver are correlated. • Tonnage, grades and recoveries, you have a geological and metallurgical relationship. • CAPEX and OPEX often move together. • Exchange rates and commodity prices are related macroeconomic variables. Making the model very close to reality. 4. Monte Carlo simulation evaluates decisions under uncertainty (Risk based decision making). Monte Carlo not only analyzes but also allows for decisions such as: • Is it advisable to postpone an investment until the conditions are right? • Should we expand, reduce, abandon, or continue?
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