What is the primary purpose of conducting a Monte Carlo simulation?

• A. To gain insight on the potential magnitude and probability of undesirable outcomes
• B. To identify the single best decision
• C. To replace all uncertainties with fixed numbers
• D. To compute exact future values

Answer: (A)

Monte Carlo simulation explores uncertainty by repeatedly sampling from input distributions and recomputing the model, producing a wide set of possible results. The strength of this approach is that it reveals not just a single forecast, but the range of outcomes and how likely each is. This lets you quantify risk: how big a loss could be, and how probable different levels of impact are. In short, its primary purpose is to gain insight into the potential magnitude and probability of undesirable outcomes, so you can assess risk and inform decisions under uncertainty. It does not identify a single best decision, because there may be trade-offs and uncertainty about future conditions. It does not replace all uncertainties with fixed numbers—that would defeat the purpose of modeling uncertainty. And it does not compute exact future values—the results are probabilistic, providing distributions, not precise point predictions.