The Monte Carlo Simulation can be used to model uncertainty in inputs or any problem having a probabilistic interpretation. It can be used to create prices for assets based on an average of hundreds to thousands of hypothetical scenarios.

Because this analysis is ultimately a statistical test, many of its drawbacks come from the assumptions that must be made to do it. One assumption is that these simulations are built around a specific type of statistical distribution. Using the incorrect distribution leads to meaningless results. Another example is that assumptions must be made about the inputs for this analysis. Selection of the inputs related to the probability of the success of what is being analyzed is a key issue that determines the usefulness of the simulation.