Monte Carlo Simulation

A Monte Carlo simulation allows an organization to estimate the probability of several different outcomes when faced with a decision. This tool, which has uses beyond finance, utilizes random numbers to help the organization understand the ramifications of different courses of action under uncertainty. Not only can the most likely scenario be derived, but also realistic optimistic and pessimistic scenarios.

BENEFITS OF A MONTE CARLO SIMULATION

A Monte Carlo simulation breaks very complex problems down into manageable parts. The results give your firm better insights into realistic potential results.

THE MONTE CARLO SIMULATION PROCESS

Determine the nature of the simulation and the variables and components that will comprise it
Determine the appropriate values and probabilities for each variable-component combination
Ascertain the appropriate number of simulations and compute the results
Determine what percentiles of the results will serve as the most likely, pessimistic, and optimistic scenarios
If the output is deemed unacceptable, decide what actions can be taken to change the assumptions in order to obtain a more favorable result
Follow up as needed to evaluate actual results against expected values

FURTHER READING

These links elaborate on the topic at hand. They serve as a good starting point for those companies that would like to learn more or would like to address these topics “in house.” For those firms that prefer to continue to focus on their current responsibilities and would value the objective viewpoint of a professional from outside of the organization, click here.

Monte Carlo Simulation – Introduction
Excerpt: “Whenever you need to make an estimate, forecast or decision where there is significant uncertainty, you'd be well advised to consider Monte Carlo simulation -- if you don't, your estimates or forecasts could be way off the mark, with adverse consequences for your decisions! “

http://www.riskamp.com/files/RiskAMP%20-%20Monte%20Carlo%20Simulation.pdf
Excerpt: “This demonstrates the risk in the model. Based on this information, we might make different choices when planning the project. In construction, for example, this information might have an impact on our financing, insurance, permits, and hiring needs.“

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