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Would presenting a project’s financial plan to your management or venture capital group sound better if instead of saying the 10 year NPV for Project Alpha is blah, blah, blah, you could present the results as there is 80% probability that the NPV is above this amount and the project is the most sensitive to market timing and pricing. If so then a Monte Carlo simulation is what you need.

Monte Carlo Simulation is an excellent tool for risk analysis in quantitative analysis and decision making, especially financial risk. While it can be used in a number of ways, finance is still the number one use that I have seen for this type of simulation. Instead of presenting a single number, a Monte Carlo Simulation will do 1,000′s of calculations based on the ranges you assign to your variables. This gives you a much larger picture of an opportunity. Also with the software you can run robust sensitivity analysis that show which of your variables is driving the calculations.


Monte Carlo simulations were first done for the Manhattan Project and derives it’s name from Monte Carlo, Monaco. It incorporates variability and risk determination into the evaluation. It is often characterized as “Brute Force” computation. However today’s modern PC’s have more than enough computational power to quickly calculate a several thousand sample size.


Decision makers need to understand both variability and uncertainty. With variability, there is the certainty that different items are subjected to risks. With uncertainty, one needs to judge how probable those risks will be estimated. There are many types of Risk Assessment; single point estimates which is what many decisions today are still based on, range estimates which are typically calculated with three points (Best, Worst and Most likely) and what if scenarios. Monte Carlo simulations aid decision makers in understanding variability and probability when looking at projects.

Let’s look at an example. Suppose you have a Project A that has an

Software:

1. @RISK performs risk analysis using Monte Carlo simulation to show you many possible outcomes in your Microsoft Excel spreadsheet.
2. Risk Solver is the easiest, fastest, and most powerful tool you can buy for risk analysis of your Excel models, using Monte Carlo simulation.
3. Lumenaut Monte Carlo Risk Simulation PackageThe Lumenaut Monte Carlo Simulation package provides a range of tools that enable the user to easily and quickly build interactive monte carlo risk simulation models natively in Excel.
4. Oracle Crystal Ball – Oracle Crystal Ball is the leading spreadsheet-based application suite for predictive modeling, forecasting, simulation, and optimization. It gives you unparalleled insight into the critical factors affecting risk. With Crystal Ball, you can make the right tactical decisions to reach your objectives and gain a competitive edge under even the most uncertain market conditions.