What is Monte Carlo simulation? In short, it is a way to represent and analyze risk and uncertainty. It was named after the Monte Carlo Casino which opened in 1863 in the Principality of Monaco on the French Riviera. The Monte Carlo simulation generates random numbers using a pseudo-random number algorithm. The uncertainty in key input quantities is represented as a probability distribution.
In standard Monte Carlo simulation, a software program samples a random value from each input distribution and runs the model using those values. After repeating the process a number of times, usually 100-10,00, it estimates the probability distributions of uncertain outputs of the model from the random sample of output values. The larger the sample size, the more accurate the estimation of the output distributions.
A common misconception is that computational effort is combinatorial in the number of uncertain inputs – making it impractical for large models. This is true for simple discrete probability tree methods, but the great advantage of this method is that the computation is linear in the number of uncertain inputs. It is proportional to the number of input distributions to be sampled.
The sample size you need is controlled by the degree of precision that you want in the output distributions you care about. For example, you are interested in estimating percentiles of a cumulative distribution. There is no need to increase the sample size just because you have more uncertain inputs. For most models, a few hundred up to a thousand runs are sufficient. You only need a larger sample if you want high precision in your resulting distributions and a smooth looking density function. Given the inherent uncertainty of the inputs, higher precision is usually an aesthetic preference rather than a functional need.
Microsoft Excel and other spreadsheets do not support Monte Carlo simulation directly. But there are a number of software products that are add-ins to Excel that let you perform the simulation. There are products that are well known to do this, but what sets Analytica apart? We have designed Analytica specifically to perform Monte Carlo simulations so the probabilistic analysis is fully integrated into the product from the start. This gives Analytica certain advantages over spreadsheet add-ins in terms of ease of use and speed of computation. For more information about Analytica visit www.analytica.com or call 650-212-1212.
Analytica is a visual software environment for building, exploring, and sharing quantitative decision models such as the Monte Carlo simulation.