When to use Monte Carlo Simulation (and when not to)

See also: Introduction to risk analysis, Modeling with objects, Random number generation in ModelRisk, How_many_iterations_to_run

How to do Monte Carlo Simulations with ModelRisk

ModelRisk provides a large number of Monte Carlo functions that either sample from distributions (both univariate and multivariate) or return the values from more complex Monte Carlo simulation models. In order to get the greatest value from your Monte Carlo Excel add-in you should review this topic.

 We suggest that you write a model with ModelRisk as follows: the following steps:

1. Describe the model is words and diagrams;

2. Write the data in Excel (and label them) and construct the model, including distributions in Excel, to match your diagrams;

3. Use ModelRisk's "Add Output" button to nominate which cells are the outputs you are interested in and run (simulate) the model; and

4. Review the results in ModelRisk's Results Viewer.

Monte Carlo add-ins generally offer two methods of generating samples from probability distributions: Monte Carlo sampling, and Latin Hypercube sampling. There are also a number of other sampling methods available in simulation you may wish to investigate. All the methods for generating random samples rely on a Seed value, and it is sometimes useful to control that value to check the quality of your results.

A common question is how to determine how many iterations to run a Monte Carlo model for - discussed here.