TABLE OF CONTENTS Correlations can be applied in Risk Simulator in several ways, as long as there is more than one simulation assumption:
When defining assumptions, simply enter the correlations into the correlation grid in the Distribution Gallery.
With existing data, run the Multi-Variable Distribution Fitting tool to perform distributional fitting and to obtain the correlation matrix between pairwise variables. If a simulation profile exists, the assumptions fitted will automatically contain the relevant correlation values.
With the use of a direct-input correlation matrix, click on Risk Simulator Edit Correlations to view and edit the correlation matrix used in the simulation.
Note that the correlation matrix must be positive definite. That is, the correlation must be mathematically valid. For instance, suppose you are trying to correlate three variables: grades of graduate students in a particular year, the number of beers they consume a week, and the number of hours they study a week. One would assume that the following correlation relationships exist:
| Grades and Beer: ? | The more they drink, the lower the grades (no show on exams) |
| Grades and Study: + | The more they study, the higher the grades |
| Beer and Study: ? | The more they drink, the less they study (drunk and partying all the time) |
However, if you input a negative correlation between Grades and Study and assume that the correlation coefficients have high magnitudes, the correlation matrix will be nonpositive definite. It would defy logic, correlation requirements,...
