Examine Stress Scenarios
An explanation on how to use the examine stress scenarios screen
Last updated
An explanation on how to use the examine stress scenarios screen
Last updated
This is the core of Stress Test Lab. This screen allows you to
Create prospective stress scenarios and an alternative composite (non-stress scenario).
Review the underlying Covariance assumption.
Evaluate probabilities of stress scenarios relative to the alternative composite.
The grid at the top of the screen shows the stress scenarios (columns) and the corresponding economic variables / values (rows). Stress Test Lab measures the statistical distance of each stress scenario to an anchor condition: past historical norm or current prevailing conditions
Stress Test Lab then converts these statistical distances from either the historical norm or current conditions into relative likelihoods.
The relative likelihoods are then normalized and displayed as probabilities in the bottom grid.
To add a new stress scenario (column) in the top grid, click on the new stress scenario button, and follow on-screen instructions.
We provide a wizard option to help you set up each stress scenario.
To review the historical covariance used for the underlying analysis, click on Review Covariance to show a table of standard deviations and correlation coefficients across the economic variables.
The Gaussian probability column assumes that the statistical distances are normally distributed. Unfortunately, real world data is rarely this well behaved.
To account for non-normality, adjust the model to empirically align the statistical distances. We show the details of j adjustments as described in our research paper, you can review this by clicking the ellipses on the empirically aligned probability column.
