Release Notes
Change log for communicating new features, fixes, and revisions for Scenario Lab and Stress Test Lab.
1.2.0.11448 (2022-04-25)
We have added features and made improvements since our launch of Stress Test Lab.
Added
Modify probabilities of prospective stress scenarios and reconcile scenario estimates with your views.
Review the covariance matrix on the examine stress scenario screen.
Updated
Squashed bug that sometimes did not let users switch anchor scenarios.
1.2.0.11419 (2022-03-07)
We are proud to announce our newest innovation, Stress Test Lab! Stress Test Lab allows you assess the probability of stress scenarios. This work is based on recently published research in the Journal of Risk.
Added
Smart stress scenarios allow users to select data that lies above or below a certain percentile range for an economic variable.
Adaptive anchoring allows a user to forecast probabilities based on their views of economic conditions persisting or reverting to its historical norms.
Adjust the plausibility model to align theoretical assumptions with the empirical distribution.
Updated
Improved cyber security.
Improved chart presentation.
Improved performance of the application so you can analyze scenarios faster.
Improved table presentation.
Replaced scientific notation with rounding.
1.1.0.10829 (2020-12-08)
More improvements just in time for the holiday season, warm wishes from the Windham Labs team!
Added
Expanded data set available for analysis.
Licensing and security improvements.
Updated
Optimized loading of instruments and economic variables, 10x improvement!
Improved database infrastructure.
1.1.0.10755 (2020-11-16)
The Labs team have been busy generating new modeling ideas and implementing them for your analysis needs. We've added our recent research insight into a different approach to regression - for mapping relative scenario probabilities onto asset class returns.
Added
Access the Partial Sample Regression as a regression model for mapping scenario probabilities onto asset class returns, and configure a relevance threshold.
Added a Help menu item under the user profile.
Updated
Improve administration panel configuration.
1.1.0.10710 (2020-10-28)
Added
Partial sample regression model to the calculation engine (see the our research paper in the Journal of Portfolio Management September 2020)
New endpoints for Historical Events and authentication.
Updated
Prospective change to reference anchor scenario when calculating expected scenario returns.
Squashed bug when creating prospective scenarios with the same name as anchor scenarios.
1.1.0.10661 (2020-10-07)
Hello World! Scenario Lab's first version gets introduced to the market today.
Added
Export diagnostics data for advanced and internal users.
Updated
Fixed asynchronous request conflict on View Historical Impact screen.
View Historical Impact now defaults to grouping by attribute across all portfolios.
Independent variables treatment (yearly changes) in multi-factor regressions.
Updated research portal reference.
Minor UI revisions.
1.1.0.10621 (2020-10-05)
You can now review historical events and their impact across your portfolios and use a new index of the business cycle, the KKT Index - a recession probability indicator.
Added
The Kinlaw-Kritzman-Turkington (KKT) Index, a recession probability indicator, is now included in Scenario Lab.
View Historical Impact screen: analyze historical events across portfolios.
Updated
Improved server security.
Minor control behavior fixes across data selection screens.
Stability fix on Examine Scenarios screen.
1.0.0.10544 (2020-07-31)
Introducing Scenario Lab internally, we believe this is going to be a neat tool for analysts.
Added
Store and encapsulate case studies into "case files".
Select economic variable and asset data from a Windham-curated list of instruments.
Review timeseries and descriptive statistics about timeseries data.
Specify and customize prospective scenarios as projections of economic variables.
Analyze and update probabilities of prospective scenarios given anchor scenarios.
Inspect economic variable returns mapped onto asset class returns.
Observe each portfolio’s expected return based on (scenario) probability-weighted returns.
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