The First Predictive Risk and Skill Analytics
Passively-available beta differences with a benchmark are a byproduct, typically unintentional, of any stock-selection process. Since consistent passive differences, once properly identified, can be freely obtained or offset, they are not part of active contribution.
Isolating active performance from the impact of consistent passive differences offers tremendous oversight advantages.
Unfortunately, current methodologies all fail to properly define passive exposures. As a result current analytics fail to predict future performance, and analytics are only valid to the extent they are predictive.
If risk analytics are valid, they’re predictive. Analytics that fail to predict future performance are invalid.
We’re offering highly predictive* statistical risk models built to isolate active contributions from passively-available exposures — revealing security-selection skill that persists, true active risk, opportunities to reduce relative risk without sacrificing active risk, as well as to offset any unintentional bets that may endanger performance.