ON-DEMAND WEBINAR
What’s hiding in your “idio” risk?
Methods to discover hidden correlation
Look closer at residual risk, find hidden correlations and build more efficient portfolios
Duration
50 minutes
Fundamental factor models explain a lot about equity risk, but what they leave unexplained is worth a closer look. Leon Serfaty of SimCorp and Andrew Greenby of Ripple Effect Asset Management show how Comparable Company Specific Covariance and Axioma statistical models find correlations hiding in those residuals.
This webinar, presented with Future Alpha and Ripple Effect Asset Management, covers where correlations hide in residual returns, how to find them and the resulting risk forecasting for long-short portfolio construction when using two distinct methods.
Watch to learn:
- How Comparable Company Specific Covariance (CCSC) finds clusters of related companies within an industry
- How CCSC can be used to enable more efficient long/short portfolio construction by exploiting correlated residuals to build a better hedge
- How Axioma’s statistical model identifies the systematic risk associated with the AI buildout
- What a portfolio manager can do when two risk models disagree
Speakers:
- Leon Serfaty, CFA, Senior Principal, SimCorp
- Andrew Greenby, CFA, Chief Risk Officer and Chief Data Scientist, Ripple Effect Asset Management
Preview: What your factor model can’t explain still has explanatory power
Comparable Company Specific Covariance CCSC links companies in the same industry whose residual returns move together.
Preview: What does that do to the risk forecast for a gold miners ETF?
Axioma statistical models don’t start with preset factors. Instead, they find the shared drivers of returns in the data itself, so they can pick up themes that industry and style factors don’t capture.
Preview: How one statistical factor acted like an AI factor
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