Predictive Analytics for Manager Oversight

Redefining Active Risk
Isolates Skill and Reveals Closet-indexers

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Passive 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.

Premise

Active contribution is not simply performance relative to a particular benchmark, it is instead only that portion of incremental return which could not have been obtained passively.

The true passive alternative to an active portfolio is rarely a single index, but rather a combination of index funds with various market, sector, and style exposures.

In fact, defining active contribution as performance relative to a single index, when that performance can be achieved with a combination of passive index funds and ETFs at a fraction of the cost, is economically unsound and increasingly risky from a legal and regulatory perspective.

Current limitation

Current methods of separating active from passive performance are insufficiently robust and provably unable to distinguish between portfolios taking genuine security selection risk and those merely taking high systematic market, sector, or macro risk.

Evidence that existing analytics fail to accurately estimate risk exposures is the failure of estimated exposures to predict future performance.

This is a serious limitation as passive differences obscure active skill and inflate active risk.

Solution

Statistical factor risk models, using only passively-investable factors, precisely measure all current risk exposures (region, market, sector, and style betas, and all idiosyncratic security risk exposures) that together fully predict future performance.*

Accuracy of predictions is absolute proof of validity.

Implications

Closet indexing
One-third of active mutual funds take too little active risk to ever overcome fees, even if highly skilled.1

Popular methods of measuring active risk (Active Share, tracking error, downside deviation, Sharpe, Sortino, and information ratios, etc.) fail to identify most closet indexers because they confuse a single-index benchmark with the portfolio’s passive alternative, leaving asset owners exposed to the risk of paying active fees for passive contributions.2

Statistically persistent skill
Properly isolated from passive market noise, security selection skill shows strong statistical evidence of persistence.

Managers with top decile security selection information ratios are twice as likely to outperform as not over the subsequent three years. Managers in the bottom decile are more than twice as likely to underperform as not.3

Portfolio structure and Qualitative manager assessment
Managers with complementary exposures can be combined, or passive ETFs can be incorporated, to offset unintended passive differences with the aggregate benchmark, reducing relative risk while retaining the active risk worth paying for.

Manager discussions can focus on those exposures that will drive future performance as well as any unexplained changes in risk exposures or potential conflicts with mandate.

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Please let us know if you’d like to see an analysis of any particular managers or aggregate portfolio. We’d appreciate any feedback below, particularly if you’re working in the same direction.

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* 0.97 median correlation between predicted and subsequent realized returns

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1.  mutual fund closet indexing
2. testing Active Share 
3. performance persistence within style boxes
white paper

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