Over the past decade, our research has taken multiple in-depth looks at the exogenous drivers of what we think of as “alpha availability” among active managers. Our original work focused on smaller AUM managers’ ability to deliver relatively higher levels of alpha in various market environments (“Survival of the Nimble”). In early 2013 we expanded our analysis to identify active manager alpha drivers across markets and through time (“Is Active Equity Management Alpha on Permanent or Temporary Disability”). Building on our prior work, this study looks more in-depth at the concept of alpha availability (Part 1). We analyze the drivers of alpha availability with advanced techniques and higher resolution data (Part 2). Finally, we take a top-down look at the differences in quantitative managers’ return pattern vs. their fundamental peers (Part 3), which our colleagues wrote about earlier this year (“A Challenging Environment for Quant Strategies”).

Note to reader: Our use of the term “manager” represents the collective investment decision-making mechanisms of an investment strategy or portfolio. It includes the investment staff, systems, and quantitative models employed.

Key Takeaways from This Analysis:

  • High Active share is a necessary, but not sufficient condition for high levels of excess return. Active share magnifies the skill (or lack thereof) of the manager. The availability of alpha due to market conditions will have the largest impact on highly active managers.
  • The ideal market for active managers isn’t simply a bear market. In developed markets, active strategies perform best when there is concentrated weakness in benchmarks (a heavily weighted concentration in stocks lagging the index). This is almost always true in bear markets, but it is also common in the early cycle market rebounds.
  • Periods of large, concentrated benchmark weakness are infrequent and difficult to predict. More actionable factors that coincide with high levels of alpha availability are a low to moderate liquidity environment, moderate levels of factor skew, low correlations amongst stocks and well-defined expectations for economic policy.
  • The drivers of alpha availability are unique to the markets they operate in as well as the investment approach. There are distinct factors which benefit quantitative managers over fundamental managers and vice versa.

Part 2

Quantifying Alpha Availability

In Part 1 of this study we provide evidence supporting the validity of alpha availability; the idea that the macro environment and market dynamics will impact active managers’ ability to beat their benchmark and style. Now, we use the median manager’s performance within a universe as a proxy for alpha availability to identify those explanatory factors. We chose all actively managed SMA products with at least 3 years of history in 3 broad categories. U.S. Large Cap, Non-U.S. Large Cap, and Emerging Markets. For every 12 months, ending 12/31/1998 through 12/31/2020, we calculate the products’ gross excess return vs. the best-fitting benchmark.1 This last step is extremely important and a noticeable improvement upon prior work we have done. Matching each strategy to the most appropriate benchmark (Value, Growth, or Core) provided 2 distinct benefits; we significantly broaden our universe by including dedicated value and growth products and we remove the style bias from managers that have incorrectly classified themselves in the database (which is very common in the non-U.S. and EM universes).

Jump to Section

Quantifying Alpha Availability | Page 2
Selecting Explanatory Variables | Page 4
Analysis 1 | Page 7
Concentrated Gains and Losses | Page 10
Finding Actionable Insights | Page 11
Analysis 2 | Page 11
Variables & Analysis | Page 13
Summary | Page 16
Actionable Takeaways | Page 17
Conclusion | Page 20