AB IQ Equities Case Study

Assessing Equity Allocations Using the Prime-Alpha Lens

30 April 2018

3 min read

Christopher W. Marx| Global Head—Equity Business Development

With capital-market returns likely to be lower in the years ahead, many institutional investors are taking a closer look at their portfolios and equity managers in order to improve returns. This includes reevaluating asset managers to understand the true return drivers and what investors are paying for.

Our prime-alpha tool is designed to help bring more transparency and clarity to this discussion. We recently had an opportunity to apply prime-alpha analysis during a series of conversations with a US public retirement plan sponsor.

Looking to Get More Out of Equities

Like many institutions we partner with, the plan’s chief investment officer (CIO) was exploring ways to increase the rate of return on plan assets in order to meet a higher return hurdle. An equity allocation would play a major role in that effort.

Clearly, an equity allocation shouldn’t be over-diversified and too benchmark-like, but it should also avoid unintended aggregate-level factor exposures. The CIO hoped that prime alpha, together with other tools, would provide deeper insight into how the equity managers fit—or didn’t fit—together, a key element in plan design.

Prime alpha helped us remove beta and the cyclical impact of factor exposures in order to isolate the idiosyncratic return derived from skill. Our research has found that prime alpha tends to be persistent over time: managers who deliver high prime alpha do it more consistently than do managers who simply beat a benchmark.

By applying the prime-alpha analysis, we were able to assess how the plan’s overall equity allocation worked together, whether the underlying managers effectively complemented each other and whether individual manager returns were delivering on the plan’s expectations.

Key Findings from Prime Alpha

The prime-alpha analysis was featured in a subsequent meeting with the plan sponsor, and it raised a number of conversation points to be followed up on.

Among the conclusions:

Low overall idiosyncratic exposure. Prime alpha revealed that the equity portfolio had relatively low idiosyncratic manager risk. Instead, it was largely driven by exposure to low-volatility and low-beta factors. Some of this exposure was strategic, from hiring low-volatility managers, but some was from implicit manager positions in other portfolios, leaving the equity portfolio more exposed to the cyclical nature of these factors than might be expected.

To address this issue, the plan could replace individual managers with these biases. In the plan’s small-cap allocation, for example, replacing specific small-cap managers could reduce the low-volatility and low-beta bias of that allocation and increase the amount of idiosyncratic skill. The plan might also consider replacing the explicit low-volatility allocation in its equity portfolio with a core equity strategy.

Value factor underweight. Prime-alpha analysis also revealed an underweight to the value style factor in the overall equity allocation. Given the demonstrated long-term performance of that factor over time, the plan might want to reconsider this underweight.

One way to address this bias might be to consider replacing specific investment managers in the plan’s international equity allocation who are benchmarked against a value index yet are underweight to certain value factors, including the book-to-price factor.

More clarity on performance and fees. The added clarity and transparency on the ingredients in managers’ returns—combinations of beta, factor exposure and management, and prime alpha—have clear implications for how to think about how much the plan is paying for these mixes.

For example, if naive factor exposure is uncovered, the plan could determine ways to replicate that exposure at a lower cost. The plan also wants to work through the implications of how to price active managers’ skill. For instance, how low should the base-fee level be set? Could it be reduced in some cases with the trade-off of higher incentive fees for alpha generation? What is the impact of greater fee variability?

The analysis and subsequent dialogue raised important questions and issues that still need to be worked through in collaboration with the plan, but prime alpha clearly brought a different perspective to the discussion. It also highlighted that, in the ongoing dialogue between plan sponsors and asset managers about performance and fees, more clarity is always better.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams.

About the Author

Christopher W. Marx

Christopher W. Marx is Senior Vice President and Global Head of Equity Business Development. He is responsible for overseeing the firm's team of equity investment strategists and product managers, setting strategic priorities and goals for the global Equities business, developing new products, and engaging with clients to represent market views and investment strategies of the firm. Previously, Marx was a senior investment strategist and a portfolio manager of Equities, and in 2011 he cofounded the Global, International and US Strategic Core Equity portfolios with Kent Hargis. He joined the firm in 1997 as a research analyst covering a variety of industries both domestically and internationally, including chemicals, metals, retail and consumer staples. Marx became part of the portfolio-management team in 2004. Prior to joining the firm, he spent six years as a consultant for Deloitte & Touche and Boston Consulting Group. Marx holds a BA in economics from Harvard University and an MBA from the Stanford Graduate School of Business. Location: New York

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Assessing Equity Allocations Using the Prime-Alpha Lens

Looking to Get More Out of Equities

Key Findings from Prime Alpha

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