Adding Alpha Through Investments in Hedge Equities

November 2010

This paper sets out a framework for long/short equity allocation, applicable both to long-only investors seeking to improve the risk and return characteristics of their equity exposure and to hedge fund allocators seeking explicit beta control. Allocating to equities has proved difficult in recent years, because hedge fund returns became more correlated with the broad equity market and long-only mandates delivered inconsistent alpha. The analysis links these issues to uncontrolled equity beta and proposes a structured way to allocate to long/short equity, often called hedge equity. It categorizes the manager universe by net market exposure and risk profile, so an allocator can dial equity beta up or down deliberately. It then examines how substituting a portion of a long-only allocation with hedge equity managers may improve a portfolio’s risk and return characteristics, how a portfolio can be tilted toward lower-beta managers to control market sensitivity, and how performance attribution can distinguish genuine stock-selection alpha from market exposure. The paper is written for institutional allocators, OCIOs, and consultants, and it frames its conclusions as analytical perspective grounded in a long historical study of manager returns.

What This Paper Examines

•  Why hedge fund and long-only equity allocations have become more correlated with the broad market, and how uncontrolled equity beta relates to inconsistent alpha.
• How the long/short equity universe can be categorized by net market exposure and risk profile into long-biased, opportunistic, and low-net styles.
• Whether substituting a portion of a long-only equity allocation with hedge equity managers can improve a portfolio’s risk and return characteristics.
• How a portfolio can be tilted across styles to achieve explicit beta control while retaining equity exposure.
• How performance attribution can separate stock-selection alpha from market timing, sector, and other sources of return.

Key Findings

• Long/short equity returns can carry stock-selection alpha alongside varying degrees of market beta. The return of a hedge equity manager reflects a blend of market beta, beta timing, and stock selection. Because managers differ in how much net market exposure they run, their returns tend to differ in the balance of these components.
• Categorizing managers by net exposure and risk profile supports explicit beta control. Grouping the universe into long-biased, opportunistic, and low-net styles, defined by net market exposure and statistical properties such as volatility and beta, lets an allocator raise or reduce equity beta deliberately rather than leaving it to drift.
• Substituting part of a long-only allocation with hedge equity managers can improve portfolio characteristics. Because hedge equity returns tend to compound with a different risk profile than the broad market, blending them into an equity allocation is associated with a more favorable balance of risk and return than long-only exposure alone.
• Downside behavior is a structural feature of the case for hedge equity. Long/short managers tend to participate in a portion of rising markets while giving back a smaller fraction of falling markets, which is associated with more resilient compounding across full market cycles.
• Performance attribution can distinguish genuine stock-selection alpha from beta. Adapting a classic attribution framework, returns can be decomposed into market timing, sector, and stock selection across the long and short books. This helps establish whether a manager adds value through security selection rather than market exposure.

The Authors

This paper is part of the long lineage of quantitative research that Versor’s founders began earlier in their careers and continue to build on at the firm today.

Deepak Gurnani, Founder and Chief Investment Officer

Deepak Gurnani is the Founder and Chief Investment Officer of Versor Investments. Deepak has three decades of experience in applying quantitative methods to uncover alpha across global equity markets. Over the past decade, he has focused on pioneering the use of AI and alternative data in equity investing.

Versor’s founders co-authored this research with Jonathan Feeny and Andrew Crane, colleagues at the firm where this work was originally conducted.

Disclaimer: Past performance is not necessarily indicative of future results. Not an offer to sell or a solicitation of any type with respect to any securities or financial products.

Methodology: The study defines long-only returns using major US equity indices and mutual fund indices, and represents hedge equity returns using published long/short equity indices across variable-bias, long-bias, and security-selection categories. It draws on manager data from third-party indices, consultants, prime brokers, and other networks, covering more than 1,500 US hedge equity managers and over 2,500 globally, and uses that breadth to construct bespoke style indices.

The method is framework-driven. Managers are grouped along two parameters, geographical exposure and risk profile, into long-biased, opportunistic, and low-net styles defined by net market exposure and by statistical measures of volatility and beta. The analysis then studies blended long-only and hedge equity allocations, examines drawdown and upside/downside capture across defined bull and bear phases, and applies a performance-attribution method adapted from the classic Brinson approach to decompose returns into market timing, sector selection, and stock selection across the long and short books. The historical study spans roughly the fifteen years to 2010, with a separate institutional composite examined over a three-year period.