Demystifying Hedge Funds: An Analysis of Trades and Alpha

December 2010

This collection brings together six studies that examine how five major hedge fund strategies actually generate their returns. The strategies covered are systematic merger arbitrage, convertible arbitrage, equity market neutral, distressed debt, and fixed income relative value. An overview study frames the common questions institutional allocators ask about hedge funds, whether they add sustainable alpha, and whether that alpha can be accessed more transparently and five companion studies then examine each strategy in depth. The unifying idea is that many managers within a strategy share a common set of trades, so simulating those trades at the security level can reproduce much of the strategy’s return character. Because the approach is rules-based, it is transparent by construction, which speaks to the process and portfolio transparency that institutional investors increasingly expect. The research is written for allocators, OCIOs, and consultants evaluating hedge fund strategies, and it frames its conclusions as analytical perspective grounded in long historical simulations.

What This Collection Examines

• Whether hedge funds add alpha, how they generate it, and whether that alpha tends to be sustainable.
• Whether the core return of a strategy can be captured with a transparent, rules-based set of common trades.
• How much of a strategy’s return comes from components shared across managers, rather than any single manager’s skill.
• Whether index-based replication and multi-manager indexes can reproduce a strategy’s returns, or only part of them.
• How the individual strategy portfolios combine into diversified multi-strategy portfolios.

Key Findings

• Within a strategy, a large share of return variation comes from components common to many managers. Managers who follow the same strategy tend to run similar trades. Identifying those shared components helps separate genuine manager alpha from returns that are simply the strategy at work.
• The core return of each strategy can often be captured with transparent, rules-based trades. Simulating the main trades of a strategy at the security level can reproduce much of its return character. This approach demystifies the strategy and supports transparency, in contrast to opaque, discretionary implementations.
• A high correlation to an index is not the same as capturing its alpha. A portfolio can track a benchmark’s risk closely while still leaving much of its average return behind. Evaluating a strategy fairly requires attention to both risk and return, not correlation alone.
• Index-based replication tends to capture risk more readily than alpha. Because these strategies deliberately hedge macro risks, approaches built from broad index or futures exposures often reproduce the risk profile but not the security-selection or trade-level return.
• Transparency, controlled leverage, and diversification are structural features, not afterthoughts. Rules-based portfolios can be run with controlled leverage and broad diversification, are less prone to blow-ups and style drift, and lend themselves to a core-satellite approach that pairs a transparent core with selectively chosen managers.

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.

Ludger Hentschel, Founding Partner, Investment Advisor

Ludger Hentschel joined Versor Investments as a Founding Partner and is based in New York. Ludger has over 20 years of experience in quantitative research and investing.

Versor’s founders co-authored this research with Dimitri Paliouras, Edward Nakon, and Leonid Keyser, 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 research spans five major hedge fund strategies, each simulated at the security or trade level rather than through index-level regressions. The universes are broad and liquid: global equities across developed Europe, Japan, the UK, and the US for the market-neutral work; announced mergers and tender offers across North America, Europe, and Asia for merger arbitrage; large, liquid convertible bonds in North America and Europe for convertible arbitrage; defaulted corporate bonds and loans for distressed debt; and government bonds, swaps, and related derivatives across four regions for fixed income relative value.

The methods are systematic and hypothesis-driven. They include factor-based mean-variance portfolio construction, delta-hedging, spread and carry analysis, a principal-components decomposition of hedge fund returns into common and idiosyncratic parts, and returns-based comparisons to hedge fund and investable indexes. Third-party data sources referenced across the studies include Bloomberg, Interactive Data Corporation, Worldscope, Thomson Reuters I/B/E/S, MSCI Barra, Moody’s, Markit, LoanX, and Monis. Sample periods run from the early 1990s through 2009.