Andrea Eisfeldt finds that hedge funds with infrastructure to execute sophisticated arbitrage crowd out less-expert investors
An asset that consistently provides a compelling risk-adjusted return would seemingly attract a new crowd of investors, the increased demand quickly driving down returns.
Yet that’s not always the case. More complex assets, such as mortgage-backed securities, which persistently generate outsized risk-adjusted returns when run through effective arbitrage strategies, tend not to be overrun by the capitalistic herd mentality.
A missed opportunity for the investing masses? Not exactly. UCLA Anderson’s Andrea Eisfeldt, Stanford’s Hanno Lustig and the University of Hong Kong’s Lei Zhang find that the complexity of the asset — more specifically, the need for an effective arbitrage strategy that grabs the excess return (alpha) without excess risk — creates a high barrier to entry.
The researchers developed a model using data from the Hedge Fund Research database. The structure of hedge funds lends itself to the world of complex assets, where extracting value works best with a two-step strategy: a long position in the asset that is focused on grabbing the potential alpha, along with a tracking portfolio run to hedge. It’s the latter that keeps demand lower. “Because each investor has their own model and strategy implementation, tracking portfolios introduce investor-specific shocks,” said Eisfeldt. That is, you’re only as good as your execution on the hedging side.
And that’s no small challenge. To capture the potential excess return of a complex asset while simultaneously taming risk requires a big-time investment in intellectual and operational capital. The more complex a strategy, the more Ph.D.-toting quants are needed to grind out sophisticated models with the support of a crack trading desk armed with state-of-the-art software and hardware that can deftly execute the strategy. That’s not exactly easy or cheap to build and maintain.
Moreover, shops with the highest level of expertise build in an extra advantage. “Investors with higher expertise have better models, and thus face lower risk,” write the authors in a working paper for the National Bureau of Economic Research. At lower risk levels, the expert can accept lower returns, again, effectively crowding out (less expert) participants who would need to chase after higher returns to compensate them for their inferior strategies, with higher risk.
Eisfeldt, Lustig and Zhang focused on funds trafficking in asset-backed fixed income, sovereign fixed income, convertible bond arbitrage and corporate fixed income relative-value strategies. They divided the funds into low, average and high tranches based on the complexity of their strategy. (The higher the fundamental risk of an asset before expertise enters the arena, the higher its complexity.) They then explored risk-return levels and participation rates at varying levels of complexity.
They find that the most complex strategies deliver alpha and higher risk-adjusted returns — as measured by the Sharpe ratio. But the level of expertise needed to extract the value dampens its popularity. In their model, less complex strategies have a Sharpe ratio of 0.50 and a 61 percent participation rate (among a class of sophisticated investors, not the general population). The most complex strategies deliver more than double that Sharpe ratio, but the number of participants is nearly halved. The researchers liken the dynamic to the “industrial organizational model” that gives more efficient (read: low-cost) expert manufacturers a competitive moat that can push out less efficient competitors.
“Thus, our theory explains why complex assets can have permanent alpha,” the researchers conclude. It might also help explain why the steep “2 and 20” standard fee structure for hedge funds is tolerated by investors.