Why would anyone want a hedge fund ETF?

By LARRY SWEDROE

In my opinion, the greatest anomaly in finance is that despite the miserable aggregate performance of hedge funds, the amount of assets under management in these vehicles has grown about tenfold over the past 20 years, to more than $3 trillion. As we began 2020, hedge funds, as measured by the performance of the HFRX Global Hedge Fund Index, underperformed the S&P 500 Index for 10 straight years.

Returning just 1.1 percent per year, they also underperformed every major equity asset class over the ten-year period, including the underperforming emerging markets, and even managed to underperform five-year Treasury notes. And they just barely outperformed, by 0.3 percentage point, the return of almost riskless one-year Treasury notes, which retuned 0.8 percent.

The results were the same for 2019. While the HFRX Global Hedge Fund Index returned 8.6 percent, it underperformed all major equity asset classes and five-year Treasuries, only outperforming the one-year Treasury note.

What about passively managed hedge fund ETFs?

One reason for the poor performance is the high cost of investing in privately managed hedge funds. An interesting question is how the performance of publicly available, passively managed hedge fund ETFs, with their lower costs, measures up. Jason Cheng, Joseph Fung and Eric Lam answer that question in their December 2019 paper The Performance of Passively-Managed Hedged ETFs.

Cheng, Fung and Lam begin by noting that while conventional, privately held hedge funds are available to only high-net-worth individuals and institutions that are not bounded by liquidity constraints, an HETF (a hybrid of hedge fund [HF] and exchange-traded fund [ETF]) offers investors a number of major benefits, including the following:

— As an ETF, they are highly divisible in investment amounts, allowing participation by retail investors.

— They expand the investment opportunity set for both individuals and institutions, which are prohibited from conducting short selling, margin purchase and derivatives trading.

— They are tradeable during the opening hours of their listing venue.

— They are translucent with respect to pre-trade and post-trade price and liquidity transparency, net asset value (NAV), and the level of benchmark index.

— Investors incur less trading and management costs compared to actively managed hedge funds.

— They are subject to regulatory oversights of the SEC and the CFTC (Commodity Futures Trading Commission).

The sample of HETFs analysed in the research covers the period 2008 through 2017. During this period, total assets under management (AUM) in the sample grew 517 percent, from $317 million in 2008 to $1.96 billion in 2017.

The total AUM of the 23 HEFTs included in the study amounts to 71 percent of all HETFs traded in the U.S. market in 2017, of which $1.38 billion (70.4 percent) are invested in global macro and $578 million (29.6 percent) in long-short strategies.

All the funds included in the sample adopt a replication approach to mimic their benchmark indexes, and most of them invest about 80 percent in the mimicking portfolio, keeping the remainder to buffer for market movements.

The authors measured the performance of the funds against their benchmark indexes as well as Fung and Hsieh’s 7-factor model, which explains about 80 percent of the monthly return variations of hedge funds.

Equity long-short hedge funds are exposed to two equity risk factors — market risk (as proxied by the S&P 500 Index), and the spread between small-capitalisation stock returns and large-capitalisation stock returns. Fixed-income hedge funds are exposed to two interest-rate-related risk factors — the change in 10-year U.S. Treasury yields, and the change in the yield spread between 10-year T-bonds and Moody’s Investors Service Baa bonds. Trend-following funds are exposed to the same risk factors as three portfolios of “look-back” options — on bond futures, on currency futures, and on commodity futures. They also benchmarked performance against Edelman, Fung and Hsieh’s revised 8-factor model, which adds an emerging markets factor to the 7-factor Fung-Hseih model.

Unfortunately, their sample does include survivorship bias, which they note.

Here is a summary of their findings:

— The average expense ratio is 1.19 percent. Long-short strategies have a higher expense ratio (1.36 percent) than global macro strategies (0.94 percent). While higher than the expenses of index funds, they are much lower than those of traditional hedge funds. Three of the funds had expense ratios of below 0.5 percent.

— The bid-ask spreads are almost 3 percent (2.99), making them expensive to trade. Both HETFs’ strategies experience large bid-ask spreads (2.68 percent for global macro and 3.18 percent for long-short).

— All global macro and all long-short HETFs underperform their benchmark index and the S&P 500 (on both the basis of absolute returns and Sharpe ratios), with a number of them significant at the 5 percent confidence level.

— All global macro fund returns are significantly positively related to market return, and all but two were negatively related to interest rate change (indicating limited diversification benefits).

— With the exception of two funds (CPI and GAA), global macro HETFs generate negative alphas at the 5 percent confidence level. Note that both have expense ratios below 0.45 percent.

— Most long-short funds actually have significant market exposure.

— Both the 7-factor and 8-factor models explain excess return of global macro strategy portfolios (67.9 percent and 81.9 percent) better than that of long-short strategy portfolios (45.6 percent and 47.6 percent), as a long-short strategy aims at lowering net market exposure.

— Long-short strategies generate larger negative 7-factor and 8-factor monthly alphas (-0.33 percent and -0.29 percent) than global macro strategies (-0.24 percent and -0.12%).

Note that the findings of large negative alphas are despite the study having survivorship bias. Their findings led Cheng, Fung and Lam to conclude that hedge funds cannot generate positive alphas. Another interesting and important finding was that all but six of the 23 funds have statistically significant tracking errors.

The authors also noted that prior research on the performance of hedge funds had found that the excess returns generated in the early years of the industry could not be maintained because their strategies can be subject to diminishing returns to scale as good performers tend to grow, and there is little evidence of persistence of performance beyond the randomly expected.

Summary

The findings of Cheng, Fung and Lam demonstrate that even with their relatively lower expenses, publicly traded HEFTs have been unable to generate alphas. Their findings that the 7-factor and 8-factor asset pricing models are able to explain large portions of the variation in returns also demonstrate that the funds are typically not providing unique diversification benefits that could not be obtained cheaper elsewhere. Their finding of large tracking error also creates a problem because investors cannot have confidence in what risks their portfolios have exposure to.

LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.

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