Swedroe: Research Highlights Active Mgmt Shortcomings

In many walks of life, trying to discern the lucky from the skilled can be a difficult task. For example, it seems like every time a professional sports draft occurs, debate again flares up over whether the evaluation of college (or even high school) athletes is an exercise in skill or in luck.

Were the Portland Trail Blazers unskilled in the 1984 NBA draft when they selected Sam Bowie with the second overall pick, just ahead of Michael Jordan? Or were they just unlucky? (Bowie went on to an uneventful and injury-plagued career, while Jordan led the Chicago Bulls to six championships and is considered by many to be the greatest basketball player ever.)

The point is that sometimes it’s not easy to distinguish luck from skill. This difficulty extends to the evaluation of active mutual fund managers. With that in mind, we’ll review the academic literature on the subject of luck versus skill in mutual fund performance. We will examine the results of five studies. The first is by Bradford Cornell.

Skill Vs. Serendipity

Cornell, who contributed to the literature with his study “Luck, Skill, and Investment Performance,” which was published in the Winter 2009 issue of The Journal of Portfolio Management, noted: “Successful investing, like most activities in life, is based on a combination of skill and serendipity. Distinguishing between the two is critical for forward-looking decision-making because skill is relatively permanent while serendipity, or luck, by definition is not. An investment manager who is skillful this year presumably will be skillful next year. An investment manager who was lucky this year is no more likely to be lucky next year than any other manager.” The problem is that skill and luck are not independently observable.

Because this is the case, we are left with observing performance. However, we can apply standard statistical analysis to help differentiate the two, which is precisely what Cornell did. He used Morningstar’s 2004 database of mutual fund performance to analyze a homogenous sample of 1,034 funds that invest in large-cap value stocks.

Cornell’s findings are consistent with the previous research. The great majority (about 92%) of the cross-sectional variation in fund performance is due to random noise. This result demonstrates that “most of the annual variation in performance is due to luck, not skill.” Cornell concluded: “The analysis also provides further support for the view that annual rankings of fund performance provide almost no information regarding management skill.”

French & Fama Weigh In
Our second study is by Eugene Fama and Kenneth French, who contributed to the literature with their study, “Luck versus Skill in the Cross-Section of Mutual Fund Returns,” which was published in the October 2010 issue of The Journal of Finance. They found fewer active managers (about 2%) were able to outperform their three-factor (beta, size and value)-model benchmark than would be expected by chance.

Stated differently, the very-best-performing traditional active managers have delivered returns in excess of the Fama-French three-factor model. However, their returns have not been high enough to conclude they have enough skill to cover their costs, or that their good returns were due to skill rather than luck.

Fama and French concluded: “For (active) fund investors the simulation results are disheartening.” They did concede their results appear better when looking at gross returns (the returns without the expense ratio included). But gross returns are irrelevant to investors unless they can find an active manager willing to work for free.

Increasing Difficulty
Our third study is “Conviction in Equity Investing” by Mike Sebastian and Sudhakar Attaluri, which appears in the Summer 2014 issue of The Journal of Portfolio Management. Their study is of interest because it showed a declining ability to generate alpha. The authors found:

• Since 1989, the percentage of managers who evidenced enough skill to basically match their costs (showed no net alpha) has ranged from about 70% to as high as about 90%, and by 2011, was at about 82%.
• The percentage of unskilled managers has ranged from about 10% to about 20%, and by 2011, was at about 16%.
• The percentage of skilled managers, those showing net alphas (demonstrating enough skill to more than cover their costs), began the period at about 10%, rose to as high as about 20% in 1993, and by 2011 had fallen to just 1.6%, virtually matching the results of the aforementioned paper by Fama and French.

Our fourth study is “Scale and Skill in Active Management,” which appeared in the April 2015 issue of the Journal of Financial Economics. The authors, Lubos Pastor, Robert Stambaugh and Lucian Taylor, provided further insight into why the hurdles to generating alpha have been growing. Their study covered the period 1979 to 2011 and more than 3,000 mutual funds. They concluded that fund managers have become more skillful over time.

They write: “We find that the average fund’s skill has increased substantially over time, from -5 basis points (bp) per month in 1979 to +13 bp per month in 2011.” However, they also found that the higher skill level has not been translated into better performance.

They reconcile the upward trend in skill with no trend in performance by noting: “Growing industry size makes it harder for fund managers to outperform despite their improving skill. The active management industry today is bigger and more competitive than it was 30 years ago, so it takes more skill just to keep up with the rest of the pack.”

Pastor, Stambaugh and Taylor came to another interesting conclusion: The rising skill level they observed was not due to increasing skill within firms. Instead, they found that “the new funds entering the industry are more skilled on average than the existing funds. Consistent with this interpretation, we find that younger funds outperform older funds in a typical month.” For example, the authors found that “funds aged up to three years outperform those aged more than 10 years by a statistically significant 0.9% per year.”

They hypothesized this is the result of newer funds having managers who are better educated or better acquainted with new technology, though they provide no evidence to support that thesis. They also found all fund performance deteriorates with age, as industry growth creates decreasing returns to scale, and newer, and more skilled, funds create more competition.

A Factor-Based Analysis
Our fifth and final study is “Mutual Fund Performance through a Five-Factor Lens,” an August 2016 research paper by Philipp Meyer-Brauns of Dimensional Fund Advisors. His sample contained 3,870 active funds over the 32-year period 1984 to 2015.

Benchmarking their returns against the newer Fama-French five-factor model (which adds profitability and investment to beta, size and value), he found an average negative monthly alpha of -0.06% (with a t-stat of 2.3). He also found that about 2.4% of the funds had alpha t-stats of 2 or greater, which is slightly fewer than what we would expect by chance (2.9%).

Meyer-Brauns also found that the distribution of actual alpha t-stats had shifted to the left of what would be expected from chance if all managers were able to produce excess returns over the five-factor model sufficient to cover their costs.

He concluded: “There is strong evidence that the vast majority of active managers are unable to produce excess returns that cover their costs.” He added that “funds do about as well as would be expected from extremely lucky funds in a zero-alpha world. This means that ex-ante, investors could not have expected any outperformance from these top performers.”

Summary

In 1998, at a time when about 20% of actively managed mutual funds were outperforming their risk-adjusted benchmarks, Charles Ellis called active management a loser’s game. What he meant was that, while it certainly was possible to win the game by selecting funds that would outperform, the odds of doing so were so poor that it wasn’t prudent to try.

Today the combination of academics having converted what once was alpha into beta (a common factor explaining returns)—thus eliminating potential sources of alpha—and that increasingly skilled competition has raised the hurdles, now only about 2% of actively managed mutual funds are generating statistically significant alpha. And that’s even before the impact of taxes on taxable investors.

The choice is yours. You could try to beat overwhelming odds and attempt to find one of the few active mutual funds that will deliver future alpha. Or you could accept market returns by investing passively in the factors to which you desire exposure. The academic research shows that investing in passively managed funds is playing the winner’s game.

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.