Swedroe: Hard To Time Outperformance

April 30, 2014

Outperformance is linked to luck and skill, which makes it almost impossible to see it coming, Swedroe says.

The efficient market hypothesis asserts that financial markets are “informationally efficient”; that is, investors shouldn’t expect to consistently achieve returns in excess of average market returns on a risk-adjusted basis, given the information available at the time the investment is made. However, we know that the market isn’t perfectly efficient.

In fact, as I explained in my Seeking Alpha series on the subject, it doesn’t hold for any of the three forms of market efficiency: strong; semi-strong; or weak. However, there’s a large body of evidence demonstrating it succeeds in the only way that really matters: There are fewer active managers that outperform appropriate risk-adjusted benchmarks, after expenses, than would be randomly expected. In addition, there’s little to no evidence of persistence of performance beyond the randomly expected.

It’s important to understand that this doesn’t rule out the possibility that some investors will outperform. In fact, given the large numbers of investors engaged in the effort, randomly we should expect to see many outperform their appropriate risk-adjusted benchmarks purely by chance. However, we should expect that as the investment horizon increases, the percentage that outperforms will decrease.

As Bradford Cornell of the California Institute of Technology put it, “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’s 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.”

Since skill and luck are not directly observable we are left with observing performance. However, we can apply standard statistical analysis to help differentiate the two.

Brad Cornell’s 2009 study, “Luck, Skill and Investment Performance,” 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 found that the great majority (92 percent) 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.”



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