Selecting actively managed U.S. stock funds.
All right, perhaps that is an exaggeration. There surely must be a more difficult investment task than finding an active U.S. stock fund manager who is likely to outperform the stock market indexes over the next decade, after expenses.
I don't happen to know what that is, however. Whether academic studies, industry research, or Morningstar's Fund Manager of the Year selections, all results point to the difficulty of identifying consistently successful U.S. stock managers. The academic findings have been pessimistic, industry studies have echoed that note, and, while Morningstar's International-Stock Fund Managers of the Year have mostly gone on to great things and Morningstar's Fixed-Income Fund Managers of the Year on to good things, Morningstar's Domestic-Stock Fund Managers of the Year have looked distinctly ordinary after the fact.
The news isn't improving. Three Oxford University professors have released a study on the performance of pension-fund consultants when selecting active U.S. stock fund managers. Their conclusion: "We find that consultants' recommendations of funds ... have a very significant effect on fund flows, but we find no evidence that these recommendations add value to plan sponsors."
This isn't a conclusive finding. It uses only 13 years' worth of data, and it makes assumptions in translating consultants' recommendations into buy/not buy signals. The database of consultants' recommendations is self-reported, meaning that it is subject to various biases. Also, the sample size is small. Although the study tracks the seemingly large number of 1,500 fund recommendations each year, these come from an average of only 29 consultants. (Then again, there aren't many pension-fund consultants in the first place. The authors state that the consultants in the study "had a 91% share of the consulting market"--a vague statement, but nonetheless a sign that the findings are reasonably representative of that marketplace.)
Within that context, though, the professors did a thorough job. They examined each fund's results in three ways: 1) against individual style benchmarks (for example, Russell 1000 Growth), 2) against the Fama-French three-factor model that takes under consideration market, size, and value/growth performance, and 3) against the Carhart four-factor model that adds a momentum factor to the Fama-French calculation. They conducted these calculations on both an equal-weighted basis, wherein all funds counted the same regardless of asset size, and on an asset-weighted basis (which they term "value-weighted"). They then compared the aggregate results of the recommended funds to the aggregate results of the nonrecommended funds.
The showing was dismal on the equal-weighted basis. No matter which of the three performance measures was used, the single-style benchmark, the three-factor Fama-French, or the four-factor Carhart, the recommended funds lagged the nonrecommended funds. This held true for all seven investment styles (large-cap growth, large-cap value, mid-cap growth, mid-cap value, small-cap growth, small-cap value, and core). The typical underperformance was from 50 to 100 basis points per year. Most of these results were not statistically significant--but the direction was always wrong.
On the asset-weighted basis, the consultants fared better but not well enough to celebrate. Their results were positive for five of the seven investment styles according to all three models and were statistically significant (at the 1% level) for the three- and four-factor models with mid-cap growth funds. However, aside from mid-cap growth and small-cap growth funds, the margin of victory when it existed was very small.
The asset-weighted basis seems to me the fairest way of viewing the matter. When asked to select among the larger, better-known U.S. stock fund managers, the pension-fund consultants didn't cause harm. Their selections weren't worse than throwing darts (and were better with the two growth styles). The consultants were less successful as measured by the equal-weighted method because they tended to recommend the bigger fund managers, who tended to lag their smaller, less-known competitors.