"Average mutual fund managers show stock-picking skill, in the sense that the subsequent earnings announcement returns on their weight-increasing stocks are significantly higher than those on their weight-decreasing stocks."
Can mutual fund managers pick stocks that "beat the market"? This question has long interested economists because of its practical importance to millions of investors, who currently hold over $3 trillion in U.S. corporate equities through mutual funds, as well as for the light it sheds on the efficiency of securities markets. But despite many attempts to answer the question, no consensus has emerged. One problem is statistical power: a large fraction of the return on any fund manager's portfolio reflects luck, not skill. Isolating the component of returns that reflects skill is difficult. A second problem is defining risk-adjusted returns: portfolio performance must be adjusted for risk and, to date, the proper adjustment has eluded researchers. These problems cloud the interpretation of most studies of fund manager performance and have led to prolonged debate about whether fund managers can truly discern among winning and losing stocks.
In Can Mutual Fund Managers Pick Stocks? Evidence from the Trades Prior to Earnings Announcements (NBER Working Paper No. 10685), authors Malcolm Baker, Lubomir Litov, Jessica Wachter, and Jeffrey Wurgler introduce a new method to measure the stock-selection ability of fund managers based on returns around the time of earnings announcements. Their basic idea is to determine whether skill is associated with the tendency to hold stocks that are about to enjoy high earnings announcements and likewise to avoid stocks that are about to suffer low earnings announcements. Their approach has two key features, responding to the main difficulties with prior studies. First, it uses the segment of returns data -- returns at earnings announcements -- that contains the most concentrated information about whether a manager held a correct view on the stock's fundamentals.
The dataset merges mutual funds' portfolio holdings with the respective returns that each holding realized at its next quarterly earnings announcement. The portfolio holdings are drawn from mandatory, periodic SEC filings that have been tabulated by Thompson Financial. For each fund-date-holding observation, the authors merge in the return that that stock earned in the 3-day window around its next earnings announcement. The sample covers 1980 through 2002 and contains 6.3 million fund report date-holding observations with associated earnings announcement returns.
For each fund in this dataset, the authors track the subsequent earnings announcement returns for the stocks on which the fund increases portfolio weight over the prior period and the stocks on which it decreases portfolio weight. They find that the average mutual fund managers show stock-picking skill, in the sense that the subsequent earnings announcement returns on their weight-increasing stocks are significantly higher than those on their weight-decreasing stocks. The difference is about 12 basis points over the three-day period around the quarterly announcement or, multiplying by four, about 47 "annualized" basis points. The contrast between buys that initiate a fund's position in a stock, and sells that close out a position, is even larger. While these numbers are not large in absolute terms, they apply to only a small fraction of the trading year. More important, they constitute unusually clean evidence of trading skill.
The results do not reflect a pattern in which fund managers move toward categories of stocks (size, book-to market, and prior announcement returns) that are about to earn higher announcement returns. Instead, the bulk of the effect comes from picking stocks within these categories.
The authors also find significant differences in skill in the cross-section of funds. Funds that do better are more likely to have a growth than an income style, a finding that is consistent with other long-horizon studies. In addition, the authors find that larger funds, higher turnover funds, and those that use incentive fees show better performance, lending support to earlier studies that follow fund manager performance using long-horizon returns. However, the methodology allows these differences in performance to be linked more convincingly to information-based trading.
The methodology used in the paper largely avoids the problem associated with evaluating performance with risk-adjusted returns. Just as stock returns around earnings announcements are mostly abnormal, regardless of the risk adjustment, a mutual fund's returns from holding that stock are also mostly abnormal. In particular, by comparing the subsequent earnings announcement returns on stocks that a given fund has been buying to those on the stocks that it has been selling, the authors address even a strict version of the critique which argues that required returns are systematically different around earnings announcement dates. A related advantage of this approach is that it makes intensive use of the segment of returns data -- returns around earnings announcements -- that contain the most concentrated information about a firm's fundamentals and hence about a fund manager's skill at fundamental analysis. As a result, the authors' "earnings announcement alpha" methodology allows for sharp new tests for inform ation-based trading.
Although the authors find new evidence that mutual fund managers have some stock-picking skill, their approach, because it uses only a subset of total returns data and a particular, well-defined notion of skill, may not be suited to measuring the total returns earned by fund managers. They also do not address whether active mutual fund managers earn abnormal returns that are large enough to exceed the fees they charge. Their measures of skill are designed to establish a lower bound on the abnormal performance attributable to stock-selection ability. To that end, the "earnings announcement alpha" methodology offers a useful complement to the standard, long-horizon measures of fund performance.