Aurora Borealis
1 November 1999 CFA Institute Journal Review

Mutual Fund Herding and the Impact on Stock Prices (Digest Summary)

  1. H. Kent Baker

The author investigates whether mutual funds tend to "herd" when trading stocks. He also examines the impact of herding on stock prices and whether any such impact is stabilizing or destabilizing by analyzing quarterly data for the 1975–94 period.

Mutual Fund Herding and the Impact on Stock Prices (Digest Summary) View the full article (PDF)

Several theories suggest that institutional investors might trade together, or in “herds.” These theories claim that institutional investors herd because they have an aversion to acting differently from other managers, receive correlated private information, infer private information from the prior trades of better-informed managers, and share an aversion to stocks with certain characteristics. Past research provides some support that institutional investors trade in herds.

The sample includes almost all mutual funds existing at any time during the 20-year period from 1975 to 1995. Over this period, dramatic increases occurred in the number of funds (from 393 funds to 2,424 funds), average fund size (from $98.6 million to $401.3 million), and the average number of stocks held per fund (from 44.6 stocks to 89.5 stocks). Wermers measures herding during calendar quarters by examining the proportion of funds that are buyers of a given stock. Thus, funds exhibit herding behavior if stocks tend to have large imbalances between the number of buyers and sellers.

The results show that the overall levels of herding by mutual funds in the average stock are not very large. Herding slightly decreases as trading activity by funds increases. For example, the average level of herding decreases for stocks traded by at least 5 funds compared with stocks traded by 50 or more funds. Growth-oriented funds show a greater tendency to herd than income-oriented funds. For example, aggressive growth funds have a level of herding about twice that of growth and income funds. Specialty funds, as indicated by Wermers' “International or other” category, show the greatest tendency to herd.

Wermers also examines levels of herding in subgroups of stocks with certain characteristics, such as similar market capitalizations and past returns, and with buy-side or sell-side mutual fund trading. The evidence shows that herds form more often on the sell-side than on the buy-side in trades of small stocks, but levels of buy-side and sell-side herding are similar for larger stocks. The most compelling evidence of herding occurs in sales of small stocks by growth-oriented funds. The levels of herding are also higher for stocks having extreme prior-quarter returns. Herding on the buy side is strongest in high-past-return stocks; herding on the sell side is strongest in low-past-return stocks. The results show little evidence of a relationship between sell-side herding and window-dressing strategies.

Wermers investigates whether stocks experiencing high levels of herding show a significant price adjustment and whether any such price adjustment is temporary or permanent. The results show a relationship between abnormal stock returns and the direction of herding in stocks. Stocks that are bought in herds outperform stocks that are sold in herds during the following six months. This return difference is particularly pronounced for small stocks. Another finding is that past returns are highest for stocks bought in herds and lowest for stocks sold in herds. Stocks sold in herds, however, exhibit a larger future return than stocks bought in herds. Future return differences appear to be permanent. Finally, the results show that herding speeds up the price-adjustment process and is not destabilizing. Wermers' use of quarterly data prevents him from making conclusions about whether herding destabilizes daily or weekly stock prices.

We’re using cookies, but you can turn them off in Privacy Settings.  Otherwise, you are agreeing to our use of cookies.  Accepting cookies does not mean that we are collecting personal data. Learn more in our Privacy Policy.