Analyst Recommendations, Mutual Fund Herding, and Overreaction in Stock Prices

1. Analyst Recommendations, Mutual Fund Herding, and Overreaction in Stock Prices Nerissa C. Brown University of Southern California Kelsey D. Wei University of Texas – Dallas Russ Wermers University of Maryland

2. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 2 Relevant Quotes by the Media “Mutual fund managers are extremely focused on the short term” Jason Zweig, Money Magazine “They (large investors) buy the same stocks at the same time and sell the same stocks at the same time” Louis Rukeyser, Wall $treet Week

3. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 3 Motivation Mutual funds tend to “herd” or exhibit correlated trading patterns (e.g. Grinblatt, Titman and Wermers 1995; Wermers 1999; Sias 2004). Mutual fund herds speed up the incorporation of information in stock prices in prior-studied periods (Wermers 1999). Prior studies provide little evidence on: why funds herd, beyond that they herd on certain stock characteristics (e.g., Falkenstein (1996), Wermers (1999) whether funds herd on public vs. private information

4. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 4 Main objectives We examine herding around an important price-setting mechanism in U.S. equity markets – recommendation revisions by sell-side analysts. We examine how analyst revision-induced herding impacts stock prices. We focus on analyst recommendations because: “clear and unequivocal” public signal of fundamental value (Elton, Gruber, & Grossman 1986). has short-lived investment value (Barber et al. 2001). institutional investors are sensitive to recommendation revisions and correct for potential biases (Chen and Cheng 2005, Mikhail et al. 2006).

5. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 5 Theories of Herding Principal-agent problem: money managers mimic others to avoid reputational risks. Scharfstein and Stein (1990; AER) Money managers receive correlated private information Some perhaps before others. Hirshleifer, Subrahmanyam, and Titman (1994; JF) Managers infer private information from trades of others. Bikhchandani, Hirshleifer, and Welch (1992; JPE) Institutional investors prefer highly liquid or low transaction-cost stocks Falkenstein (1996)

6. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 6 Empirical Predictionsof Herding Theories “Rational” herding stories (e.g., HST, BHW) Stock prices permanently adjust after fund herding Stabilizing “Irrational” herding stories (e.g., Scharfstein and Stein) Stock prices temporarily adjust after fund herding Destabilizing

7. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 7 Recent Empirical Work Lakonishok, Shleifer, and Vishny (1992; JFE) Pension fund herding Found little herding or momentum investing, except in small stocks Grinblatt, Titman, and Wermers (1995; AER) Mutual funds use momentum investing strategies Did not test long-term stock returns Sias (2004; RFS) Institutional trading is more strongly related to the past trades of others than to past returns.

8. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 8 Recent Empirical Work contd. Wermers (1999; JoF) Sample period: 1975 to 1994 Average level of fund herding is similar to LSV results More herds among growth- than income-oriented funds Similar herding on the buy- and sell-sides, except Stronger herding in small stocks, especially on the sell-side Stronger herding in high (or low) past-return stocks Herding is followed by a permanent price adjustment Biggest price adjustment in small stocks and during first 10 years (1975-1984).

9. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 9 Empirically Measured Herding “Trading together” is labeled “herding,” although it may be due to: Exogenous changes in # shares Controlled for Random occurrences Herding measure adjusts for this Herding on same information “Rational” Pure mimicry “Irrational

10. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 10 Data Quarterly portfolio holdings for all domestic-equity mutual funds between 1994 and 2003. does not allow us to capture intra-quarter round-trip trades. Thomson Financial (Available via WRDS). Matched with CRSP mutual fund returns and stock prices and returns. I/B/E/S analyst stock recommendations

11. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 11 Sample Selection Include only actively managed domestic funds, i.e., exclude index, international, bond, metals funds. New issues excluded for one year; delisted stocks excluded for prior year. Stock splits and other share adjustments “reversed” from end-of-quarter holdings and share prices. Each stock must be: traded by at least 5 funds. covered by at least 2 analysts.

12. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 12 Measuring Herding LSV (1992) herding measure: the proportion of funds trading stock i during quarter t that are buyers. E| pi,t - E[pi,t]| = adjustment factor for random variation Herding by a subgroup of funds is studied by limiting the herding measure calculation to that subgroup. Herding in a subset of stock-quarters is studied by averaging the measure over only that subset.

13. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 13 Limitations of the Measure “A trade is a trade,” no matter how big. A proxy must be chosen for we choose a cross-sectional average, but another approach would be a time-series average.

14. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 14 Conditional Herding Measures Buy- and sell-herding measures: is recomputed conditionally for each of these measures

15. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 15 Measuring Consensus Analyst Recommendation Changes = mean analyst recommendation (1 through 5) at the end of quarter t–i (i = 1,2) measured in quarter t–1 to mitigate possible spurious relations between herding and analyst revisions. Recommendations are brought forward a maximum of 180 days. If no recommendation update, CHGREC = 0 No recommendation change is treated as informative We use only the most recent recommendation issued by an analyst during a quarter.

16. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 16 Summary Statistics(Table I)

17. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 17 Summary Statistics(Table II)

18. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 18 Buy- and Sell-Herd Measures(Table III)

19. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 19 Buy- and Sell-Herd Measures(Table III contd.)

20. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 20 Multivariate Tests Controls: ULEVEL (DLEVEL) = “1” for stocks with consecutive strong buy (strong sell) recommendations. LAGBUY (LAGSELL) = “1” if stock is classified as a buy- (sell-) herd stock in quarter t–1. ADD (DROP) = “1” if stock added (dropped) from S&P 500 index. RET = prior-quarter stock return. SIZE = log of market capitalization. BM = log of book-to-market ratio. DISP = std. dev. of quarter t–1 analyst earnings forecasts (scaled by end-of-quarter price). STD = std. dev. of daily stock returns during quarter t–1. TURN = average daily trading volume divided by shares outstanding during quarter t–1.

21. Multivariate Tests (Table IV)

22. Herding and DGTW Returns (Table V)

23. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 23 DGTW Returns, Sorted by Recommendation Revisions (Table VI)

24. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 24

25. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 25 Alternative Herding Measure: Dollar Trade Imbalances (Table VII) Average quarterly price is used to compute $buys and $sells. Dollar-weighted, rather than # of funds weighted. Weaker relation between dollar trades and past returns. Future return reversals are similar to those for the LSV herding measure.

26. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 26 Winner vs. Loser Funds Do losing funds herd more? Funds are classified based on their past-year Carhart four-factor alpha Above-mean alpha are “winner funds”; below-mean are “loser funds.” Then, look at DGTW returns to herding within each subgroup of funds.

27. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 27 Winner Funds (Panel A: Table VIII)

28. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 28 Loser Funds (Panel B: Table VIII)

29. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 29 Robustness Tests 1. We control for other investment signals to make sure that herding is driven by analyst revisions (Table IX) Result: relation between herding and past analyst revisions becomes even stronger! 2. We substitute analyst earnings forecast revisions for recommendation revisions (Tables X and XI) Result: similar to results using recommendation revisions.

30. April 23, 2012 Analyst Recommendations and Mutual Fund Herding 30 Conclusions Herding much higher during 1994 to 2003 period than during 1975 to 1994. Strong reversals in abnormal returns, especially when herds follow analyst revisions. Herding stronger on sell-side; reversals also stronger when sell-herds follow analyst downgrades (relative to buy-herds following upgrades) Losing funds herd and trend-follow more than winning funds; seem to drive reversal. Herds of funds overreact to public information signals; partly driven by reputational effects.