Research Articles

Can Mutual Fund Managers Pick Stocks? Evidence from Their Trades Prior to Earnings Announcements

Malcolm Bakera1, Lubomir Litova2, Jessica A. Wachtera3 and Jeffrey Wurglera4

a1 Harvard Business School, Soldiers Field, Boston, MA 02163, and NBER. [email protected].

a2 Washington University in St. Louis, Olin Business School, Campus Box 1133, St. Louis, MO 63130. [email protected].

a3 University of Pennsylvania, Wharton School, 3620 Locust Walk, Ste. SH-DH 2300, Philadelphia, PA 19104, and NBER. [email protected].

a4 New York University, Stern School of Business, 44 W. 4th St., Ste. 9-190, New York, NY 10012, and NBER. [email protected].


Recent research finds that the stocks that mutual fund managers buy outperform the stocks that they sell (e.g., Chen, Jegadeesh, and Wermers (2000)). We study the nature of this stock-picking ability. We construct measures of trading skill based on how the stocks held and traded by fund managers perform at subsequent corporate earnings announcements. This approach increases the power to detect skilled trading and sheds light on its source. We find that the average fund’s recent buys significantly outperform its recent sells around the next earnings announcement, and that this accounts for a disproportionate fraction of the total abnormal returns to fund trades estimated in prior work. We find that mutual fund trades also forecast earnings surprises. We conclude that mutual fund managers are able to trade profitably in part because they are able to forecast earnings-related fundamentals.


We thank Stephen Brown (the editor), Susan Christoffersen, Marcin Kacperczyk, Andrew Metrick, Lasse Pedersen, Robert Stambaugh, Russell Wermers (the referee), Lu Zheng, and seminar participants at New York University, Yale University, the 2005 European Finance Association Meeting, the 2005 University of Colorado Investment Conference, and the 2005 Western Finance Association Meeting for helpful comments. We thank Christopher Blake, Russell Wermers, and Jin Xu for assistance with data. Baker gratefully acknowledges the Division of Research of the Harvard Business School for financial support, and all authors thank the Glucksman Institute at NYU Stern School of Business.