tailieunhanh - Mutual Fund Herding and the Impact on Stock Prices

Historically speaking, the earliest asset pricing models made rel- atively simple predictions about what it means for a benchmark to be OE to a managed portfolio. The Capital Asset Pricing Model of Sharpe (CAPM, 1964) implies that all investors should hold a broadly diversified “market portfolio,” combined with safe assets or “cash,” according to the investor’s tastes for risk. It follows that an OE portfolio is a broadly diversified portfolio, combined with safe assets or cash, mixed to have the same market risk exposure, or “beta” coefficient as the fund. This is the logic of Jensen’s (1968) alpha, which remains one of the most widely used measures of risk- adjusted. | THE JOURNAL OF FINANCE VOL. LIV NO. 2 APRIL 1999 Mutual Fund Herding and the Impact on Stock Prices RUSS WERMERS ABSTRACT We analyze the trading activity of the mutual fund industry from 1975 through 1994 to determine whether funds herd when they trade stocks and to investigate the impact of herding on stock prices. Although we find little herding by mutual funds in the average stock we find much higher levels in trades of small stocks and in trading by growth-oriented funds. Stocks that herds buy outperform stocks that they sell by 4 percent during the following six months this return difference is much more pronounced among small stocks. Our results are consistent with mutual fund herding speeding the price-adjustment process. Do institutional investors flock together or herd as it is often called when they trade securities Do some investors follow the lead of others when they trade Such questions have interested researchers for some time and are central to understanding the impact of institutional trading on securities markets and to understanding the way in which information becomes incorporated into market Graduate School of Business Administration University of Colorado at Boulder. This paper was formerly titled Herding Trade Reversals and Cascading by Institutional Investors and is derived from Chapter 3 of my dissertation at The University of California Los Angeles. I gratefully acknowledge a grant from the UCLA Academic Senate for the purchase of data used in this study. My thanks to Michael Brennan Yehning Chen Bhagwan Chowdhry Nick Crew Kent Daniel Allen Huffman Lisa Kramer Josef Lakonishok Francis Longstaff Richard Roll Juan Siu and especially Trudy Cameron David Hirshleifer Eduardo Schwartz and Walt Tor-ous for helpful assistance and comments on this research. Thanks also to Toby Moskowitz and Vincent Warther for providing data used in two of the sections of this paper. Most signif icantly I thank Mark Grinblatt and Sheridan Titman for their .

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