Kelsey D. Wei

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

This paper documents that mutual funds “herd” trade together into stocks with consensus sell-side analyst upgrades, and herd out of stocks with consensus downgrades. This influence of analyst recommendation changes on fund herding is stronger for downgrades, and among managers with greater career concerns. These findings indicate that career-concerned managers are incentivized to follow analyst information, and that managers have a greater tendency to herd on negative stock information, given the greater reputational and litigation risk of holding losing stocks. Furthermore, starting in the mid-1990s when aggregate mutual fund equity ownership is significantly higher, stocks traded by career-concerned herds of fund managers in response to analyst recommendation changes experience a significant same-quarter price impact, followed by a sharp subsequent price reversal. Our evidence suggests that analyst recommendation revisions induce herding by career-concerned fund managers, and that this type of trading has become price destabilizing with the increasing level of mutual fund ownership of stocks. This paper was accepted by Wei Jiang, finance.

Uncommon Value: The Characteristics and Investment Performance of Contrarian Funds

Motivated by extant theories of herding behavior, this paper empirically identifies contrarian mutual funds as those trading most frequently against the crowd. We find that contrarian funds generate superior performance both when they trade against and with the herd, indicating that they possess superior private information. Furthermore, contrarians do not trade in a particularly correlated fashion with each other, consistent with these funds having disparate information. Our fund-level contrarian measure is largely unrelated to existing measures of fund strategy uniqueness, as both contrarian and herding funds score highly on such measures. Building on our finding of superior alphas for contrarian funds, we construct a stock-level contrarian score that reflects the aggregate stock selection information possessed by contrarian managers. This stock-level contrarian score significantly predicts stock returns after controlling for measures of stock-level herding, as well as a battery of return-predictive investment signals documented in prior studies. This paper was accepted by Wei Jiang, finance.

CEO Compensation and Stock Mispricing: How Do Boards React to Mutual Fund Flow-Driven Price Pressure?

The endogeneity of board structure complicates studies of board decisions on CEO compensation. Using mutual fund flow-driven trading pressure as an exogenous shock to stock price informativeness of CEO effort, we examine how boards adjust CEO pay in response to such exogenous price movements. Consistent with economic efficiency, boards rely more on accounting and less on stock performance in setting CEO bonuses when the stock price becomes less informative. Boards consisting of directors with greater advising ability are more likely to make such adjustments. We find only weak evidence that boards selectively adjust bonuses to benefit the CEO.

Against the ‘Wisdom of Crowds’: The Investment Performance of Contrarian Funds

In an article published in the Financial Analysts Journal (Treynor, 1987), Jack Treynor wrote about a series of “bean jar” experiments he conducted with students in his investments courses at the University of Southern California. In the first set of experiments, he asked students to independently estimate the number of beans contained in a full jar. While most students’ individual estimates missed the actual number by a wide margin, surprisingly, the average estimates were pretty close to being correct. In the second set of experiments, he first provided students with advice on properties of the jar, such as the air space at the top of the jar, and materials of the jar. While such information supposedly could help improve the accuracy of students’ estimates, the resulting average estimates, alas, had much larger errors than those from the first set of experiments. It seems his advice did nothing more than cause common errors among students!