Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.

The anomalous returns associated with net stock issues, accruals, and momentum are pervasive; they show up in all size groups (micro, small, and big) in cross-section regressions, and they are also strong in sorts, at least in the extremes. The asset growth and profitability anomalies are less robust. There is an asset growth anomaly in average returns on microcaps and small stocks, but it is absent for big stocks. Among profitable firms, higher profitability tends to be associated with abnormally high returns, but there is little evidence that unprofitable firms have unusually low returns.

Anomalies are empirical results that seem to be inconsistent with maintained theories of asset-pricing behavior. They indicate either market inefficiency (profit opportunities) or inadequacies in the underlying asset-pricing model. The evidence in this paper shows that the size effect, the value effect, the weekend effect, and the dividend yield effect seem to have weakened or disappeared after the papers that highlighted them were published. At about the same time, practitioners began investment vehicles that implemented the strategies implied by some of these academic papers. The small-firm turn-of-the-year effect became weaker in the years after it was first documented in the academic literature, although there is some evidence that it still exists. Interestingly, however, it does not seem to exist in the portfolio returns of practitioners who focus on small-capitalization firms. All of these findings raise the possibility that anomalies are more apparent than real. The notoriety associated with the findings of unusual evidence tempts authors to further investigate puzzling anomalies and later to try to explain them. But even if the anomalies existed in the sample

We study the daily and intradaily cross-sectional relation between stock re-turns and the trading of institutional and individual investors in Nasdaq 100 securities. Based on the previous day’s stock return, the top performing decile of securities is 23.9 % more likely to be bought in net by institutions (and sold by individuals) than those in the bottom performance decile. Strong contem-poraneous daily patterns can largely be explained by net institutional (indivi-dual) trading positively (negatively) following past intradaily excess stock returns (or the news associated therein). In comparison, evidence of return predictability and price pressure are economically small. RECENT STUDIES EXAMINING THE RELATION between institutional ownership and stock returns document three main ¢ndings. First, institutions are momentum investors and tend to follow past prices (Grinblatt, Titman, and Wermers (1995)).1 Second, mutual funds sometimes tend to move together or engage in herding (Wermers (1999)).2 Third, the contemporaneous relation between changes in institutional ownership and stock returns is much stronger than the trend chasing e¡ect (Nofsinger and Sias (1999) and Wermers (1999)).We explain the positive contemporaneous relation between returns and changes in institu-tional ownership found at quarterly intervals in previous studies and, more im-portantly, provide new daily and intradaily evidence on the role of short-term THE JOURNAL OF FINANCE VOL. LVIII, NO. 6 DECEMBER 2003

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This paper provides evidence of informed trading by individual investors around earn-ings announcements using a unique data set of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) ab-normal returns on and after earnings announcement dates. We decompose abnormal returns following the event into information and liquidity provision components, and show that about half of the returns can be attributed to private information. We also find that individuals trade in both return-contrarian and news-contrarian man-ners after earnings announcements. The latter behavior has the potential to slow the adjustment of prices to earnings news. DO INDIVIDUAL INVESTORS GAIN by trading on private information? Do they pos-sess skills in interpreting public information? While individual investors are often portrayed in the behavioral finance literature as unsophisticated “noise” traders who are subject to fads and psychological biases, these important ques-tions have added relevance in light of recent interest in theoretical models

A number of recent studies show that institutional herding positively predicts future returns on a two to four quarter horizon. These studies concentrate on relatively short-term herding behavior, typically measured over one or two quarters. Motivated by the theoretical herding literature, which emphasizes endogenous persistence in decisions over time, we focus on the temporal dimension of institutional trading behavior. We test the impact of multi-quarter persistent patterns of buying and selling by institutions on the cross-section of future stock returns. Using both regression and portfolio tests, we find that stocks that are persistently sold by institutions over three to five quarters outperform stocks that are persistently bought by them for a period of up to two years. The cross-sectional return predictability that is associated with persistent institutional trading is not subsumed by the well-known predictability associated with past returns and other stock characteristics. It is robust to using different measures of institutional trading and different definitions of institutional herding, and is not confined to small stocks. We also analyze how the persistent trading choices of institutions over several quarters affect institutional trade. We find that institutions, as an aggregate, tend to buy

1 We are grateful to the Taiwan Stock Exchange for providing the data used in this study. Michael Bowers provided excellent computing support. Barber appreciates the National Science Council of Taiwan for underwriting a visit to Taipei, where Timothy Lin (Yuanta Core Pacific Securities) and Keh Hsiao Lin (Taiwan Securities) organized excellent overviews of their trading operations. We appreciate the comments of Charles Jones, Mark Kritzberg, and seminar participants at UC-Davis, the University of North Carolina, and the Wharton 2004 Household Finance Conference.

and Dick Thaler for assistance with the data used in this paper. We are grateful for a number of helpful discussions with Dan Bernhardt and for nancial support from the Ofce for Futures

We present a simple theoretical model of the price impact of institutional herding. In our model, career-concerned fund managers interact with pro…t-motivated proprietary traders and monopolistic market makers in a pure dealer-market. The reputational concerns of fund managers generate an endogenous tendency to imitate past trades, which, in turn, impacts the prices of the assets they trade. In contrast, proprietary traders trade in a contrarian manner. We show that, in markets dominated by fund managers, assets persistently bought (sold) by fund managers trade at prices that are too high (low) and thus experience negative (positive) long-term returns, after uncertainty is resolved. The pattern of equilibrium trade is also consistent with increasing (decreasing) short-term transaction-price paths during or immediately after an institutional buy (sell) sequence. Our results provide a simple and stylized framework within which to interpret the empirical literature on the price impact of institutional herding. In addition, our paper generates several new testable implications.