Abstract
Institutional investors (active vs. passive) play various roles in the capital market and in assets prices, in particular. Institutional investors affect assets prices either because they play a monitoring role and mitigate the agency problem, or because they have information advantages, or finally, they can arbitrage away mispricing. This research note relates Hu, Ke, and Yu’s (forthcoming) article to both the traditional positive views that institutional investors are sophisticated and help correct stock mispricing and the complementary emerging literature that argues that institutions may contribute to stock return anomalies rather than eliminate them. My research note concludes that current research on the role of institutional investors has generated a number of useful insights. I identify many fundamental questions that remain unanswered, and changes in the economic environment that raise new questions for research.
Keywords
Introduction
Institutional investors (active vs. passive) play various roles in the capital market and in assets prices, in particular. Institutional investors affect assets prices either because they play a monitoring role and mitigate the agency problem, or because they have information advantages, or finally, they can arbitrage away mispricing This research note relates Hu, Ke, and Yu’s (HKY; forthcoming) article to both the traditional positive views that institutional investors are sophisticated and help correct stock mispricing and the complementary emerging literature that argues that institutions may contribute to stock return anomalies rather than eliminate them. HKY’s (forthcoming) article investigates the trading behavior of transient institutions toward small negative earnings surprises using post-Regulation FD period data. As previous researches have argued on whether transient institutional investors have the ability to interpret information, it provides new evidence to this debate. It uses event study methodology with ordinary least squares (OLS) regression models. The results indicate that transient institutions sell in response to growth firms’ negative earnings surprises, and it has an impact on current stock price. And the significantly positive association between selling behavior and stock’s future negative abnormal return suggests the ability of predicting firms’ future performance. This article contributes to the existing literature by providing new evidence on the ability of transient institutions. It also corrects the current belief that transient institutions overreact to small negative earnings surprises.
My research note proceeds as follow: “The Role of Institutional Investors” section discusses the role of institutional investors (active and passive) in assets pricing. “Are Transient Institutions Sophisticated Enough to Interpret Small Negative Earnings Surprises?” section relates the finding of HKY (forthcoming) to both the traditional positive views that institutional investors are sophisticated and help correct stock mispricing and the complementary emerging literature that argues that institutions may contribute to stock return anomalies rather than eliminate them. “Do Transient Institutions Correctly Interpret Small Negative Earnings Surprises?” section proposes an alternative design to assess whether transient institutions correctly interpret small negative earnings surprises in the absence of access to management’s private information. It also identifies many fundamental questions that remain unanswered and changes in the economic environment that raise new questions for research.
The Role of Institutional Investors
A large body of literature is devoted to investigate the roles of institutional investors on assets prices. Grinblatt and Titman (1993) document that aggregate institutional demand is positively correlated with subsequent returns. Chen, Jegadeesh, and Wermers (2000) show that stock bought by mutual funds has higher performance than those they liquidate. Yan, Sterling, and Zhang (2009) show that the positive relation between institutional ownership and future stock returns is driven by short-term institutions. Furthermore, short-term institutions’ trading forecasts future stock returns. In contrast, Cai and Zheng (2004) show that stock returns appear to be negatively related to lagged institutional trading. A further analysis of the behavior of trading and the returns of the traded stocks reveals evidence that stocks with heavy institutional buying (selling) experience positive (negative) excess returns over the previous 12 months.
Several papers investigate whether institutional investors are better informed by looking at their trading pattern prior to news announcement. Ke and Petroni (2004) examine whether transient institutional investors’ information that allows them to predict a break in a string of consecutive quarterly earnings increases and thereby avoid the economically significant negative stock price response associated with the break announcement. Ke and Petroni show that transient institutions predict the break at least one quarter in advance of the break quarter. These results suggest that transient institutions obtained information regarding the impending break from private communications with management. Baker, Litov, Wachter, and Wurgler (2010) investigate institutional investors’ trading around earnings announcements. Baker et al. 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. These findings suggest that institutional investors are able to trade profitably in part because they are able to forecast earnings-related fundamentals.
A complementary emerging literature that argues that institutions may contribute to stock return anomalies rather than eliminate them. Edlen, Ince, and Kadlec (2016) examine institutional demand prior to well-known stock return anomalies and find that institutions have a strong tendency to buy stocks classified as overvalued, and that these stocks have particularly negative ex-post abnormal returns. These findings rule out explanations based on flow and limits-of-arbitrage, but is more consistent with agency-induced preferences for stock characteristics that relate to poor long-run performance.
Are Transient Institutions Sophisticated Enough to Interpret Small Negative Earnings Surprises?
HKY (forthcoming) examine three interrelated research questions:
HKY (forthcoming) show that transient institutions do sell intensively in reaction to announcements of small negative earnings surprises. The findings also show that transient institutions’ selling in response to small negative earnings surprises is almost twice as large as their selling in response to −2-cent earnings surprises.
The results show that transient institutions’ trading in reaction to small negative earnings surprises is positively correlated with contemporaneous abnormal stock returns.
HKY (forthcoming) show that transient institutions’ trading in reaction to small negative earnings surprises is positively associated with the subsequent abnormal returns. Answering these research questions is critical because transient institutions’ trading might significantly affect stock prices. Moreover, the conflict between the sophisticated investor argument and the myopic investor argument created a debate on the transient institutions’ processing capability of financial and other public and private information. There are two major sources of transient institutions’ sophistication: access to private information (Ke & Petroni, 2004; Ke, Petroni & Yu, 2008) and independent information acquisition and processing ability (Lewellen, 2011). Finally, CEOs fear the side effects of transient institutions’ misinterpretation of small negative surprises (i.e., price drops and increased volatility). HKY’s proprietary database of institutional investors’ daily stock trading records enabled them to assess whether transient institutions correctly interpret small negative earnings surprises in the absence of access to management’s private information. It contains institutional investors’ daily stock trading records as opposed to the institutions’ quarterly ownership change used in previous researches. The uniqueness of the data gives it advantage compared with existing articles for there is no direct measure of observed transient institutions’ private information in previous research. Thus, by merging the data from two databases, an event study is conducted to verify the hypotheses. Furthermore, it eliminates the possibility of trading behavior driven by superior access to private information. The data are collected in the post-Regulation FD period. An extent literature has already demonstrated that the adoption of Regulation FD has been effective in curtailing selective disclosure (Gintschel & Markov, 2004). At the same time, this article also runs the regression model using the daily trading records of 1 month prior to the earnings announcement. So, it further proves that the transient institutions’ trading behavior is not due to obtaining private information about the other earnings surprises earlier. Finally, by running the regression model and comparing the benchmarks, this article proves that transient institutions’ selling reaction to growth firms’ small negative earnings surprises is economically significant instead of just being significant statistically.
Do Transient Institutions Correctly Interpret Small Negative Earnings Surprises?
To answer the question whether transient institutions correctly interpret small negative earnings surprises, the focus should be more on the tension between myopic investor view and independent information acquisition and processing ability. In fact, post-Regulation FD period, there is little room for privileged access to management’s private information. Mangers are not the only source of private information. Transient institution might be trading opportunistically on the leakage of future analysts’ stock recommendation changes.
On another plan, HKY (forthcoming) assume that the information environment is exogenous. However, Li, Radhakrishnan, Shin, and Zhang (2011) examine the impact of Regulation Fair Disclosure (RFD) on transient institutional investors’ abnormal trading behavior around accounting restatements. Li et al. show that while in the pre-RFD period, transient institutional investors exhibit abnormal selling of restating firms’ stocks one quarter before the restatement is publicly announced, in the post-RFD period, there is no such abnormal selling. The results document that this phenomenon is driven by (a) firms with low analyst following (i.e., firms with poor information environment), (b) firms with high stock price reaction to earnings surprise (i.e., firms with high informativeness of earnings), (c) firms where the restatements’ impact on earnings is high, and (d) firms with nonrevenue related restatements. In a related study, Klein, Saunders, and Wong (2015) argue that investors who take advantage of analysts’ recommendation changes will act like transient investors (e.g., Bushee, 1998, 2001) . This implies they will buy or sell securities in the direction of the upcoming recommendation changes and reverse their holdings shortly afterwards.
To answer the question, do transient institutions correctly interpret small negative earnings surprises, one should also include the noninstitutional investors’ reaction to small negative earnings surprises and its correlation with future abnormal returns as a benchmark. Results from previous research suggest that after the adoption of the Regulation FD, firms also increase their quantity of voluntary disclosures (Bailey, Li, Mao, & Zhong, 2003), and analysts and investors are better able to gather uncertainty-relieving information. So there is a possibility that all investors are able to better interpret announcements of small negative earnings surprises in the post-Regulation FD period due to the increased information released to the market and the opinions of analysts’ forecast. So the correlation between transient institutional investors’ selling behavior and the stock’s negative future abnormal return may not be explained by their superior ability of interpreting information.
Taken all together, what do HKY (forthcoming) results mean? Transient institutional investors are third party providers of private information. Transient institutional investors’ trading behavior improves the market efficiency. Transient institutional trading behavior improves the information environment. The econometric design proposed by HKY (forthcoming) strongly supports their finding, but what is the mechanic driving transient institutional investors’ trading behavior? We do not know. What is the decision usefulness of HKY (forthcoming) findings?
Conclusion
Current research on the role of institutional investors has generated a number of useful insights. HKY (forthcoming) is an interesting study that examines an issue of great importance to both practitioners and academics. It is an unresolved issue—whether there exist material differences between transient institutions and other class of shareholders in correctly interpreting complex accounting information, and whether such differences (if they exist) have economic consequences. HKY provide motivation for future research on the economic consequences of transient institutions around the world. Many fundamental questions remain unanswered, and changes in the economic environment that raise new questions for research. For instance, how effective are institutions in mitigating macroeconomic uncertainty? Do institutional investors adequately advance the goals of the individuals who have invested in them? Do institutional investors contribute significantly to “undesirable short-termism” in their publicly held investee companies? Can institutional investors become more effective “stewards” of publicly held investee corporations? Finally, do institutions avoid investing in companies with poor corporate social responsibility practices?
Footnotes
Acknowledgements
Samir Trabelsi thanks the CPA Ontario Research Excellence Centre for its generous support.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
