Expected Mispricing: The Joint Influence of Accounting Transparency and Investor Base

We examine how accounting transparency and investor base jointly affect financial analysts' expectations of mispricing (i.e., expectations of stock price deviations from fundamental value). Within a range of transparency, these two factors interactively amplify analysts' expectations of mispricing—analysts expect a larger positive deviation when a firm's disclosures more transparently reveal income‐increasing earnings management and the firm's most important investors are described as transient institutional investors with a shorter‐term horizon (low concentration in holdings, high portfolio turnover, and frequent momentum trading) rather than dedicated institutional investors with a longer‐term horizon (high concentration in holdings, low portfolio turnover, and little momentum trading). Results are consistent with analysts anticipating that transient institutional investors are more likely than dedicated institutional investors to adjust their trading strategies for near‐term factors affecting stock mispricings. Our theory and findings extend the accounting disclosure literature by identifying a boundary condition to the common supposition that disclosure transparency necessarily mitigates expected mispricing, and by providing evidence that analysts' pricing judgments are influenced by their anticipation of different investors' reactions to firm disclosures.     

GLAMOUR VERSUS VALUE: TRADING BEHAVIOR OF INSTITUTIONS AND INDIVIDUAL INVESTORS

We design a new metric to measure the net buying and selling by institutions and individual investors and find that from 1980 to 2004 institutional investors were net buyers of growth stocks and net sellers of value stocks, implying that individual investors were net buyers of value stocks and net sellers of glamour stocks. The institutional preference for glamour and value stocks seems to be related to sell‐side analysts' recommendations and recent favorable stock price performances, especially during the post‐1994 period. Finally, the institutional buying of growth stocks and sale of value stocks was not based on superior information.     

The dynamics of individual and institutional trading on the Shanghai Stock Exchange

We investigate the daily dynamic relation between returns and institutional and individual trades in the emerging Chinese stock market. Consistent with the hypotheses of trend-chasing and attention-grabbing trading, we find that the response of individual trading to return shocks is much stronger than that of institutional trading, and individuals are net buyers following return shocks. Second, we find that past individual buys and sells have predictive power, whereas past institutional buys and sells have predictive power for market returns in longer horizons. However, both institutional and individual trading activities are more strongly related to past trades than past returns, and individual trading is also influenced by institutional trading. Moreover, we find that institutional trading in the largest quintile leads the trading in the smallest quintile, but no such lead–lag relation is found for individual trades. Finally, we find that the average cumulative abnormal trading volume of individuals is much larger than that of institutions around the firms' earnings announcement, suggesting that less-informed individual investors are more heavily influenced by firm-specific information disclosures and attention-grabbing events.     

A comparison of buy‐side and sell‐side analysts

There is very little research on the topic of buy-side analyst performance, and that which does exist yields mixed results. We use a large sample from both the buy-side and the sell-side and report several new results. First, while the contemporaneous returns to portfolios based on sell-side recommendations are positive, the returns for buy-side analysts, proxied by changes in institutional holdings, are negative. Second, the buy-side analysts' underperformance is accentuated when they trade against sell-side analysts' recommendations. Third, abnormal returns positively relate to both the portfolio size and the portfolio turnover of buy-side analysts' institutions, suggesting that large institutions employ superior analysts and that superior analysts frequently change their recommendations. Abnormal returns are also positively related to buy-side portfolios with stocks that have higher analyst coverage, greater institutional holding, and lower earnings forecast dispersion. Fourth, there is substantial persistence in buy-side performance, but even the top decile performs poorly. These findings suggest that sell-side analysts still outperform buy-side analysts despite the severe conflicts of interest documented in the literature.     

Whose money is smart? Individual and institutional investors’ trades based on analyst recommendations

This study explores how institutional and individual investors respond to analyst recommendations. Using a unique account-level trading dataset taken from the Shanghai Stock Exchange, we obtain direct evidence to show that (1) active institutional investors are significantly net buyers (net sellers) on “strong buy” and “buy” (“hold” and “sell”) recommendations; (2) active institutional investors condition their trades based on the buy-side pressure of analysts; (3) institutional investors earn abnormal returns by incorporating analysts’ buy-side pressure into their trading reactions to analyst recommendations; and (4) individual investors, in contrast, exhibit abnormal trade reactions opposite to those of active institutional investors. Our results are robust to alternative measures and different specifications. This study provides evidence that active institutional investors are more sophisticated processors of information and provides support for regulators’ concerns about the sub-optimal investment decisions made by individual investors who are unaware of the potential conflicts of interest analysts may face.     

Has local informational advantage disappeared?

This study examines how changes in the information environment affect the informational advantage of geographically proximate agents. The long‐term advantage of local agents disappeared at the turn of the millennium. This is accompanied by the reduction in local bias of institutional investors and equity analysts. However, institutional investors continue to trade local stocks disproportionately more often than non‐local stocks; moreover, their local trades outperform non‐local trades in the short term—even for large and liquid stocks. Our results are consistent with improvements in the information environment shortening the horizon of proximity‐based informational advantage.     

Analyst Reputation,Communication, and Information Acquisition

Earlier studies have shown that reputational concerns tend to reduce agents' opportunistic behavior. However, a recent study by Morris argued that analysts' (experts') reputational concerns may discourage truthful communication when they try to avoid being perceived as being misaligned with investors. In this paper, I examine the effect of reputational concerns on communication in a setting where analysts can choose their precision endogenously. Because both misaligned and aligned analysts want investors to trust their reports in the future, both will aim to build a reputation for being aligned. In equilibrium, aligned analysts will acquire more information than misaligned analysts. As a result, investors may favorably update their beliefs about the analysts' type when the report is proven to be accurate. Therefore, both types of analysts will have reputational incentives to communicate truthfully. The paper also derives conditions under which the analysts' reputational concerns have a nonmonotonic impact on aligned analysts' equilibrium precision choices and investors' welfare.     

Investor Sentiment and Corporate Disclosure

This paper investigates how firms react strategically to investor sentiment via their disclosure policies in an attempt to influence the sentiment‐induced biases in expectations. Proxying for sentiment using the Michigan Consumer Confidence Index, we show that during low‐sentiment periods, managers increase forecasts to “walk up” current estimates of future earnings over long horizons. In contrast, during periods of high sentiment, managers reduce their long‐horizon forecasting activity. Further, while there is an association between sentiment and the biases in analysts' estimates of future earnings, management disclosures vary with sentiment even after controlling for analyst pessimism, indicating that managers attempt to communicate with investors at large, and not just analysts. Our study provides evidence that firms' long‐horizon disclosure choices reflect managers' desire to maintain optimistic earnings valuations.     

The value relevance of timely information: The case of comparable store sales growth

Investors and analysts have called for more timely disclosure of corporate information. Responding to these demands, some retail firms issue comparable store sales (CSS) on a monthly or a quarterly basis in addition to an annual basis. This study examines whether a timely disclosure of CSS provides value-relevant information to market participants by examining investors' and financial analysts' responses at the time of CSS disclosures (short-horizon) and over the month or the quarter (long-horizon). We find that both monthly and quarterly CSS are associated with contemporaneous market returns and analyst forecast revisions. More importantly, we find that quarterly CSS news becomes less important to investors when firms provide more timely CSS information, indicating that monthly CSS reports may preempt the information content of quarterly CSS. Additional tests show that investors and analysts rely less on CSS if CSS news and earnings (sales) news are inconsistent.     

Disclosure Practices, Enforcement of Accounting Standards, and Analysts' Forecast Accuracy: An International Study

Using a sample from 22 countries, I investigate the relations between the accuracy of analysts' earnings forecasts and the level of annual report disclosure, and between forecast accuracy and the degree of enforcement of accounting standards. I document that firm‐level disclosures are positively related to forecast accuracy, suggesting that such disclosures provide useful information to analysts. I construct a comprehensive measure of enforcement and find that strong enforcement is associated with higher forecast accuracy. This finding is consistent with the hypothesis that enforcement encourages managers to follow prescribed accounting rules, which, in turn, reduces analysts' uncertainty about future earnings. I also find evidence consistent with disclosures being more important when analyst following is low and with enforcement being more important when more choice among accounting methods is allowed.     

Stock market openness and analyst forecast bias

Biases in analysts’ forecasts can be reduced not only through regulation but also through market mechanisms. In 2014, China launched the Shanghai-Hong Kong Connect program, which opened part of its domestic equity market to foreign investors. The implementation of this program provides a quasi-natural experimental setting to explore whether stock market openness plays a governance role in brokerage firms and minimizes their affiliated analysts' forecast biases. We find that the participation of foreign institutional investors mitigates the forecast biases of affiliated analysts. We also show that these analysts exert more significant effort by conducting more site visits. Our findings suggest that market liberalization can help improving the quality of analysts’ forecasts.     

The Reluctant Analyst

We estimate the dynamics of recommendations by financial analysts, uncovering the determinants of inertia in their recommendations. We provide overwhelming evidence that analysts revise recommendations reluctantly, introducing frictions to avoid frequent revisions. More generally, we characterize the sources underlying the infrequent revisions that analysts make. Publicly available data matter far less for explaining recommendation dynamics than do the recommendation frictions and the long‐lived information that analysts acquire but the econometrician does not observe. Estimates suggest that analysts structure recommendations strategically to generate a profitable order flow from retail traders. We provide extensive evidence that our model describes how investors believe analysts make recommendations, and that investors value private information revealed by analysts' recommendations.     

Fool's mate: What does CHESS tell us about individual investor trading performance?

We investigate the short‐term relation between individual investor trading and stock returns on the Australian Securities Exchange. Stocks heavily bought by individual investors underperform stocks heavily sold over the subsequent three days, with respective returns on to a long–short portfolio of ?93, ?67 and ?12 basis points on days one, two and three. Individuals underperform in small and mid‐size stocks when they trade passively using limit orders waiting for the market price to move in their favour. Individuals underperform in large stocks when they trade aggressively using marketable orders. Foreign institutions gain from taking the opposite side of individual trades. We present an information asymmetry‐based explanation for the findings.     

Underwriting relationships,analysts' earnings forecasts and investment recommendations

We examine the effect of underwriting relationships on analysts' earnings forecasts and recommendations. Lead and co-underwriter analysts' growth forecasts and recommendations are significantly more favorable than those made by unaffiliated analysts, although their earnings forecasts are not generally greater. Investors respond similarly to lead underwriter and unaffiliated `Strong buy' and `Buy' recommendations, but three-day returns to lead underwriter `Hold' recommendations are significantly more negative than those to unaffiliated `Hold' recommendations. The findings suggest investors expect lead analysts are more likely to recommend `Hold' when `Sell' is warranted. The post-announcement returns following affiliated and unaffiliated analysts' recommendations are not significantly different.     

Factors Influencing Corporate Environmental Disclosures

We investigate the effectiveness of the Carbon Disclosure Project (CDP), a not‐for‐profit organization that facilitates environmental disclosures of firms with institutional investors, thereby serving as a corporate governance mechanism for shareholders to influence the firm's environmental disclosures. We examine firm characteristics associated with firms' decisions to disclose carbon‐related information via the CDP for a sample of 319 Canadian firms over a four‐year period. In particular, we examine how firms' decisions to disclose via CDP are associated with shareholder activism, litigation risk, and the opportunity for low‐cost positive publicity once requested by the firms' “signatory” investors. Our results also show that management's decision to release climate change data is associated with domestic, but not foreign, signatory investors. We also find that disclosing firms tend to be those from lower polluting industries with less exposure to litigation risk. This suggests that this new form of coordinated shareholder activism may not be successful at altering the behavior of firms that are heavier polluters.     

Analysts' Forecasts Following Forced CEO Changes

This paper examines analysts' earnings forecasts during the period of uncertainty following a change of chief executive officer (CEO). It distinguishes between forced and non‐forced CEO changes, and examines whether analysts utilize their information advantage to reduce the heightened uncertainty of a forced change of CEO. Examining a sample of Australian companies followed by analysts between 1999 and 2009, we find that forecasting accuracy is lower and earnings forecasts are more optimistic for firms experiencing forced CEO turnover compared to firms not undergoing such a change. However, dispersion is not statistically different. The results suggest that forced CEO turnover events provide a challenge to the forecasting environment for analysts. During CEO changes, investors should be aware that forecasts are less accurate and have an optimistic bias.     

Do Limit Orders Alter Inferences about Investor Performance and Behavior?

Individual investors lose money around earnings announcements, experience poor posttrade returns, exhibit the disposition effect, and make contrarian trades. Using simulations and trading records of all individual investors in Finland, I find that these trading patterns can be explained in large part by investors' use of limit orders. These patterns arise mechanically because limit orders are price‐contingent and suffer from adverse selection. Reverse causality from behavioral biases to order choices does not appear to explain my findings. I propose a simple method for measuring a data set's susceptibility to this limit order effect.     

Short selling and the independence of business-related analysts: Evidence from an emerging market

This paper investigates whether short-sale deregulation improves analysts' independence in an emerging market where conventional mechanisms mitigating conflicts of interest are either ineffective or absent. Short selling reduces the effectiveness of analysts' favourable opinions in creating or sustaining overvalued stock prices, thus decreasing the incentives of institutional clients of brokerages to exert pressure on related analysts to initiate coverage and issue biased opinions. Using a difference-in-difference approach, we find strong evidence that stocks that are eligible for short sales experience a greater reduction in coverage by related analysts than stocks that are ineligible for short sales. When covered firms become eligible for short sales, the quality of forecasts and recommendations issued by related analysts improves considerably. Further analyses show that shortable firms with a significant reduction in related analysts' coverage are more likely to underperform and to experience stock price crashes in the future. Altogether, our results are consistent with short selling effectively restoring related analysts' independence in emerging markets.     

Which Institutional Investors Trade Based on Private Information About Earnings and Returns?

Recent work suggests that institutional investors execute profitable trades based on private information about earnings and returns. We provide new evidence on the prevalence and sources of such informed trading by (1) testing for the creation and liquidation of positions based on private information, (2) introducing private information proxies that reflect the size and nature of an institution's position in each portfolio firm, and (3) using a methodology that examines multiple investor characteristics simultaneously at the institution‐firm level. We find that changes in ownership by institutions with large positions in a firm are consistent with informed trading. However, other previously documented proxies for private information produce results more consistent with risk‐based trading (e.g., investment style) or insignificant in the presence of other proxies (e.g., fiduciary type). We also find that informed trading is more prevalent in small firms and when the large positions are taken by investment advisers and large institutions.     

Inferring investor behavior: Evidence from TORQ data

We use a unique dataset (TORQ) to calibrate several techniques commonly used to infer investor behavior from transactions data. Specifically, we evaluate the Lee–Ready (1991) Journal of Finance 46, 733–746) algorithm for distinguishing trade direction, and we examine the use of trade size as a proxy for trader identity. We find that, due to complexities in the NYSE auction process, up to 40% of reported trades cannot be unambiguously classified as either buyer- or seller-initiated. However, for those trades that can be classified, the Lee–Ready algorithm is 93% accurate. In addition, we construct a firm-specific trade size proxy that is highly effective in separating the trading activities of individual and institutional investors. These findings should be useful to researchers interested in inferring trader sophistication and buy/sell direction from transactions data.