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Abstract:
We examine market participants' reactions to dividend changes conditional on earnings quality. We define earnings quality as the extent to which current earnings are associated with one-year, two-year, or three-year ahead operating cash flows. Controlling for the magnitude of the dividend change, the firm's information environment, the firm's investment opportunity set, the effects of dividend clienteles, and the firm's operating risk, we find that the market reacts less to dividend change announcements from firms with higher earnings quality. Similarly, controlling for the magnitude of the dividend change, the firm's information environment, and the release of other information around the dividend declaration date, we find that the magnitude of analyst forecast revisions is significantly less for firms with higher earnings quality. Overall, our results are consistent with market participants incorporating earnings quality when reacting to information in other financial disclosures.

Abstract:
We investigate if sell-side security analysts exhibit relative persistence in their stock picking ability. We find that analysts whose recommendation revisions earned the most (least) positive excess returns in the past continue to outperform (underperform) other analysts in the future. Further, we find that the market recognizes these performance differences in the five-day period surrounding the recommendation revision. This market reaction, however, is incomplete. Excess returns measured over the one and three trading months following the revision are significantly different from zero and positively associated with the analysts' prior performance. A trading strategy taking long (short) positions in recommendation upgrades (downgrades) conditional on an analyst's prior performance generates excess returns, but these returns are insufficient to cover transaction costs.

Security analysts, Stock recommendations, Persistence, Trading strategy

Abstract:
We investigate if sell-side security analysts exhibit relative persistence in their stock picking ability. We find that analysts whose recommendation revisions earned the most (least) positive excess returns in the past continue to outperform (underperform) other analysts in the future. Further, we find that the market recognizes these performance differences in the five-day period surrounding the recommendation revision. This market reaction, however, is incomplete. Excess returns measured over the one and three trading months following the revision are significantly different from zero and positively associated with the analysts' prior performance. A trading strategy taking long (short) positions in recommendation upgrades (downgrades) conditional on an analyst's prior performance generates excess returns, but these returns are insufficient to cover transaction costs.

Security analysts; Stock recommendations; Persistence; Trading strategy

Abstract:
Abnormal stock returns measured over intervals of less than a year exhibit positive serial correlation, or returns momentum, while returns measured over longer periods exhibit negative serial correlation, or returns reversals. This paper examines if patterns in earnings surprises, together with investors? inefficient reactions to those earnings surprises, account for the observed serial correlation in returns. Prior literature has documented that over periods of less than one year, earnings surprises are positively serially correlated. We document that over longer periods, they are negatively serially correlated. This pattern is strikingly similar to the pattern in returns. In addition to documenting these patterns across intervals, we also show that for any particular interval, the serial correlation of returns and the serial correlation of earnings surprises are related. Controlling for cross-sectional differences in firms? serial correlations in earnings surprises, we are able to eliminate the serial correlation in returns at 3-, 24-, 36-, and 48-month intervals. We find some evidence of residual serial correlation in returns at 6-, 12-, and 60-month intervals. Overall, our results suggest that the serial correlation in earnings surprises is an important factor in determining the sign and magnitude of the serial correlation in returns.

Abstract:
Using a database provided by First Call Corporation, we examine the factors influencing whether a firm voluntarily accelerates the mandatory release of actual earnings via a "preannouncement." We find that firms are more likely to preannounce earnings if the consensus of analysts' forecasts is very different from actual earnings, if the dispersion in these forecasts is high, or if the firm has negative news. Further, we document that there is a systematic pattern in the amount managers provide in the preannouncement. On average, firms with positive news only release some of this news at the preannouncement date, while firms with negative news tend to release all of this news at the preannouncement date. We also document that the decision to preannounce magnifies the stock price reaction to earnings surprises. Compared to the control sample, firms that preannounce good (bad) news experience a greater positive (negative) excess return from the preannouncement date to the earnings announcement date. Finally, we investigate whether the market efficiently incorporates the relation between the sign of the news at the preannouncement date and the sign of the news at the earnings announcement date. Buying (shorting) those stocks with the most positive (negative) news at the preannouncement date yields an excess return of approximately 8% over 27 calendar days. This profitable zero-investment trading strategy indicates that the market does not efficiently react to preannouncements.

Abstract:
We investigate if earnings forecast accuracy matters to analysts by examining its association with analyst turnover from one brokerage house to another. Controlling for firm- and time-period effects, forecast horizon, and industry forecasting experience, we find that an analyst is more likely to turn over if his forecast accuracy declines relative to his peers. We find no association between an analyst's probability of turnover and his absolute forecast accuracy. These results hold if we include another measure of the analyst's performance, the profitability of his stock recommendations, in our logit specifications. In fact, there is no statistical relation between the absolute or rank profitability of an analyst's stock recommendations and the probability of turnover. Our findings indicate that forecast accuracy is important to analysts.

Abstract:
We examine whether analysts more fully incorporate prior earnings and returns information in their current quarter forecasts as their experience following a firm increases. Prior research suggests that various financial anomalies are related to investors' inability to rationally process historical earnings and price information. In particular, analysts' inability to efficiently incorporate the serial correlation in earnings surprises provides at least a partial explanation for post-earnings-announcement drift. Measuring analyst firm-specific forecasting experience as the number of prior quarters for which the analyst has issued an earnings forecast for the firm, we find that analysts underreact to prior earnings information less as their experience increases. We also find that post-earnings-announcement drift associated with firms with a more experienced analyst following is less than that for firms with a less experienced analyst following. This result, in conjunction with the finding that underreaction declines as analysts gain experience, suggests that the efficiency of a firm's market price is affected by the aggregate experience level of its analyst following. Our findings also provide evidence on one potential source of the superior earnings forecasting performance of more experienced analysts, the more efficient use of prior earnings information.

Security analysts; Underreaction; Post-earnings-announcement

Abstract:
Regulators' interest in analyst reports stems from the belief that small investors are unaware of the conflicts sell-side analysts face and may, as a consequence, be misled into making suboptimal investment decisions. We examine who trades on security analyst stock recommendations by extending prior research to focus on investor-specific responses to revisions. We find that both large and small traders react to analyst reports; however, large investors appear to trade more than small traders in response to the information conveyed by the analyst's recommendation and earnings forecast revision (proxied by the magnitudes of the recommendation change and the earnings forecast revision, respectively). We also find that small investors do not fully account for the effects of analysts' incentives on the credibility of analyst reports, as captured by the type of recommendation (i.e., upgrade versus downgrade or buy versus sell). In particular, small investors not only trade more than large investors following upgrade and buy recommendations, but also trade more following upgrade and buy recommendations than they do following downgrade and hold/sell recommendations. Furthermore, we observe that, on average, small traders are net purchasers following recommendation revisions regardless of the type of the recommendation; large traders tend to be net sellers following downgrades and sells. Consequently, large traders generate statistically positive returns from their trading, while small traders generate statistically negative returns from their trading. These findings are consistent with large investors being more sophisticated processors of information, and provide some support for regulators' concerns that analysts may more easily mislead small investors.

Security analysts, Stock recommendations, Trading volume, Investor sophistication

Abstract:
Regulators' interest in analyst reports stems from the belief that small investors are unaware of the conflicts sell-side analysts face and may, as a consequence, be misled into making suboptimal investment decisions. We examine who trades on security analyst stock recommendations by extending prior research to focus on investor-specific responses to revisions. We find that both large and small traders react to analyst reports; however, large investors appear to trade more than small traders in response to the information conveyed by the analyst's recommendation and earnings forecast revision (proxied by the magnitudes of the recommendation change and the earnings forecast revision, respectively). We also find that small investors do not fully account for the effects of analysts' incentives on the credibility of analyst reports, as captured by the type of recommendation (i.e., upgrade versus downgrade or buy versus sell). In particular, small investors not only trade more than large investors following upgrade and buy recommendations, but also trade more following upgrade and buy recommendations than they do following downgrade and hold/sell recommendations. Furthermore, we observe that, on average, small traders are net purchasers following recommendation revisions regardless of the type of the recommendation; large traders tend to be net sellers following downgrades and sells. Consequently, large traders generate statistically positive returns from their trading, while small traders generate statistically negative returns from their trading. These findings are consistent with large investors being more sophisticated processors of information, and provide some support for regulators' concerns that analysts may more easily mislead small investors.

Security analysts, Stock recommendations, Trading volume, Investor sophistication

Abstract:
In this study we examine differences between sophisticated
and unsophisticated investors' incorporation of information
about the accuracy of sell-side analysts' revisions of quarterly earnings forecasts. Our results indicate that sophisticated
investors' weights on information cues associated with
accuracy more closely match the weights derived from
environmental models of forecast accuracy. Further, our findings suggest that sophisticated investors' strategies better reflect the costs and benefits of using accuracy cues that provide
statistically significant, but economically small,
explanatory power for forecast accuracy. Our evidence is
consistent with sophisticated investors having greater knowledge about the factors that are related to forecast accuracy and
exhibiting more adaptive cue-weighting strategies.

Analyst forecast revisions; Market reaction; Investor sophistication; Cue weighting; Adaptive decision-making

Abstract:
Controlling for other determinants of the cost of capital, we find that firms with repeated large earnings surprises experience a higher cost of equity capital. This finding holds regardless of the sign of the earnings surprises, but firms that consistently report negative surprises have relatively higher cost of equity capital. Although firms that frequently surprise the market experience a decrease in analyst following relative to no surprise firms, this reduction in monitoring cannot account for the higher cost of equity capital. Overall, these findings document that repeated earnings surprises are costly, and provide evidence that managers have incentives to avoid missing earnings targets.

Cost of Capital, Earnings Surprises, Analyst Following, Institutional Ownership

Abstract:
We investigate potential costs experienced by firms that repeatedly have large quarterly earnings surprises during a condensed period of time. Consistent with our predictions, our univariate results indicate that surprise firms have lower analyst following, lower institutional ownership, and higher earnings-price ratios than firms that do not have large earnings surprises. Our multivariate findings, controlling for potentially confounding factors, are generally consistent with the univariate results, although our conclusions regarding institutional ownership are weaker. Further, our results generally hold regardless of whether the firm has positive surprises, negative surprises, or earnings surprises of mixed sign, suggesting that negative earnings surprises do not drive the results. Assuming that the documented differences represent a cost of earnings surprises, our findings provide an explanation for managers' desire to avoid surprising the market and their willingness to voluntarily disclose earnings-related information in advance of the mandated earnings announcement.

Abstract:
This paper provides evidence that in quarterly earnings announcements, managers use discretion to strategically report a large, transitory component of prior-period earnings. Managers are more likely to report separately a prior-period transitory gain from the sale of property, plant, and equipment (PPE) than to report a loss. This strategy provides the lowest possible benchmark to evaluate current earnings, thereby allowing the manager to highlight the largest possible change in earnings. This strategic reporting behavior is consistent with a conjecture by managers that investors will forget the transitory nature of the prior-period gain/loss unless it is separately reported in the current earnings announcement. Consistent with this conjecture of an investor processing bias, the stock price reactions suggest that the market does not unravel the strategic reporting at the time earnings are announced. There is some evidence that the market corrects for this bias in the 30 days subsequent to the earnings announcement date.

Abstract:
We examine the effects of analysts' celebrity on investor reaction to earnings forecast revisions. We measure celebrity as the quantity of media coverage analysts receive in sources included in the Dow Jones Interactive database, and find that media coverage is positively related to investor reaction to forecast revisions. The effect of celebrity on the reaction to forecast revisions remains significant after controlling for forecast performance variables examined in prior studies (ex post forecast accuracy, ex ante accuracy, award status, and other variables shown to be related to forecast accuracy). While these results are consistent with the familiarity of the analyst's name affecting the market reaction, we cannot rule out that our measure of celebrity is correlated with error in the performance measures we examine and/or correlated with other unexamined dimensions of forecast performance. A content analysis of a random subsample of the media coverage of our sample analysts suggests that our findings likely are not due to the increased availability of forecast revisions. Finally, an investigation of the excess returns around the quarterly earnings announcement date suggests that market participants react too strongly to forecast revisions issued by analysts with high levels of media coverage. Taken together, these findings suggest that an analyst's level of media coverage can affect the initial market reaction to his forecast revisions.

Analyst forecast revisions, investor reaction, celebrity, media coverage, forecast

Abstract:
This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Specifically, I investigate if earnings-announcement-related returns are more closely associated with analyst (SRW) forecasts for firms for which the marginal investor is more (less) likely to be sophisticated. My proxies for investor sophistication are institutional ownership, analyst following, and firm size (Atiase [1985], Hand [1990]). I predict that market participants place more weight on the analyst forecast for firms with high institutional ownership, firms with high analyst following, and large firms. For a sample of 89,246 firm-quarter observations over 1980-1995, I find that the weight placed on the analyst (SRW) forecast is increasing (decreasing) in institutional ownership, analyst following, and firm size. Forecast availability (as captured by publication in The Wall Street Journal) or forecast accuracy cannot account for these findings. Overall, my results suggest that market earnings expectations do not consistently resemble either analyst or SRW forecasts. Rather, the cross-sectional variation in the relative weights placed on these two forecasts is related to proxies for the sophistication of the marginal investor.

Abstract:
This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Specifically, I investigate if earnings-announcement-related returns are more closely associated with analyst (SRW) forecasts for firms for which the marginal investor is more (less) likely to be sophisticated. My proxies for investor sophistication are institutional ownership, analyst following, and firm size (Atiase [1985], Hand [1990]). I predict that market participants place more weight on the analyst forecast for firms with high institutional ownership, firms with high analyst following, and large firms.

For a sample of 89,246 firm-quarter observations over 1980-1995, I find that the weight placed on the analyst (SRW) forecast is increasing (decreasing) in institutional ownership, analyst following, and firm size. Forecast availability (as captured by publication in The Wall Street Journal) or forecast accuracy cannot account for these findings. Overall, my results suggest that market earnings expectations do not consistently resemble either analyst or SRW forecasts. Rather, the cross-sectional variation in the relative weights placed on these two forecasts is related to proxies for the sophistication of the marginal investor.

Abstract:
Modern economies are characterized by a separation of ownership and control. The information asymmetry between investors and entrepreneurs and the agency problems that result from the separation of ownership and control cause corporate information environments to develop endogenously. We discuss and provide a framework for analyzing the three main decisions that shape the corporate information environment in a capital markets setting: (1) managers’ voluntary reporting and disclosure decisions, (2) reporting and disclosures mandated by regulators, and (3) reporting decisions by third-party intermediaries (analysts). We review and critique current research on disclosure regulation, information intermediaries, and the determinants and economic consequences of corporate disclosure and financial reporting decisions. We conclude that in the last ten years, research has generated a number of useful insights. Despite this progress, we call for researchers to consider interdependencies between the various decisions that shape the corporate information environment and highlight changes in the economic financial environment that raise new and interesting issues for researchers to address.

Financial Reporting, Information Environment, Disclosure, Analyst Forecasts

Abstract:
We examine the effects of analysts' celebrity on investor reaction to earnings forecast revisions. We measure celebrity as the quantity of media coverage analysts receive in sources included in the Dow Jones Interactive database, and find that media coverage is positively related to investor reaction to forecast revisions. The effect of celebrity on the reaction to forecast revisions remains significant after controlling for forecast performance variables examined in prior studies (ex post forecast accuracy, ex ante accuracy, award status, and other variables shown to be related to forecast accuracy). While these results are consistent with the familiarity of the analyst's name affecting the market reaction, we cannot rule out that our measure of celebrity is correlated with error in the performance measures we examine and/or correlated with other unexamined dimensions of forecast performance. A content analysis of a random subsample of the media coverage of our sample analysts suggests that our findings likely are not due to the increased availability of forecast revisions. Finally, an investigation of the excess returns around the quarterly earnings announcement date suggests that market participants react too strongly to forecast revisions issued by analysts with high levels of media coverage. Taken together, these findings suggest that an analyst's level of media coverage can affect the initial market reaction to his forecast revisions.

Abstract:
We examine if analysts more fully incorporate prior earnings and returns information in their current quarter forecasts as their experience following a firm increases. We measure analyst firm-specific forecasting experience as the number of prior quarters for which the analyst has issued an earnings forecast for the firm. We find that analysts underreact to prior earnings information less as their experience increases, suggesting one reason why analysts become more accurate with experience.

underreaction, experience, earnings forecasts, security analysts

Abstract:
We examine the disclosure strategies managers follow when they "preannounce" quarterly earnings shortly before formal earnings announcements. We document that managers with bad news release essentially all of their news at the preannouncement date, while managers with good news only release about half of their news. Controlling for the combined news released at the preannouncement and earnings announcement dates, firms with negative earnings announcement surprises have significantly lower excess returns for the period from just before the preannouncement to just after the earnings announcement. This finding is consistent with the observed disclosure strategies whereby managers attempt to avoid negative earnings announcement surprises, and suggests that how information is presented can affect the market's reaction to that information.

Abstract:
We investigate if earnings forecast accuracy matters to security analysts by examining its association with analyst turnover. Controlling for firm- and time-period effects, forecast horizon, and industry forecasting experience, we find that an analyst is more likely to turn over if his forecast accuracy is lower than his peers. We find no association between an analyst's probability of turnover and his absolute forecast accuracy. We also investigate another observable measure of the analyst's performance, the profitability of his stock recommendations. There is no statistical relation between the absolute or relative profitability of an analyst's stock recommendations and his probability of turnover. We interpret our findings as indicating that forecast accuracy is important to analysts.

Abstract:
Published market concentration statistics have aroused concerns that industry leaders may have monopolized the U.S. accounting market. Using the law and advertising service industries as benchmarks, this paper analyzes local (single Metropolitan Statistical Area) concentration measures. Consistent with national measures, the average local concentration measures indicate that accounting is statistically more concentrated than law or advertising. However, the relative difference between accounting and the benchmark advertising and law concentration measures declines considerably as one moves from the national to the local level. Moreover, accounting is statistically more concentrated than law or advertising only in the largest local markets; concentration measures of the three service industries are not statistically different in smaller local markets. These results are consistent with large discretionary expenditures (e.g., training, research and development, advertising) in accounting relative to advertising or law. Our findings suggest that, in smaller local markets, accounting is not more prone to collusion than other professional services. The results also suggest an important difference in the market structure of accounting and other service industries.

Abstract:
In this paper, we examine whether sell-side security analysts generate more accurate quarterly earnings forecasts and more profitable stock recommendations as their experience with a specific firm increases. We also examine whether the market relies more on forecasts made by analysts who have more firm-specific experience. Consistent with the "Learning By Doing" model, we find that the accuracy of quarterly earnings forecasts improves with the number of prior quarters the analyst has followed the firm, controlling for both the functional form of the learning phenomenon and other factors previously shown to affect analyst forecasting performance. Moreover, we find that the market incorporates the analyst's experience level in forming expected earnings; the weight placed on the analyst forecast increases with the experience level of the analyst. Our results suggest knowledge of an analyst's experience can be used to improve the accuracy of consensus earnings forecasts.