ABNORMAL RETURNS AND ANALYSTS' EARNINGS FORECAST REVISIONS ASSOCIATED WITH THE PUBLICATION OF “STOCK HIGHLIGHTS” BY VALUE LINE INVESTMENT SURVEY

We examine the reaction of stocks and the response of financial analysts' earnings forecasts to securities recommended as “Stock Highlights” by Value Line Investment Survey. Significant abnormal returns appear around the publication of stock highlights. Stock price responses are relatively efficient and permanent. Using earnings expectation data provided by the Institutional Brokers Estimate System, we find analysts raise their forecasts significantly following Value Line recommendations. Near-term forecast revisions are significantly related to stock returns at the time of the recommendations. Thus, an explanation for Value Line's security recommendation success is its ability to generate firm-specific earnings information.     

RATIONAL EXPECTATIONS AND THE DYNAMIC ADJUSTMENT OF SECURITY ANALYSTS' FORECASTS TO NEW INFORMATION

We report the results of unbiasedness tests of security analysts' earnings forecasts. By examining how analysts incorporate new information into their updated earnings forecasts we can analyze directly the effect of new information on analysts' forecast revisions and evaluate whether these revised forecasts converge to rational expectations forecasts. The forecasts made by security analysts participating in the Institutional Brokers Estimate System (IBES) database are analyzed. Using standard statistical tests, we reject the simple form of the rational expectations hypothesis. However, by extending the standard tests used in previous studies, we obtain results that suggest that analysts' earnings forecasts conform to a dynamic form of rationality. The tendency of revised forecasts to converge stochastically toward the rational expectations forecast cautions against the rejection of more complicated forms of rationality.     

The role of financial analysts in stock market efficiency with respect to annual earnings and its cash and accrual components

This study examines biases in stock prices and financial analysts' earnings forecasts. These biases take the form of systematic overweighting or underweighting of the persistence characteristics of cash versus accrual earnings components. Our evidence suggests that stock prices tend to overweight and financial analysts tend to underweight these persistence characteristics. Furthermore, we find that analysts' underweighting attenuates stock price overweighting. However, we find little evidence that the overweighting in stock prices attenuates analyst underweighting. This study brings a new perspective to the literature regarding the disciplining role of financial analysts in capital markets.     

Analyst target price revisions and institutional herding

We document that institutional herding behavior is associated with analyst target price revisions even after controlling for the effects of analyst recommendations and earnings forecasts, and provide insights into the price impact of institutional herding. Institutional investors tend to buy the same stocks following an upward target price revision and sell the same stocks following a downward price revision. Moreover, institutional investors tend to overreact to analysts' target price revisions, which exacerbates the mispricing in the stock market. Such price destabilizing effect is particularly pronounced for herding among investment firms.     

Does Shareholder Composition Matter? Evidence from the Market Reaction to Corporate Earnings Announcements

We examine whether institutional ownership composition is related to parameters of the market reaction to negative earnings announcements. When firms report earnings below analysts' expectations, the stock price response is more negative for firms with higher levels of ownership by momentum or aggressive growth investors. There is no evidence, however, that these institutions cause an “overreaction” to earnings news. Ownership structure is also related to trading volume and to stock price volatility on days around earnings announcements. Our findings are consistent with the idea that the composition of institutional shareholders effects stock price behavior around the release of corporate information.     

Model-based earnings forecasts vs. financial analysts' earnings forecasts

Existing accounting-based forecasting models of earnings either do not fully consider information that is contained in stock prices or use an ad hoc specification that is not based on rigorous valuation theory. In this paper, we develop an earnings forecasting model built on the theoretical linkages between future earnings and stock prices as well as a number of accounting fundamental variables. We find that our model-based forecasts of earnings are in general less biased and more accurate than both existing model-based forecasts and analysts' consensus forecasts, at both shorter and longer horizons. We also show that the accuracy of both model-based forecasts and financial analysts' forecasts depend on firm-specific characteristics such as firm size and industry membership.     

Does revenue-expense matching play a differential role in analysts’ earnings and revenue forecasts?

This paper investigates whether matching has differential implications for the accuracy of analysts' earnings and revenue forecasts. We construct a novel measure of firm-level matching and document that matching improves analysts' earnings forecasts to a greater extent than their revenue forecasts. We also document matching's differential impact on analysts' earnings and sales forecasts by proposing a new count metric capturing a wedge in the accuracy of earnings and revenue forecasts. In additional tests, we report that the differential impact of matching is less (more) pronounced in a situation where the balance sheet (income statement) orientation likely dominates. We also report that matching's differential role is weaker (stronger) when firms have high intangible intensity (analysts have appropriate resources or expertise). In short window tests, matching's role in analysts' forecast revisions is more pronounced for earnings than sales forecasts. Overall, these results show how analysts benefit from better revenue-expense matching.     

Investor and (Value Line) Analyst Underreaction to Information about Future Earnings: The Corrective Role of Non-Earnings-Surprise Information

Prior research suggests that financial analysts' earnings forecasts and stock prices underreact to earnings news. This paper provides evidence that analysts and investors correct this underreaction in response to the next earnings announcement and to other (non-earnings-surprise) information available between earnings announcements. Our evidence also suggests that analysts and investors underreact to information reflected in analysts' earnings forecast revisions and that non-earnings-surprise information helps correct this underreaction as well. Controlling for corrective non-earnings-surprise information significantly increases estimates of the degree to which analysts' forecasting behavior can explain drifts in returns following both earnings announcements and analysts' earnings forecast revisions.     

Sell-side analyst heterogeneity and insider trading

This study explores insider trading patterns under different earnings surprises. After controlling for stock market liquidity and earnings announcements returns, we show that insiders sell more aggressively depending on the heterogeneity of analysts whose EPS forecasts are met or beaten to camouflage their trades. Specifically, insiders sell more shares of their company sooner after the publication of earnings when top analysts' forecasts are met or beaten. Consistent with the informed trading literature, insiders strategically select these moments because the stock price impact is low and the legal scrutiny of their trades is minimal. To support this result, we employ an exogenous drop in firms' analyst coverage due to the closure or merger of brokerage houses. Furthermore, in line with the camouflage incentives, by selling after top analysts' forecasts are met or beaten, stock prices adjust slowly to insider trades. Finally, we show that the incentives of insiders to hide their trades are concentrated in opportunistic insiders and members of the top management team, who are more likely to bear the costs of selling shares after positive news.     

Valuing Loss Firms: What Can Be Learned From Analysts' Forecasts?

Prior research documents an anomalous negative price–earnings relation when a simple earnings capitalization model is estimated for loss‐making firms. Collins et al. (1999 ) suggest that the model is misspecified due to the omission of book value of equity. However, results from previous studies are confusing. We try to enrich prior literature by focusing on analysts' forecasts. In particular, we assess the role of earnings and book value in valuing loss firms using several measures based on the information provided by analysts. We hypothesize that the role of accounting figures depends on whether the loss firm is supported or not by investors. According to this argument, we construct several measures of investor support based on analysts' forecasts, and then test the value relevance of accounting information depending on the degree of support. Our results confirm the usefulness of the notion of ‘investor support’. For those loss firms that are expected to liquidate, we find that the inclusion of book value of equity in the model removes the negative sign on the earnings coefficient. However, for those loss firms that are expected to reverse current losses, we find that the coefficient on earnings remains negative despite the inclusion of book value.     

Bonus schemes and trading activity

Little is known about how different bonus schemes affect traders' propensity to trade and which bonus schemes improve traders' performance. We study the effects of linear versus threshold bonus schemes on traders' behavior. Traders buy and sell shares in an experimental stock market on the basis of fundamental and technical information (past share price evolution, realized earnings, analysts' earnings forecasts, and evolution of the market index). We find that linear and threshold bonus schemes have different effects on trading behavior: traders make more transactions but of a smaller size under the threshold than under the linear bonus scheme. Furthermore, transaction frequency significantly decreases when bonus thresholds are reached but only after building in a safety margin. Under the threshold scheme, the traders' performance is lower (even when there are no transaction costs) than under the linear bonus scheme as a consequence of poorer market timing. This is especially the case when earning money by trading is relatively difficult (i.e., under low profitability conditions). Nevertheless, under low profitability conditions, traders seem to collect more information about the relationships between share price and market returns, earnings, and earnings forecasts, put more effort into understanding those relationships, and thus eventually learn to perform better.     

The use of management forecasts to dampen analysts' expectations by Chinese listed firms

This paper studies the use of management earnings forecasts (MEF) to dampen analysts' expectations, i.e. expectation management, by Chinese listed companies. We reveal several important findings: Firstly, information asymmetry is positively associated with the use of MEF to dampen analysts' expectations. State control has been found to moderate this relationship. Secondly, dampening analysts' expectations using MEF leads to negative stock return reactions and downward analysts' forecast revisions. Thirdly, the effectiveness of “pre-empting bad news through MEF” appears mixed and dependent on the information content of MEF and measures of actual earnings surprises. Finally, firms that disclose MEF are found to engage in more earnings management to meet the forecasts than firms that do not.     

Momentum Strategies

We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk, size, and book–to–market effects do not explain the drifts. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Security analysts' earnings forecasts also respond sluggishly to past news, especially in the case of stocks with the worst past performance. The results suggest a market that responds only gradually to new information.     

Earnings Forecast Revisions and Security Returns: Canadian Evidence

The impact that revisions of financial analysts' forecasts of earnings have on Canadian security returns during the 1979-1988 period is tested using an event study methodology. A post-revision announcement drift in security prices is documented; the Canadian capital market displays a marked delay in reacting to positive revisions in earnings forecasts. Contingent on revision size, positive and significant excess returns are apparent for up to seven months following their release. The returns, before transaction costs, are not marginal; over a 12-month holding period, excess returns are 18.2%. The results for negative and non-revisions in earnings forecasts suggest that the market reacts quite efficiently to the information implicit in these events. An explanation for the asymmetrical results for the positive and negative revision portfolios is offered. These findings are robust to five control procedures used to test the sensitivity of the reported results to changes in the methodology. A number of explanations for this result are proposed including overlapping excess returns and beta shifts; none reconciles the anomalous results.     

Common Stock Offerings and Earnings Expectations: A Test of the Release of Unfavorable Information

This paper examines the revisions of analysts' forecasts of future earnings around announcements of common stock offerings. The forecasts of the current year earnings are, on average, decreased when firms announce plans to issue additional common stock. The size of the decrease is significantly related to announcement period abnormal stock returns. In contrast, forecasts of the five-year growth rate of earnings are, on average, unchanged. We interpret these results as being consistent with the claim that equity offering announcements convey unfavorable information regarding the firm's short-term but not its long-term earnings prospects.     

Natural disasters and analysts' earnings forecasts

The effects of natural disasters on capital markets have been investigated by limited evidence even though these calamities bring considerable damages or loss of life. To fill this gap, we investigate the impacts of natural disasters, particularly earthquakes, on security analysts' earnings forecasts for affected firms in China. We obtain three key findings. First, analysts' optimism significantly decreases for firms located in neighborhood areas. Second, earthquakes do not significantly affect firm earnings and stock returns, thereby indicating that post-earthquake analyst pessimism is not based on rational judgment. Third, media attention promotes irrational pessimism among analysts, and post-earthquake pessimism is a result of heuristics bias attributable to psychological shocks. However, analysts correct the bias after initial irrational forecasts. Taken together, our findings contribute to the broader psychology and economics literature on the effects of natural disasters on analyst forecasts.     

Stock returns after major price shocks: The impact of information

This paper focuses on stocks that experience major price changes. Using analyst reports as a proxy, I find that price events accompanied by information are followed by drift, while no-information ones result in reversals. One interpretation of these results is that investors underreact to news about fundamentals and overreact to other shocks that move stock prices. Consistent with this hypothesis, information-based price changes are more strongly correlated with future earnings surprises than no-information ones. Furthermore, drift exists only when the direction of the price move and of the change in analyst recommendations have the same sign. Finally, the ratio of no-information to information-based price shocks is strongly correlated with aggregate implied volatility and also forecasts momentum returns.     

An Empirical Analysis of Analysts' Target Prices: Short-term Informativeness and Long-term Dynamics

Using a large database of analysts' target prices issued over the period 1997–1999, we examine short‐term market reactions to target price revisions and long‐term comovement of target and stock prices. We find a significant market reaction to the information contained in analysts' target prices, both unconditionally and conditional on contemporaneously issued stock recommendation and earnings forecast revisions. Using a cointegration approach, we analyze the long‐term behavior of market and target prices. We find that, on average, the one‐year‐ahead target price is 28 percent higher than the current market price.     

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time‐series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time‐series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.     

More Than Words: Quantifying Language to Measure Firms' Fundamentals

We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm-specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard-to-quantify aspects of firms' fundamentals, which investors quickly incorporate into stock prices.