Does the Stock Market See a Zero or Small Positive Earnings Surprise as a Red Flag?

This study shows that firms collectively incur a cost for managing earnings and analyst expectations to meet earnings forecasts. We compare the coefficient in the regression of abnormal stock returns on earnings surprise (the earnings response coefficient [ERC]) across ranges of earnings surprises. The ERC for earnings surprises in the range [0, 1¢] is significantly lower than ERCs for earnings surprises in adjacent ranges for firm-quarters in the early and mid 2000s, but not for those in the 1990s. The results are robust to controlling for the sign of estimated discretionary accruals and the trajectory of analyst earnings forecasts. We further find that investors are right to be skeptical about earnings surprises in the range [0, 1¢]. The relation of future earnings surprise with current earnings surprise is more negative for current earnings surprises in that range than for those in any other range. Evidence also suggests analysts react negatively to earnings surprises in that range.     

A Temporal Analysis of Earnings Surprises: Profits versus Losses

I show that median earnings surprise has shifted rightward from small negative (miss analyst estimates by a small amount) to zero (meet analyst estimates exactly) to small positive (beat analyst estimates by a small amount) during the 16 years, 1984 to 1999. I show that a rightward temporal shift in median surprise from negative to positive describes earnings, but neither profits nor losses. Median profit surprise shifts within the positive quadrant, from zero to one cent per share. Median loss surprise shifts within the negative quadrant from extreme negative (about -33 cents per share) to zero. I show that the median surprise for profits exceeds that for losses in every year. I document significant positive temporal trends in both meet and beat analyst estimates for both profits and losses, but I find a greater frequency of profits that either meet or beat analyst estimates in every year. I find a significant positive temporal trend in positive profits that are "a little bit of good news," and a significant negative temporal trend in managers who report losses that are an "extreme amount of bad news." My results are robust to the four internal validity threats I consider—namely temporal changes in: (1) analyst forecast accuracy, (2) the mix of earnings of one sign preceded by earnings of another sign four quarters ago, (3) the timeliness of the most recent analyst forecast, and (4) the I/B/E/S definition of actual earnings. I find that managers of growth firms are relatively more likely than managers of value firms to report good news profits. I show that when they do report positive profit surprises, managers of growth firms are more likely to report "a little bit of good news" in every year.     

Analyst information precision and small earnings surprises

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings.     

A new perspective on post‐earnings‐announcement‐drift: Using a relative drift measure

Prior research finds that there is a delayed reaction to both analyst‐based earnings surprises and random‐walk‐based earnings surprises. Focusing on the market reaction from the post‐announcement window, prior studies show that analyst‐based drift is larger than random walk‐based drift. This finding is counter‐intuitive if we believe large, sophisticated investors tend to trade on analysts’ forecast earnings news and thus react faster and more completely than smaller and less sophisticated investors react to random walk earnings news. In this study, we construct a relative measure of post‐earnings‐announcement drift (PEAD) (i.e., drift as a proportion of total market reaction to earnings news) which we refer to as the ‘drift ratio’, and we provide evidence, consistent with our intuition, that analyst‐based drift ratio is smaller (not greater) than random‐walk‐based drift ratio. We find that this difference is more pronounced in more recent periods and for firms with more sophisticated investors. Our approach to measure the PEAD is more intuitive than that in traditional PEAD literature. Our results thus complement existing research findings by utilizing the drift ratio measure to generate new insights about the drift phenomenon.     

Separating Winners from Losers among LowBook-to-Market Stocks using Financial Statement Analysis

This paper combines traditional fundamentals, such as earnings and cash flows, with measures tailored for growth firms, such as earnings stability, growth stability and intensity of R&D, capital expenditure and advertising, to create an index – GSCORE. A long–short strategy based on GSCORE earns significant excess returns, though most of the returns come from the short side. Results are robust in partitions of size, analyst following and liquidity and persist after controlling for momentum, book-to-market, accruals and size. High GSCORE firms have greater market reaction and analyst forecast surprises with respect to future earnings announcements. Further, the results are inconsistent with a risk-based explanation as returns are positive in most years, and firms with lower risk earn higher returns. Finally, a contextual approach towards fundamental analysis works best, with traditional analysis appropriate for high BM stocks and growth oriented fundamental analysis appropriate for low BM stocks.This revised version was published online in August 2005 with a corrected cover date.     

Sell‐Side Analyst Research and Stock Comovement

We document that a stock's price around a recommendation or forecast covaries with prices of other stocks the issuing analyst covers. The effect of shared analyst coverage on stock price comovement extends beyond analyst activity days. A stock's daily returns covary with the returns of other stocks with which it shares analyst coverage. These links between stock price comovement and shared analyst coverage are consistent with the coverage‐specific information we find in earnings forecasts; analysts who cover both stocks in a pair expect future earnings of the stocks to be more highly correlated than do analysts who cover only one stock from the pair. Collectively, our evidence indicates that analyst research produces coverage‐specific spillovers that raise price comovement among stocks that share analyst coverage. The strength of these spillovers is comparable to spillovers from broad industry and market information in analyst research.     

The Dynamics of Earnings Forecast Management

This paper examines whether firms manage analyst forecasts andthe associated value consequences. We find that earnings forecaststend to grow pessimistic over the forecast horizon and theseforecast changes and their timing are key determinants of whetherfirms generate positive earnings surprises: Late forecasts thatraise (lower) the consensus sharply reduce (raise) the probabilityof positive surprises. This findng is the opposite of that predictedif consensus revisions reflected new information arrival. Investorsseem to be "misled": downward consensus revisions lead to largeabnormal returns following the earnings announcement. Paradoxically,downward forecast management reduces post-announcement shareprice, as the impact of reduced forecasts dominates the gainfrom generating positive surprises.     

Effects of Preannouncements on Analyst and Stock Price Reactions to Earnings News

This study examines the effects of earnings preannouncements on financial analyst and stock price reactions to earnings news. Prior experimental research documents that when the signs of a preannouncement surprise and subsequent earnings announcement surprise are consistent (i.e., both either positive or negative), analysts make larger magnitude revisions to their future period earnings forecasts in response to the total earnings news conveyed in the preannouncement and earnings announcement than when the surprise signs are inconsistent. This study extends this research by examining a sample of actual preannouncements from 1993–1997 to determine whether the effects documented in laboratory settings manifest at the aggregate market level in stock prices and consensus analyst forecast revisions. Results indicate that after controlling for the sign of earnings news, sign of earnings, and sign of the earnings announcement surprise, stock prices and analyst forecast revisions respond more strongly when a preannouncement and subsequent earnings announcement elicit the same surprise signs than when the surprise signs are inconsistent. Further analysis indicates that the consistency of the signs of a preannouncement surprise and earnings announcement surprise is not associated with future earnings, suggesting that the magnified reaction of investors and analysts to consistent surprise signs is not a rational reaction to associations observed in market settings.     

Accounting-based downside risk and expected stock returns: Evidence from China

We document that earnings downside risk contains information on firms' future operating performance and is positively associated with expected stock returns in Chinese stock markets, and the return predictability of earning downside risk mainly comes from its accrual downside risk component. The pricing of earnings downside risk is especially evident among firms with more transparent information environment and stronger governance efficacy, such as large firms, non-high-tech firms, old firms, and firms with high analyst coverage. Lastly, we show that aggregated earnings downside risk and its components at the market level are all significantly and positively associated with subsequent stock market returns, which is consistent with the notion that the accounting-based downside risk measures contain information about future macroeconomic conditions.     

The outperformance of family firms: the role of variance in earnings per share and analyst forecast dispersion on the Swiss market

Recent studies provide empirical evidence that family firms are outperforming their non-family counterparts in terms of stock market performance. For the Swiss stock market we find that family firms indeed outperform their non-family counterparts after controlling for firm size and beta. In addition, our data shows that family firms display more stable earnings per share in contrast to their non-family counterparts. Furthermore we find that the variance of earnings per share positively affects analyst forecast dispersion. According to anomaly literature, lower analyst forecast dispersion has been found to induce higher excess return, which our data supports for the Swiss stock market. By linking variance of earnings per share, analyst forecast dispersion and stock performance we provide an insightful explanation for the excess stock market returns of family firms. In addition, our text extends the theory of dispersion effect with an additional empirical element, the variance of earnings per share.      

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.     

The Predictive Content of Aggregate Analyst Recommendations

Using more than 350,000 sell‐side analyst recommendations from January 1994 to August 2006, this paper examines the predictive content of aggregate analyst recommendations. We find that changes in aggregate analyst recommendations forecast future market excess returns after controlling for macroeconomic variables that have been shown to influence market returns. Similarly, changes in industry‐aggregated analyst recommendations predict future industry returns. Changes in aggregate analyst recommendations also predict one‐quarter‐ahead aggregate earnings growth. Overall, our results suggest that analyst recommendations contain market‐ and industry‐level information about future returns and earnings.     

Short Interest,Returns, and Unfavorable Fundamental Information

Several months before information becomes public, the level of short interest contains value‐relevant information about publicly traded corporations. Short interest predicts future bad news, negative earnings surprises, and downward revisions in analyst earnings forecasts. This informational content is stronger for stocks that are harder to short. We also find that nearly half of the well‐known cross‐sectional relation between short interest and future stock returns is related to future changes in firms’ value‐relevant information. Our results suggest that short interest predicts future returns, in part, due to short sellers’ ability to uncover unfavorable information about firms.     

The effect of earnings surprises on information asymmetry

We examine the effect of earnings surprises on changes in information asymmetry. We hypothesize and find that asymmetry is lower (higher) in the quarter following positive (negative) earnings surprises compared to firms that meet the consensus analyst earnings forecast. The relations between earnings surprises and information asymmetry are stronger when the surprises are more likely to capture investors’ attention. Examining the source of these changes, we show that decreased information search activities is the most important factor for asymmetry declining after positive surprises; for negative surprises, decreased uninformed trading plays a dominant role increasing asymmetry.     

Can security analyst forecasts predict gold returns?

This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be utilised to predict returns on the price of gold. We first demonstrate that analysts are at least in part basing their earnings forecasts for gold firms on the return expectations of the gold commodity market. We show this by providing evidence that analyst coverage impounds not only market-wide and industry information, but also gold price information for these firms — as measured via its impact on stock return synchronicity. We then examine if the difference between forecast and observed earnings for these firms has predictive value for changes in the price of gold whilst controlling for a number of macroeconomic factors. We find that this difference does hold predictive power, but also has some limitations. However, there is potential for it to be used as an additional variable within gold forecasting frameworks.     

To beat or not to beat? The importance of analysts’ cash flow forecasts

We investigate the implications of firms’ benchmark-beating patterns with respect to analysts’ quarterly cash flow forecasts for firms’ current capital market valuation and their future performance. We hypothesize that nonnegative earnings surprises are more likely to be supported by real operating performance and signal higher earnings quality if they are achieved via higher than expected cash flows or lower than expected accruals. We show that firms beating analyst earnings forecasts have larger positive capital market reactions and larger earnings response coefficients if they beat analyst cash flow forecasts or report lower than expected accruals. We also demonstrate that these firms’ superior future performance may provide an economic justification for their more favorable market response. Our findings suggest that firms’ ability to beat analyst cash flow forecasts is informative regarding the quality of their earnings surprises.     

Does Weak Governance Cause Weak Stock Returns? An Examination of Firm Operating Performance and Investors' Expectations

We investigate Gompers, Ishii, and Metrick's (2003) finding that firms with weak shareholder rights exhibit significant stock market underperformance. If the relation between poor governance and poor returns is causal, we expect that the market is negatively surprised by the poor operating performance of weak governance firms. We find that firms with weak shareholder rights exhibit significant operating underperformance. However, analysts' forecast errors and earnings announcement returns show no evidence that this underperformance surprises the market. Our results are robust to controls for takeover activity. Overall, our results do not support the hypothesis that weak governance causes poor stock returns.     

The effect of restatements on analyst behavior

This paper examines how changes in the credibility of financial reporting affect analyst behavior. Using a sample of restatement firms experiencing a substantial change in credibility over 1997–2006, we document that restatements have a long‐lived effect on analyst behavior and that analysts differentiate between restatements caused by irregularities and those caused by errors. We find that while irregularity restatement firms exhibit a reduction in analyst coverage and forecast accuracy and an increase in forecast dispersion in the post‐restatement period, other restatement firms exhibit only an increase in forecast error. Finally, we find evidence to suggest that remedial actions reduce the effect of irregularity restatements on analyst behavior. Overall, these results are consistent with the notion that restatements affect analyst behavior in forming judgements regarding subsequent earnings announcements.     

Analyst reputation and management earnings forecasts

Prior studies show that analysts with high reputation are influential in the market. This paper examines whether managers consider analyst reputation in shaping their voluntary disclosure strategy. Using Institutional Investor magazine’s All-American (AA) rankings as a proxy for analyst reputation, we find that the coverage of AA analysts is positively associated with the likelihood of quarterly management earnings forecasts (MEFs). We also find that AA analysts’ forecast optimism is more positively associated with the likelihood of MEFs than non-AA analysts’ forecast optimism when the firm is covered by AA analysts. Analyses based on AA analyst coverage changes and AA status changes confirm the relation between analyst reputation and MEFs. We further find that analyst reputation influences other MEF properties, such as forecast news, bias, and revisions, and that our results are robust to alternative measures of analyst reputation. Further analyses show that market reactions at quarterly earnings announcements are more positive (negative) when firms meet/beat (miss) AA analysts’ forecasts than when firms meet/beat (miss) non-AA analysts’ forecasts. Collectively, our findings suggest that managers strategically provide voluntary forecasts by taking into account the reputation of individual analysts following their firms.     

Analyst Pessimism and Forecast Timing

In this study, we show that on average relatively pessimistic analysts tend to reveal their earnings forecasts later than other analysts. Further, we find this forecast timing effect explains a substantial proportion of the well‐known decrease in consensus analyst forecast optimism over the forecast period prior to earnings announcements, which helps explain why analysts’ longer term earnings forecasts are more optimistically biased than their shorter term forecasts. We extend the theory of analyst self‐selection regarding their coverage decisions to argue that analysts with a relatively pessimistic view–compared to other analysts–are more reluctant to issue their earnings forecasts, with the result that they tend to defer revealing their earnings forecasts until later in the forecasting period than other analysts.