Post–earnings–announcement Drift in the UK

This paper fills a void in the market efficiency literature by testing for the presence of post–earnings–announcement drift in a non–US market. We test for drift using alternative earnings surprise measures based on: (i) the time–series of earnings; (ii) market prices; and (iii) analyst forecasts. Using each of the measures we find evidence of significant post–earnings–announcement drift, robust to alternative controls for risk and market microstructure effects. Using a one–dimensional analysis, the price–based measure of earnings surprise gives the strongest drift, and using a two–dimensional analysis the drift associated with the price–based measure almost subsumes drift associated with the other two measures. Our conclusion is that the UK stock market is inefficient with respect to publicly available corporate earnings information. This evidence provides out–of–sample confirmation of the post–earnings–announcement drift documented in the USA.     

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.     

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.     

Post earnings announcement drift and the roles of drift-enhanced factors in New Zealand

This study examines the profitability of trading on analyst forecast-based earnings surprises during the post announcement period in the New Zealand stock market over the period 1994 to 2008. The results show that a post earnings announcement drift (PEAD) anomaly exists in the New Zealand equity market. A hedge strategy of going long the top quintile of earnings surprise stocks and short the bottom quintile of earnings surprise stocks can generate more than 6% excess return in the 60 days following the earnings announcement. I further test the association between PEAD and several control variables and find that PEAD is increasing in 1) earnings surprise defined relative to past earnings, and 2) the level of arbitrage risk. Interestingly, I do not find evidence of a positive relation between PEAD and revenue surprise after controlling for earnings surprise as documented in the United States (Jegadeesh and Livnat, 2006). There is also no evidence that the 2002 Disclosure Reform in the New Zealand Stock Exchange reduced the magnitude of PEAD.     

Conditional Persistence of Earnings Components and Accounting Anomalies

We suggest that the failure of investors to distinguish between an earnings component's autocorrelation coefficient (unconditional persistence) and the marginal contribution of that component's persistence to the persistence of earnings (conditional persistence) provides a partial explanation of post‐earnings‐announcement drift, post‐revenue‐announcement drift, and the accrual anomaly. When the conditional persistence of revenue surprises is high (low) relative to its unconditional persistence, both the post‐earnings‐announcement drift and the post‐revenue‐announcement drift are high (low), because investors’ under‐reaction to revenues and earnings is stronger when the persistence of revenue surprises is more strongly associated with the persistence of earnings surprises. Also, the mispricing of accruals decreases substantially when the conditional persistence of accruals is high relative to its unconditional persistence, because investors’ over‐reaction to accruals is mitigated when the persistence of accruals is indeed more strongly associated with the persistence of earnings. Our findings also suggest that financial analysts’ failure to distinguish between unconditional and conditional persistence of revenues and accruals results in more biased revenue and earnings predictions.     

Information,uncertainty, and behavioral effects: Evidence from abnormal returns around real estate investment trust earnings announcements

In this study, we examine the influence of real estate market sentiment, market-level uncertainty, and REIT-level uncertainty on cumulative abnormal earnings announcement returns over the 1995–2009 time period. We first document the relative coverage of analysts' earnings forecasts on U.S. REITs, as well as REITs from several countries (i.e., Australia, Belgium, Canada, France, Hong Kong, Japan, the Netherlands, and UK). We show that coverage outside of the U.S. is limited, and we consequently focus our analysis on U.S. REITs. We find strong evidence that earnings announcements contain pricing relevant information, with positive (negative) earnings surprises relative to analysts' forecasts resulting in significantly positive (negative) abnormal returns around the announcement date. Consistent with the findings from the broader equity market literature, we find limited evidence of a pre-announcement drift in the cumulative abnormal returns. However, in sharp contrast to the existing equity literature, we find no evidence of a post-earnings announcement drift in our aggregate sample or when the sample is restricted to the largest negative surprises. We find evidence of a post-earnings announcement drift for only the largest positive earnings surprises. These results are consistent with REIT returns more quickly impounding information relative to the broader equity market, in part because of the parallel private real estate market and because of the U.S. REIT structure and information environment. Finally, in our conditional regression analysis of cumulative abnormal returns, we find that real estate investor sentiment, market-wide uncertainty, and firm-level uncertainty significantly affect the magnitude of abnormal announcement returns and also influence the effect of unexpected earnings on abnormal returns.     

Unsophisticated Arbitrageurs and Market Efficiency: Overreacting to a History of Underreaction?

Prior research has documented that arbitrage activity significantly reduces or eliminates stock market anomalies. However, if anomalies arise due to unsophisticated investors’ behavioral biases, then these same biases can also apply to unsophisticated arbitrageurs and thereby disrupt the arbitrage process. Consistent with a disruption in the arbitrage process for the post‐earnings announcement drift anomaly, I document that the historically positive autocorrelation in firms’ earnings announcement news has become significantly negative for firms with active exchange‐traded options. For these easy‐to‐arbitrage firms, the firms in the highest decile of prior earnings announcement abnormal return (prior earnings surprise), on average, underperform the firms in the lowest decile by 1.59% (1.43%) at their next earnings announcement. Additional analyses are consistent with investors learning about the post‐earnings announcement drift anomaly and overcompensating. This study suggests that unsophisticated attempts to profit from a well‐known anomaly can significantly reverse a previously documented stock return pattern.     

How Much New Information Is There in Earnings?

We quantify the relative importance of earnings announcements in providing new information to the share market, using the R² in a regression of securities' calendar‐year returns on their four quarterly earnings‐announcement “window” returns. The R², which averages approximately 5% to 9%, measures the proportion of total information incorporated in share prices annually that is associated with earnings announcements. We conclude that the average quarterly announcement is associated with approximately 1% to 2% of total annual information, thus providing a modest but not overwhelming amount of incremental information to the market. The results are consistent with the view that the primary economic role of reported earnings is not to provide timely new information to the share market. By inference, that role lies elsewhere, for example, in settling debt and compensation contracts and in disciplining prior information, including more timely managerial disclosures of information originating in the firm's accounting system. The relative informativeness of earnings announcements is a concave function of size. Increased information during earnings‐announcement windows in recent years is due only in part to increased concurrent releases of management forecasts. There is no evidence of abnormal information arrival in the weeks surrounding earnings announcements. Substantial information is released in management forecasts and in analyst forecast revisions prior (but not subsequent) to earnings announcements.     

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.     

Earnings surprise and sophisticated investor preferences in India

In this paper, I examine the existence of earnings surprise anomaly for a sample of actively traded stocks in the Bombay Stock Exchange during 2001–2006. I also examine if sophisticated institutional investors, in particular transient investors, exploit the earnings surprise anomaly. My results indicate that using a standard time series model to forecast earnings, there is clear evidence of a post-earnings announcement drift in the Indian market, even after controlling for common factors that affect risk and transaction costs. However, I find very little evidence that indicates transient investors exploit the earnings surprise mispricing. Attribution analysis of hedge portfolio returns based on increases in ownership by transient investors indicates that earnings surprise does not play a role; risk and liquidity does. A direct test of what causes increase in ownership by transient investors provides little support for the role of earnings surprise. Robustness tests also indicate that while earnings surprise is mispriced by the market, the level of transient investor ownership does not mitigate this effect.     

Diagnostic Expectations and Stock Returns

We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.     

The Extreme Future Stock Returns Following I/B/E/S Earnings Surprises

We investigate the stock returns subsequent to quarterly earnings surprises, where the benchmark for an earnings surprise is the consensus analyst forecast. By defining the surprise relative to an analyst forecast rather than a time‐series model of expected earnings, we document returns subsequent to earnings announcements that are much larger, persist for much longer, and are more heavily concentrated in the long portion of the hedge portfolio than shown in previous studies. We show that our results hold after controlling for risk and previously documented anomalies, and are positive for every quarter between 1988 and 2000. Finally, we explore the financial results and information environment of firms with extreme earnings surprises and find that they tend to be “neglected” stocks with relatively high book‐to‐market ratios, low analyst coverage, and high analyst forecast dispersion. In the three subsequent years, firms with extreme positive earnings surprises tend to have persistent earnings surprises in the same direction, strong growth in cash flows and earnings, and large increases in analyst coverage, relative to firms with extreme negative earnings surprises. We also show that the returns to the earnings surprise strategy are highest in the quartile of firms where transaction costs are highest and institutional investor interest is lowest, consistent with the idea that market inefficiencies are more prevalent when frictions make it difficult for large, sophisticated investors to exploit the inefficiencies.     

EARNINGS NEWS AND MARKET RISK: IS THE MAGNITUDE OF THE POSTEARNINGS ANNOUNCEMENT DRIFT UNDERESTIMATED?

Postearnings announcement drift is the tendency for cumulative abnormal returns to drift in the direction of earnings surprise after the earnings news is released. I show that a standard approach to measuring abnormal returns by using preannouncement estimates of market risk (betas) causes the magnitude of this phenomenon to be significantly underestimated. I find that stock beta tends to rise (fall) following the release of bad (good) earnings news. In addition, I find that by not taking into account postannouncement shifts in betas, prior studies are likely to have underestimated the magnitude of the drift. My results are robust to different model specifications, as well as to different earnings surprise measures.     

Sell on the news: Differences of opinion,short-sales constraints,and returns around earnings announcements

Miller [1977. Risk, uncertainty, and divergence of opinion. Journal of Finance 32, 1151–1168] hypothesizes that prices of stocks subject to high differences of opinion and short-sales constraints are biased upward. We expect earnings announcements to reduce differences of opinion among investors, and consequently, these announcements should reduce overvaluation. Using five distinct proxies for differences of opinion, we find that high differences of opinion stocks earn significantly lower returns around earnings announcements than low differences of opinion stocks. In addition, the returns on high differences of opinion stocks are more negative within the subsample of stocks that are most difficult for investors to sell short. These results are robust when we control for the size effect and the market-to-book effect and when we examine alternative explanations such as financial leverage, earnings announcement premium, post-earnings announcement drift, return momentum, and potential biases in analysts’ forecasts. Also consistent with Miller's theory, we find that stocks subject to high differences of opinion and more binding short-sales constraints have a price run-up just prior to earnings announcements that is followed by an even larger decline after the announcements.     

Does voluntary balance sheet disclosure mitigate post-earnings-announcement drift?

Theory suggests that balance sheet information such as total assets, total equity, or total liabilities complements earnings information in helping investors assess a firm’s profitability and estimate earnings growth. The voluntary disclosure of balance sheet information at earnings announcement could help investors gather and process this information at a lower cost. We therefore predict that voluntary balance sheet disclosure at the time of an earnings announcement helps investors promptly understand the implication of current earnings news for future earnings and subsequently reduces post-earnings-announcement drift (PEAD). Consistent with these predictions, our results show that when firms provide voluntary balance sheet disclosures, the earnings response coefficient in the event window is significantly higher and the corresponding PEAD is significantly lower. We further find that the impact of voluntary balance sheet disclosure on PEAD is more pronounced when the magnitude of balance sheet value surprise is larger, when balance sheet value is more informative about future earnings, when earnings uncertainty is higher, or when information cost is higher, consistent with our conjectures that helping investors to better understand future earnings performance and lowering information costs are key mechanisms underlying the effect of voluntary balance sheet disclosure on PEAD.     

Earnings Surprise "Materiality" as Measured by Stock Returns

Ranked earnings surprise portfolios formed from First Call files for 1992–97 are used to assess the annual earnings surprise magnitude for an individual firm sufficient to expect a "significant market reaction." We find that, for an individual firm, the maximum probability of a gain from trading on prior knowledge of any surprise magnitude is .622. The lack of probable trading gains is due to the S–shaped surprise/return relation and the large variance of returns for a given magnitude of surprise. In turn, we find that the S–shape is related empirically to the dispersion of analyst forecasts. Thus, factors underlying dispersion differences are related to the importance or "materiality" of earnings surprise as measured by stock returns and explain at least part of the S–shaped surprise/return relation.     

Do Publicly Signalled Earnings Management Incentives Affect Analyst Forecast Accuracy?

Using a panel of listed Australian firms for the years 1999–2007, this paper investigates whether analysts' forecast efficiency is improved by the occurrence of a publicly observable event, such as a CEO appointment, which signals a firm's earnings management incentives. Two supporting hypotheses are also tested: first, that CEO appointments are associated with income‐decreasing earnings management; and second, that analyst forecast errors increase with the level of earnings management present in current period financial statements. Consistent with prior literature, we find income‐decreasing earnings management in the year of CEO appointment. Earnings management, as a general phenomenon, is found to be significantly related to analyst forecast errors in the period in which the earnings management occurs. However, we present evidence that analyst forecasts for current year earnings are significantly more accurate with respect to earnings management in cases where a CEO is appointed during the current financial period.     

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.     

Objective estimation versus subjective perceptions of earnings patterns and post‐earnings‐announcement drift

We investigate how the market's subjective estimates of autocorrelation in quarterly earnings vary with objective time‐series estimates. Our results suggest that investors increasingly underestimate the correlation as the autocorrelation level increases, and as a result, the post‐earnings‐announcement drift (PEAD) increases with the level of autocorrelation. We further show that the ability of autocorrelation to explain variation in the PEAD is robust to alternative explanations based on risk and institutional factors. Additional analysis indicates that the market's inefficiency in assessing the existence and magnitude of autocorrelation (and the related impact on PEAD) is inversely related to the richness of the information environment.     

Does short selling reduce analysts’ optimism bias in earnings forecasts?

We examine the relationship between short selling and analyst optimism bias of earnings forecasts of stocks in China. We propose two possible hypotheses: short selling enhances analysts’ information set to lower optimism bias and analysts drum up optimistic earnings forecasts to counter short selling. Our results suggest that short selling and earnings optimism bias are negatively correlated. The findings are robust to a two-stage least square method, a difference in-differences fixed effect model, an alternative measure of optimism bias, incorporated different time windows to calculate short selling, considered bull and bear market conditions, accounting for media coverage, and using abnormal short selling. By leveraging rich data, we conduct additional analyses using stocks with different forecasting horizons and earnings forecasts that were made after the accounting year but prior to the earnings announcement to further support expanding the information set argument. Lastly, we document that short selling information improves the accuracy of earnings forecasts.