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Journal ArticleDOI

Information Uncertainty and the Post–Earnings Announcement Drift in Europe

21 Mar 2012-Financial Analysts Journal (CFA Institute)-Vol. 68, Iss: 2, pp 51-69

Abstract: Investigating the effect of earnings announcement abnormal return and of abnormal trading volume on future returns for a large sample of European companies with both annual and interim announcements over 1997–2010, the author found that the two measures of market surprise are positively related to future abnormal returns, especially when information uncertainty is high. These two effects also appear to be complementary in that each retains some incremental predictive power for future returns.

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Information Uncertainty and the Post-Earnings Announcement Drift in Europe
Xavier Gerard
xavier.gerard@rbs.com
The Royal Bank of Scotland
250 Bishopsgate, London UK, EC2M 4AA
Abstract
This paper investigates the relation between earnings announcement abnormal return,
abnormal trading volume, and subsequent returns for a large sample of European firms. In
addition to bringing new insights for the dynamics of the abnormal return and abnormal
trading volume effects, our analysis provides out-of-sample confirmations of several prior US
findings. We show that each measure of market surprise is positively related to future
abnormal returns, and especially so when information uncertainty is high. These two effects
appear to be complementary as each retain some incremental predicting power for future
returns. Finally, our empirical evidence is not limited to small, illiquid, stocks; and it is robust
to controlling for potential market microstructure biases.
JEL classification: M4, G12, G14
Keywords: Market efficiency; Trading Volume; High-Volume Premium; Post-Earnings
Announcement Drift; Earnings Surprises; Information Uncertainty

2
1. Introduction
Since Ball and Brown (1968), over forty years ago, an extensive body of mainly US
academic research has documented a positive relation between earnings forecast errors,
computed using either a time series approach or analyst estimates, and abnormal post-
announcement returns. In contrast, due to several data limitations, the evidence for the post-
earnings announcement drift in Europe is relatively scarce. The historical coverage for analyst
forecasts of interim numbers, as well as for the actual interim numbers released by the firms,
is typically low or unreliable in Europe. Moreover, pan-European accounting studies are
plagued by differences of accounting practices across member states.
This paper extends the US evidence to a large sample of European firms with annual as
well as interim earnings announcements from 1997 to 2010. To avoid using analyst forecasts
of interim numbers or the actual interim numbers released by the firm, we resort to some
recent academic findings and quantify the degree of market surprise with some market related
information, namely, the abnormal return and the abnormal trading volume at the time of the
announcement. The use of market data implies that our metrics of market surprise can be
easily computed for a large number of European firms. Moreover, by using market data we
largely alleviate concerns related to differences of accounting practices across European
countries.
The current predominant belief for the post-earnings announcement drift is that it is
caused by some form of under-reaction to the information contained in earnings
announcements. Although previous empirical work has focused on the earnings surprise, it
has recently been noted that some important non-earnings information is also released at the
time of the announcement. For example, firms provide information about components of
earnings such as sales, and operating margins. Still further, earnings announcements tend to
be accompanied by conference calls and press releases where valuable information is
disseminated. Therefore, to the extent that the abnormal return captures a wide range of
earnings and non-earnings related news, it could be argued that it is a broader measure of
market surprise than traditional proxies.
In contrast with the post-earnings announcement drift of Ball and Brown (1968), the
abnormal volume anomaly has been discovered recently. It refers to the outperformance of
high volume stocks relative to low volume stocks following an earnings announcement.
Explanations for this anomaly includes models of capital market equilibrium (Merton, 1987),
behavioural biases arising from the limitations of individual investors to process large

3
amounts of information (Barber and Odean, 2004), and risk-based arguments where the
abnormal volume is seen as a proxy for opinion divergence (Garfinkel and Sokobin, 2006).
Given that the empirical evidence for this effect is still limited, extending the analysis to the
European market should help bring about some valuable insights.
Last but not least, we investigate the role played by information uncertainty in explaining
the pay-offs associated with the abnormal volume and the abnormal return effects. Our proxy
for information uncertainty is the idiosyncratic volatility of the securities in our sample.
Hirshleifer (2001) posits that greater uncertainty combined with the lack of accurate feedback
about fundamentals leave more room for behavioural biases. Although behavioural biases
could well be accentuated in settings of higher information uncertainty, it is also possible that
idiosyncratic risk constitutes a limit to arbitrage preventing investors from eliminating the
anomalies. In any case, we predict that high idiosyncratic risk is associated with larger drifts,
and this analysis should help further our understanding of the mechanisms at play behind
these two empirical patterns.
Our results are four-fold. First, we find, in line with the US evidence, that a measure of
market surprise, computed as the abnormal return around an earnings announcement, is
positively related with future returns in Europe. The effect is not short lived as we show that
firms with a positive surprise in one quarter continue to surprise the market, in the same
direction, up to one year after the announcement.
Second, we are able to demonstrate, to our knowledge for the first time in Europe, the
existence of a strong abnormal volume anomaly following earnings announcements. Firms
with high abnormal volume around their earnings announcement date outperform low
abnormal volume stocks for up to ninety days after the event. This outperformance is
followed by a short period of underperformance, which strongly reverts one year after the
event. Therefore, as with the abnormal return effect, we find that firms which surprise the
market in one quarter continue to do so one year later. This evidence is echoed by patterns of
abnormal trading volume following the earnings announcement date. Those firms with the
highest abnormal trading volume in one quarter also experience a surge in their trading
volume one year later. All in all, these results strongly suggest that investors in Europe fail to
understand the implications of current announcements for future ones.
Third, as predicted, we show that the anomalies tend to generate stronger premiums when
information uncertainty is larger. For instance, although significant abnormal returns are
observed within stocks that have high and low idiosyncratic risk, we find that the abnormal

4
return and abnormal volume effects are typically stronger within those stocks that experience
the highest level of idiosyncratic volatility. Similarly, we show that the abnormal volume
effect arises primarily during periods of high aggregate idiosyncratic risk.
Finally, the two effects appear to capture independent dimensions of the market surprise
around an earnings announcement. Controlling for the degree of abnormal volume or
abnormal return around an earnings announcement, we continue to find that the other effect is
associated with positive future returns. Given their independent information contents we
investigate their combined predictive power. We find that a trading strategy based on these
two indicators of market surprise earns a monthly quintile spread return of approximately
0.70%. The trading strategy is implemented with a monthly rebalancing frequency so that a
signal is used for the first time on average two weeks after the earnings announcement, hence
alleviating concerns that our findings are contaminated by potential market microstructure
biases. Controlling for risk does not explain away the premium earned by the combined
strategies. Moreover, these findings are not restricted to small firms, and they are robust to
taking into account stock illiquidity and the volatility of stock returns over the announcement
days.
The remainder of this paper is organised as follows. The next section discusses the
relevant literature and motivates our analysis. The third section describes the sample data and
introduce the main variables of this study. The fourth section presents and discusses our
empirical findings. We test the robustness of our results in section five. Finally, the last
section concludes the study.
2. Literature Review and Motivations
This analysis is related to prior US findings that show a positive association between
measures of earnings surprise and future abnormal returns. The earnings surprise indicator,
calculated at the time of an announcement, is typically defined as the scaled difference
between the actual earnings figure and a proxy for market expectations computed using either
analyst forecasts or the time series of prior earnings. Despite having been extensively
researched since its discovery more than forty years ago by Ball and Brown (1968), the
reason for the existence of the post-earnings announcement drift continues to be heavily
debated. The prior empirical evidence offers little support for a risk-based explanation or
potential flaws in research design (Bernard and Thomas, 1989). Instead, the current
predominant belief for the post-earnings announcement drift is that it is caused by some form
of under-reaction to the information contained in earnings announcements. The exact nature

5
of the under-reaction remains vague however. Bernard and Thomas (1990) point out that the
drift occurs at subsequent earnings announcement dates. This finding lead them and others
(see for instance Ball and Bartov, 1996) to argue that investors fail to understand the
implications of current earnings for future ones. However, Jacob et al (1999) offer an
alternative interpretation of the causes of the post-earnings announcement drift when looking
at the autocorrelation structure of forecast errors, and Livnat and Mendenhall (2006) put
forward an explanation based on a more general hypothesis of under-reaction to earnings
information.
Although the bulk of the prior evidence has focused on the earnings surprise, little
attention has been paid to non-earnings information. However, considering non-earnings
related news make sense for several reasons. For instance, Liu and Thomas (2000) show that
a significant portion of the market reaction around earnings announcement is due to non-
earnings related information. It is also obvious that some important non-earnings related news
are released at the time of an announcement. For example, firms provide information about
components of earnings such as sales, and operating margins (see Jegadeesh and Livnat,
2006). Still further, earnings announcements tend to be accompanied by conference calls and
press releases where some additional valuable information is disseminated. Finally, a number
of recent empirical findings suggest that market participants incorrectly value non-financial
information. For instance, Ragjopal et al (2003) find that investors overestimate the valuation
implications of order backlogs, while Gu (2005) and Deng et al (1999) show that investors
systematically underweight patent counts, as well as the level change in patent citations.
In this study we follow Brandt et al (2006) and use as our first measure of market surprise
the abnormal stock return around an earnings announcement date. To the extent that the
abnormal return captures a wide range of earnings and non-earnings related news, both
tangible and intangible, it could be argued that it is a broader measure of market surprise than
previous indicators. In line with earlier findings, Brandt et al (2006) report a strong post-
earnings announcement drift when ranking stocks on the basis of their abnormal return at the
time of the earnings announcement. However, it has to be noted that the magnitude of the
price change around the earnings announcement could also be increasing in the information
content of the news and decreasing in the degree of under-reaction.
Using market data as a proxy for the market surprise also achieves another objective, as it
helps alleviate several data issues that have plagued European studies. First, the historical
coverage for analyst forecasts of interim numbers, as well as for the actual interim numbers
released by the firms, is typically low or unreliable in Europe. As a result the empirical

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References
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Abstract: This paper tests the relationship between average return and risk for New York Stock Exchange common stocks. The theoretical basis of the tests is the "two-parameter" portfolio model and models of market equilibrium derived from the two-parameter portfolio model. We cannot reject the hypothesis of these models that the pricing of common stocks reflects the attempts of risk-averse investors to hold portfolios that are "efficient" in terms of expected value and dispersion of return. Moreover, the observed "fair game" properties of the coefficients and residuals of the risk-return regressions are consistent with an "efficient capital market"--that is, a market where prices of securities

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"Information Uncertainty and the Pos..." refers background or methods in this paper

  • ...(2008) and Garfinkel and Sokobin (2006) found a strong post–earnings announcement drift in the United States when ranking stocks on the basis of their earnings announcement abnormal volume. These findings echo those of Gervais, Kaniel, and Mingelgrin (2001), who showed that a positive relationship exists between short-term abnormal trading volume and subsequent returns, even without conditioning on earnings announcements....

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  • ...(2008) and Garfinkel and Sokobin (2006) found a strong post–earnings announcement drift in the United States when ranking stocks on the basis of their earnings announcement abnormal volume....

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  • ...To perform this test, I ran monthly cross-sectional regressions, along the lines of Fama and MacBeth (1973), as follows: where is the return of company i in month t; X is stock characteristics at the end of the previous month, such as size, book-to-market, momentum, and the (standardized) earnings…...

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  • ...To perform this test, I ran monthly cross-sectional regressions, along the lines of Fama and MacBeth (1973), as follows:...

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Abstract: Using a sample free of survivor bias, I demonstrate that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual funds' mean and risk-adjusted returns Hendricks, Patel and Zeckhauser's (1993) "hot hands" result is mostly driven by the one-year momentum effect of Jegadeesh and Titman (1993), but individual funds do not earn higher returns from following the momentum strategy in stocks The only significant persistence not explained is concentrated in strong underperformance by the worst-return mutual funds The results do not support the existence of skilled or informed mutual fund portfolio managers PERSISTENCE IN MUTUAL FUND performance does not reflect superior stock-picking skill Rather, common factors in stock returns and persistent differences in mutual fund expenses and transaction costs explain almost all of the predictability in mutual fund returns Only the strong, persistent underperformance by the worst-return mutual funds remains anomalous Mutual fund persistence is well documented in the finance literature, but not well explained Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), and Wermers (1996) find evidence of persistence in mutual fund performance over short-term horizons of one to three years, and attribute the persistence to "hot hands" or common investment strategies Grinblatt and Titman (1992), Elton, Gruber, Das, and Hlavka (1993), and Elton, Gruber, Das, and Blake (1996) document mutual fund return predictability over longer horizons of five to ten years, and attribute this to manager differential information or stock-picking talent Contrary evidence comes from Jensen (1969), who does not find that good subsequent performance follows good past performance Carhart (1992) shows that persistence in expense ratios drives much of the long-term persistence in mutual fund performance My analysis indicates that Jegadeesh and Titman's (1993) one-year momentum in stock returns accounts for Hendricks, Patel, and Zeckhauser's (1993) hot hands effect in mutual fund performance However, funds that earn higher

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Abstract: Accounting theorists have generally evaluated the usefulness of accounting practices by the extent of their agreement with a particular analytic model. The model may consist of only a few assertions or it may be a rigorously developed argument. In each case, the method of evaluation has been to compare existing practices with the more preferable practices implied by the model or with some standard which the model implies all practices should possess. The shortcoming of this method is that it ignores a significant source of knowledge of the world, namely, the extent to which the predictions of the model conform to observed behavior. It is not enough to defend an analytical inquiry on the basis that its assumptions are empirically supportable, for how is one to know that a theory embraces all of the relevant supportable assumptions? And how does one explain the predictive powers of propositions which are based on unverifiable assumptions such as the maximization of utility functions? Further, how is one to resolve differences between propositions which arise from considering different aspects of the world? The limitations of a completely analytical approach to usefulness are illustrated by the argument that income numbers cannot be defined substantively, that they lack "meaning" and are therefore of doubtful utility.' The argument stems in part from the patchwork development of account-

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"Information Uncertainty and the Pos..." refers background or result in this paper

  • ...In contrast to the post–earnings announcement drift of Ball and Brown (1968), the abnormal volume effect was discovered only recently, and so a theoretical explanation for this result can be difficult to find. Nonetheless, a few theories stand out. Merton (1987) posited that visibility induces positive returns. The key behavioral assumption behind this model is that investors use a security in their portfolio only if they know about it. Given that the equilibrium market value of a company is a function of the aggregate demand for its shares, that value is lower when fewer investors are aware of the company’s existence. An unusually large trading volume on announcement day should increase investor awareness and, in turn, the demand for the company’s shares. According to Barber and Odean (2008), individual investors face a notable search problem when deciding which stocks to buy and thus tend to focus on those stocks that catch their attention. They do not face the same issue when selling because they rarely short and tend to sell only the stocks that they already own. Hence, individual investors are net buyers of stocks that are in the news. To the extent that abnormal trading volume “grabs” investors’ attention, this attention-driven buying could explain the post–earnings announcement drift. The positive returns on expected earnings announcement dates reported by Frazzini and Lamont (2007) are consistent with the “attentiongrabbing” hypothesis....

    [...]

  • ...In contrast to the post–earnings announcement drift of Ball and Brown (1968), the abnormal volume effect was discovered only recently, and so a theoretical explanation for this result can be difficult to find....

    [...]

  • ...These two effects also appear to be complementary in that each retains some incremental predictive power for future returns. eginning with Ball and Brown (1968), almost 45 years ago, an extensive body of mainly U.S. academic research has documented a positive relationship between earnings forecast…...

    [...]

  • ...In contrast to the post–earnings announcement drift of Ball and Brown (1968), the abnormal volume effect was discovered only recently, and so a theoretical explanation for this result can be difficult to find. Nonetheless, a few theories stand out. Merton (1987) posited that visibility induces positive returns. The key behavioral assumption behind this model is that investors use a security in their portfolio only if they know about it. Given that the equilibrium market value of a company is a function of the aggregate demand for its shares, that value is lower when fewer investors are aware of the company’s existence. An unusually large trading volume on announcement day should increase investor awareness and, in turn, the demand for the company’s shares. According to Barber and Odean (2008), individual investors face a notable search problem when deciding which stocks to buy and thus tend to focus on those stocks that catch their attention. They do not face the same issue when selling because they rarely short and tend to sell only the stocks that they already own. Hence, individual investors are net buyers of stocks that are in the news. To the extent that abnormal trading volume “grabs” investors’ attention, this attention-driven buying could explain the post–earnings announcement drift. The positive returns on expected earnings announcement dates reported by Frazzini and Lamont (2007) are consistent with the “attentiongrabbing” hypothesis. Similarly, Barber and Odean (2008) and Hirshleifer, Myers, Myers, and Teoh (2004) found that individual investors are net buyers in response to either positive or negative surprises. A further implication of the theory is that if individual investors push prices too high or prevent prices from falling in response to bad news, the ensuing performance of the attention-grabbing stocks will be poor. Finally, a risk-based explanation can be given for the high-volume premium. For instance, Garfinkel and Sokobin (2006) argued that the abnormal volume around earnings announcements is an indicator of opinion divergence and, therefore, a risk factor that commands higher equilibrium returns....

    [...]

  • ...In contrast to the post–earnings announcement drift of Ball and Brown (1968), the abnormal volume effect was discovered only recently, and so a theoretical explanation for this result can be difficult to find. Nonetheless, a few theories stand out. Merton (1987) posited that visibility induces positive returns. The key behavioral assumption behind this model is that investors use a security in their portfolio only if they know about it. Given that the equilibrium market value of a company is a function of the aggregate demand for its shares, that value is lower when fewer investors are aware of the company’s existence. An unusually large trading volume on announcement day should increase investor awareness and, in turn, the demand for the company’s shares. According to Barber and Odean (2008), individual investors face a notable search problem when deciding which stocks to buy and thus tend to focus on those stocks that catch their attention. They do not face the same issue when selling because they rarely short and tend to sell only the stocks that they already own. Hence, individual investors are net buyers of stocks that are in the news. To the extent that abnormal trading volume “grabs” investors’ attention, this attention-driven buying could explain the post–earnings announcement drift. The positive returns on expected earnings announcement dates reported by Frazzini and Lamont (2007) are consistent with the “attentiongrabbing” hypothesis. Similarly, Barber and Odean (2008) and Hirshleifer, Myers, Myers, and Teoh (2004) found that individual investors are net buyers in response to either positive or negative surprises....

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"Information Uncertainty and the Pos..." refers methods in this paper

  • ...Finally, in addition to the abnormal returns that are characteristic adjusted, I computed the alpha of the strategy as specified in the following Carhart (1997) four-factor model:...

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  • ...I estimated stock-specific risk by using 52 weeks of data and the Carhart (1997) four-factor model of Equation 3....

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  • ...Finally, in addition to the abnormal returns that are characteristic adjusted, I computed the alpha of the strategy as specified in the following Carhart (1997) four-factor model: (5) where SMB, HML, and UMD are the Fama–French size, book-to-market, and momentum factors adapted for the European…...

    [...]

  • ...The specific risk of each security is calculated by using 52 weeks of data and the following Carhart (1997) four-factor model: (3) where SMB, HML, and UMD are the Fama–French size, book-to-market, and momentum factors adapted for the European market and rm and rf are the market return and the…...

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Journal ArticleDOI
01 Jul 1987-Journal of Finance
Abstract: THE SPHERE of model financial economics encompasses finance, micro investment theory and much of the economics of uncertainty. As is evident from its influence on other branches of economics including public finance, industrial organization and monetary theory, the boundaries of this sphere are both permeable and flexible. The complex interactions of time and uncertainty guarantee intellectual challenge and intrinsic excitement to the study of financial economics. Indeed, the mathematics of the subject contain some of the most interesting applications of probability and optimization theory. But for all its mathematical refinement, the research has nevertheless had a direct and significant influence on practice. ’ It was not always thus. Thirty years ago, finance theory was little more than a collection of anecdotes, rules of thumb, and manipulations of accounting data with an almost exclusive focus on corporate financial management. There is no need in this meeting of the guild to recount the subsequent evolution from this conceptual potpourri to a rigorous economic theory subjected to systematic empirical examination? Nor is there a need on this occasion to document the wide-ranging impact of the research on finance practice.2 I simply note that the conjoining of intrinsic intellectual interest with extrinsic application is a prevailing theme of research in financial economics. The later stages of this successful evolution have however been marked by a substantial accumulation of empirical anomalies; discoveries of theoretical inconsistencies; and a well-founded concern about the statistical power of many of the test methodologies.3 Finance thus finds itself today in the seemingly-paradoxical position of having more questions and empirical puzzles than at the start of its

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