Investor Trading and the Post-Earnings-Announcement Drift

2011 ◽  
Vol 86 (2) ◽  
pp. 385-416 ◽  
Author(s):  
Benjamin C. Ayers ◽  
Oliver Zhen Li ◽  
P. Eric Yeung
Keyword(s):  
Random Walk ◽  
Earnings Announcements ◽  
Discovery Process ◽  
Earnings Announcement ◽  
Post Earnings Announcement Drift ◽  
Earnings Surprises ◽  
Trading Activities ◽  
Investor Trading ◽  
Small Traders ◽  
Price Discovery Process

ABSTRACT: We examine whether the two distinct post-earnings-announcement drifts associated with seasonal random-walk-based and analyst-based earnings surprises are attributable to the trading activities of distinct sets of investors. We predict and find that small (large) traders continue to trade in the direction of seasonal random-walk-based (analyst-based) earnings surprises after earnings announcements. We also find that when small (large) traders react more thoroughly to seasonal random-walk- (analyst-) based earnings surprises at the earnings announcements, the respective drift attenuates. Further evidence suggests that delayed small trades associated with random-walk-based surprises are consistent with small traders’ failure to understand time-series properties of earnings, whereas delayed large trades associated with analyst-based surprises are more consistent with a longer price discovery process. We also find that the analyst-based drift has declined in recent years.

The Incremental Value Relevance of Media Coverage of Earnings Announcements: Evidence from the Trading of Short Sellers

2021 ◽  
Author(s):  
Lynn Rees ◽  
Brady Twedt
Keyword(s):  
Media Coverage ◽  
Price Discovery ◽  
Value Relevance ◽  
Earnings Announcements ◽  
Discovery Process ◽  
Trading Behavior ◽  
Earnings Announcement ◽  
Short Sellers ◽  
The Media ◽  
Price Discovery Process

We investigate the relation between media coverage and the trading behavior of short sellers around earnings announcements. Prior research provides conflicting evidence on the role of the media, with some studies finding that the media can impede the price discovery process. Our evidence indicates that short sellers increase their activity in line with the tone of media coverage around earnings announcements, after controlling for earnings news and other factors that affect relative levels of short selling. Furthermore, we show that information in the media successfully forecasts earnings information in the days leading up to the earnings announcement, and that short sellers trade in a manner consistent with information reflected in media coverage preceding the earnings announcement. Our findings are consistent with information contained in the media having value relevance, and suggest that the media may help to facilitate the price discovery process around the release of earnings.

Do Individual Investors Cause Post-Earnings Announcement Drift? Direct Evidence from Personal Trades

2008 ◽  
Vol 83 (6) ◽  
pp. 1521-1550 ◽  
Author(s):  
David A. Hirshleifer ◽  
James N. Myers ◽  
Linda A. Myers ◽  
Siew Hong Teoh
Keyword(s):  
Direct Evidence ◽  
Abnormal Returns ◽  
Individual Investors ◽  
Individual Investor ◽  
Earnings Announcement ◽  
Attention Effect ◽  
Post Earnings Announcement Drift ◽  
Earnings Surprises ◽  
Investor Trading ◽  
The Individual

ABSTRACT: This study tests whether nai¨ve trading by individual investors, or some class of individual investors, causes post-earnings announcement drift (PEAD). Inconsistent with the individual trading hypothesis, individual investor trading fails to subsume any of the power of extreme earnings surprises to predict future abnormal returns. Moreover, individuals are significant net buyers after both negative and positive extreme earnings surprises, consistent with an attention effect, but not with their trades causing PEAD. Finally, we find no indication that trading by individuals explains the concentration of drift at subsequent earnings announcement dates.

Investors' Trade Size and Trading Responses around Earnings Announcements: An Empirical Investigation

2001 ◽  
Vol 76 (2) ◽  
pp. 221-244 ◽  
Author(s):  
Nilabhra Bhattacharya
Keyword(s):  
Random Walk ◽  
Earnings Announcements ◽  
Random Walk Model ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Analyst Following ◽  
Earnings Expectations ◽  
Trading Activities ◽  
Trading Response ◽  
Small Traders

Prior research suggests that the earnings expectations of a segment of the market can be described by the seasonal random-walk model. Prior research also provides evidence that less wealthy and less informed investors tend to make smaller trades (small traders) than wealthier and betterinformed investors (large traders). I hypothesize that it is the earnings expectations of small traders that are associated with predictions from the seasonal random-walk model. By directly analyzing the trading activities of small and large traders, this study provides evidence that is largely consistent with the hypotheses. Specifically, small traders' trading response around earnings announcements is increasing in the magnitude of seasonal random-walk forecast errors, even after controlling for absolute analyst forecast errors, contemporaneous price changes, and market-wide trading. Supplementary analysis reveals that this effect is largely confined to firms with relatively impoverished information environments (i.e., smaller firms and firms with little to moderate analyst following).

scholarly journals Rest in Peace Post-Earnings Announcement Drift

2021 ◽  
Author(s):  
Charles Martineau
Keyword(s):  
Financial Markets ◽  
Stock Prices ◽  
Earnings Announcements ◽  
Price Formation ◽  
Future Research ◽  
Earnings Announcement ◽  
Post Earnings Announcement Drift ◽  
Announcement Date ◽  
Earnings Surprises ◽  
Area Of Study

This paper revisits price formation following earnings announcements. In modern financial markets, stock prices fully reflect earnings surprises on the announcement date, leading to the disappearance of post-earnings announcement drifts (PEAD). For large stocks, PEAD have been non-existent since 2006 but has only disappeared recently for microcap stocks. PEAD remain a prevalent area of study in finance and accounting despite having largely disappeared. This paper concludes with a set of recommendations for researchers who conduct such studies to better assess the existence of PEAD and suggests future research avenues to examine price formation following earnings news.

scholarly journals Overconfident Institutions and Their Self-Attribution Bias: Evidence from Earnings Announcements

2020 ◽  
pp. 1-33 ◽  
Author(s):  
Hsin-I Chou ◽  
Mingyi Li ◽  
Xiangkang Yin ◽  
Jing Zhao
Keyword(s):  
Information Asymmetry ◽  
Earnings Announcements ◽  
Earnings Announcement ◽  
Behavioral Bias ◽  
Price Pressure ◽  
Post Earnings Announcement Drift ◽  
Institutional Demand ◽  
Attribution Bias

Abstract Institutional demand for a stock before its earnings announcement is negatively related to subsequent returns. The relation is not attributable to the price pressure of institutional demand and is stronger for stocks with higher information asymmetry and/or greater valuation difficulty. These findings support the notion that overconfident institutions misprice stocks. Following announcements, institutions’ behavior exhibits the outcome-dependent feature of self-attribution bias. Whether they become more overconfident and delay their mispricing correction depends on whether earnings news confirms their preannouncement trades. This behavioral bias also offers a new explanation for the well-known post-earnings-announcement drift.

scholarly journals The Effect of Ex Ante Management Forecast Accuracy on the Post-Earnings-Announcement Drift

2012 ◽  
Vol 87 (5) ◽  
pp. 1791-1818 ◽  
Author(s):  
Li Zhang
Keyword(s):  
Earnings Announcements ◽  
Forecast Accuracy ◽  
Data Availability ◽  
Management Forecasts ◽  
Composite Measure ◽  
Earnings Announcement ◽  
Post Earnings Announcement Drift ◽  
Management Forecast ◽  
Ex Ante

ABSTRACT I examine the effect of ex ante management forecast accuracy on the post-earnings-announcement drift when management forecasts about next quarter's earnings are bundled with current quarter's earnings announcements. I build a composite measure of ex ante management forecast accuracy that takes into account forecast ability, forecast difficulty, and forecast environment. The results show that the bundled forecasts with higher ex ante accuracy mitigate investors' under-reaction to current earnings and reduce the magnitude of the post-earnings-announcement drift. Data Availability: The data used in this paper are available from the sources listed in the text.

Earnings management and institutional investor trading prior to earnings announcements

2019 ◽  
Vol 9 (1) ◽  
pp. 22-50 ◽  
Author(s):  
Shasha Liu
Keyword(s):  
Earnings Management ◽  
Institutional Investors ◽  
Earnings Announcements ◽  
Chinese Stock Market ◽  
Data Set ◽  
Content Type ◽  
Trading Patterns ◽  
Earnings Surprises ◽  
Trading Pattern ◽  
Investor Trading

PurposeThe purpose of this paper is to investigate if earnings management affects the trades of different investors prior to earnings announcements.Design/methodology/approachUsing a unique account-level trading data set from the Chinese stock market, the author investigates the different investor trading patterns prior to earnings announcements.FindingsThe author obtains direct evidence to show that: first, institutional investors, particularly active ones, tend to sell (buy) stocks before negative (positive) earnings surprises; second, institutional investors buy stocks intensively with the lowest earnings management and the highest earnings surprises, and the trading patterns are primarily driven by active institutions. No significant trading pattern is observed on the stocks with negative earnings surprises; and third, the author uses a natural experiment in accordance with the Chinese accounting standards reform to address endogeneity, and the causality of the results still holds.Originality/valueThe findings provide clear evidence by emphasizing the importance of earnings management in the formulation of investor decisions.

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