In financial economics and accounting research, postâÂÂearnings-announcement drift or PEAD (also named the SUE effect) is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks (even several months) following an earnings announcement. This phenomenon is one of the oldest and most persistent capital market anomalies, with evidence dating back to the late 1960s.
PEAD was first documented by Ball and Brown in their seminal 1968 study. They found that after an earnings announcement, stock prices continue to drift in the direction of the earnings surprise for an extended period, suggesting that market participants do not immediately incorporate all information from earnings announcements. This finding challenged the efficient market hypothesis, which implies that new information should be rapidly reflected in stock prices.
The drift is quite persistent. Bernard and Thomas (1989) report that the spread in average return between stocks in the top and bottom deciles in standardized unexpected earnings (SUE) is positive in 41 of the 48 quarters from 1974 to 1985 and in 11 of the 16 quarters in which returns on the NYSE index are negative.
Once a firm's current earnings become known, the information content should be quickly digested by investors and incorporated into the efficient market price. However, it has long been known that this is not exactly what happens. For firms that report good news in quarterly earnings, their abnormal security returns tend to drift upwards for at least 60 days following their earnings announcement. Similarly, firms that report bad news in earnings tend to have their abnormal security returns drift downwards for a similar period.
A particularly notable feature of PEAD is that a disproportionate amount of drift is concentrated around the three subsequent quarterly earnings announcements following the initial surprise, suggesting a predictable pattern of price movements. Bernard and Thomas (1990) found that approximately 25-30% of the post-earnings announcement drift occurs during the three-day windows surrounding subsequent earnings announcements, despite these windows representing only about 5% of trading days.
According to Bernard and Thomas (1989), PEAD occurs because investors fail "to recognize fully the implications of current earnings for future earnings." In other words, investors underreact to the information in current earnings that informs predictions of future earnings.
Several methods exist to measure earnings surprises and detect PEAD:
Researchers sometimes define earnings surprise (UE) using a seasonal random-walk model, calculated as the difference between the most recent quarterly earnings and the quarterly earnings four quarters earlier, scaled by the market capitalization from four quarters earlier.
Research by Bernard and Thomas (1990) documents that quarterly earnings have a systematic time-series pattern that can predict future abnormal returns. Specifically:
1. Seasonal differences in quarterly earnings (comparing the same quarter year-over-year) show positive autocorrelations for the first three lags that decline in magnitude:
2. At the fourth lag, there is a negative autocorrelation of approximately -0.24, suggesting that a portion of an earnings change tends to reverse four quarters later.
This autocorrelation structure suggests that earnings changes are partially predictable based on past quarters' results. For example, if a company reports a positive earnings surprise in the current quarter, this pattern would predict positive but declining earnings surprises in the next three quarters, followed by a negative surprise in the fourth subsequent quarter.
Liquidity plays a crucial role in the magnitude and persistence of PEAD. Research shows that PEAD is stronger in firms with higher illiquidity levels and information asymmetry. In particular, zero-leverage firms (companies with no outstanding debt) exhibit stronger PEAD effects.
A study of zero-leverage firms listed on the FTSE 350 index over the period 2000-2015 found that:
Zero-leverage firms face greater information asymmetry and less public information compared to levered firms, making the information obtained from earnings announcements particularly important for these firms. Consequently, they exhibit greater PEAD effects than companies with debt and equity in their capital structure.
One significant factor affecting PEAD is the delayed disclosure of financial statement items in earnings announcements. When companies delay complete financial statement disclosure until their formal 10-Q filings, investors and analysts demonstrate a delayed response to earnings news.
Key findings regarding delayed disclosure include:
A limited attention model suggests that delayed disclosure increases arbitrage risk for attentive investors by increasing uncertainty about firm value at the earnings announcement date. As a result, attentive investors trade less aggressively, leading to a lower immediate reaction to earnings news and greater PEAD.
The phenomenon can be explained with a number of hypotheses which fall into two main categories:
Some researchers suggest that PEAD represents compensation for unobservable priced risk. According to this view, the returns to PEAD strategies are simply compensation for bearing some form of underlying risk.
Several risk factors have been proposed:
Kim and Kim (2003) constructed a risk factor related to unexpected earnings surprises and found that a four-factor model including this new factor reduced a substantial portion of PEAD.
Kim, Lee, and Min (2017) suggest that expected growth risk can explain PEAD. Using Johnson's (2002) theoretical model, they argue that the log price-dividend ratio is convex with respect to expected growth rates. This convexity implies that stock returns are more sensitively affected by changes in expected growth when expected growth is higher.
Their research found that:
This hypothesis suggests that PEAD results from a delayed price response or investor under-reaction to earnings news. The delay may be due to:
Francis et al. (2007) reveal that under-reaction to earnings announcements causes the PEAD. Some investors may overreact to their private information and underweight public earnings reports.
Bernard and Thomas (1990) provide compelling evidence that stock prices fail to fully reflect the implications of current earnings for future earnings. They hypothesize that stock prices partially reflect a naive earnings expectation model (seasonal random walk), where investors expect earnings to be similar to the same quarter of the previous year, without fully accounting for the time-series properties of earnings.
Key findings supporting this hypothesis include:
The evidence is remarkably consistent across firm size categories, though the effect is more pronounced for small firms. This pattern persisted consistently over the researchers' 13-year sample period (1974-1986).
Research examining the UK stock market by Zhang et al. (2024) provides evidence of the role price impact plays in PEAD. Their findings reveal:
The authors decomposed bid-ask spreads into three components (adverse selection, inventory holding, and order processing costs) and found that only adverse selection costs increased significantly during earnings announcements, while the other components remained unchanged. This provides evidence that information asymmetry is the primary driver of PEAD rather than changes in inventory holding or order processing costs.
Recent studies have found a U-shaped relationship between firm characteristics and earnings surprise deciles, with extreme deciles (both highest and lowest surprises) typically having smaller firm sizes, lower trading volumes, and higher bid-ask spreads compared to middle deciles.
Research has documented significant changes in PEAD over time:
The magnitude of PEAD has declined significantly over time, and may have even disappeared in recent years. Specifically:
Two main explanations exist for the decline in PEAD:
PEAD creates potential profit opportunities for traders and investors. Strategies typically involve:
Bernard and Thomas (1990) documented that zero-investment portfolios constructed on the basis of earnings surprises generated abnormal returns of approximately 8-9% over a quarter (or about 35% annualized before transaction costs). Even higher abnormal returns (about 67% annualized) were available when portfolios were constructed 15 days prior to subsequent earnings announcements and held through those announcements.
Trading strategies based on earnings surprises have historically provided valuable information to investors and generated excess returns. Some studies have shown these strategies can yield quarterly returns in excess of 6% in certain markets, particularly when combined with measures of investor attention.
Research by Garfinkel, Hribar, and Hsiao (2024) finds that a hedge portfolio going long in the top SUE decile (Good News) and short in the bottom SUE decile (Bad News) generates a risk-adjusted return of 5.1% over three months, which translates to an annual return of over 20%. The return to the PEAD trading strategy has been documented to be approximately between 8.76% and 43.08% annually in previous studies.
However, research suggests that the magnitude of PEAD has been declining in developed markets, particularly in the US, possibly due to increased market efficiency and increased institutional investor focus on this anomaly.
Recent research by Meursault et al. (2021) introduces a new numerical measure of earnings announcement surprises called standardized unexpected earnings call text (SUE.txt), which does not explicitly incorporate reported earnings values. Their measure generates a text-based post-earnings-announcement drift (PEAD.txt) that is larger than classic PEAD, particularly in recent years.
The researchers find that SUE.txt has a stronger association with abnormal returns than classic SUE in panel regressions. The PEAD.txt portfolio held for a quarter generates larger alpha than the traditional PEAD portfolio within the Fama-French five factors plus momentum framework.
Key findings include:
This research suggests that a more meaningful distinction between textual information and earnings might be its form (unstructured compared to structured) rather than substance.
Research by Beckmeyer and Meyerhof (2022) connects PEAD to the short-duration premium in stocks. Their study examines whether this premium arises due to risk or alternative explanations.
Their key findings include:
This research provides evidence that the short-duration premium and its relationship to earnings announcements might be explained by behavioral factors rather than risk-based explanations.
The implementation of the Sarbanes-Oxley Act (SOX) has been found to impact PEAD. Research shows:
Some research has examined whether individual investors drive PEAD. One theory suggests that if individual investors are the source of drift, they would tend to be net buyers after negative earnings surprises and net sellers after positive earnings surprises, thus impeding full price adjustment. However, studies have found that individuals are actually significant net buyers after both negative and positive earnings surprises, contradicting this theory.
Instead, empirical evidence suggests that individual investors may exhibit an "earnings attention effect," where the magnitude of earnings surprise affects trading volume but not necessarily the direction of trades.
Recent research has explored applying artificial intelligence to predict PEAD. Garfinkel, Hribar, and Hsiao (2024) examined whether AI can perform financial analysis on visual representations of earnings data to predict PEAD in a manner orthogonal to traditional drift predictors. They transformed firms' historical quarterly earnings into bar chart images and employed a convolutional neural network (CNN) to extract predictive features.
Their findings indicate that:
Their study highlights the potential of applying deep learning techniques to visualized financial data for predicting earnings-based anomalies.
Recent research by Katz, McCubbins, and McMullin (2018) raises concerns about how PEAD is traditionally measured. They argue that portfolio analysis introduces an aggregation bias that clouds inferences about firm-level stock price behavior.
Their key findings include:
This research suggests that the PEAD may not exist when returns are disaggregated and raises questions about whether PEAD is truly an anomaly of market efficiency or just an artifact of aggregation.
The magnitude of PEAD represents a significant anomaly in market efficiency. Bernard and Thomas (1990) found that three-day announcement-period returns on portfolios constructed with only prior-quarter earnings information were approximately half as large as the returns to portfolios constructed using the contemporaneous earnings information. This finding calls into question the reliability of studies that rely heavily on the assumption that prices fully reflect all publicly available earnings information.
Bernard and Thomas (1990) investigated several alternative explanations for PEAD, including risk shifts and research design flaws, but found evidence inconsistent with these alternatives. The consistency of the PEAD effect across 13 consecutive years in their sample, with abnormal returns showing the predicted pattern in almost every year, presents a substantial challenge to rational explanations of the phenomenon.