Post–earnings-announcement drift

Overview

In financial economics and accounting research, post–earnings-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.

History and Discovery

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.

Cause and Effect

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.

Measurement and Detection

Several methods exist to measure earnings surprises and detect PEAD:

Standardized Unexpected Earnings (SUE) - The difference between actual earnings and expected earnings (based on analyst forecasts or time-series models), normalized by the standard deviation of earnings. Cumulative Abnormal Returns (CARs) - Measuring the cumulative abnormal returns around earnings announcements. Overnight Returns (OR) - More recent research has shown that overnight returns following earnings announcements can be effective in capturing unexpected information and measuring earnings surprises. 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.

Time-Series Properties of Quarterly Earnings

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:

First-order autocorrelation: approximately 0.34 Second-order autocorrelation: approximately 0.19 Third-order autocorrelation: approximately 0.06 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 and Zero-Leverage Firms

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:

Illiquidity levels are significantly enhanced around both the earnings and post-announcement period for zero-leverage firms, with larger bid-ask spreads and higher price impact ratios. When bid-ask spread components are decomposed, adverse selection costs increase significantly during earnings announcements, while inventory holding and order processing costs remain unchanged, suggesting that PEAD is primarily related to information asymmetry. The relationship between PEAD returns, earnings surprises, and liquidity costs remains robust even after controlling for firm characteristics such as size, stock price, and trading volume. 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.

Delayed Disclosure Impact

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:

Higher delayed disclosure (DD) is associated with a weaker immediate market reaction to earnings surprises and a stronger post-earnings announcement drift. Specifically, an increase in DD from zero to one corresponds to approximately a 37% decrease in the earnings response coefficient (ERC) and a 42% increase in PEAD. The delayed reaction persists even after the 10-Q filing when the previously withheld information becomes available. The full correction of the price only occurs at the next earnings announcement, suggesting that "opportunity knocks but once" - firms have a special opportunity to convey value-relevant information at earnings announcements when investor attention is high. Analysts are less likely to issue earnings forecasts immediately after earnings announcements and more likely to delay their forecasts to after the 10-Q filing when financial statement disclosure is delayed. This delayed response pattern persists beyond the 10-Q filing and continues until the next earnings announcement. Higher delayed disclosure is associated with greater analyst underreaction to earnings surprises, lower forecast accuracy, and higher forecast dispersion, indicating that the lack of complete financial information impedes analysts' ability to process earnings news effectively. 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.

Hypotheses

The phenomenon can be explained with a number of hypotheses which fall into two main categories:

Risk-Based Rational Explanations

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:

Changes in equities' risk following earnings announcements Inflation risk in forecasting future earnings growth Relationship to future macroeconomic activity Liquidity risk Divergence in investor opinion as additional risk 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.

Expected Growth Risk Explanation

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:

Firms with higher SUE have higher expected growth rates High-SUE portfolios have greater exposure to expected growth risk than low-SUE portfolios Expected growth risk is significantly priced in the cross-section of returns A model including expected growth risk alone explains PEAD satisfactorily

Mispricing Due to Delayed Price Response

This hypothesis suggests that PEAD results from a delayed price response or investor under-reaction to earnings news. The delay may be due to:

Limits-to-arbitrage - Trading frictions, transaction costs, and limited arbitrage prevent rapid price adjustment. Studies show that PEAD is more pronounced for stocks with: Higher transaction costs (bid-ask spreads) Lower share price and trading volume Lower institutional ownership Less analyst coverage Higher idiosyncratic volatility Investor bias - Behavioral explanations suggest that investors systematically underreact to earnings-related news. Bernard and Thomas (1990) find that PEAD is caused by investors failing to incorporate the implications of current earnings for future earnings. 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.

Naive Earnings Expectation Hypothesis

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 three-day abnormal returns around subsequent earnings announcements are predictable based on the current quarter's earnings surprise The pattern of these predictable returns matches the autocorrelation structure of quarterly earnings Three-day abnormal returns are positive but declining in magnitude for the next three quarterly announcements, and then negative for the fourth subsequent announcement, precisely matching what would be expected if investors failed to account for the time-series properties of earnings 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).