Post-Earnings Announcement Drift

Definition

Post-earnings announcement drift refers to the tendency of a stock's price to continue moving in the same direction after an earnings announcement for a certain period, typically over days or weeks. This phenomenon challenges the efficient market hypothesis, as it suggests that investors do not immediately incorporate all available information into stock prices, resulting in abnormal returns that can be exploited. This behavior can impact financial decision-making and is linked to the broader concepts of momentum and behavioral asset pricing models.

5 Must Know Facts For Your Next Test

1. Post-earnings announcement drift typically lasts for about 60 days following an earnings report, during which stock prices may continue to adjust to new information.
2. This phenomenon was first documented in the early 1990s and has been supported by numerous empirical studies demonstrating abnormal returns after earnings announcements.
3. The drift occurs because investors may underreact to earnings information, leading to a gradual adjustment of prices rather than an immediate incorporation of news.
4. Investors can potentially exploit post-earnings announcement drift by employing strategies that involve buying stocks with positive earnings surprises and selling those with negative surprises.
5. Behavioral biases such as overconfidence and anchoring can contribute to the persistence of post-earnings announcement drift, influencing how investors interpret and react to new information.

Review Questions

• How does post-earnings announcement drift challenge the concept of market efficiency?
  • Post-earnings announcement drift challenges market efficiency by demonstrating that stock prices do not fully reflect all available information immediately after earnings announcements. Instead of quickly adjusting to the new information, stock prices may continue to trend in the direction indicated by the earnings results for days or weeks. This suggests that investors often underreact to earnings news, leaving room for subsequent price adjustments that contradict the efficient market hypothesis.
• Discuss how post-earnings announcement drift can be applied in financial decision-making for investors.
  • Investors can apply the insights from post-earnings announcement drift by creating strategies that take advantage of this delayed reaction to earnings announcements. For example, after a company reports positive earnings surprises, investors might buy shares expecting continued upward movement in price over time. Similarly, recognizing negative surprises could lead investors to sell or short-sell those stocks. Understanding this drift allows investors to make more informed decisions based on anticipated price movements following earnings announcements.
• Evaluate the implications of post-earnings announcement drift within behavioral asset pricing models and how they relate to investor psychology.
  • Post-earnings announcement drift has significant implications for behavioral asset pricing models as it illustrates how investor psychology affects market dynamics. Behavioral finance suggests that cognitive biases like overconfidence may lead investors to misinterpret earnings reports or hold onto losing stocks longer than warranted. These psychological factors create inefficiencies in pricing, which behavioral asset pricing models seek to explain. By incorporating these biases into their frameworks, researchers can better understand how irrational behaviors influence asset pricing patterns, including the post-earnings announcement drift phenomenon.

Related terms

Efficient Market Hypothesis: A theory suggesting that asset prices reflect all available information, implying that it is impossible to consistently achieve higher returns than the overall market.

Momentum Investing: An investment strategy that aims to capitalize on the continuation of existing trends in stock prices, often relying on past performance to predict future movements.

Behavioral Finance: A field of study that combines psychology and economics to understand how emotional and cognitive biases influence investor behavior and market outcomes.