Session 25 (of 42): Information Trading - Earnings Reports

Why It Matters

Understanding earnings‑surprise dynamics and post‑announcement drifts enables investors to capture mispricings that persist despite rapid price adjustments, directly impacting portfolio returns.

Key Takeaways

• Earnings surprise drives price, not raw earnings number.
• Pre‑announcement drift suggests information leakage or market forecasting.
• Post‑announcement drift persists, contradicting strict market efficiency norms.
• Delayed earnings releases signal potential bad news, causing price decline.
• Earnings quality and cash vs accrual metrics affect surprise interpretation.

Summary

The session dissects how quarterly earnings reports shape stock movements, emphasizing that markets react to the surprise relative to expectations rather than the headline numbers. It explains that analysts’ forecasts set the benchmark, and any deviation—positive or negative—triggers price adjustments.

Data from academic studies show a measurable drift in stock prices both before and after the announcement. Prices often climb days ahead of a positive surprise, hinting at information leakage or sophisticated forecasting, while a post‑announcement drift of roughly 5% for strong beats and -2% for misses persists beyond the initial reaction, challenging the notion of instantaneous market efficiency. Delays in filing earnings further depress prices, as investors infer concealed bad news.

The presenter cites specific findings: 91% of price reaction occurs within three hours of release, and the drift is more pronounced in less‑liquid stocks. He also warns that companies can manipulate expectations through guidance, and stresses the importance of scrutinizing earnings quality—comparing accrual earnings to cash flow—to avoid being misled by superficial beat‑the‑estimate headlines.

For investors, these dynamics suggest opportunities to exploit pre‑ and post‑announcement drifts, especially in smaller, less‑followed firms, while also highlighting the risks of over‑reliance on headline surprises. Mastery of forensic accounting metrics and alternative forecasting methods may provide a competitive edge in the earnings‑driven trading arena.

Original Description

In this session, we begin our discussion of trading based upon public information by looking at earnings reports. Since markets react to the news in earnings reports, we begin by categorizing that news into good, neutral and bad, by comparing the actual earnings to the predicted earnings. Not only do we see a price change that is consistent with the nature and magnitude of the surprise (positive price changes on positive surprises) but we also see two other phenomena. The first is that prices start to drift in the direction of the surprise even before the earnings report is made public (suggesting that someone is trading illegally ahead of the report) and that they continue to drift in the same direction after the report comes out (suggesting a slow learning market). We also look at earnings reports that are delayed and find that they are more likely to contain bad news. Finally, we look at the speed of price reaction on the day of the report and find that prices adjust quickly to earnings surprises, suggesting that any investment strategy built around earnings surprises has to be built around speedy trading/execution.

Playlist for class (Intro + 42 sessions): https://youtube.com/playlist?list=PLUkh9m2BorqnZGADa8cTzeJblmrZY_SqP&si=zI2pk17pJeld4nWR

Slides: https://www.stern.nyu.edu/~adamodar/pdfiles/invphilslides25/session25.pdf

Post-class test: https://www.stern.nyu.edu/~adamodar/pdfiles/invphilcertificate/postclass/session25test.pdf

Post-class solution: https://www.stern.nyu.edu/~adamodar/pdfiles/invphilcertificate/postclass/session25soln.pdf