Trading Around Seasonal Earnings Surprises in Equities

Summary

The document describes a seasonal earnings anomaly: companies may have predictable high- and low-profit quarters, yet announcements of peak or trough earnings can still surprise investors and produce abnormal stock returns. It attributes the mispricing partly to the difficulty of forecasting seasonal patterns, sensitivity to model assumptions, and investors' tendency to overweight recent information when estimating future earnings.

The proposed strategy buys stocks with positive seasonal earnings patterns ten trading days before the expected report of quarterly peak earnings and sells ten trading days after the announcement, with a 10% cap per stock. It also discusses shorting stocks ahead of seasonal lows, but says short-sale costs and the smaller sample make that side difficult to implement. A reported 2010–2017 backtest compares two rolling classification methods and gives their excess returns, relative drawdowns, and return-to-drawdown ratios. These results are historical summaries from the source; details on costs, robustness, and out-of-sample performance are not provided in the text.

Key ideas

• Seasonal earnings patterns can be difficult to forecast and may be mispriced around peak or trough announcements.
• The document links potential investor errors to model sensitivity and overreliance on recent earnings information.
• The main strategy buys positive-seasonality stocks before expected peak-earnings reports and exits after the announcement.
• The strategy caps each stock's position at 10% and evaluates two rolling classification methods over 2010–2017.
• The short side is presented as less practical because of borrowing costs and a smaller sample, while broader robustness details are absent.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.