How to measure earnings surprises: Based on revised market reaction

Qin Pan and Kai Huang

PLOS ONE, 2023, vol. 18, issue 12, 1-24

Abstract: We investigate the robustness of earnings surprise measures in the context of a revised market reaction. While existing literature suggests that financial anomalies may distort cumulative abnormal returns (CAR) during annual announcements, our research proves that a revised market reaction offers a more accurate reflection of investor reactions to earnings correction. Specifically, we introduce an innovative adjustment to CAR using stock price jumps, and prove that the fraction of misses on the same side (FOM) provides a superior measure of earnings surprises. Furthermore, we find that investor trading patterns align with FOM, and the post-earnings announcement drift (PEAD) strategy based on FOM outperforms that based on analysts’ forecast error.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0296394

DOI: 10.1371/journal.pone.0296394

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