PEAD.txt: Post-Earnings-Announcement Drift Using Text
67 Pages Posted: 22 Apr 2021 Last revised: 13 Jan 2022
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Pead.Txt: Post-Earnings-Announcement Drift Using Text
Date Written: April 9, 2021
Abstract
We construct a new numerical measure of earnings announcement surprises, standardized unexpected earnings call text (SUE.txt), that does not explicitly incorporate the reported earnings value. SUE.txt generates a text-based post-earnings-announcement drift (PEAD.txt) larger than the classic PEAD. The magnitude of PEAD.txt is considerable even in recent years when the classic PEAD is close to zero. We explore our text-based empirical model to show that the calls’ news content is about details behind the earnings number and the fundamentals of the firm.
Keywords: PEAD, Machine Learning, NLP, Text Analysis
JEL Classification: G14, G12, C00
Suggested Citation: Suggested Citation