PEAD.txt: Post-Earnings-Announcement Drift Using Text

Vitaly Meursault, Pierre Jinghong Liang, Bryan R. Routledge, and Madeline Marco Scanlon

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.