Articlehybrid2022

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

Vitaly Meursault · Pierre Jinghong Liang · Bryan Routledge · Madeline Marco Scanlon

30 citations0/0 files storedJournal of Financial and Quantitative Analysis

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Financial Markets and Investment Strategies Financial Analysis and Corporate Governance Stock Market Forecasting Methods

Abstract

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 0. 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.

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References

1997On Persistence in Mutual Fund Performance 2014A five-factor asset pricing model 1968An Empirical Evaluation of Accounting Income Numbers 2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks 1989Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?2010The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach 1989Financial statement analysis and the prediction of stock returns 2000Investor Sophistication and Patterns in Stock Returns after Earnings Announcements

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