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

85 Pages Posted: 22 Apr 2021

See all articles by Vitaly Meursault

Vitaly Meursault

Federal Reserve Banks - Federal Reserve Bank of Philadelphia

Pierre Jinghong Liang

Tepper School of Business, Carnegie Mellon University; CAFR/SAIF

Bryan Routledge

Carnegie Mellon University - David A. Tepper School of Business

Madeline Scanlon

University of Pittsburgh

Multiple version iconThere are 2 versions of this paper

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 and can be used to create a profitable trading strategy. The magnitude of PEAD.txt is considerable even in recent years when the classic PEAD is close to zero. Leveraging the prediction model underlying SUE.txt, we propose new tools to study the news content of text: paragraph-level SUE.txt and paragraph classification scheme based on the business curriculum. With these tools, we document many asymmetries in the distribution of news across content types, demonstrating that earnings calls contain a wide range of news about firms and their environment.

Keywords: PEAD, Machine Learning, NLP, Text Analysis

JEL Classification: G14, G12, C00

Suggested Citation

Meursault, Vitaly and Liang, Pierre Jinghong and Routledge, Bryan R. and Scanlon, Madeline, PEAD.txt: Post-Earnings-Announcement Drift Using Text (April 9, 2021). Available at SSRN: https://ssrn.com/abstract=3778798 or http://dx.doi.org/10.2139/ssrn.3778798

Vitaly Meursault (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Philadelphia ( email )

Ten Independence Mall
Philadelphia, PA 19106-1574
United States

Pierre Jinghong Liang

Tepper School of Business, Carnegie Mellon University ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
412-268-3315 (Phone)
412-268-6837 (Fax)

HOME PAGE: http://www2.tepper.cmu.edu/andrew/liangj

CAFR/SAIF ( email )

1954 Huashan Road
Shanghai P.R.China, 200030
China

Bryan R. Routledge

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
(412) 268-7588 (Phone)
(412) 268-7064 (Fax)

Madeline Scanlon

University of Pittsburgh ( email )

135 N Bellefield Ave
Pittsburgh, PA 15260
United States

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