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The Review of Asset Pricing Studies Vol. 11 No. 4 2021

Is Positive Sentiment in Corporate Annual Reports Informative? Evidence from Deep Learning

Mehran Azimi1; Anup Agrawal2

1 University of Massachusetts Boston · 2 University of Alabama

open access

Abstract

We use a novel text classification approach from deep learning to more accurately measure sentiment in a large sample of 10-Ks. In contrast to most prior literature, we find that positive and negative sentiments predict abnormal returns and abnormal trading volume around the 10-K filing date and future firm fundamentals and policies. Our results suggest that the qualitative information contained in corporate annual reports is richer than previously found. Both positive and negative sentiments are informative when measured accurately, but they do not have symmetric implications, suggesting that a net sentiment measure advocated by prior studies would be less informative.

DOI
10.1093/rapstu/raab005
Volume
11
Issue
4
Pages
762-805
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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