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Is Positive Sentiment in Corporate Annual Reports Informative? Evidence from Deep Learning Cash holdings and credit risk

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https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frapstu%2Fraab005;h=repec:oup:rasset:v:11:y:2021:i:4:p:762-805.
Time Added
6/20/2022, 12:20:15 PM
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Deep Learning
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Authors
Mehran Azimi and Anup Agrawal
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. (JEL C81 D83 G10 G14 G30 M41)
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Year Published
2021
Series
Review of Asset Pricing Studies 2021 vol. 11 issue 4 762-805
Rank
0.68
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