期刊
FINANCE RESEARCH LETTERS
卷 59, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.frl.2023.104794
关键词
Facial expression; Deep learning; Company performance; Performance prediction
This study adopts a cognitive dissonance theory viewpoint to investigate the impact of managers' facial emotion on market performance and risk in Chinese listed companies. The findings suggest that more positive facial expressions of managers in earnings conference call predict better market performance and lower risk. The study provides investors with a new analytical method and offers reference for market regulators in policy formulation.
This paper adopts a cognitive dissonance theory viewpoint to investigate the impact of managers' facial emotion on market performance and risk in Chinese listed companies from 2016 to 2022, and employs a deep learning model to analyze managers' facial emotion. We find that the more positive facial expressions of managers in earnings conference call predict better market performance, lower volatility and stock price crash risk. After conducting a series of robustness tests, the conclusion still holds. This study provides investors with a new analytical method and also provides market regulators with a reference for relevant policy formulation.
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