The Effect of News Photo Sentiment on Stock Price Crash Risk Based on Deep Learning Models

被引:0
|
作者
Wang, Gaoshan [1 ,2 ]
Wang, Xiaomin [1 ]
机构
[1] Shandong Univ Finance & Econ, Sch Management Sci & Engn, 7366 Erhuan Dong Rd, Jinan 250014, Peoples R China
[2] Shandong Univ Finance & Econ, Inst Digital Econ, 7366 Erhuan Dong Rd, Jinan 250014, Peoples R China
关键词
News photo sentiment; Stock price crash risk; Deep learning; Investor sentiment; INVESTOR SENTIMENT; CROSS-SECTION; MARKET; IMAGES; NOISE;
D O I
10.1007/s10614-024-10659-5
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study examines the impact of investor sentiment on stock price crash risk from the perspective of news photo sentiment. First, the paper derives investor sentiment from news photos based on deep learning models. Second, we develop regression models analyzing the relationship between investor sentiment and stock price crash risk. The empirical analysis results show that news photo sentiment has a significantly positive effect on stock price crash risk and exhibits a stronger predictive power than sentiment embedded in news text. In addition, our study shows that positive news photo sentiment has a stronger impact on stock price crash risk in bull markets than in bearish markets. Our findings have great implications for investors, market analysts, and policy makers.
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页数:28
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