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

Author

Listed:
  • Gaoshan Wang

    (Shandong University of Finance and Economics
    Shandong University of Finance and Economics)

  • Xiaomin Wang

    (Shandong University of Finance and Economics)

Abstract

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.

Suggested Citation

  • Gaoshan Wang & Xiaomin Wang, 2025. "The Effect of News Photo Sentiment on Stock Price Crash Risk Based on Deep Learning Models," Computational Economics, Springer;Society for Computational Economics, vol. 65(5), pages 2679-2706, May.
    • Handle: RePEc:kap:compec:v:65:y:2025:i:5:d:10.1007_s10614-024-10659-5
    DOI: 10.1007/s10614-024-10659-5
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