IDEAS home Printed from https://ideas.repec.org/a/bla/acctfi/v64y2024i4p4447-4472.html
   My bibliography  Save this article

Does image sentiment of major public emergency affect the stock market performance? New insight from deep learning techniques

Author

Listed:
  • Yun Liu
  • Dengshi Huang
  • Jianan Zhou
  • Sirui Wang

Abstract

Leveraging deep learning to analyse COVID‐19 image sentiment, this study reveals its significant impact on stock market dynamics. It highlights how vivid imagery prompts marked emotional responses, altering market performance and how news sentiment can modulate this effect. Further, it underscores the pivotal role of forum‐based investor sentiment, particularly affecting small‐minus‐big stocks during downturns and trading week commencements. This research not only advances behavioural finance understanding but also informs management and regulatory strategies.

Suggested Citation

  • Yun Liu & Dengshi Huang & Jianan Zhou & Sirui Wang, 2024. "Does image sentiment of major public emergency affect the stock market performance? New insight from deep learning techniques," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 4447-4472, December.
    • Handle: RePEc:bla:acctfi:v:64:y:2024:i:4:p:4447-4472
    DOI: 10.1111/acfi.13313
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/acfi.13313
    Download Restriction: no
    File URL: https://libkey.io/10.1111/acfi.13313?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Slovic, Paul & Finucane, Melissa L. & Peters, Ellen & MacGregor, Donald G., 2007. "The affect heuristic," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1333-1352, March.
    2. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    3. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    4. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    5. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    6. Ying Zhang & Peggy Swanson, 2010. "Are day traders bias free?—evidence from internet stock message boards," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 34(1), pages 96-112, January.
    7. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    8. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    9. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    10. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    11. Gao, Zhenyu & Ren, Haohan & Zhang, Bohui, 2020. "Googling Investor Sentiment around the World," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(2), pages 549-580, March.
    12. Selin Duz Tan & Oktay Tas, 2021. "Social Media Sentiment in International Stock Returns and Trading Activity," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(2), pages 221-234, April.
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. William J. Bazley & Henrik Cronqvist & Milica Mormann, 2021. "Visual Finance: The Pervasive Effects of Red on Investor Behavior," Management Science, INFORMS, vol. 67(9), pages 5616-5641, September.
    15. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    16. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    17. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    18. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    19. Chen, Yuan & Han, Dongmei & Zhou, Xiaofeng, 2023. "Mining the emotional information in the audio of earnings conference calls : A deep learning approach for sentiment analysis of securities analysts' follow-up behavior," International Review of Financial Analysis, Elsevier, vol. 88(C).
    20. Mark Johnman & Bruce James Vanstone & Adrian Gepp, 2018. "Predicting FTSE 100 returns and volatility using sentiment analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 253-274, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    4. Ding, Rui & Guo, Jintong & Zhang, Min, 2024. "Practice a poker face: Manager emotion and investor sentiment," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    5. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    6. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    7. Zongwu Cai & Pixiong Chen, 2022. "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202216, University of Kansas, Department of Economics, revised Nov 2022.
    8. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    9. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    10. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    11. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    12. Ung, Sze Nie & Gebka, Bartosz & Anderson, Robert D.J., 2023. "Is sentiment the solution to the risk–return puzzle? A (cautionary) note," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    13. Lee, Geul & Ryu, Doojin, 2024. "Investor sentiment or information content? A simple test for investor sentiment proxies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    14. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    15. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    16. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    17. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    18. Chen Gu & Xu Guo & Ruwan Adikaram & Kam C. Chan & Jing Lu, 2023. "Treasury return predictability and investor sentiment," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(4), pages 905-924, December.
    19. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    20. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:acctfi:v:64:y:2024:i:4:p:4447-4472. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaanzea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.