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Sensitivity of Chinese stock markets to individual investor sentiment: An analysis of Sina Weibo mood related to COVID-19

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  • Li, Jiaqi
  • Ahn, Hee-Joon

Abstract

This research explores the impact of individual investor sentiment derived from social networks on stock market returns. Using keyword-based techniques, we collect and analyze Sina Weibo posts related to COVID-19, extracting daily influential weighted sentiment indexes from a dataset of over 2.4 million posts in 2020. Empirical tests utilizing a sentiment-augmented three-factor model reveal that individual investor sentiment exerts an independent influence on Chinese financial markets, after controlling for market risk, size, and value effects. We further find that negative sentiment carries a stronger impact on stock returns, which is in line with the loss-averse behavior commonly observed among individual investors. We also find an asymmetric pattern in the sentiment-return relation across different industry types. While positive sentiment affects both types of industries that suffer or benefit from COVID-19, negative sentiment affects only the industries that suffer from the pandemic. Overall, our empirical results provide robust support for the significance of individual investor sentiment in explaining the behavior of the Chinese financial markets.

Suggested Citation

  • Li, Jiaqi & Ahn, Hee-Joon, 2024. "Sensitivity of Chinese stock markets to individual investor sentiment: An analysis of Sina Weibo mood related to COVID-19," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    • Handle: RePEc:eee:beexfi:v:41:y:2024:i:c:s2214635023000746
    DOI: 10.1016/j.jbef.2023.100860
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    1. Haiqiang Chen & Terence Tai-Leung Chong & Xin Duan, 2010. "A principal-component approach to measuring investor sentiment," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 339-347.
    2. Donghua Wang & Jingqing Tu & Xiaohui Chang & Saiping Li, 2017. "The lead–lag relationship between the spot and futures markets in China," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1447-1456, September.
    3. Campbell, Sean D. & Diebold, Francis X., 2009. "Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 266-278.
    4. Priyank Gandhi & Tim Loughran & Bill McDonald, 2019. "Using Annual Report Sentiment as a Proxy for Financial Distress in U.S. Banks," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(4), pages 424-436, October.
    5. repec:eco:journ2:2017-04-04 is not listed on IDEAS
    6. David Blitz & Matthias X. Hanauer & Pim Vliet, 2021. "The Volatility Effect in China," Journal of Asset Management, Palgrave Macmillan, vol. 22(5), pages 338-349, September.
    7. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    8. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
    9. Yanhui Chen & Hanhui Zhao & Ziyu Li & Jinrong Lu, 2020. "A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-18, December.
    10. Daifeng Li & Yintian Wang & Andrew Madden & Ying Ding & Jie Tang & Gordon Guozheng Sun & Ning Zhang & Enguo Zhou, 2019. "Analyzing stock market trends using social media user moods and social influence," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(9), pages 1000-1013, September.
    11. John A. Doukas & Xiao Han, 2021. "Sentiment‐scaled CAPM and market mispricing," European Financial Management, European Financial Management Association, vol. 27(2), pages 208-243, March.
    12. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    13. Hui-Chu Shu & Jung-Hsien Chang, 2015. "Investor Sentiment and Financial Market Volatility," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 16(3), pages 206-219, July.
    14. Guo, Kun & Sun, Yi & Qian, Xin, 2017. "Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 390-396.
    15. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    16. Chi Xie & Yuanxia Wang, 2017. "Does Online Investor Sentiment Affect the Asset Price Movement? Evidence from the Chinese Stock Market," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-11, January.
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