IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v88y2024ics0927538x24002725.html
   My bibliography  Save this article

Social media sentiment contagion and stock price jumps and crashes

Author

Listed:
  • Yang, Jing
  • Xiong, Yan

Abstract

Inspired by the SIR model, we adopt sentiment extracted from the social media platform (Guba) of Eastmoney in China during 2008–2022 to construct a firm-specific investor sentiment contagion speed measurement and investigate the association between sentiment contagion speed and stock price jumps and crashes. Specifically, we find that the contagion of optimistic sentiment is positively associated with jumps in stock price, while the contagion of pessimistic sentiment is positively associated with the crash risk of stock prices. Moreover, these associations vary based on the prevailing proportion of the sentiment and the market's bull and bear status. Additionally, the stock price movement associated with social sentiment contagion is influenced by short-selling constraints, analyst coverage and institutional ownership.

Suggested Citation

  • Yang, Jing & Xiong, Yan, 2024. "Social media sentiment contagion and stock price jumps and crashes," Pacific-Basin Finance Journal, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:pacfin:v:88:y:2024:i:c:s0927538x24002725
    DOI: 10.1016/j.pacfin.2024.102520
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X24002725
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2024.102520?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    3. Harrison Hong & Jeremy C. Stein, 2003. "Differences of Opinion, Short-Sales Constraints, and Market Crashes," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 487-525.
    4. Jin, Li & Myers, Stewart C., 2006. "R2 around the world: New theory and new tests," Journal of Financial Economics, Elsevier, vol. 79(2), pages 257-292, February.
    5. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    6. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    7. 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.
    8. Lee, Charles M C & Shleifer, Andrei & Thaler, Richard H, 1991. "Investor Sentiment and the Closed-End Fund Puzzle," Journal of Finance, American Finance Association, vol. 46(1), pages 75-109, March.
    9. Chou, Pin-Huang & Chou, Robin K. & Ko, Kuan-Cheng & Chao, Chun-Yi, 2013. "What affects the cool-off duration under price limits?," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 256-278.
    10. Yao, Shouyu & Wang, Chunfeng & Cui, Xin & Fang, Zhenming, 2019. "Idiosyncratic skewness, gambling preference, and cross-section of stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 464-483.
    11. Nagel, Stefan, 2005. "Short sales, institutional investors and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 78(2), pages 277-309, November.
    12. Yang, Xiaolan & Zhu, Yu & Cheng, Teng Yuan, 2020. "How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    13. Hutton, Amy P. & Marcus, Alan J. & Tehranian, Hassan, 2009. "Opaque financial reports, R2, and crash risk," Journal of Financial Economics, Elsevier, vol. 94(1), pages 67-86, October.
    14. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Schmeling, Maik, 2007. "Institutional and individual sentiment: Smart money and noise trader risk?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 127-145.
    16. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    17. Wei Xiong & Jialin Yu, 2011. "The Chinese Warrants Bubble," American Economic Review, American Economic Association, vol. 101(6), pages 2723-2753, October.
    18. Jinfang Li & Chunpeng Yang, 2017. "The cross-section and time-series effects of individual stock sentiment on stock prices," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4806-4815, October.
    19. Ding, David K. & Charoenwong, Charlie & Seetoh, Raymond, 2004. "Prospect theory, analyst forecasts, and stock returns," Journal of Multinational Financial Management, Elsevier, vol. 14(4-5), pages 425-442.
    20. Paul Hribar & John McInnis, 2012. "Investor Sentiment and Analysts' Earnings Forecast Errors," Management Science, INFORMS, vol. 58(2), pages 293-307, February.
    21. 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.
    22. Aman, Hiroyuki, 2013. "An analysis of the impact of media coverage on stock price crashes and jumps: Evidence from Japan," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 22-38.
    23. Frazzini, Andrea & Lamont, Owen A., 2008. "Dumb money: Mutual fund flows and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 88(2), pages 299-322, May.
    24. Feng He & Yaqian Feng & Lingbing Feng, 2023. "Social media information dissemination and corporate bad news hoarding," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(S1), pages 1503-1532, April.
    25. Jeon, Yoontae & McCurdy, Thomas H. & Zhao, Xiaofei, 2022. "News as sources of jumps in stock returns: Evidence from 21 million news articles for 9000 companies," Journal of Financial Economics, Elsevier, vol. 145(2), pages 1-17.
    26. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    27. Zhou, Liyun & Chen, Dongqiao & Huang, Jialiang, 2023. "Stock-level sentiment contagion and the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    28. repec:bla:jfinan:v:59:y:2004:i:5:p:2013-2040 is not listed on IDEAS
    29. Callen, Jeffrey L. & Fang, Xiaohua, 2015. "Short interest and stock price crash risk," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 181-194.
    30. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    31. Jiang, George J. & Yao, Tong, 2013. "Stock Price Jumps and Cross-Sectional Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1519-1544, October.
    32. Wei Xiong & Jialin Yu, 2011. "The Chinese Warrants Bubble," Working Papers 1398, Princeton University, Department of Economics, Econometric Research Program..
    33. David Eil & Justin M. Rao, 2011. "The Good News-Bad News Effect: Asymmetric Processing of Objective Information about Yourself," American Economic Journal: Microeconomics, American Economic Association, vol. 3(2), pages 114-138, May.
    34. Tsai, I-Chun, 2017. "Diffusion of optimistic and pessimistic investor sentiment: An empirical study of an emerging market," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 22-34.
    35. 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.
    36. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    37. Jeffrey R. Brown & Zoran Ivković & Paul A. Smith & Scott Weisbenner, 2008. "Neighbors Matter: Causal Community Effects and Stock Market Participation," Journal of Finance, American Finance Association, vol. 63(3), pages 1509-1531, June.
    38. Lilian Ng & Fei Wu, 2010. "Peer Effects in the Trading Decisions of Individual Investors," Financial Management, Financial Management Association International, vol. 39(2), pages 807-831, June.
    39. Suzanne S. Lee, 2012. "Jumps and Information Flow in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 439-479.
    40. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    41. Shiller, 021Robert J. & Pound, John, 1989. "Survey evidence on diffusion of interest and information among investors," Journal of Economic Behavior & Organization, Elsevier, vol. 12(1), pages 47-66, August.
    42. Zhang, Wenlang & Semmler, Willi, 2009. "Prospect theory for stock markets: Empirical evidence with time-series data," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 835-849, December.
    43. Deniz Erdemlioglu & Xiye Yang, 2023. "News Arrival, Time-Varying Jump Intensity, and Realized Volatility: Conditional Testing Approach," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1519-1556.
    44. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
    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. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2022. "The conditional impact of investor sentiment in global stock markets: A two-channel examination," Journal of Banking & Finance, Elsevier, vol. 138(C).
    2. 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.
    3. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    4. Di, Li & Shaiban, Mohammed Sharaf & Hasanov, Akram Shavkatovich, 2021. "The power of investor sentiment in explaining bank stock performance: Listed conventional vs. Islamic banks," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    5. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    6. Michael Firth & Kailong (Philip) Wang & Sonia ML Wong, 2015. "Corporate Transparency and the Impact of Investor Sentiment on Stock Prices," Management Science, INFORMS, vol. 61(7), pages 1630-1647, July.
    7. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    8. Wenjie Ding & Khelifa Mazouz & Qingwei Wang, 2019. "Investor sentiment and the cross-section of stock returns: new theory and evidence," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 493-525, August.
    9. Aissia, Dorsaf Ben, 2016. "Home and foreign investor sentiment and the stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 71-77.
    10. David C. Ling & Andy Naranjo & Benjamin Scheick, 2014. "Investor Sentiment, Limits to Arbitrage and Private Market Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 531-577, September.
    11. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    12. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and daily stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    13. Prajwal Eachempati & Praveen Ranjan Srivastava, 2021. "Accounting for unadjusted news sentiment for asset pricing," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(3), pages 383-422, May.
    14. Mehwish Aziz Khan & Eatzaz Ahmad, 2018. "Measurement of Investor Sentiment and Its Bi-Directional Contemporaneous and Lead–Lag Relationship with Returns: Evidence from Pakistan," Sustainability, MDPI, vol. 11(1), pages 1-20, December.
    15. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    16. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    17. Ahmed, Bouteska, 2020. "Understanding the impact of investor sentiment on the price formation process: A review of the conduct of American stock markets," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    18. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    19. Tan, Xiaoyu & Zhang, Zili & Zhao, Xuejun & Wang, Chengxiang, 2021. "Investor sentiment and limits of arbitrage: Evidence from Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 577-595.
    20. Gric, Zuzana & Bajzík, Josef & Badura, Ondřej, 2023. "Does sentiment affect stock returns? A meta-analysis across survey-based measures," International Review of Financial Analysis, Elsevier, vol. 89(C).

    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:eee:pacfin:v:88:y:2024:i:c:s0927538x24002725. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/pacfin .

    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.