IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v59y2020ics0927538x19301349.html
   My bibliography  Save this article

How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash

Author

Listed:
  • Yang, Xiaolan
  • Zhu, Yu
  • Cheng, Teng Yuan

Abstract

This study examines whether the sentiments expressed in the stock forum posted by individual investors lead to abnormal trading and impose a significant impact on stock price crashes. The history of world financial crises reveals that investor panic is one of the most important factors triggering market crashes. In this paper, we propose a measure to estimate investor panic and its effect on a stock price crash. Using Growth Enterprise Market firms in China's Shenzhen Stock Exchange as a sample, we utilize a computer text mining tool to analyze the contents of nearly one million posts from the largest Chinese stock message board. According to the posting contents, we built a daily Sentiment Index and a Panic Index at the firm level. The empirical results show that the high Sentiment Index leads to a significant following abnormal trading. After controlling public information announcements, this effect is still significant. Moreover, the Panic Index could predict the stock price crash. The effect of the Panic Index on the price crash is stronger either when the information disclosure is opaque or when the proportion of shares held by institutional investors is low.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:pacfin:v:59:y:2020:i:c:s0927538x19301349
    DOI: 10.1016/j.pacfin.2019.101245
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X19301349
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2019.101245?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. 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.
    3. Amir Rubin & Eran Rubin, 2010. "Informed Investors and the Internet," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(7‐8), pages 841-865, July.
    4. 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.
    5. 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.
    6. 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.
    7. Hans Byström, 2009. "News aggregators, volatility and the stock market," Economics Bulletin, AccessEcon, vol. 29(4), pages 2673-2682.
    8. Kim, Jeong-Bon & Li, Yinghua & Zhang, Liandong, 2011. "Corporate tax avoidance and stock price crash risk: Firm-level analysis," Journal of Financial Economics, Elsevier, vol. 100(3), pages 639-662, June.
    9. Amir Rubin & Eran Rubin, 2010. "Informed Investors and the Internet," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(7-8), pages 841-865.
    10. 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.
    11. Robert J. Shiller, 1987. "Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence," NBER Working Papers 2446, National Bureau of Economic Research, Inc.
    12. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    13. Giannini, Robert & Irvine, Paul & Shu, Tao, 2019. "The convergence and divergence of investors' opinions around earnings news: Evidence from a social network," Journal of Financial Markets, Elsevier, vol. 42(C), pages 94-120.
    14. Dayong Dong & Keke Wu, 2019. "Investor attention is a risk pricing factor? Evidence from Chinese investors for self-selected stocks," China Finance Review International, Emerald Group Publishing Limited, vol. 10(1), pages 95-112, March.
    15. Kim, Jeong-Bon & Li, Yinghua & Zhang, Liandong, 2011. "CFOs versus CEOs: Equity incentives and crashes," Journal of Financial Economics, Elsevier, vol. 101(3), pages 713-730, September.
    16. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    17. Uriel Spiegel & Tchai Tavor & Joseph Templeman, 2010. "The effects of rumours on financial market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 17(15), pages 1461-1464.
    18. Robert J. Shiller, 1987. "Investor Behavior in the 1987-10 Stock Market Crash: Survey Evidence," Cowles Foundation Discussion Papers 853, Cowles Foundation for Research in Economics, Yale University.
    19. 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.
    20. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruwei Zhao & Ruixin Fan & Xiong Xiong & Jianli Wang & Jitka Hilliard, 2023. "Media Tone and Stock Price Crash Risk: Evidence from China," Mathematics, MDPI, vol. 11(17), pages 1-14, August.
    2. Irfan Safdar & Michael Neel & Babatunde Odusami, 2022. "Accounting information and left-tail risk," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1709-1740, May.
    3. Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022. "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Atri, Hanen & Kouki, Saoussen & Gallali, Mohamed imen, 2021. "The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach," Resources Policy, Elsevier, vol. 72(C).
    5. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Do messages on online stock forums spur firm productivity?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    6. Xuejun Jin & Jiawei Yu, 2022. "Does communication increase investors’ trading frequency? Evidence from a Chinese social trading platform," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-32, December.
    7. Ziqin Yu & Xiang Xiao, 2022. "Innovation information disclosure and stock price crash risk‐based supervision and insurance effect path analysis," Australian Economic Papers, Wiley Blackwell, vol. 61(3), pages 534-590, September.
    8. Li, Yanshuang & Shi, Yujie & Shi, Yongdong & Xiong, Xiong & Yi, Shangkun, 2024. "Time-frequency extreme risk spillovers between COVID-19 news-based panic sentiment and stock market volatility in the multi-layer network: Evidence from the RCEP countries," International Review of Financial Analysis, Elsevier, vol. 94(C).
    9. Hu, Debao & Li, Xin & Xiang, George & Zhou, Qiyao, 2023. "Asset pricing models in the presence of higher moments: Theory and evidence from the U.S. and China stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    10. Lu, Jing & Chen, Rongze, 2023. "Do individual investors pay attention to the information acquisition activities of institutional investors?," Finance Research Letters, Elsevier, vol. 58(PD).
    11. Sahar Arshad & Nikhar Azhar & Sana Sajid & Seemab Latif & Rabia Latif, 2024. "Cross-Lingual News Event Correlation for Stock Market Trend Prediction," Papers 2410.00024, arXiv.org.
    12. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    13. Saeed, Abubakr & Riaz, Hammad & Baloch, Muhammad Saad, 2022. "Does big data utilization improve firm legitimacy?," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    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. Gang Chu & Xiao Li & Dehua Shen & Yongjie Zhang, 2021. "Stock Crashes and Jumps Reactions to Information Demand and Supply: An Intraday Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 397-427, September.
    2. An, Suwei, 2023. "Essays on incentive contracts, M&As, and firm risk," Other publications TiSEM dd97d2f5-1c9d-47c5-ba62-f, Tilburg University, School of Economics and Management.
    3. Xu, Yongxin & Xuan, Yuhao & Zheng, Gaoping, 2021. "Internet searching and stock price crash risk: Evidence from a quasi-natural experiment," Journal of Financial Economics, Elsevier, vol. 141(1), pages 255-275.
    4. Wen, Fenghua & Xu, Longhao & Ouyang, Guangda & Kou, Gang, 2019. "Retail investor attention and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 65(C).
    5. Habib, Ahsan & Hasan, Mostafa Monzur, 2017. "Business strategy, overvalued equities, and stock price crash risk," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 389-405.
    6. Luo, Yan & Zhang, Chenyang, 2020. "Economic policy uncertainty and stock price crash risk," Research in International Business and Finance, Elsevier, vol. 51(C).
    7. 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).
    8. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
    9. Li, Qian & Liu, Shangqun, 2023. "Does alternative data reduce stock price crash risk? Evidence from third-party online sales disclosure in China," International Review of Financial Analysis, Elsevier, vol. 88(C).
    10. Li, Xiao & Shen, Dehua & Xue, Mei & Zhang, Wei, 2017. "Daily happiness and stock returns: The case of Chinese company listed in the United States," Economic Modelling, Elsevier, vol. 64(C), pages 496-501.
    11. 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).
    12. Fu, Junhui & Wu, Xiang & Liu, Yufang & Chen, Rongda, 2021. "Firm-specific investor sentiment and stock price crash risk," Finance Research Letters, Elsevier, vol. 38(C).
    13. Tzomakas, Christos & Anastasiou, Dimitrios & Katsafados, Apostolos & Krokida, Styliani Iris, 2023. "Crisis sentiment and banks’ stock price crash risk: A missing piece of the puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 87(C).
    14. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    15. Liu, Simeng & Wang, Kun Tracy & Walpola, Sonali & Zhu, Nathan Zhenghang, 2024. "CSR contracting and stock price crash risk: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
    16. Yu, Haixu & Liang, Chuanyu & Liu, Zhaohua & Wang, He, 2023. "News-based ESG sentiment and stock price crash risk," International Review of Financial Analysis, Elsevier, vol. 88(C).
    17. Larry Fauver & Gilberto Loureiro, 2015. "Equity Offerings, Stock Price Crash Risk, and the Impact of Securities Regulation: International Evidence," NIPE Working Papers 14/2015, NIPE - Universidade do Minho.
    18. Hu, Gang & Liu, Yiye & Wang, Jacqueline Wenjie & Zhou, Gaoguang & Zhu, Xindong, 2022. "Insider ownership and stock price crash risk around the globe," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    19. Hsu, Audrey Wen-hsin & Pourjalali, Hamid & Song, Yi-Ju, 2018. "Fair value disclosures and crash risk," Journal of Contemporary Accounting and Economics, Elsevier, vol. 14(3), pages 358-372.
    20. Min Jung Kang & Y. Han (Andy) Kim & Qunfeng Liao, 2020. "Do bankers on the board reduce crash risk?," European Financial Management, European Financial Management Association, vol. 26(3), pages 684-723, June.

    More about this item

    Keywords

    Stock message board; Investor panic; Stock price crash; Text mining; Spiral of silence;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:eee:pacfin:v:59:y:2020:i:c:s0927538x19301349. 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.