IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v61y2024ics1544612324000941.html
   My bibliography  Save this article

Internet stock message boards and the price–volume relationship: Registered users vs non-registered users

Author

Listed:
  • Zhang, Zuochao
  • Shen, Dehua

Abstract

With the newly available data distinguishing between registered users and non-registered users, we empirically reveal that there exists a significantly negative relationship between the number of Internet stock message boards postings from non-registered users and return volatility. Considering the theory that investors overreact to stale information, this finding suggests that postings from non-registered users generate temporary mispricing.

Suggested Citation

  • Zhang, Zuochao & Shen, Dehua, 2024. "Internet stock message boards and the price–volume relationship: Registered users vs non-registered users," Finance Research Letters, Elsevier, vol. 61(C).
  • Handle: RePEc:eee:finlet:v:61:y:2024:i:c:s1544612324000941
    DOI: 10.1016/j.frl.2024.105064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324000941
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2024.105064?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. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    2. Tsangyao Chang & Chien-Chiang Lee & Chi-Hung Chang, 2014. "Does insurance activity promote economic growth? Further evidence based on bootstrap panel Granger causality test," The European Journal of Finance, Taylor & Francis Journals, vol. 20(12), pages 1187-1210, December.
    3. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    4. Le, Van & Zurbruegg, Ralf, 2010. "The role of trading volume in volatility forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 533-555, December.
    5. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
    6. Hisham Farag & Robert Cressy, 2012. "Stock market regulation and news dissemination: evidence from an emerging market," The European Journal of Finance, Taylor & Francis Journals, vol. 18(3-4), pages 351-368, April.
    7. Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    8. Darrat, Ali F. & Zhong, Maosen & Cheng, Louis T.W., 2007. "Intraday volume and volatility relations with and without public news," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2711-2729, September.
    9. Darolles, Serge & Le Fol, Gaëlle & Mero, Gulten, 2017. "Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows," Journal of Econometrics, Elsevier, vol. 201(2), pages 367-383.
    10. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    11. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    12. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    13. Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2012. "Testing for Granger non-causality in heterogeneous panels," Economic Modelling, Elsevier, vol. 29(4), pages 1450-1460.
    14. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    15. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    16. Shen, Dehua & Tong, Zezheng & Goodell, John W., 2024. "Do online message boards convey cryptocurrency-specific information?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    17. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    18. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    19. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    20. Shen, Dehua & Li, Xiao & Zhang, Wei, 2017. "Baidu news coverage and its impacts on order imbalance and large-size trade of Chinese stocks," Finance Research Letters, Elsevier, vol. 23(C), pages 210-216.
    21. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    22. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    23. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2020. "News and return volatility of Chinese bank stocks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1095-1105.
    24. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    25. Bai, Zhidong & Wong, Wing-Keung & Zhang, Bingzhi, 2010. "Multivariate linear and nonlinear causality tests," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 5-17.
    26. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    27. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    28. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.
    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, Zuochao & Shen, Dehua, 2024. "Not all the news fitting to reprint: Evidence from price-volume relationship," Finance Research Letters, Elsevier, vol. 62(PA).
    2. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    3. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    4. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    5. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    6. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    7. Slim, Skander & Dahmene, Meriam, 2016. "Asymmetric information, volatility components and the volume–volatility relationship for the CAC40 stocks," Global Finance Journal, Elsevier, vol. 29(C), pages 70-84.
    8. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
    9. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    10. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    11. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    12. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    13. Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
    14. Ling-Yun He & Sheng Yang & Wen-Si Xie & Zhi-Hong Han, 2014. "Contemporaneous and Asymmetric Properties in the Price-Volume Relationships in China's Agricultural Futures Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(S1), pages 148-166.
    15. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    16. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    17. Ming-Hsien Chen & Vivian Tai, 2014. "The price discovery of day trading activities in futures market," Review of Derivatives Research, Springer, vol. 17(2), pages 217-239, July.
    18. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    19. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    20. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.

    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:finlet:v:61:y:2024:i:c:s1544612324000941. 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/frl .

    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.