[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v13y2020i10p244-d428944.html
   My bibliography  Save this article

The Unusual Trading Volume and Earnings Surprises in China’s Market

Author

Listed:
  • Terence Tai Leung Chong

    (Department of Economics, The Chinese University of Hong Kong, Shatin, Hong Kong, China)

  • Yueer Wu

    (Department of Economics, The Chinese University of Hong Kong, Shatin, Hong Kong, China)

  • Jue Su

    (Department of Economics, The Chinese University of Hong Kong, Shatin, Hong Kong, China)

Abstract
This study examines the empirical relationship between unusual trading volume and earnings surprises in China’s A-share market. We provide evidence that an unusually low trading volume can signify negative information about firm fundamentals. Moreover, unusual trading volumes could predict abnormal returns close to the earnings announcement date. The degree of, and changes in, divergence of opinion could explain this result. Our study provides an insight into China’s market, where short sales are strictly forbidden. We report a strong relationship that is quite different from that described in most studies on the United States market.

Suggested Citation

  • Terence Tai Leung Chong & Yueer Wu & Jue Su, 2020. "The Unusual Trading Volume and Earnings Surprises in China’s Market," JRFM, MDPI, vol. 13(10), pages 1-17, October.
  • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:10:p:244-:d:428944
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/13/10/244/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/13/10/244/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marfatia, Hardik A., 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, Elsevier, vol. 34(C), pages 33-49.
    2. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    3. Mayshar, Joram, 1983. "On Divergence of Opinion and Imperfections in Capital Markets," American Economic Review, American Economic Association, vol. 73(1), pages 114-128, March.
    4. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    5. Ji, Qiang & Marfatia, Hardik & Gupta, Rangan, 2018. "Information spillover across international real estate investment trusts: Evidence from an entropy-based network analysis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 103-113.
    6. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    7. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    8. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    9. Diamond, Douglas W. & Verrecchia, Robert E., 1987. "Constraints on short-selling and asset price adjustment to private information," Journal of Financial Economics, Elsevier, vol. 18(2), pages 277-311, June.
    10. Rangan Gupta & Chi Keng Marco Lau & Ruipeng Liu & Hardik A. Marfatia, 2019. "Price jumps in developed stock markets: the role of monetary policy committee meetings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 298-312, April.
    11. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    12. Ioannis Chatziantoniou & David Gabauer & Hardik A. Marfatia, 2022. "Dynamic connectedness and spillovers across sectors: Evidence from the Indian stock market," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 283-300, July.
    13. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    14. Kaniel, Ron & Ozoguz, Arzu & Starks, Laura, 2012. "The high volume return premium: Cross-country evidence," Journal of Financial Economics, Elsevier, vol. 103(2), pages 255-279.
    15. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    16. Berkman, Henk & Dimitrov, Valentin & Jain, Prem C. & Koch, Paul D. & Tice, Sheri, 2009. "Sell on the news: Differences of opinion, short-sales constraints, and returns around earnings announcements," Journal of Financial Economics, Elsevier, vol. 92(3), pages 376-399, June.
    17. Snehal Banerjee & Ilan Kremer, 2010. "Disagreement and Learning: Dynamic Patterns of Trade," Journal of Finance, American Finance Association, vol. 65(4), pages 1269-1302, August.
    18. Joshua Livnat & Richard R. Mendenhall, 2006. "Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 44(1), pages 177-205, March.
    19. Ferhat Akbas, 2016. "The Calm before the Storm," Journal of Finance, American Finance Association, vol. 71(1), pages 225-266, February.
    20. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    21. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    22. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    23. Fischbacher, Urs & Hens, Thorsten & Zeisberger, Stefan, 2013. "The impact of monetary policy on stock market bubbles and trading behavior: Evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 37(10), pages 2104-2122.
    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. Mark Wong & Adrian Wai Kong Cheung & Wei Hu, 2021. "When two anomalies meet: Volume and timing effects on earnings announcements," The Financial Review, Eastern Finance Association, vol. 56(2), pages 355-380, May.
    2. Gharghori, Philip & See, Quin & Veeraraghavan, Madhu, 2011. "Difference of opinion and the cross-section of equity returns: Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 19(4), pages 435-446, September.
    3. Wang, Peipei & Wen, Yuanji & Singh, Harminder, 2017. "The high-volume return premium: Does it exist in the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 323-336.
    4. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    5. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    6. Chae, Joon & Kang, Mhin, 2019. "Low-volume return premium in the Korean stock market," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    7. Andrew Ang & Assaf A. Shtauber & Paul C. Tetlock, 2013. "Asset Pricing in the Dark: The Cross-Section of OTC Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 26(12), pages 2985-3028.
    8. Gordon, Narelle & Wu, Qiongbing, 2018. "The high-volume return premium and changes in investor recognition," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 121-136.
    9. Turan G. Bali & Andriy Bodnaruk & Anna Scherbina & Yi Tang, 2018. "Unusual News Flow and the Cross Section of Stock Returns," Management Science, INFORMS, vol. 64(9), pages 4137-4155, September.
    10. Bai, Min & Li, Xiao-Ming & Qin, Yafeng, 2017. "Shortability and asset pricing model: Evidence from the Hong Kong stock market," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 15-29.
    11. Ma, Yao & Yang, Baochen & Su, Yunpeng, 2021. "Stock return predictability: Evidence from moving averages of trading volume," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    12. Yen‐Cheng Chang & Pei‐Jie Hsiao & Alexander Ljungqvist & Kevin Tseng, 2022. "Testing Disagreement Models," Journal of Finance, American Finance Association, vol. 77(4), pages 2239-2285, August.
    13. Woon Sau Leung & Nicholas Taylor, 2013. "Testing for contagion: the impact of US structured markets on international financial markets," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 11, pages 256-284, Edward Elgar Publishing.
    14. Wang, Zijun, 2021. "The high volume return premium and economic fundamentals," Journal of Financial Economics, Elsevier, vol. 140(1), pages 325-345.
    15. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    16. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    17. Sun, Kaisi & Wang, Hui & Zhu, Yifeng, 2023. "Salience theory in price and trading volume: Evidence from China," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 38-61.
    18. 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.
    19. Mamdouh Medhat & Maik Schmeling, 2022. "Short-term Momentum," The Review of Financial Studies, Society for Financial Studies, vol. 35(3), pages 1480-1526.
    20. Shai Levi & Xiao-Jun Zhang, 2015. "Do Temporary Increases in Information Asymmetry Affect the Cost of Equity?," Management Science, INFORMS, vol. 61(2), pages 354-371, February.

    More about this item

    Keywords

    unusual trading volume; earnings surprises; divergence of opinion; stock return; China’s market;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:gam:jjrfmx:v:13:y:2020:i:10:p:244-:d:428944. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.