IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v87y2023ics1057521923001242.html
   My bibliography  Save this article

Heterogeneously informed trading and the stock market efficiency during the COVID-19 pandemic

Author

Listed:
  • Xu, Liao
  • Xue, Mingqi
  • Zhang, Xuan
  • Zhao, Yang

Abstract

This study investigates the U.S. stock market efficiency from the symmetric and asymmetric perspectives during the COVID-19 pandemic. We explore that the pandemic boosts (hurts) the information role of symmetrically (asymmetrically) informed trading. Specifically, we find that the epidemic outbreak and infection scale strengthen (weaken) the stock return reaction to symmetrically (asymmetrically) informed trading. Evidence also indicates that the effect of symmetrically (asymmetrically) informed trading on stocks' permanent price shocks and price informational efficiency is enhanced (impaired) during the pandemic. Moreover, all these effects are consistently more intensive to informed buys.

Suggested Citation

  • Xu, Liao & Xue, Mingqi & Zhang, Xuan & Zhao, Yang, 2023. "Heterogeneously informed trading and the stock market efficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 87(C).
    • Handle: RePEc:eee:finana:v:87:y:2023:i:c:s1057521923001242
    DOI: 10.1016/j.irfa.2023.102608
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521923001242
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2023.102608?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. Brunetti, Celso & Harris, Jeffrey H. & Mankad, Shawn, 2022. "Sidedness in the interbank market," Journal of Financial Markets, Elsevier, vol. 59(PA).
    2. Xu, Liao & Yin, Xiangkang, 2017. "Does ETF trading affect the efficiency of the underlying index?," International Review of Financial Analysis, Elsevier, vol. 51(C), pages 82-101.
    3. Comerton-Forde, Carole & Jones, Charles M. & Putniņš, Tālis J., 2016. "Shorting at close range: A tale of two types," Journal of Financial Economics, Elsevier, vol. 121(3), pages 546-568.
    4. Niels Joachim Gormsen & Ralph S J Koijen & Nikolai Roussanov, 0. "Coronavirus: Impact on Stock Prices and Growth Expectations," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 574-597.
    5. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
    6. Dominik M. Rösch & Avanidhar Subrahmanyam & Mathijs A. van Dijk, 2017. "The Dynamics of Market Efficiency," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1151-1187.
    7. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    8. Xu, Liao & Zhang, Xuan & Zhao, Jing, 2023. "Limited investor attention and biased reactions to information: Evidence from the COVID-19 pandemic," Journal of Financial Markets, Elsevier, vol. 62(C).
    9. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    10. J Anthony Cookson & Joseph E Engelberg & William Mullins & Hui Chen, 0. "Does Partisanship Shape Investor Beliefs? Evidence from the COVID-19 Pandemic," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 863-893.
    11. Choonsik Lee & Kee H. Chung & Sean Yang, 2016. "Corporate Governance and the Informational Efficiency of Prices," Financial Management, Financial Management Association International, vol. 45(1), pages 239-260, March.
    12. Itzhak Ben‐David & Francesco Franzoni & Rabih Moussawi, 2018. "Do ETFs Increase Volatility?," Journal of Finance, American Finance Association, vol. 73(6), pages 2471-2535, December.
    13. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    14. Comerton-Forde, Carole & Putniņš, Tālis J., 2015. "Dark trading and price discovery," Journal of Financial Economics, Elsevier, vol. 118(1), pages 70-92.
    15. Asani Sarkar & Robert A. Schwartz, 2009. "Market Sidedness: Insights into Motives for Trade Initiation," Journal of Finance, American Finance Association, vol. 64(1), pages 375-423, February.
    16. Xu, Liao & Yin, Xiangkang & Zhao, Jing, 2019. "The sidedness and informativeness of ETF trading and the market efficiency of their underlying indexes," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    17. Bernile, Gennaro & Hu, Jianfeng & Tang, Yuehua, 2016. "Can information be locked up? Informed trading ahead of macro-news announcements," Journal of Financial Economics, Elsevier, vol. 121(3), pages 496-520.
    18. Ekkehart Boehmer & Eric K. Kelley, 2009. "Institutional Investors and the Informational Efficiency of Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3563-3594, September.
    19. Corbet, Shaen & Hou, Yang & Hu, Yang & Oxley, Les, 2020. "The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry," International Review of Financial Analysis, Elsevier, vol. 72(C).
    20. Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
    21. Armstrong, Will J. & Cardella, Laura & Sabah, Nasim, 2021. "Information shocks, disagreement, and drift," Journal of Financial Economics, Elsevier, vol. 140(3), pages 916-940.
    22. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    23. Xiangkang Yin & Jing Zhao, 2015. "A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1210-1234, November.
    24. Wang, Hua & Xu, Liao & Sharma, Susan Sunila, 2021. "Does investor attention increase stock market volatility during the COVID-19 pandemic?," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    25. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    26. Hasbrouck, Joel, 1993. "Assessing the Quality of a Security Market: A New Approach to Transaction-Cost Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 6(1), pages 191-212.
    27. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    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. Xu, Liao & Xu, Lu & Zhao, Jing & Zhao, Yang, 2020. "Information-based trading and information propagation: Evidence from the exchange traded fund market," International Review of Financial Analysis, Elsevier, vol. 70(C).
    2. Xu, Liao & Zhang, Xuan & Zhao, Jing, 2023. "Limited investor attention and biased reactions to information: Evidence from the COVID-19 pandemic," Journal of Financial Markets, Elsevier, vol. 62(C).
    3. Xu, Liao & Yin, Xiangkang & Zhao, Jing, 2019. "The sidedness and informativeness of ETF trading and the market efficiency of their underlying indexes," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    4. Jilong Chen & Liao Xu & Yang Zhao, 2020. "Do ETF flows increase market efficiency? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(5), pages 4795-4819, December.
    5. Lauter, Tobias & Prokopczuk, Marcel, 2022. "Measuring commodity market quality," Journal of Banking & Finance, Elsevier, vol. 145(C).
    6. Albuquerque, Rui & Song, Shiyun & Yao, Chen, 2017. "The Price Effects of Liquidity Shocks: A Study of SEC’s Tick-Size Experiment," CEPR Discussion Papers 12486, C.E.P.R. Discussion Papers.
    7. Kee H. Chung & Choonsik Lee & Carl Hsin‐han Shen, 2020. "Passive blockholders, informational efficiency of prices, and firm value," Review of Financial Economics, John Wiley & Sons, vol. 38(3), pages 494-512, July.
    8. Liao Xu & Xiangkang Yin & Jing Zhao, 2022. "Are the flows of exchange‐traded funds informative?," Financial Management, Financial Management Association International, vol. 51(4), pages 1165-1200, December.
    9. Foley, Sean & Putniņš, Tālis J., 2016. "Should we be afraid of the dark? Dark trading and market quality," Journal of Financial Economics, Elsevier, vol. 122(3), pages 456-481.
    10. Zhang, Chris H. & Frijns, Bart, 2019. "Noise trading and informational efficiency," EconStor Preprints 198037, ZBW - Leibniz Information Centre for Economics.
    11. Zhang, Chris H. & Kalev, Petko S., 2021. "How noise trading affects informational efficiency: Evidence from an order-driven market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    12. Albuquerque, Rui & Song, Shiyun & Yao, Chen, 2020. "The price effects of liquidity shocks: A study of the SEC’s tick size experiment," Journal of Financial Economics, Elsevier, vol. 138(3), pages 700-724.
    13. Comerton-Forde, Carole & Grégoire, Vincent & Zhong, Zhuo, 2019. "Inverted fee structures, tick size, and market quality," Journal of Financial Economics, Elsevier, vol. 134(1), pages 141-164.
    14. Xu, Liao & Pu, Wenyan, 2022. "ETFs, arbitrage activity, and stock market efficiency: Evidence from Chinese CSI 300 ETFs," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 1-9.
    15. Lin, Hai & Lo, Ingrid & Qiao, Rui, 2021. "Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market," Journal of Banking & Finance, Elsevier, vol. 133(C).
    16. Rösch, Dominik, 2021. "The impact of arbitrage on market liquidity," Journal of Financial Economics, Elsevier, vol. 142(1), pages 195-213.
    17. Hua Wang & Liao Xu, 2019. "Do exchange‐traded fund flows increase the volatility of the underlying index? Evidence from the emerging market in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1525-1548, March.
    18. Cakici, Nusret & Zaremba, Adam, 2021. "Who should be afraid of infections? Pandemic exposure and the cross-section of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    19. Ibikunle, Gbenga & Aquilina, Matteo & Diaz-Rainey, Ivan & Sun, Yuxin, 2021. "City goes dark: Dark trading and adverse selection in aggregate markets," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 1-22.
    20. Jacob Thomas & Frank Zhang & Wei Zhu, 2021. "Dark Trading and Post-Earnings-Announcement Drift," Management Science, INFORMS, vol. 67(12), pages 7785-7811, December.

    More about this item

    Keywords

    Asymmetric information; COVID-19; Informed trading; Market efficiency; Symmetric information;
    All these keywords.

    JEL classification:

    • 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:eee:finana:v:87:y:2023:i:c:s1057521923001242. 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/inca/620166 .

    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.