IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v27y2022i4p4556-4574.html
   My bibliography  Save this article

Delayed informed trades and opinion divergence: Evidence from earnings releases

Author

Listed:
  • Tao Chen

Abstract

This study begins to verify whether delayed informed trades occur surrounding an earnings release. Next, we discover that post‐event investor opinions tend to diverge when more informed trades are delayed after the earnings release. As additional empirical evidence indicates, investors are likely compelled to postpone their informed trades due to information complexity, stock illiquidity, and institutional competition. Finally, such a documented association between delayed informed trades and opinion divergence remains robust to the placebo test, endogeneity problem, and large‐cap sample bias.

Suggested Citation

  • Tao Chen, 2022. "Delayed informed trades and opinion divergence: Evidence from earnings releases," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4556-4574, October.
    • Handle: RePEc:wly:ijfiec:v:27:y:2022:i:4:p:4556-4574
    DOI: 10.1002/ijfe.2387
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2387
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.2387?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
    ---><---

    References listed on IDEAS

    as
    1. Chen, Tao, 2020. "Does news affect disagreement in global markets?," Journal of Business Research, Elsevier, vol. 109(C), pages 174-183.
    2. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    3. Ron Kaniel & Shuming Liu & Gideon Saar & Sheridan Titman, 2012. "Individual Investor Trading and Return Patterns around Earnings Announcements," Journal of Finance, American Finance Association, vol. 67(2), pages 639-680, April.
    4. Chen, Tao, 2021. "Informed trading and earnings announcement driven disagreement in global markets," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 43(C).
    5. Tunde Kovacs, 2016. "Intra†Industry Information Transfers and the Post†Earnings Announcement Drift," Contemporary Accounting Research, John Wiley & Sons, vol. 33(4), pages 1549-1575, December.
    6. 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.
    7. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    8. Turan G. Bali & Lin Peng & Yannan Shen & Yi Tang, 2014. "Liquidity Shocks and Stock Market Reactions," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1434-1485.
    9. Ekkehart Boehmer & Eric K. Kelley, 2009. "Institutional Investors and the Informational Efficiency of Prices," Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3563-3594, September.
    10. Brian J. Bushee & Theodore H. Goodman, 2007. "Which Institutional Investors Trade Based on Private Information About Earnings and Returns?," Journal of Accounting Research, Wiley Blackwell, vol. 45(2), pages 289-321, May.
    11. Péter Kondor, 2012. "The More We Know about the Fundamental, the Less We Agree on the Price," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1175-1207.
    12. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    13. 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.
    14. Finucane, Thomas J., 2000. "A Direct Test of Methods for Inferring Trade Direction from Intra-Day Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 553-576, December.
    15. Guay, Wayne & Samuels, Delphine & Taylor, Daniel, 2016. "Guiding through the Fog: Financial statement complexity and voluntary disclosure," Journal of Accounting and Economics, Elsevier, vol. 62(2), pages 234-269.
    16. Verardo, Michela, 2009. "Heterogeneous Beliefs and Momentum Profits," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 795-822, August.
    17. Joel Hasbrouck, 2009. "Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data," Journal of Finance, American Finance Association, vol. 64(3), pages 1445-1477, June.
    18. Snehal Banerjee, 2011. "Learning from Prices and the Dispersion in Beliefs," Review of Financial Studies, Society for Financial Studies, vol. 24(9), pages 3025-3068.
    19. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    20. Jianguo Xu, 2007. "Price Convexity and Skewness," Journal of Finance, American Finance Association, vol. 62(5), pages 2521-2552, October.
    21. Lang, Mark & Stice-Lawrence, Lorien, 2015. "Textual analysis and international financial reporting: Large sample evidence," Journal of Accounting and Economics, Elsevier, vol. 60(2), pages 110-135.
    22. Doukas, John A. & Kim, Chansog (Francis) & Pantzalis, Christos, 2006. "Divergence of Opinion and Equity Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(3), pages 573-606, September.
    23. Moulton, Pamela C., 2005. "You can't always get what you want: Trade-size clustering and quantity choice in liquidity," Journal of Financial Economics, Elsevier, vol. 78(1), pages 89-119, October.
    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. Tao Chen & Andreas Karathanasopoulos, 2022. "Do Heterogeneous Beliefs Matter to Post‐announcement Informed Trading?," Abacus, Accounting Foundation, University of Sydney, vol. 58(4), pages 714-741, December.
    2. Chu-Lan Michael Kao & Emily Lin, 2023. "A new PIN model with application of the change-point detection method," Review of Quantitative Finance and Accounting, Springer, vol. 61(4), pages 1513-1528, November.

    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. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    2. Chen, Tao, 2020. "Does news affect disagreement in global markets?," Journal of Business Research, Elsevier, vol. 109(C), pages 174-183.
    3. Chen, Tao, 2019. "Trade-size clustering and price efficiency," Japan and the World Economy, Elsevier, vol. 49(C), pages 195-203.
    4. Giovanni Cespa & Xavier Vives, 2011. "Expectations, Liquidity, and Short-term Trading," CESifo Working Paper Series 3390, CESifo.
    5. Li, Xiafei & Luo, Di, 2019. "Financial constraints, stock liquidity, and stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    6. Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2022. "Price revelation from insider trading: Evidence from hacked earnings news," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1162-1184.
    7. Arie E. Gozluklu & Pietro Perotti & Barbara Rindi & Roberta Fredella, 2015. "Lot Size Constraints and Market Quality: Evidence from the Borsa Italiana," Financial Management, Financial Management Association International, vol. 44(4), pages 905-945, October.
    8. Lawrence, Alastair, 2013. "Individual investors and financial disclosure," Journal of Accounting and Economics, Elsevier, vol. 56(1), pages 130-147.
    9. Lili Dai & Jerry T. Parwada & Donald W. Winchester & Bohui Zhang, 2022. "The more we know, the less we agree: A test of the trading horizon heterogeneity theory," The Financial Review, Eastern Finance Association, vol. 57(1), pages 45-67, February.
    10. Jieun Lee & Kee H. Chung, 2015. "Foreign Ownership, Legal System and Stock Market Liquidity," Working Papers 2015-15, Economic Research Institute, Bank of Korea.
    11. Tao Chen & Andreas Karathanasopoulos, 2022. "Do Heterogeneous Beliefs Matter to Post‐announcement Informed Trading?," Abacus, Accounting Foundation, University of Sydney, vol. 58(4), pages 714-741, December.
    12. Lee, Jieun & Chung, Kee H., 2018. "Foreign ownership and stock market liquidity," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 311-325.
    13. Richardson, Scott & Tuna, Irem & Wysocki, Peter, 2010. "Accounting anomalies and fundamental analysis: A review of recent research advances," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 410-454, December.
    14. Hao Li & Zhisheng Li, 2022. "The effect of daily price limits on stock liquidity: Evidence from the Chinese stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(5), pages 4885-4917, December.
    15. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    16. Hatheway, Frank & Kwan, Amy & Zheng, Hui, 2017. "An Empirical Analysis of Market Segmentation on U.S. Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2399-2427, December.
    17. 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).
    18. Giovanni Cespa & Xavier Vives, 2015. "The Beauty Contest and Short-Term Trading," Journal of Finance, American Finance Association, vol. 70(5), pages 2099-2154, October.
    19. Hyunkwon Cho & Robert Kim, 2021. "Asymmetric effects of voluntary disclosure on stock liquidity: evidence from 8‐K filings," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 803-846, March.
    20. Al-Nasseri, Alya & Menla Ali, Faek, 2018. "What does investors' online divergence of opinion tell us about stock returns and trading volume?," Journal of Business Research, Elsevier, vol. 86(C), pages 166-178.

    More about this item

    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:wly:ijfiec:v:27:y:2022:i:4:p:4556-4574. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.