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Asymmetric post earnings announcement drift and order flow imbalance: The impact on stock market returns

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  • Zhang, Sijia
  • Gregoriou, Andros
  • Wu, He

Abstract

We conduct an event study around the earning announcement to examine the asymmetric post earnings announcement drift, and its relationship with the bid-ask bias, order follow imbalance on post earnings announcement period for UK stock market from 2000 2021. The earning drift is significantly asymmetric in the post earnings announcement period, stocks with good news have less drift, and it (at least) partly due to the order flow imbalance during the event period. The earning announcement attracts more sell than buy orders, and an overall negative reaction in the market. The difference between transaction price return and quote price returns shows that the bid-ask bias is also a possible explanation of post earnings announcement drift. Our results are robust across different estimations and robustness tests.

Suggested Citation

  • Zhang, Sijia & Gregoriou, Andros & Wu, He, 2024. "Asymmetric post earnings announcement drift and order flow imbalance: The impact on stock market returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:finana:v:94:y:2024:i:c:s1057521924002485
    DOI: 10.1016/j.irfa.2024.103316
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    1. Christina Dargenidou & Ian Tonks & Fanis Tsoligkas, 2018. "Insider trading and the post†earnings announcement drift," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 45(3-4), pages 482-508, March.
    2. Engle, Robert F. & Patton, Andrew J., 2004. "Impacts of trades in an error-correction model of quote prices," Journal of Financial Markets, Elsevier, vol. 7(1), pages 1-25, January.
    3. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    4. Henk Berkman & Cameron Truong, 2009. "Event Day 0? After‐Hours Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 47(1), pages 71-103, March.
    5. Joon Chae, 2005. "Trading Volume, Information Asymmetry, and Timing Information," Journal of Finance, American Finance Association, vol. 60(1), pages 413-442, February.
    6. Lee, Charles M C & Mucklow, Belinda & Ready, Mark J, 1993. "Spreads, Depths, and the Impact of Earnings Information: An Intraday Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 345-374.
    7. Bernard, Victor L. & Thomas, Jacob K., 1990. "Evidence that stock prices do not fully reflect the implications of current earnings for future earnings," Journal of Accounting and Economics, Elsevier, vol. 13(4), pages 305-340, December.
    8. Levi, Shai & Zhang, Xiao-Jun, 2015. "Asymmetric decrease in liquidity trading before earnings announcements and the announcement return premium," Journal of Financial Economics, Elsevier, vol. 118(2), pages 383-398.
    9. Graham, John R. & Harvey, Campbell R. & Rajgopal, Shiva, 2005. "The economic implications of corporate financial reporting," Journal of Accounting and Economics, Elsevier, vol. 40(1-3), pages 3-73, December.
    10. Park, Tae-Jun & Lee, Youngjoo & Song, Kyojik “Roy”, 2014. "Informed trading before positive vs. negative earnings surprises," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 228-241.
    11. Keim, Donald B. & Madhavan, Ananth, 1995. "Anatomy of the trading process Empirical evidence on the behavior of institutional traders," Journal of Financial Economics, Elsevier, vol. 37(3), pages 371-398, March.
    12. Jennings, Robert & Starks, Laura, 1986. "Earnings Announcements, Stock Price Adjustment, and the Existence of Option Markets," Journal of Finance, American Finance Association, vol. 41(1), pages 107-125, March.
    13. 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.
    14. Alex Frino & Vito Mollica & Maria Grazia Romano & Zeyang Zhou, 2017. "Asymmetry in the Permanent Price Impact of Block Purchases and Sales: Theory and Empirical Evidence," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(4), pages 359-373, April.
    15. Savor, Pavel G., 2012. "Stock returns after major price shocks: The impact of information," Journal of Financial Economics, Elsevier, vol. 106(3), pages 635-659.
    16. Theissen, Erik, 2001. "A test of the accuracy of the Lee/Ready trade classification algorithm," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 11(2), pages 147-165, June.
    17. Andrea Frazzini, 2006. "The Disposition Effect and Underreaction to News," Journal of Finance, American Finance Association, vol. 61(4), pages 2017-2046, August.
    18. Hirshleifer, David & Teoh, Siew Hong, 2003. "Limited attention, information disclosure, and financial reporting," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 337-386, December.
    19. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    20. Brown, Philip & Walsh, David & Yuen, Andrea, 1997. "The interaction between order imbalance and stock price," Pacific-Basin Finance Journal, Elsevier, vol. 5(5), pages 539-557, December.
    21. Hendershott, Terrence & Livdan, Dmitry & Schürhoff, Norman, 2015. "Are institutions informed about news?," Journal of Financial Economics, Elsevier, vol. 117(2), pages 249-287.
    22. Ganapathi Narayanamoorthy, 2006. "Conservatism and Cross‐Sectional Variation in the Post–Earnings Announcement Drift," Journal of Accounting Research, Wiley Blackwell, vol. 44(4), pages 763-789, September.
    23. Brown, Stephen & Hillegeist, Stephen A. & Lo, Kin, 2009. "The effect of earnings surprises on information asymmetry," Journal of Accounting and Economics, Elsevier, vol. 47(3), pages 208-225, June.
    24. Lo, Kevin & Coggins, Richard, 2006. "Effects of order flow imbalance on short-horizon contrarian strategies in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 14(3), pages 291-310, June.
    25. 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.
    26. Howard Chan & Robert Faff & Alan Ramsay, 2005. "Firm Size and the Information Content of Annual Earnings Announcements: Australian Evidence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(1‐2), pages 211-253, January.
    27. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan, 2019. "Asymmetric relationship between order imbalance and realized volatility: Evidence from the Australian market," International Review of Economics & Finance, Elsevier, vol. 62(C), pages 309-320.
    28. Lease, Ronald C & Masulis, Ronald W & Page, John R, 1991. "An Investigation of Market Microstructure Impacts on Event Study Returns," Journal of Finance, American Finance Association, vol. 46(4), pages 1523-1536, September.
    29. Kim, Sukwon Thomas & Stoll, Hans R., 2014. "Are trading imbalances indicative of private information?," Journal of Financial Markets, Elsevier, vol. 20(C), pages 151-174.
    30. Howard Chan & Robert Faff & Alan Ramsay, 2005. "Firm Size and the Information Content of Annual Earnings Announcements: Australian Evidence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(1‐2), pages 211-253, January.
    31. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and the stock market response to earnings news," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 221-240.
    32. Campbell, John Y. & Ramadorai, Tarun & Schwartz, Allie, 2009. "Caught on tape: Institutional trading, stock returns, and earnings announcements," Journal of Financial Economics, Elsevier, vol. 92(1), pages 66-91, April.
    33. Ball, R & Brown, P, 1968. "Empirical Evaluation Of Accounting Income Numbers," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 159-178.
    34. Jeffrey Ng & Tjomme O. Rusticus & Rodrigo S. Verdi, 2008. "Implications of Transaction Costs for the Post–Earnings Announcement Drift," Journal of Accounting Research, Wiley Blackwell, vol. 46(3), pages 661-696, June.
    35. Stefano Dellavigna & Joshua M. Pollet, 2009. "Investor Inattention and Friday Earnings Announcements," Journal of Finance, American Finance Association, vol. 64(2), pages 709-749, April.
    36. Lee, Charles M. C., 1992. "Earnings news and small traders : An intraday analysis," Journal of Accounting and Economics, Elsevier, vol. 15(2-3), pages 265-302, August.
    37. S. P. Kothari & Susan Shu & Peter D. Wysocki, 2009. "Do Managers Withhold Bad News?," Journal of Accounting Research, Wiley Blackwell, vol. 47(1), pages 241-276, March.
    38. Chan, Louis K. C. & Lakonishok, Josef, 1993. "Institutional trades and intraday stock price behavior," Journal of Financial Economics, Elsevier, vol. 33(2), pages 173-199, April.
    39. Jennifer Conrad & Bradford Cornell & Wayne R. Landsman, 2002. "When Is Bad News Really Bad News?," Journal of Finance, American Finance Association, vol. 57(6), pages 2507-2532, December.
    40. Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
    41. Yufeng Han & David Lesmond, 2011. "Liquidity Biases and the Pricing of Cross-sectional Idiosyncratic Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1590-1629.
    42. Tarun Chordia & Jianfeng Hu & Avanidhar Subrahmanyam & Qing Tong, 2019. "Order Flow Volatility and Equity Costs of Capital," Management Science, INFORMS, vol. 65(4), pages 1520-1551, April.
    43. David Hirshleifer & Sonya Seongyeon Lim & Siew Hong Teoh, 2009. "Driven to Distraction: Extraneous Events and Underreaction to Earnings News," Journal of Finance, American Finance Association, vol. 64(5), pages 2289-2325, October.
    44. Eom, Yunsung & Hahn, Jaehoon & Sohn, Wook, 2019. "Individual investors and post-earnings-announcement drift: Evidence from Korea," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 379-398.
    45. Michaely, Roni & Rubin, Amir & Vedrashko, Alexander, 2016. "Further evidence on the strategic timing of earnings news: Joint analysis of weekdays and times of day," Journal of Accounting and Economics, Elsevier, vol. 62(1), pages 24-45.
    46. deHaan, Ed & Shevlin, Terry & Thornock, Jacob, 2015. "Market (in)attention and the strategic scheduling and timing of earnings announcements," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 36-55.
    47. Gosnell, Thomas F. & Keown, Arthur J. & Pinkerton, John M., 1996. "The intraday speed of stock price adjustment to major dividend changes: Bid-ask bounce and order flow imbalances," Journal of Banking & Finance, Elsevier, vol. 20(2), pages 247-266, March.
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    More about this item

    Keywords

    Post earnings announcement drift; Order flow imbalance; Bid-ask bias; Earnings surprises; Market efficiency;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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