IDEAS home Printed from https://ideas.repec.org/a/eee/jaecon/v70y2020i2s0165410120300379.html
   My bibliography  Save this article

Market efficiency in real time: Evidence from low latency activity around earnings announcements

Author

Listed:
  • Chordia, Tarun
  • Miao, Bin

Abstract

The literature has used small samples to show that fast trading or low latency trading (LLT) improves efficiency at extremely high frequencies. However, it is not clear whether LLT driven high frequency improvements in efficiency can impact corporate decision making and investor risk sharing or hedging, which are low frequency processes. This paper uses a comprehensive cross-sectional and time-series sample to provide evidence that LLT enhances efficiency around earnings announcements. Low latency traders trade aggressively at the time of the earnings announcements, such that the information in earnings surprises is quickly incorporated into prices and the post-announcement drift is reduced.

Suggested Citation

  • Chordia, Tarun & Miao, Bin, 2020. "Market efficiency in real time: Evidence from low latency activity around earnings announcements," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    • Handle: RePEc:eee:jaecon:v:70:y:2020:i:2:s0165410120300379
    DOI: 10.1016/j.jacceco.2020.101335
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165410120300379
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jacceco.2020.101335?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. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2011. "Recent trends in trading activity and market quality," Journal of Financial Economics, Elsevier, vol. 101(2), pages 243-263, August.
    2. Craig W. Holden & Stacey Jacobsen, 2014. "Liquidity Measurement Problems in Fast, Competitive Markets: Expensive and Cheap Solutions," Journal of Finance, American Finance Association, vol. 69(4), pages 1747-1785, August.
    3. Dechow, Patricia & Ge, Weili & Schrand, Catherine, 2010. "Understanding earnings quality: A review of the proxies, their determinants and their consequences," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 344-401, December.
    4. Andrea Frazzini, 2006. "The Disposition Effect and Underreaction to News," Journal of Finance, American Finance Association, vol. 61(4), pages 2017-2046, August.
    5. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    6. Daniel, Kent, et al, 1997. "Measuring Mutual Fund Performance with Characteristic-Based Benchmarks," Journal of Finance, American Finance Association, vol. 52(3), pages 1035-1058, July.
    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. Beaver, William & McNichols, Maureen & Price, Richard, 2007. "Delisting returns and their effect on accounting-based market anomalies," Journal of Accounting and Economics, Elsevier, vol. 43(2-3), pages 341-368, July.
    9. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    10. 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.
    11. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    12. Landsman, Wayne R. & Maydew, Edward L. & Thornock, Jacob R., 2012. "The information content of annual earnings announcements and mandatory adoption of IFRS," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 34-54.
    13. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    14. Conrad, Jennifer & Wahal, Sunil & Xiang, Jin, 2015. "High-frequency quoting, trading, and the efficiency of prices," Journal of Financial Economics, Elsevier, vol. 116(2), pages 271-291.
    15. Ball, R & Brown, P, 1968. "Empirical Evaluation Of Accounting Income Numbers," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 159-178.
    16. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    17. Chambers, Ae & Penman, Sh, 1984. "Timeliness Of Reporting And The Stock-Price Reaction To Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 21-47.
    18. Collins, Daniel W. & Kothari, S. P., 1989. "An analysis of intertemporal and cross-sectional determinants of earnings response coefficients," Journal of Accounting and Economics, Elsevier, vol. 11(2-3), pages 143-181, July.
    19. 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.
    20. 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.
    21. William H. Beaver & Maureen F. McNichols & Zach Z. Wang, 2018. "The information content of earnings announcements: new insights from intertemporal and cross-sectional behavior," Review of Accounting Studies, Springer, vol. 23(1), pages 95-135, March.
    22. Henock Louis & Amy Sun, 2010. "Investor Inattention and the Market Reaction to Merger Announcements," Management Science, INFORMS, vol. 56(10), pages 1781-1793, October.
    23. Beaver, Wh, 1968. "Information Content Of Annual Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 6, pages 67-92.
    24. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    25. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    26. Jonathan L. Rogers & Douglas J. Skinner & Sarah L. C. Zechman, 2017. "Run EDGAR Run: SEC Dissemination in a High‐Frequency World," Journal of Accounting Research, Wiley Blackwell, vol. 55(2), pages 459-505, May.
    27. Bernard, Vl & Thomas, Jk, 1989. "Post-Earnings-Announcement Drift - Delayed Price Response Or Risk Premium," Journal of Accounting Research, Wiley Blackwell, vol. 27, pages 1-36.
    28. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    29. John H. Cochrane, 2013. "Finance: Function Matters, Not Size," Journal of Economic Perspectives, American Economic Association, vol. 27(2), pages 29-50, Spring.
    30. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    31. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    32. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    33. Travlos, Nickolaos G, 1987. "Corporate Takeover Bids, Methods of Payment, and Bidding Firms' Stock Returns," Journal of Finance, American Finance Association, vol. 42(4), pages 943-963, September.
    34. Kormendi, Roger & Lipe, Robert, 1987. "Earnings Innovations, Earnings Persistence, and Stock Returns," The Journal of Business, University of Chicago Press, vol. 60(3), pages 323-345, July.
    35. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    36. Saeyoung Chang, 1998. "Takeovers of Privately Held Targets, Methods of Payment, and Bidder Returns," Journal of Finance, American Finance Association, vol. 53(2), pages 773-784, April.
    37. Wayne R. Landsman & Edward L. Maydew, 2002. "Has the Information Content of Quarterly Earnings Announcements Declined in the Past Three Decades?," Journal of Accounting Research, Wiley Blackwell, vol. 40(3), pages 797-808, June.
    38. 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.
    39. Jeffrey T. Doyle & Russell J. Lundholm & Mark T. Soliman, 2006. "The Extreme Future Stock Returns Following I/B/E/S Earnings Surprises," Journal of Accounting Research, Wiley Blackwell, vol. 44(5), pages 849-887, December.
    40. 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.
    41. Shumway, Tyler, 1997. "The Delisting Bias in CRSP Data," Journal of Finance, American Finance Association, vol. 52(1), pages 327-340, March.
    42. Tarun Chordia & T Clifton Green & Badrinath Kottimukkalur, 2018. "Rent Seeking by Low-Latency Traders: Evidence from Trading on Macroeconomic Announcements," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4650-4687.
    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. Ye, Mao & Zheng, Miles Y. & Zhu, Wei, 2023. "The effect of tick size on managerial learning from stock prices," Journal of Accounting and Economics, Elsevier, vol. 75(1).
    2. Laurent Bouton & Aniol Llorente-Saguer & Antonin Macé & Adam Meirowitz & Shaoting Pi & Dimitrios Xefteris, 2022. "Public Information as a Source of Disagreement Among Shareholders," NBER Working Papers 30757, National Bureau of Economic Research, Inc.
    3. Kee H. Chung & Chairat Chuwonganant, 2023. "Tick size and price efficiency: Further evidence from the Tick Size Pilot Program," Financial Management, Financial Management Association International, vol. 52(3), pages 483-511, September.
    4. Chakrabarty, Bidisha & Moulton, Pamela C. & Wang, Xu (Frank), 2022. "Attention: How high-frequency trading improves price efficiency following earnings announcements," Journal of Financial Markets, Elsevier, vol. 57(C).
    5. Jacob Thomas & Frank Zhang & Wei Zhu, 2021. "Dark Trading and Post-Earnings-Announcement Drift," Management Science, INFORMS, vol. 67(12), pages 7785-7811, December.
    6. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    7. Brice Corgnet & Mark DeSantis & Christoph Siemroth, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Working Papers 2313, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    8. Millicent Chang & John Gould & Yuyun Huang & Sirimon Treepongkaruna & Joey Wenling Yang, 2022. "Insider trading and the algorithmic trading environment," International Review of Finance, International Review of Finance Ltd., vol. 22(4), pages 725-750, December.
    9. Ibikunle, Gbenga & Rzayev, Khaladdin, 2023. "Volatility and dark trading: Evidence from the Covid-19 pandemic," The British Accounting Review, Elsevier, vol. 55(4).
    10. Aliyev, Nihad & Huseynov, Fariz & Rzayev, Khaladdin, 2022. "Algorithmic trading and investment-to-price sensitivity," LSE Research Online Documents on Economics 118844, London School of Economics and Political Science, LSE Library.

    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. Karolis Liaudinskas, 2022. "Human vs. Machine: Disposition Effect among Algorithmic and Human Day Traders," Working Paper 2022/6, Norges Bank.
    3. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    4. S. P. Kothari & Charles Wasley, 2019. "Commemorating the 50‐Year Anniversary of Ball and Brown (1968): The Evolution of Capital Market Research over the Past 50 Years," Journal of Accounting Research, Wiley Blackwell, vol. 57(5), pages 1117-1159, December.
    5. Nilabhra Bhattacharya & Bidisha Chakrabarty & Xu (Frank) Wang, 2020. "High-frequency traders and price informativeness during earnings announcements," Review of Accounting Studies, Springer, vol. 25(3), pages 1156-1199, September.
    6. Cox, Justin & Woods, Donovan, 2023. "COVID-19 and market structure dynamics," Journal of Banking & Finance, Elsevier, vol. 147(C).
    7. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    8. Josef Fink, 2020. "A Review of the Post-Earnings-Announcement Drift," Working Paper Series, Social and Economic Sciences 2020-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    9. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    10. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    11. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    12. Donald B. Keim & Massimo Massa & Bastian von Beschwitz, 2018. "First to \"Read\" the News: New Analytics and Algorithmic Trading," International Finance Discussion Papers 1233, Board of Governors of the Federal Reserve System (U.S.).
    13. Aliyev, Nihad & Huseynov, Fariz & Rzayev, Khaladdin, 2022. "Algorithmic trading and investment-to-price sensitivity," LSE Research Online Documents on Economics 118844, London School of Economics and Political Science, LSE Library.
    14. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    15. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    16. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    17. Zhou, Hao & Elliott, Robert J. & Kalev, Petko S., 2019. "Information or noise: What does algorithmic trading incorporate into the stock prices?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 27-39.
    18. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    19. Schnaubelt, Matthias & Seifert, Oleg, 2020. "Valuation ratios, surprises, uncertainty or sentiment: How does financial machine learning predict returns from earnings announcements?," FAU Discussion Papers in Economics 04/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    20. Zhou, Hao & Kalev, Petko S. & Frino, Alex, 2020. "Algorithmic trading in turbulent markets," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).

    More about this item

    Keywords

    Low-latency trading; Market efficiency; Earnings announcement; Post-earnings announcement drift;
    All these keywords.

    JEL classification:

    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • 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:jaecon:v:70:y:2020:i:2:s0165410120300379. 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/jae .

    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.