IDEAS home Printed from https://ideas.repec.org/a/eee/bracre/v55y2023i4s0890838922000828.html
   My bibliography  Save this article

Algorithmic trading and block ownership initiation: An information perspective

Author

Listed:
  • Zheng, Jiayi
  • Zhu, Yushu

Abstract

This paper examines the impact of algorithmic trading (AT) on investors' incentives to initiate block ownership in U.S. public companies. We find that a one standard deviation change in AT activity reduces the block ownership initiation likelihood by 3.5%. Using the SEC's randomised tick size pilot experiment in 2016 as a negative shock to AT, we show that the effect of AT on block ownership initiation is causal. Further evidence supports the information-hindering explanation that AT discourages sophisticated investors from acquiring information, which results in a decrease in block ownership initiation. We find that the effect of AT is more pronounced among information-sensitive investors and that institutional investors reduce their information-gathering activities in AT-targeted stocks. Additional tests exploring information-based trading behaviour in the presence of AT provide strong evidence to support the explanation of information-hindering, and our results hold across a battery of robustness tests.

Suggested Citation

  • Zheng, Jiayi & Zhu, Yushu, 2023. "Algorithmic trading and block ownership initiation: An information perspective," The British Accounting Review, Elsevier, vol. 55(4).
    • Handle: RePEc:eee:bracre:v:55:y:2023:i:4:s0890838922000828
    DOI: 10.1016/j.bar.2022.101146
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0890838922000828
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.bar.2022.101146?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. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows," Review of Finance, European Finance Association, vol. 33(4), pages 1484-1533.
    2. Hatch, Brian C. & Johnson, Shane A. & Wang, Qin Emma & Zhang, Jun, 2021. "Algorithmic trading and firm value," Journal of Banking & Finance, Elsevier, vol. 125(C).
    3. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    4. Alex Edmans & Vivian W. Fang & Emanuel Zur, 2013. "The Effect of Liquidity on Governance," Review of Financial Studies, Society for Financial Studies, vol. 26(6), pages 1443-1482.
    5. Anwer S. Ahmed & Yiwen Li & Nina Xu, 2020. "Tick Size and Financial Reporting Quality in Small‐Cap Firms: Evidence from a Natural Experiment," Journal of Accounting Research, Wiley Blackwell, vol. 58(4), pages 869-914, September.
    6. Kingsley Y. L. Fong & Craig W. Holden & Charles A. Trzcinka, 2017. "What Are the Best Liquidity Proxies for Global Research?," Review of Finance, European Finance Association, vol. 21(4), pages 1355-1401.
    7. 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.
    8. Agarwal, Vikas & Ruenzi, Stefan & Weigert, Florian, 2017. "Tail risk in hedge funds: A unique view from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 125(3), pages 610-636.
    9. Morck, Randall & Shleifer, Andrei & Vishny, Robert W., 1988. "Management ownership and market valuation," Scholarly Articles 29407535, Harvard University Department of Economics.
    10. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    11. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    12. Chung, Kee H. & Zhang, Hao, 2014. "A simple approximation of intraday spreads using daily data," Journal of Financial Markets, Elsevier, vol. 17(C), pages 94-120.
    13. Garel, Alexandre & Martin-Flores, Jose M. & Petit-Romec, Arthur & Scott, Ayesha, 2021. "Institutional investor distraction and earnings management," Journal of Corporate Finance, Elsevier, vol. 66(C).
    14. Griffith, Todd G. & Roseman, Brian S., 2019. "Making cents of tick sizes: The effect of the 2016 U.S. SEC tick size pilot on limit order book liquidity," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 104-121.
    15. Boone, Audra L. & White, Joshua T., 2015. "The effect of institutional ownership on firm transparency and information production," Journal of Financial Economics, Elsevier, vol. 117(3), pages 508-533.
    16. Ghaly, Mohamed & Dang, Viet Anh & Stathopoulos, Konstantinos, 2020. "Institutional investors' horizons and corporate employment decisions," Journal of Corporate Finance, Elsevier, vol. 64(C).
    17. Clifford, Christopher P. & Lindsey, Laura, 2016. "Blockholder Heterogeneity, CEO Compensation, and Firm Performance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(5), pages 1491-1520, October.
    18. Rajan, Raghuram G, 1992. "Insiders and Outsiders: The Choice between Informed and Arm's-Length Debt," Journal of Finance, American Finance Association, vol. 47(4), pages 1367-1400, September.
    19. 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.
    20. Vikas Agarwal & Wei Jiang & Yuehua Tang & Baozhong Yang, 2013. "Uncovering Hedge Fund Skill from the Portfolio Holdings They Hide," Journal of Finance, American Finance Association, vol. 68(2), pages 739-783, April.
    21. 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.
    22. Khedmati, Mehdi & Sualihu, Mohammed Aminu & Yawson, Alfred, 2020. "CEO-director ties and labor investment efficiency," Journal of Corporate Finance, Elsevier, vol. 65(C).
    23. Pierre Collin-Dufresne & Vyacheslav Fos, 2015. "Do Prices Reveal the Presence of Informed Trading?," Journal of Finance, American Finance Association, vol. 70(4), pages 1555-1582, August.
    24. Michael Goldstein & Jonathan Brogaard & Terrence Hendershott & Stefan Hunt & Carla Ysusi, 2014. "High-Frequency Trading and the Execution Costs of Institutional Investors," The Financial Review, Eastern Finance Association, vol. 49(2), pages 345-369, May.
    25. Brian J. Bushee, 2001. "Do Institutional Investors Prefer Near†Term Earnings over Long†Run Value?," Contemporary Accounting Research, John Wiley & Sons, vol. 18(2), pages 207-246, June.
    26. 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.
    27. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    28. 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.
    29. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    30. Matteo Aquilina & Eric Budish, 2020. "Quantifying the High-Frequency Trading “Arms Race†: A Simple New Methodology and Estimates," Working Papers 2020-86, Becker Friedman Institute for Research In Economics.
    31. 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.
    32. Boochun Jung & Woo†Jong Lee & David P. Weber, 2014. "Financial Reporting Quality and Labor Investment Efficiency," Contemporary Accounting Research, John Wiley & Sons, vol. 31(4), pages 1047-1076, December.
    33. Chung, Kee H. & Lee, Albert J. & Rösch, Dominik, 2020. "Tick size, liquidity for small and large orders, and price informativeness: Evidence from the Tick Size Pilot Program," Journal of Financial Economics, Elsevier, vol. 136(3), pages 879-899.
    34. Vikas Agarwal & Vyacheslav Fos & Wei Jiang, 2013. "Inferring Reporting-Related Biases in Hedge Fund Databases from Hedge Fund Equity Holdings," Management Science, INFORMS, vol. 59(6), pages 1271-1289, June.
    35. Ernst Maug, 1998. "Large Shareholders as Monitors: Is There a Trade-Off between Liquidity and Control?," Journal of Finance, American Finance Association, vol. 53(1), pages 65-98, February.
    36. Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    37. Chen, Marie & Garriott, Corey, 2020. "High-frequency trading and institutional trading costs," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 74-93.
    38. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows [Arbitraging arbitrageurs]," Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1484-1533.
    39. Pierre Collin-Dufresne & Vyacheslav Fos, 2013. "Do Prices Reveal the Presence of Informed Trading?," Swiss Finance Institute Research Paper Series 13-69, Swiss Finance Institute, revised Sep 2015.
    40. repec:oup:rfinst:v:21:y:2017:i:4:p:1355-1401. is not listed on IDEAS
    41. Holderness, Clifford G., 2016. "Problems Using Aggregate Data to Infer Individual Behavior: Evidence from Law, Finance, and Ownership Concentration," Critical Finance Review, now publishers, vol. 5(1), pages 1-40, May.
    42. Robert A Korajczyk & Dermot Murphy, 2019. "High-Frequency Market Making to Large Institutional Trades," Review of Financial Studies, Society for Financial Studies, vol. 32(3), pages 1034-1067.
    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. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    2. Kemme, David M. & McInish, Thomas H. & Zhang, Jiang, 2022. "Market fairness and efficiency: Evidence from the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 134(C).
    3. Corey Garriot & Ryan Riordan, 2020. "Trading on Long-term Information," Staff Working Papers 20-20, Bank of Canada.
    4. Cox, Justin & Woods, Donovan, 2023. "COVID-19 and market structure dynamics," Journal of Banking & Finance, Elsevier, vol. 147(C).
    5. 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.
    6. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2018. "Do liquidity proxies measure liquidity accurately in ETFs?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 94-111.
    7. 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).
    8. Hatch, Brian C. & Johnson, Shane A. & Wang, Qin Emma & Zhang, Jun, 2021. "Algorithmic trading and firm value," Journal of Banking & Finance, Elsevier, vol. 125(C).
    9. Dasgupta, Amil & Fos, Vyacheslav & Sautner, Zacharias, 2021. "Institutional investors and corporate governance," LSE Research Online Documents on Economics 112114, London School of Economics and Political Science, LSE Library.
    10. Chen, Jiayuan & Gong, Di & Muckley, Cal, 2020. "Stock market illiquidity, bargaining power and the cost of borrowing," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 181-206.
    11. 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.
    12. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    13. Ee, Mong Shan & Hasan, Iftekhar & Huang, He, 2022. "Stock liquidity and corporate labor investment11We are grateful to the editor (Heitor Almeida) and an anynmous reviewer for detailed and significant guidance and suggestions. We thank Huu Duong, Alvin," Journal of Corporate Finance, Elsevier, vol. 72(C).
    14. 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).
    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. Tripathi, Abhinava & Dixit, Alok & Vipul,, 2021. "Information content of order imbalance in an order-driven market: Indian Evidence," Finance Research Letters, Elsevier, vol. 41(C).
    17. 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).
    18. Shang, Chenguang, 2020. "Trade credit and stock liquidity," Journal of Corporate Finance, Elsevier, vol. 62(C).
    19. Eaton, Gregory W. & Irvine, Paul J. & Liu, Tingting, 2021. "Measuring institutional trading costs and the implications for finance research: The case of tick size reductions," Journal of Financial Economics, Elsevier, vol. 139(3), pages 832-851.
    20. 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.

    More about this item

    Keywords

    Blockholder; Algorithmic trading; Ownership composition; Informed trading; Information incentive;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

    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:bracre:v:55:y:2023:i:4:s0890838922000828. 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: https://www.journals.elsevier.com/the-british-accounting-review .

    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.