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Algorithmic trading and market quality: International evidence of the impact of errors in colocation dates

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  • Aitken, Michael
  • Cumming, Douglas
  • Zhan, Feng

Abstract

This paper examines evidence on colocation dates and their impact on market efficiency. International colocation dates can be sourced from a number of avenues including: [1] an 'exchange's news announcements and reports, [2] news media, and [3] by direct communication with the officers of an exchange. Boehmer et al. (2021) report colocation dates based on [1] and [2] and do not reference prior work that reports colocation dates that are primarily sourced from [3]. The consequence is that the discrepancies between prior studies and Boehmer et al. (2021) are significant and economically meaningful: the errors average 12.75 months with the largest being 46 months. This paper documents these discrepancies and provides evidence of how these differences in colocation dates matter for evidence of their impact on market efficiency.

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  • Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2023. "Algorithmic trading and market quality: International evidence of the impact of errors in colocation dates," Journal of Banking & Finance, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:jbfina:v:151:y:2023:i:c:s0378426623000687
    DOI: 10.1016/j.jbankfin.2023.106843
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    References listed on IDEAS

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    1. Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2015. "High frequency trading and end-of-day price dislocation," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 330-349.
    2. Cumming, Douglas & Johan, Sofia, 2019. "Capital-market effects of securities regulation: Prior conditions, implementation, and enforcement revisited," Finance Research Letters, Elsevier, vol. 31(C).
    3. Franklin Allen & Xian Gu & Julapa Jagtiani, 2021. "A Survey of Fintech Research and Policy Discussion," Review of Corporate Finance, now publishers, vol. 1(3-4), pages 259-339, July.
    4. Cumming, Douglas & Johan, Sofia & Li, Dan, 2011. "Exchange trading rules and stock market liquidity," Journal of Financial Economics, Elsevier, vol. 99(3), pages 651-671, March.
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    Cited by:

    1. Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    High frequency trading; Algorithmic trading; Colocation;
    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
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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