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

Michael Aitken, Douglas Cumming and Feng Zhan

Journal of Banking & Finance, 2023, vol. 151, issue C

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.

Keywords: High frequency trading; Algorithmic trading; Colocation (search for similar items in EconPapers)
JEL-codes: G12 G14 G18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:151:y:2023:i:c:s0378426623000687

DOI: 10.1016/j.jbankfin.2023.106843

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