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Colocation technology in the Australian equities market: assessing the impacts on market microstructure and efficiency

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posted on 2024-05-03, 05:23 authored by Imtiaz Bhayat

This study examines the influence of colocation services on microstructure and addresses knowledge gaps around its impact on the Australian equities market, particularly in terms of market efficiency and effectiveness. The research aims to contribute to the existing literature by providing a detailed analysis of colocation implementation and its effects on various efficiency measures and comparing the results to international studies. To the best of the author’s knowledge, no other study of this nature has occurred in an Australian context.  A review of previous studies identified eight themes relating to measures of market efficiency and effectiveness: encompassing trade volume, message numbers, bid-ask spreads, algo trade ratio, order-to-trade ratio, market quality, price discovery, and the influence of news and announcements. To better understand these themes, two events were proposed for analysis: the date of colocation and the impact of announcements.

The research methodology included a detailed study of the market prior to and post colocation to assess differences. Previous studies have considered the impact of colocation using end-of-day, end-of-month or yearly statistics, but these large time periods cannot provide insights into the impact of the faster speeds enabled by colocation. The analysis therefore utilised minute-by-minute trade and announcement data, one year prior and one year post colocation, to assess the market microstructure impacts more accurately in the context of a milli- and micro-second trading environment. The sample included events such as the date of colocation and details of price-sensitive and non-price-sensitive announcements. Additionally, robustness checks and difference-in-difference analysis were conducted to account for changing macroeconomic environments, a new regulatory regime and other confounding factors. 

Initial analysis revealed a noticeable shift in market microstructure following colocation. Announcement days, particularly those with price-sensitive announcements, were associated with increased market activity. The imposition of a message fee reduced orders and order changes on non-announcement days. Analysis of minute-by-minute pre- and post-colocation trends around announcements offered new insights into market behavior. Following colocation, volume traded, message numbers and algorithmic trading displayed unique patterns, with mixed results for market efficiency measures. 

More detailed analysis found improvements in market efficiency for specific measures, such as volumes traded, number of trades, and bid-ask spread. However, the number of messages, order-to-trade ratio and algo trade ratio showed mixed results, with the message fee potentially causing these discrepancies. The research indicated that the market generally became more efficient post-colocation, with faster trading, higher volumes and lower spreads. Post-colocation trade occurred soon after an announcement when the details of the announcement were known, while prior to colocation more trade occurred before an announcement. Returns also behaved differently post-colocation, with traders able to act and achieve desired results faster, contributing to market efficiency. 

Overall, the analysis revealed that colocation had a substantial impact on market microstructure and trading dynamics. The market became more efficient, with faster trading, higher volumes, lower spreads and a lower order-to-trade ratio. 

The findings offer valuable insights for trading participants in terms of market dynamics and the impact of colocation on market efficiency, enabling informed decision-making and optimisation of trading strategies. The mixed results observed in specific market efficiency measures highlight the need for effective regulatory policies and risk management, particularly during periods of increased market activity and price-sensitive announcements. These findings can help shape trading participants’ behaviour in a colocated environment by promoting informed decisions, effective risk management and advocacy for improved regulatory policies.


Table of Contents

Chapter 1 – Colocation In Australia and the Market Dynamics -- Chapter 2 – Literature Review -- Chapter 3 – Colocation Initial Findings -- Chapter 4 – Detailed Colocation Findings -- Chapter 5 – Robustness Checks and Controlling for Exogenous Factors -- Chapter 6 – Conclusion -- Bibliography

Awarding Institution

Macquarie University

Degree Type

Thesis PhD


Doctor of Philosophy

Department, Centre or School

Department of Applied Finance

Year of Award


Principal Supervisor

Andrew Lepone


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272 pages

Former Identifiers

AMIS ID: 306940

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