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Comparing the market microstructure between two South African exchanges

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  • Ivan Jericevich
  • Patrick Chang
  • Tim Gebbie

Abstract

We consider shared listings on two South African equity exchanges: the Johannesburg Stock Exchange (JSE) and the A2X Exchange. A2X is an alternative exchange that provides for both shared listings and new listings within the financial market ecosystem of South Africa. From a science perspective it provides the opportunity to compare markets trading similar shares, in a similar regulatory and economic environment, but with vastly different liquidity, costs and business models. A2X currently has competitive settlement and transaction pricing when compared to the JSE, but the JSE has deeper liquidity. In pursuit of an empirical understanding of how these differences relate to their respective price response dynamics, we compare the distributions and auto-correlations of returns on different time scales; we compare price impact and master curves; and we compare the cost of trading on each exchange. This allows us to empirically compare the two markets. We find that various stylised facts become similar as the measurement or sampling time scale increase. However, the same securities can have vastly different price responses irrespective of time scales. This is not surprising given the different liquidity and order-book resilience. Here we demonstrate that direct costs dominate the cost of trading, and the importance of competitively positioning cost ceilings. Universality is crucial for being able to meaningfully compare cross-exchange price responses, but in the case of A2X, it has yet to emerge in a meaningful way due to the infancy of the exchange -- making meaningful comparisons difficult.

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  • Ivan Jericevich & Patrick Chang & Tim Gebbie, 2020. "Comparing the market microstructure between two South African exchanges," Papers 2011.04367, arXiv.org.
    • Handle: RePEc:arx:papers:2011.04367
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    References listed on IDEAS

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    Cited by:

    1. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
    2. Ivan Jericevich & Dharmesh Sing & Tim Gebbie, 2021. "CoinTossX: An open-source low-latency high-throughput matching engine," Papers 2102.10925, arXiv.org.
    3. Matthew Dicks & Andrew Paskaramoorthy & Tim Gebbie, 2023. "Many learning agents interacting with an agent-based market model," Papers 2303.07393, arXiv.org, revised Nov 2023.

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