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Determinants of liquidity and execution probability in exchange operated dark pool: Evidence from the Australian Securities Exchange

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  • He, William Peng
  • Lepone, Andrew

Abstract

This study investigates the determinants of liquidity and execution probability in an exchange operated dark pool. We analyse a unique set of data collated from the Australian Securities Exchange (ASX) that allows the identification of trades and orders in its Centre Point dark pool. This study contributes to the understanding of factors that influence traders' preference to transact through an exchange operated dark pool and the execution probability of dark orders. We also examine the impact of Centre Point dark pool trading on market quality. The results show that the level of trading activity in the dark pool is higher for larger stocks with lower prices. Dark pool's share of total volume is higher when quoted spreads are wider, best depth is thicker, and when order imbalance, volatility and adverse selection are lower in the central limit order book. Execution probability of Centre Point orders increases when dark pool trading is most active and when average Centre Point order size is greater. We find no evidence of Centre Point trading being detrimental to market quality in our sample.

Suggested Citation

  • He, William Peng & Lepone, Andrew, 2014. "Determinants of liquidity and execution probability in exchange operated dark pool: Evidence from the Australian Securities Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 1-16.
    • Handle: RePEc:eee:pacfin:v:30:y:2014:i:c:p:1-16
    DOI: 10.1016/j.pacfin.2014.07.004
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    Cited by:

    1. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2017. "Research in finance: A review of influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 188-199.
    2. Duong, Huu Nhan & Kalev, Petko S. & Tian, Xiao Jason, 2022. "Does the bid–ask spread affect trading in exchange operated dark pools? Evidence from a natural experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    3. Bayona, Anna & Dumitrescu, Ariadna & Manzano, Carolina, 2023. "Information and optimal trading strategies with dark pools," Economic Modelling, Elsevier, vol. 126(C).
    4. Linlin Ye, 2016. "Understanding the Impacts of Dark Pools on Price Discovery," Papers 1612.08486, arXiv.org.
    5. Smales, Lee A., 2016. "Order aggressiveness of different broker-types in response to monetary policy news," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 367-383.
    6. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    7. He, Peng William & Jarnecic, Elvis & Liu, Yubo, 2015. "The determinants of alternative trading venue market share: Global evidence from the introduction of Chi-X," Journal of Financial Markets, Elsevier, vol. 22(C), pages 27-49.
    8. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2016. "Emerging trends in Asia-Pacific finance research: A review of recent influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 66-76.
    9. Millicent Chang & Andrew B. Jackson & Marvin Wee, 2018. "A review of research on regulation changes in the Asia‐Pacific region," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 635-667, September.

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    More about this item

    Keywords

    Dark pool; Market microstructure; Centre Point; Execution probability; Market quality;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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