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Trade size clustering and the cost of trading at the London Stock Exchange

Author

Listed:
  • Verousis, Thanos
  • ap Gwilym, Owain
Abstract
For the London Stock Exchange, this paper investigates differences in trading costs between market maker (off-book) and order book trades, in the context of clustering in trade sizes and prices. We report several substantial findings. Even after controlling for differences in trade size, the realised spread measure is lower for off-book trades. For the order book, trade size clustering is not associated with differences in transaction costs nor with differences in the information content of trades. For the off-book market, trades in clustered (popular) sizes carry significantly more information than non-clustered trades. Despite the significant differences in the price impact estimates between the order book and off-book, we show that traders placing large orders off-book are still better off than trading via the order book as they benefit from a large discount from the current midpoint price. Additionally, we highlight that price and size clustering tend to occur simultaneously rather than being substitutes in this market setting.

Suggested Citation

  • Verousis, Thanos & ap Gwilym, Owain, 2013. "Trade size clustering and the cost of trading at the London Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 91-102.
    • Handle: RePEc:eee:finana:v:27:y:2013:i:c:p:91-102
    DOI: 10.1016/j.irfa.2012.08.007
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    References listed on IDEAS

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    Cited by:

    1. Fernando Palao & Ángel Pardo Tornero, 2012. "When size matters: Clustering in the European Carbon Market," Working Papers. Serie EC 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Han, SeungOh, 2024. "Price clustering on cryptocurrency order books at a US-based exchange," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    3. Palao, Fernando & Pardo, Ángel, 2014. "What makes carbon traders cluster their orders?," Energy Economics, Elsevier, vol. 43(C), pages 158-165.
    4. Lin William Cong & Xi Li & Ke Tang & Yang Yang, 2023. "Crypto Wash Trading," Management Science, INFORMS, vol. 69(11), pages 6427-6454, November.
    5. Narayan, Paresh Kumar & Smyth, Russell, 2013. "Has political instability contributed to price clustering on Fiji's stock market?," Journal of Asian Economics, Elsevier, vol. 28(C), pages 125-130.
    6. Donglian Ma & Hisashi Tanizaki, 2022. "Intraday patterns of price clustering in Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    7. Chen, Tao, 2019. "Trade-size clustering and price efficiency," Japan and the World Economy, Elsevier, vol. 49(C), pages 195-203.
    8. Mishra, Ajay Kumar & Tripathy, Trilochan, 2018. "Price and trade size clustering: Evidence from the national stock exchange of India," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 63-72.

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    More about this item

    Keywords

    Trade-size clustering; Transaction costs; Price impact; LSE;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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