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Time Pro‐rata Matching: Evidence of a Change in LIFFE STIR Futures

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  • Angelo Aspris
  • Sean Foley
  • Drew Harris
  • Peter O'Neill

Abstract

Matching algorithms are important for well‐functioning financial markets. This paper examines the 2007 change by LIFFE, to move from pure pro‐rata to time pro‐rata allocation for the Euribor, Short Sterling, and Euroswiss futures contracts. We show that the removal of pure pro‐rata matching reduces market depth but suggest that this outcome improves execution quality for market participants. Our results are consistent with suggestions in the literature that the former regime creates incentives for traders to “drown” the order book with large orders and that the addition of a time element to this algorithm alters their behavior. We provide evidence that traders increase the amount of order splitting in the new framework, consistent with local optimizing, but argue that this may hinder overall market efficiency. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 35:522–541, 2015

Suggested Citation

  • Angelo Aspris & Sean Foley & Drew Harris & Peter O'Neill, 2015. "Time Pro‐rata Matching: Evidence of a Change in LIFFE STIR Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(6), pages 522-541, June.
    • Handle: RePEc:wly:jfutmk:v:35:y:2015:i:6:p:522-541
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    Cited by:

    1. Vasilios Mavroudis, 2019. "Market Manipulation as a Security Problem," Papers 1903.12458, arXiv.org.
    2. Haynes, Richard & Onur, Esen, 2020. "Precedence rules in matching algorithms," Journal of Commodity Markets, Elsevier, vol. 19(C).
    3. Gil Hersch, 2023. "Procedural Fairness in Exchange Matching Systems," Journal of Business Ethics, Springer, vol. 188(2), pages 367-377, November.
    4. Khairul Zharif Zaharudin & Martin R. Young & Wei‐Huei Hsu, 2022. "High‐frequency trading: Definition, implications, and controversies," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 75-107, February.
    5. Foley, Sean & Krekel, William & Mollica, Vito & Svec, Jiri, 2023. "Not so fast: Identifying and remediating slow and imprecise cryptocurrency exchange data," Finance Research Letters, Elsevier, vol. 51(C).

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