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Price and Size Discovery in Financial Markets: Evidence from the U.S. Treasury Securities Market

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  • Michael J Fleming
  • Giang Nguyen

Abstract

We study the workup protocol, an important size discovery mechanism in the U.S. Treasury market. We find that workup order flow shocks explain 6%–8% of the variation of returns on benchmark notes and, across maturities, 10% of the variation of the yield curve level factor. Information related to proprietary client order flow is more likely to show up in workup trades, whereas information derived from public announcements tends to come through preworkup trades. Our findings highlight how the nature of information affects the trade-off between speed and execution price when informed traders choose between the lit and workup channels.Received May 3, 2017; Editorial decision August 1, 2018 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online. Internet Appendix tables are numbered with “IA” prefix.

Suggested Citation

  • Michael J Fleming & Giang Nguyen, 2019. "Price and Size Discovery in Financial Markets: Evidence from the U.S. Treasury Securities Market," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 9(2), pages 256-295.
  • Handle: RePEc:oup:rasset:v:9:y:2019:i:2:p:256-295.
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    Cited by:

    1. Adrian, Tobias & Capponi, Agostino & Fleming, Michael & Vogt, Erik & Zhang, Hongzhong, 2020. "Intraday market making with overnight inventory costs," Journal of Financial Markets, Elsevier, vol. 50(C).
    2. Pierre Collin‐Dufresne & Benjamin Junge & Anders B. Trolle, 2020. "Market Structure and Transaction Costs of Index CDSs," Journal of Finance, American Finance Association, vol. 75(5), pages 2719-2763, October.
    3. Han, Seung-Oh & Huh, Sahn-Wook & Park, Jeayoung, 2023. "Detecting jumps amidst prevalent zero returns: Evidence from the U.S. Treasury securities," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 276-307.
    4. 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.
    5. Corey Garriott & Adrian Walton, 2016. "Retail Order Flow Segmentation," Staff Working Papers 16-20, Bank of Canada.
    6. Papavassiliou, Vassilios G. & Kinateder, Harald, 2021. "Information shares and market quality before and during the European sovereign debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    7. Indriawan, Ivan & Jiao, Feng & Tse, Yiuman, 2021. "The FOMC announcement returns on long-term US and German bond futures," Journal of Banking & Finance, Elsevier, vol. 123(C).

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    More about this item

    Keywords

    G01; G12; G14; G18;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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