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Taking Orders and Taking Notes: Dealer Information Sharing in Treasury Markets

Author

Listed:
  • Laura Veldkamp

    (New York University)

  • David Lucca

    (Federal Reserve Bank of New York)

  • Nina Boyarchenko

    (Federal Reserve Bank of New York)

Abstract

The use of order flow information by financial firms has come to the forefront of the regulatory debate. A central question is: Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients and issuer revenues in U.S. Treasury auctions. Because one cannot observe alternative information regimes, we build a model, calibrate it to auction results data, and use it to quantify counter-factuals. We estimate that yearly auction revenues with full-information sharing (with clients and between dealers) would be $5 billion higher than in a ``Chinese Wall'' regime in which no information is shared. When information sharing enables collusion, the collusion costs revenue, but prohibiting information sharing costs more. For investors, the welfare effects of information sharing depend on how information is shared. Surprisingly, investors benefit when dealers share information with each other, not when they share more with clients. For the market, when investors can bid directly, information sharing creates a new financial accelerator: Only investors with bad news bid through intermediaries, who then share that information with others. Thus, sharing amplifies the effect of negative news. Tests of two model predictions support its key features.

Suggested Citation

  • Laura Veldkamp & David Lucca & Nina Boyarchenko, 2017. "Taking Orders and Taking Notes: Dealer Information Sharing in Treasury Markets," 2017 Meeting Papers 808, Society for Economic Dynamics.
  • Handle: RePEc:red:sed017:808
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    References listed on IDEAS

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    Cited by:

    1. Babus, Ana & Parlatore, Cecilia, 2022. "Strategic fragmented markets," Journal of Financial Economics, Elsevier, vol. 145(3), pages 876-908.
    2. Sigaux, Jean-David, 2018. "Trading ahead of treasury auctions," Working Paper Series 2208, European Central Bank.
    3. Marco Di Maggio & Francesco Franzoni & Amir Kermani & Carlo Sommavilla, 2017. "The Relevance of Broker Networks for Information Diffusion in the Stock Market," NBER Working Papers 23522, National Bureau of Economic Research, Inc.
    4. Beetsma, Roel & Giuliodori, Massimo & Hanson, Jesper & de Jong, Frank, 2018. "Bid-to-cover and yield changes around public debt auctions in the euro area," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 118-134.
    5. Ali Hortaçsu & Jakub Kastl & Allen Zhang, 2018. "Bid Shading and Bidder Surplus in the US Treasury Auction System," American Economic Review, American Economic Association, vol. 108(1), pages 147-169, January.
    6. Lou, Youcheng & Parsa, Sahar & Ray, Debraj & Li, Duan & Wang, Shouyang, 2019. "Information aggregation in a financial market with general signal structure," Journal of Economic Theory, Elsevier, vol. 183(C), pages 594-624.
    7. Beetsma, Roel & Giuliodori, Massimo & Hanson, Jesper & de Jong, Frank, 2020. "Determinants of the bid-to-cover ratio in Eurozone sovereign debt auctions," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 96-120.
    8. Glode, Vincent & Opp, Christian C. & Zhang, Xingtan, 2018. "Voluntary disclosure in bilateral transactions," Journal of Economic Theory, Elsevier, vol. 175(C), pages 652-688.

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    More about this item

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • G1 - Financial Economics - - General Financial Markets
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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