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Taking orders and taking notes: dealer information sharing in financial markets

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Abstract

The use of order flow information by financial firms has come to the forefront of the regulatory debate. Central to this discussion is whether a dealer who acquires information by taking client orders can 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 counterfactuals. 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 the model?s key features.

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  • Nina Boyarchenko & David O. Lucca & Laura Veldkamp, 2015. "Taking orders and taking notes: dealer information sharing in financial markets," Staff Reports 726, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:726
    Note: Title formerly: Intermediaries as information aggregators: an application to U.S. treasury auctions
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    Cited by:

    1. Sigaux, Jean-David, 2018. "Trading ahead of treasury auctions," Working Paper Series 2208, European Central Bank.
    2. Hashimoto, Tadashi, 2018. "The generalized random priority mechanism with budgets," Journal of Economic Theory, Elsevier, vol. 177(C), pages 708-733.
    3. 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.
    4. 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.
    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. 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

    Keywords

    Treasury auctions; primary dealers; financial intermediation; information aggregation;
    All these keywords.

    JEL classification:

    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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