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Market-making with Search and Information Frictions

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  • Benjamin Lester
  • Ali Shourideh
  • Venky Venkateswaran
  • Ariel Zetlin-Jones

Abstract

We develop a dynamic model of trading through market-makers that incorporates two canonical sources of illiquidity: trading (or search) frictions, which imply that market-makers have some amount of market power; and information frictions, which imply that market-makers face some degree of adverse selection. We use this model to study the effects of various technological innovations and regulatory initiatives that have reduced trading frictions in over-the-counter markets. Our main result is that reducing trading frictions can lead to less liquidity, as measured by bid-ask spreads. The key insight is that more frequent trading—or more competition among dealers—makes traders’ behavior less dependent on asset quality. As a result, dealers learn about asset quality more slowly and set wider bid-ask spreads to compensate for this increase in uncertainty.
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Suggested Citation

  • Benjamin Lester & Ali Shourideh & Venky Venkateswaran & Ariel Zetlin-Jones, 2018. "Market-making with Search and Information Frictions," Working Papers 18-11, New York University, Leonard N. Stern School of Business, Department of Economics.
    • Handle: RePEc:ste:nystbu:18-11
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    Cited by:

    1. Asriyan, Vladimir & Fuchs, William & Green, Brett, 2021. "Aggregation and design of information in asset markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 191(C).
    2. Marzena Rostek & Ji Hee Yoon, 2021. "Exchange Design and Efficiency," Econometrica, Econometric Society, vol. 89(6), pages 2887-2928, November.
    3. Zachary Bethune & Bruno Sultanum & Nicholas Trachter, 2022. "An Information-based Theory of Financial Intermediation [Trade Dynamics in the Market for Federal Funds]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(5), pages 2381-2444.
    4. Lester, Benjamin & Shourideh, Ali & Venkateswaran, Venky & Zetlin-Jones, Ariel, 2023. "Market-making with search and information frictions," Journal of Economic Theory, Elsevier, vol. 212(C).
    5. Gábor Pintér & Chaojun Wang & Junyuan Zou, 2021. "Size Discount and Size Penalty Trading Costs in Bond Markets," Discussion Papers 2114, Centre for Macroeconomics (CFM).
    6. Pintér, Gábor & Wang, Chaojun & Zou, Junyuan, 2022. "Information chasing versus adverse selection," Bank of England working papers 971, Bank of England.
    7. Pierre-Olivier Weill, 2020. "The search theory of OTC markets," NBER Working Papers 27354, National Bureau of Economic Research, Inc.
    8. Geromichalos, Athanasios & Jung, Kuk Mo & Lee, Seungduck & Carlos, Dillon, 2021. "A model of endogenous direct and indirect asset liquidity," European Economic Review, Elsevier, vol. 132(C).

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    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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