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Trading and liquidity with limited cognition

Author

Listed:
  • Johan Hombert

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Bruno Biais

    (CRM - Centre de Recherche en Management - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - IAE - Institut d'Administration des Entreprises - Toulouse - CNRS - Centre National de la Recherche Scientifique)

  • Pierre-Olivier Weill

    (UCLA - University of California [Los Angeles] - UC - University of California, NBER - The National Bureau of Economic Research)

Abstract
We study the reaction of financial markets to aggregate liquidity shocks when traders face cognition limits. While each financial institution recovers from the shock at a random time, the trader representing the institution observes this recovery with a delay, reecting the time it takes to collect and process information about positions, counterparties and risk exposure. Cognition limits lengthen the recovery process. They also imply that traders who find their institution has not yet recovered from the shock place market sell orders, and then progressively buy back at relatively low prices, while simultaneously placing limit orders to sell later when the price will have recovered. This generates round trip trades, which raise trading volume. We compare the case where algorithms enable traders to implement this strategy to that where traders can only place orders when they have completed their information processing task.

Suggested Citation

  • Johan Hombert & Bruno Biais & Pierre-Olivier Weill, 2012. "Trading and liquidity with limited cognition," Working Papers hal-00760759, HAL.
    • Handle: RePEc:hal:wpaper:hal-00760759
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Stefan Gissler, 2015. "Slow capital, fast prices: Shocks to funding liquidity and stock price reversals," Finance and Economics Discussion Series 2015-43, Board of Governors of the Federal Reserve System (U.S.).
    2. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    3. Vayanos, Dimitri & Wang, Jiang, 2012. "Market liquidity - theory and empirical evidence," LSE Research Online Documents on Economics 119044, London School of Economics and Political Science, LSE Library.
    4. Guillaume Rocheteau & Pierre-Olivier Weill, 2011. "Liquidity in Frictional Asset Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 261-282, October.
    5. George Jiang & Ingrid Lo & Giorgio Valente, 2014. "High-Frequency Trading around Macroeconomic News Announcements: Evidence from the U.S. Treasury Market," Staff Working Papers 14-56, Bank of Canada.
    6. Gissler, Stefan, 2017. "Lockstep in liquidity: Common dealers and co-movement in bond liquidity," Journal of Financial Markets, Elsevier, vol. 33(C), pages 1-21.
    7. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    8. Sarah Draus & Mark van Achter, 2012. "Circuit Breakers and Market Runs," CSEF Working Papers 313, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.

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    More about this item

    Keywords

    liquidity; limited cognition; Trading;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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