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Equilibrium Fast Trading

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Author Info

  • Biais, Bruno

    ()

  • Foucault, Thierry

    ()

  • Moinas, Sophie

    ()

Abstract

High-speed market connections and information processing improve …nancial institutions'ability to seize trading opportunities, which raises gains from trade. They also enable fast traders to process information before slow traders, which generates adverse selection. We fi…rst analyze trading equilibria for a given level of investment in fast-trading technology and then endogenize this level. Investments can be strategic substitutes or complements. In the latter case, investment waves can arise, where institutions invest in fast-trading technologies just to keep up with the others. When some traders become fast, it increases adverse selection costs for all, i.e., it generates negative externalities. Therefore equilibrium investment can exceed its welfare-maximizing counterpart.

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Bibliographic Info

Paper provided by HEC Paris in its series Les Cahiers de Recherche with number 968.

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Length: 45 pages
Date of creation: 30 Oct 2013
Date of revision:
Handle: RePEc:ebg:heccah:0968

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Postal: HEC Paris, 78351 Jouy-en-Josas cedex, France
Web page: http://www.hec.fr/
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Keywords: high frequency trading; liquidity; welfare;

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References

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  1. Manzano, Carolina & Vives, Xavier, 2010. "Public and Private Learning from Prices, Strategic Substitutability and Complementarity, and Equilibrium Multiplicity," CEPR Discussion Papers, C.E.P.R. Discussion Papers 7949, C.E.P.R. Discussion Papers.
  2. Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2009. "Rise of the machines: algorithmic trading in the foreign exchange market," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.) 980, Board of Governors of the Federal Reserve System (U.S.).
  3. Vincent Glode & Richard C. Green & Richard Lowery, 2012. "Financial Expertise as an Arms Race," Journal of Finance, American Finance Association, American Finance Association, vol. 67(5), pages 1723-1759, October.
  4. Jayant Vivek Ganguli & Liyan Yang, 2009. "Complementarities, Multiplicity, and Supply Information," Journal of the European Economic Association, MIT Press, MIT Press, vol. 7(1), pages 90-115, 03.
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Cited by:
  1. Scholtus, Martin & van Dijk, Dick & Frijns, Bart, 2014. "Speed, algorithmic trading, and market quality around macroeconomic news announcements," Journal of Banking & Finance, Elsevier, Elsevier, vol. 38(C), pages 89-105.
  2. Jørgensen, Kjell & Skjeltorp, Johannes Atle & Ødegaard, Bernt Arne, 2014. "Throttling hyperactive robots - Message to trade ratios at the Oslo Stock Exchange," UiS Working Papers in Economics and Finance, University of Stavanger 2014/3, University of Stavanger.
  3. Austin Gerig & David Michayluk, 2014. "Automated Liquidity Provision," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 345, Quantitative Finance Research Centre, University of Technology, Sydney.
  4. Jonathan Brogaard & Corey Garriott & Anna Pomeranets, 2014. "High-Frequency Trading Competition," Working Papers, Bank of Canada 14-19, Bank of Canada.
  5. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, Elsevier, vol. 113(1), pages 156-169.
  6. Zhiguo He & Asaf Manela, 2012. "Information Acquisition in Rumor Based Bank Runs," NBER Working Papers 18513, National Bureau of Economic Research, Inc.
  7. Albert J. Menkveld & and, 2014. "Need for Speed? Exchange Latency and Liquidity," Tinbergen Institute Discussion Papers, Tinbergen Institute 14-097/IV, Tinbergen Institute.
  8. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, Elsevier, vol. 16(4), pages 741-770.

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