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Liquidity Cycles and Make/Take Fees in Electronic Markets

Authors

  • THIERRY FOUCAULT,

  • OHAD KADAN,

  • EUGENE KANDEL

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    • Foucault is from HEC, Paris; Kadan is from the Olin Business School at Washington University in St. Louis; and Kandel is from the Hebrew University. We are grateful to an anonymous referee, an anonymous Associate Editor, and to Campbell Harvey (the Editor) for very helpful comments and suggestions. We also thank Torben Andersen, Hank Bessembinder, Bruno Biais, Lawrence Glosten, Jeff Harris, Lawrence Harris, Pete Kyle, Terrence Hendershott, Olivier Ledoit, Ernst Maug, Albert Menkveld, Erwan Morellec, Marios Panayides, Sébastien Pouget, Michel Robe, Jean-Charles Rochet, Ioanid Rosu, Gideon Saar, Elu Von Thadden, and participants at the 2009 Western Finance Association Meeting, the 2009 European Finance Association Meeting, the NYSE-Euronext Amsterdam-Tinbergen Institute workshop on volatility and liquidity, the Fédération des Banques Françaises-Institut d'Economie Industrielle conference on investment banking and financial markets in Toulouse, the CREATES symposium on market microstructure, and the Warwick Business School conference on high frequency econometrics, as well as seminar participants at Boston University, University of Calgary, the U.S. Commodity Futures Trading Commission, Humboldt University, Ecole Polytechnique Fédérale de Lausanne, University of Mannheim, University of Toronto, and University College in Dublin for their useful comments. The usual disclaimer applies.


ABSTRACT

We develop a model in which the speed of reaction to trading opportunities is endogenous. Traders face a trade-off between the benefit of being first to seize a profit opportunity and the cost of attention required to be first to seize this opportunity. The model provides an explanation for maker/taker pricing, and has implications for the effects of algorithmic trading on liquidity, volume, and welfare. Liquidity suppliers’ and liquidity demanders’ trading intensities reinforce each other, highlighting a new form of liquidity externalities. Data on durations between trades and quotes could be used to identify these externalities.

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