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Market efficiency and the long-memory of supply and demand: Is price impact variable and permanent or fixed and temporary?

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  • J. Doyne Farmer
  • Austin Gerig
  • Fabrizio Lillo
  • Szabolcs Mike

Abstract

In this comment we discuss the problem of reconciling the linear efficiency of price returns with the long-memory of supply and demand. We present new evidence that shows that efficiency is maintained by a liquidity imbalance that co-moves with the imbalance of buyer vs. seller initiated transactions. For example, during a period where there is an excess of buyer initiated transactions, there is also more liquidity for buy orders than sell orders, so that buy orders generate smaller and less frequent price responses than sell orders. At the moment a buy order is placed the transaction sign imbalance tends to dominate, generating a price impact. However, the liquidity imbalance rapidly increases with time, so that after a small number of time steps it cancels all the inefficiency caused by the transaction sign imbalance, bounding the price impact. While the view presented by Bouchaud et al. of a fixed and temporary bare price impact is self-consistent and formally correct, we argue that viewing this in terms of a variable but permanent price impact provides a simpler and more natural view. This is in the spirit of the original conjecture of Lillo and Farmer, but generalized to allow for finite time lags in the build up of the liquidity imbalance after a transaction. We discuss the possible strategic motivations that give rise to the liquidity imbalance and offer an alternative hypothesis. We also present some results that call into question the statistical significance of large swings in expected price impact at long times.

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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number physics/0602015.

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Date of creation: Feb 2006
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Handle: RePEc:arx:papers:physics/0602015

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  1. Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters, 2004. "Random walks, liquidity molasses and critical response in financial markets," Science & Finance (CFM) working paper archive 500063, Science & Finance, Capital Fund Management.
  2. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2003. "Fluctuations and response in financial markets: the subtle nature of `random' price changes," Science & Finance (CFM) working paper archive 0307332, Science & Finance, Capital Fund Management.
  3. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
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Cited by:
  1. J. Doyne Farmer & John Geanakoplos, 2008. "The Virtues and Vices of Equilibrium and the Future of Financial Economics," Levine's Working Paper Archive 122247000000002067, David K. Levine.
  2. Solomon Sorin & Golo Natasa, 2013. "Minsky Financial Instability, Interscale Feedback, Percolation and Marshall–Walras Disequilibrium," Accounting, Economics, and Law, De Gruyter, vol. 3(3), pages 167-260, October.
  3. Frédéric Abergel & Aymen Jedidi, 2013. "A Mathematical Approach to Order Book Modelling," Post-Print hal-00621253, HAL.
  4. Khalil al Dayri & Emmanuel Bacry & Jean-Francois Muzy, 2010. "The nature of price returns during periods of high market activity," Papers 1010.4226, arXiv.org, revised Oct 2010.
  5. Jasmina Hasanhodzic & Andrew Lo & Emanuele Viola, 2011. "A computational view of market efficiency," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1043-1050.
  6. B. T�th & Z. Eisler & F. Lillo & J. Kockelkoren & J.-P. Bouchaud & J.D. Farmer, 2012. "How does the market react to your order flow?," Quantitative Finance, Taylor & Francis Journals, vol. 12(7), pages 1015-1024, May.
  7. Jean-Philippe Bouchaud, 2011. "Panel Statement: The endogenous dynamics of markets: price impact and feedback loops," Chapters, European Central Bank.
  8. Wang, Yougui & Stanley, H.E., 2009. "Statistical approach to partial equilibrium analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1173-1180.
  9. Damian Eduardo Taranto & Giacomo Bormetti & Fabrizio Lillo, 2014. "The adaptive nature of liquidity taking in limit order books," Papers 1403.0842, arXiv.org, revised Apr 2014.
  10. Szabolcs Mike & J. Doyne Farmer, 2007. "An empirical behavioral model of liquidity and volatility," Papers 0709.0159, arXiv.org.

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