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When Market Illiquidity Generates Volumes

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  • Serge Darolles

    ()
    (DRM - Dauphine Recherches en Management - CNRS : UMR7088 - Université Paris IX - Paris Dauphine)

  • Gaëlle Le Fol

    ()
    (DRM - Dauphine Recherches en Management - CNRS : UMR7088 - Université Paris IX - Paris Dauphine)

  • Gulten Mero

    (CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique, CREM - Centre de Recherche en Economie et Management - CNRS : UMR6211 - Université de Rennes 1 - Université de Caen)

Abstract

We develop a model of the daily return-volume relationship which incorporates information and liquidity shocks. First, we distinguish between two trading strategies, information-based and liquidity-based trading and suggest that their respective impacts on returns and volume should be modeled differently. Second, we integrate the microstructure setting of Grossman-Miller (1988) with the information flow perspective of Tauchen-Pitts (1983) and derive a modified MDH model with two latent factors related to information and liquidity. Our model explains how the liquidity frictions can increase the daily traded volume, in the presence of liquidity arbitragers. Finally, we propose a stock-specific liquidity measure using daily return and volume observations of FTSE100 stocks.

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Bibliographic Info

Paper provided by HAL in its series Working Papers with number halshs-00536046.

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Date of creation: 2010
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Handle: RePEc:hal:wpaper:halshs-00536046

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Related research

Keywords: Volatility-volume relationship; mixture of distribution hypothesis; liquidity shocks; informed trading; liquidity arbitrage;

References

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  1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  2. Jedrzej Białkowski & Serge Darolles & Gaëlle Le Fol, 2006. "Improving VWAP strategies: A dynamical volume approach," Documents de recherche 06-08, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
  3. Viral V. Acharya & Lasse Heje Pedersen, 2004. "Asset Pricing with Liquidity Risk," NBER Working Papers 10814, National Bureau of Economic Research, Inc.
  4. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-60, April.
  5. Lawrence R. Glosten & Paul R. Milgrom, 1983. "Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders," Discussion Papers 570, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  6. Richardson, Matthew & Smith, Tom, 1994. "A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(01), pages 101-116, March.
  7. Grossman, Sanford J & Miller, Merton H, 1988. " Liquidity and Market Structure," Journal of Finance, American Finance Association, vol. 43(3), pages 617-37, July.
  8. Vladimir Borgy & Julien Idier & Gaëlle Le Fol, 2010. "Liquidity Problems in the FX Liquid Market," Working Papers halshs-00539985, HAL.
  9. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
  10. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
  11. Diamond, Douglas W. & Verrecchia, Robert E., 1987. "Constraints on short-selling and asset price adjustment to private information," Journal of Financial Economics, Elsevier, vol. 18(2), pages 277-311, June.
  12. Harris, Lawrence, 1986. "Cross-Security Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(01), pages 39-46, March.
  13. Copeland, Thomas E., 1977. "A Probability Model of Asset Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(04), pages 563-578, November.
  14. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
  15. Foster, F Douglas & Viswanathan, S, 1993. " Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models," Journal of Finance, American Finance Association, vol. 48(1), pages 187-211, March.
  16. Tarun Chordia, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, 04.
  17. Domowitz, Ian & Wang, Jianxin, 1994. "Auctions as algorithms : Computerized trade execution and price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 29-60, January.
  18. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-64, December.
  19. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-21, March.
  20. Datar, Vinay T. & Y. Naik, Narayan & Radcliffe, Robert, 1998. "Liquidity and stock returns: An alternative test," Journal of Financial Markets, Elsevier, vol. 1(2), pages 203-219, August.
  21. Easley, David, et al, 1996. " Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-36, September.
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