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Trading volume and Arbitrage

Author

Listed:
  • Gaëlle Le Fol

    () (DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique)

  • Serge Darolles

    () (DRM-Finance - DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique)

Abstract

Decomposing returns into market and stock specific components is common practice and forms the basis of popular asset pricing models. What about volume? Can volume be decomposed in the same way as returns? Lo and Wang (2000) suggest such a decomposition. Our paper contributes to this literature in two different ways. First, we provide a model to explain why volumes deviate from the benchmark. Our interpretation is in terms of arbitrage strategies and liquidity. Second, we propose a new efficient screening tool that allows practitioners to extract specific information from volume time series. We provide an empirical illustration of the relevance and the possible uses of our approach on daily data from the FTSE index from 2000 to 2002.

Suggested Citation

  • Gaëlle Le Fol & Serge Darolles, 2014. "Trading volume and Arbitrage," Post-Print halshs-01061280, HAL.
  • Handle: RePEc:hal:journl:halshs-01061280
    DOI: 10.5176/2010-4804_3.3.321
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01061280
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    References listed on IDEAS

    as
    1. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, Oxford University Press, vol. 108(4), pages 905-939.
    2. Andrew W. Lo & Jiang Wang, 2006. "Trading Volume: Implications of an Intertemporal Capital Asset Pricing Model," Journal of Finance, American Finance Association, vol. 61(6), pages 2805-2840, December.
    3. Foster, F Douglas & Viswanathan, S, 1990. "A Theory of the Interday Variations in Volume, Variance, and Trading Costs in Securities Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 593-624.
    4. Lakonishok, Josef & Smidt, Seymour, 1986. " Volume for Winners and Losers: Taxation and Other Motives for Stock Trading," Journal of Finance, American Finance Association, vol. 41(4), pages 951-974, September.
    5. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    6. 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 305-321, March.
    7. Stephen A. Ross, 2005. "Mutual Fund Separation in Financial Theory—The Separating Distributions," World Scientific Book Chapters,in: Theory Of Valuation, chapter 10, pages 309-356 World Scientific Publishing Co. Pte. Ltd..
    8. Morse, Dale, 1980. "Asymmetrical Information in Securities Markets and Trading Volume," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(05), pages 1129-1148, December.
    9. Jaisimha Manchaldore & Imon Palit & Oleg Soloviev, 2010. "Wavelet decomposition for intra-day volume dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 917-930.
    10. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(01), pages 109-126, March.
    11. Bialkowski, Jedrzej & Darolles, Serge & Le Fol, Gaëlle, 2008. "Improving VWAP strategies: A dynamic volume approach," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1709-1722, September.
    12. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    13. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    14. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    15. Gaëlle Le Fol & Julien Idier & Caroline Jardet, 2009. "How Liquid are Markets?," Post-Print halshs-00638443, HAL.
    16. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    17. repec:bla:joares:v:24:y:1986:i:1:p:40-56 is not listed on IDEAS
    18. Merton, Robert C., 1972. "An Analytic Derivation of the Efficient Portfolio Frontier," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(04), pages 1851-1872, September.
    19. 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 1639-1664, December.
    20. Richardson, Gordon & Sefcik, Stephan E. & Thompson, Rex, 1986. "A test of dividend irrelevance using volume reactions to a change in dividend policy," Journal of Financial Economics, Elsevier, vol. 17(2), pages 313-333, December.
    21. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    22. 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.
    23. 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.
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    Cited by:

    1. Darolles, Serge & Le Fol, Gaëlle & Mero, Gulten, 2017. "Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows," Journal of Econometrics, Elsevier, vol. 201(2), pages 367-383.
    2. Bialkowski, Jedrzej & Darolles, Serge & Le Fol, Gaëlle, 2008. "Improving VWAP strategies: A dynamic volume approach," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1709-1722, September.
    3. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

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