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Trading Volume and Arbitrage

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  • Serge Darolles

    (Crest)

  • Gaëlle Le Fol

    (Crest)

Abstract

Decomposing returns into market and stock speci?c components is commonpractice and forms the basis of popular asset pricing models. But what aboutvolume ? Can volume be decomposed in the same way as returns ? Lo andWang (2000), in a recent paper, suggest such a decomposition. Our paperis in this line of work and, despite the similarity of the statistical approach,our contribution is twofold. First, we provide a theoretical model to explainthe decomposition of volume. Our model is the ?rst, to our knowledge,to justify the strategies of new generation of traders, that we call liquidityarbitrageurs. Second, we propose a new e¢ cient screening tool that allowspractitioners to extract speci?c information from volume time series. Weprovide an empirical illustration of the relevance and the possible uses ofour approach on daily data from the FTSE index from 2000 to 2002.

Suggested Citation

  • Serge Darolles & Gaëlle Le Fol, 2003. "Trading Volume and Arbitrage," Working Papers 2003-46, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2003-46
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    Cited by:

    1. Serge Darolles & Gaëlle Le Fol, 2004. "Nouvelles techniques de gestion et leur impact sur la volatilité," Revue d'Économie Financière, Programme National Persée, vol. 74(1), pages 231-243.
    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. Darolles, Serge & Fol, Gaëlle Le & Mero, Gulten, 2015. "Measuring the liquidity part of volume," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 92-105.
    4. 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.
    5. 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.
    6. Machado, André & Lima, Fabiano Guasti, 2021. "Sell-side analyst reports and decision-maker reactions: Role of heuristics," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    7. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    8. Staer, Arsenio & Sottile, Pedro, 2018. "Equivalent volume and comovement," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 143-157.
    9. Jedrzej Bialkowski & Serge Darolles & Gaëlle Le Fol, 2005. "Decomposing Volume for VWAP Strategies," Working Papers 2005-16, Center for Research in Economics and Statistics.

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