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Improving VWAP strategies: A dynamical volume approach

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Author Info

  • Jedrzej Białkowski

    ()
    (Department of Finance, Faculty of Business, Auckland University of Technology)

  • Serge Darolles

    ()
    (Société Générale Asset Management AI, Center for Research in Economics and Statistics (CREST))

  • Gaëlle Le Fol

    ()
    (University of Evry, Center for Research in Economics and Statistics (CREST), and Europlace Institute of Finance)

Abstract

In this paper, we present a new methodology for modeling intraday volume which allows for a reduction of the execution risk in VWAP (Volume Weighted Average Price) orders. The results are obtained for the all stocks included in the CAC40 index at the beginning of September 2004. The idea of considered models is based on the decomposition of traded volume into two parts: one reflects volume changes due to market evolutions, the second describes the stock specific volume pattern. The dynamics of the specific part of volume is depicted by ARMA, and SETAR models. The implementation of VWAP strategies imposes some dynamical adjustments within the day.

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File URL: http://epee.univ-evry.fr/RePEc/2006/06-08.pdf
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Bibliographic Info

Paper provided by Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne in its series Documents de recherche with number 06-08.

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Length: 62 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:eve:wpaper:06-08

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Related research

Keywords: Intraday Volume; VWAP Strategies; Principal Component Analysis; Arbitrage;

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References

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  1. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
  2. Manganelli, Simone, 2002. "Duration, volume and volatility impact of trades," Working Paper Series 0125, European Central Bank.
  3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  4. James McCulloch, 2007. "Relative volume as a doubly stochastic binomial point process," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 55-62.
  5. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. " An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-89, December.
  6. Gourieroux, Christian & Jasiak, Joanna & Le Fol, Gaelle, 1999. "Intra-day market activity," Journal of Financial Markets, Elsevier, vol. 2(3), pages 193-226, August.
  7. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
  8. 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.
  9. Berkowitz, Stephen A & Logue, Dennis E & Noser, Eugene A, Jr, 1988. " The Total Cost of Transactions on the NYSE," Journal of Finance, American Finance Association, vol. 43(1), pages 97-112, March.
  10. Serge Darolles & Gaëlle Le Fol, 2003. "Trading Volume and Arbitrage," Working Papers 2003-46, Centre de Recherche en Economie et Statistique.
  11. Le Fol, Gaëlle & Mercier, Ludovic, 1998. "Time Deformation: Definition and Comparisons," Economics Papers from University Paris Dauphine 123456789/12729, Paris Dauphine University.
  12. 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.
  13. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
  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. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
  16. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  17. Konishi, Hizuru, 2002. "Optimal slice of a VWAP trade," Journal of Financial Markets, Elsevier, vol. 5(2), pages 197-221, April.
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Citations

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Cited by:
  1. Humphery-Jenner, Mark L., 2011. "Optimal VWAP trading under noisy conditions," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2319-2329, September.
  2. Dutt, Tanuj & Humphery-Jenner, Mark, 2013. "Stock return volatility, operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 999-1017.
  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.
  4. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
  5. Olivier Gu\'eant & Guillaume Royer, 2013. "VWAP execution and guaranteed VWAP," Papers 1306.2832, arXiv.org, revised May 2014.
  6. Fong, Kingsley Y.L. & Liu, Wai-Man, 2010. "Limit order revisions," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1873-1885, August.
  7. Serge Darolles & Gaëlle Le Fol & Gulten Mero, 2010. "When Market Illiquidity Generates Volumes," Working Papers halshs-00536046, HAL.

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