IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v18y2014i2p20n5.html
   My bibliography  Save this article

Forecasting trading volume in the Chinese stock market based on the dynamic VWAP

Author

Listed:
  • Ye Xunyu

    (School of Systems Science, Beijing Normal University, Beijing, China)

  • Yan Rui

    (School of Government, Beijing Normal University, Beijing, China)

  • Li Handong

    (School of Government, Beijing Normal University, Beijing, China)

Abstract

We investigate the modeling and forecasting of the intra-daily volume time series in Chinese stock market with an application to dynamic Volume Weighted Average Price (VWAP) method. The empirical results show that: (1) This method performs better than the traditional static VWAP strategy; (2) By adjusting time scale (time window) and the composition of the stock portfolio according to the principal component analysis method, we can further improve the forecasting accuracy of the stock turnover series; (3) There is significant long memory characteristic in the special component of the turnover series when using the dynamic VWAP method, however, we find that it can not improve the prediction of turnover series by using ARFIMA model on these series. We also analyze the reasons and provide some explanations.

Suggested Citation

  • Ye Xunyu & Yan Rui & Li Handong, 2014. "Forecasting trading volume in the Chinese stock market based on the dynamic VWAP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(2), pages 125-144, April.
    • Handle: RePEc:bpj:sndecm:v:18:y:2014:i:2:p:20:n:5
    DOI: 10.1515/snde-2013-0023
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2013-0023
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2013-0023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    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. 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 1655-1689, December.
    4. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    5. Konishi, Hizuru, 2002. "Optimal slice of a VWAP trade," Journal of Financial Markets, Elsevier, vol. 5(2), pages 197-221, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang Zhao & Wei Li & Ruihan Bao & Keiko Harimoto & YunfangWu & Xu Sun, 2021. "Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling," Papers 2108.11318, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jedrzej Bialkowski & Serge Darolles & Gaëlle Le Fol, 2012. "Reducing the risk of VWAP orders execution - A new approach to modeling intra-day volume," Post-Print hal-01632822, HAL.
    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. 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.
    4. Olivier Gu'eant & Guillaume Royer, 2013. "VWAP execution and guaranteed VWAP," Papers 1306.2832, arXiv.org, revised May 2014.
    5. Olivier Guéant & Royer Guillaume, 2014. "VWAP execution and guaranteed VWAP," Post-Print hal-01393121, HAL.
    6. Christopher Kath & Florian Ziel, 2020. "Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories," Papers 2009.07892, arXiv.org, revised Oct 2020.
    7. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.
    8. 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.
    9. Serge Darolles & Gaëlle Le Fol, 2003. "Trading Volume and Arbitrage," Working Papers 2003-46, Center for Research in Economics and Statistics.
    10. Carl Hopman, 2007. "Do supply and demand drive stock prices?," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 37-53.
    11. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    12. Humphery-Jenner, M., 2011. "High Frequency Trading, Information, and Takeovers," Other publications TiSEM 30aa1477-0fb2-46ed-a5eb-f, Tilburg University, School of Economics and Management.
    13. Humphery-Jenner, M., 2011. "High Frequency Trading, Information, and Takeovers," Other publications TiSEM 0e6dd147-6f57-4f32-b265-f, Tilburg University, School of Economics and Management.
    14. Enzo Busseti & Stephen Boyd, 2015. "Volume Weighted Average Price Optimal Execution," Papers 1509.08503, arXiv.org.
    15. Ye, Xunyu & Gao, Ping & Li, Handong, 2015. "Improving estimation of the fractionally differencing parameter in the SARFIMA model using tapered periodogram," Economic Modelling, Elsevier, vol. 46(C), pages 167-179.
    16. Humphery-Jenner, M., 2011. "High Frequency Trading, Information, and Takeovers," Discussion Paper 2011-047, Tilburg University, Center for Economic Research.
    17. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    18. Alexander Buryak & Ivan Guo, 2014. "Effective and simple VWAP option pricing model," Papers 1407.7315, arXiv.org.
    19. Humphery-Jenner, Mark L., 2011. "Optimal VWAP trading under noisy conditions," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2319-2329, September.
    20. Seung Hwan Jeong & Hee Soo Lee & Hyun Nam & Kyong Joo Oh, 2021. "Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market," Sustainability, MDPI, vol. 13(3), pages 1-16, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:18:y:2014:i:2:p:20:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.