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

Ye Xunyu, Yan Rui and Li Handong ()
Additional contact information
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

Studies in Nonlinear Dynamics & Econometrics, 2014, vol. 18, issue 2, 125-144

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.

Keywords: ARFIMA; long memory; principal component; volume series; VWAP (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1515/snde-2013-0023 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:18:y:2014:i:2:p:20:n:5

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.1515/snde-2013-0023

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().