Acta Univ. Agric. Silvic. Mendelianae Brun. 2014, 62(6), 1373-1380 | DOI: 10.11118/actaun201462061373
Impact of Trading Volume on Prediction of Stock Market Development
- Department of Statistics, Faculty of Economics and Management, Czech University of Life Sciences in Prague, Kamýcká 129, 165 21 Prague 6,Czech Republic
The paper focuses on the influence of trading volume on quality of prediction of stock market development. The main objective of this article is to assess the influence of stock trading volume level on quality of prediction with use of technical analysis. The research was applied on stocks included in the S & P 500 index. Based on average daily trading volume, three aggregate indexes were constructed.
The dynamics of index return volatility was modeled by GARCH-class models. GARCH(1,1), GJR and EGARCH models were estimated for each time series. The in-sample evidence indicated that the return volatility of the indexes can be characterized by significant persistence and asymmetric effects. The best estimate of each model was produced for the index of stocks with the highest average trading volume.
However the result could differ based on the observed period, the volatility structure of the examined data supports the idea that influential investors respond to various shocks in the market primarily by closing or opening their largest position.
The importance of the level of trading volume for the prediction of financial time series development was shown in the paper. This finding could help generate such volatility structure of time series which would allow to explain development of the time series by various models with better results.
Keywords: stock market, trading volume, prediction, volatility, GARCH
Grants and funding:
The findings presented in this paper resulted from grant number 20131046 "Vliv objemu obchodů na kvalitu predikce vývoje akciového trhu" (Impact of Trading Volume on Prediction Quality of Stock Market Development) of Internal Grant Agency (IGA) of the Faculty of Economics and Management, Czech University of Life Sciences in Prague.
Published: January 17, 2015 Show citation
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