Analyzing the Causal Relations between Trading Volume and Stock Returns and between Trading Volume and Return Volatility in Tehran Stock Exchange

Document Type: Original Article

Authors

1 Assistant Prof., Department of Finance, Faculty of management, Alzahra University, Tehran, Iran.

2 MSc., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.

3 Ph.D. Candidate, Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.

10.22034/ijf.2019.101108

Abstract

Identifying the causal relations between trading volume and stock returns and between trading volume and return volatility plays a vital role in identifying profitable investment opportunities. In this study, the Granger causality test was conducted to analyze the causal relationships between the mentioned variables in Tehran Stock Exchange. Consequently, the Vector Auto Regression (VAR) model was employed to determine the conditional mean equations of returns and volume. Moreover, the bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was used to model the conditional variance equation, stating the relationship between volume and return volatility. According to the results, no bilateral causal relationship can be ascertained between returns, volume, and return volatility. In other words, return and return volatility could barely predict volume; therefore, volume cannot be the Granger causality of the other two variables. However, stock returns were found to have an important role in determining the volume. Likewise, return volatility can be used to predict volume accurately. In fact, stock returns and the return volatility were both the Granger causalities of the volume.

Keywords

References

Esmaeeli, Shahpour (2006). The Relationship between Dividend Quality and Stock Returns, Master’s Thesis, Allameh Tabataba’i University
Omid Ghaemi, Mustafa (2000). Analyzing the Relationship between Volume and Stock Prices at Companies Listed in Tehran Stock Exchange, Master’s Thesis, Shahid Beheshti University
Jahankhani, Ali; Parsaeeyan, Ali; Financial Management, First and Second Volumes, SAMT Publications
Rahnama Roudposhti, Fereydoun; Mir Ghafari, Seyed Reza. Portfolio Performance Evaluation at Tehran Stock Exchange: The Use of Value at Risk, Journal of Financial Engineering and Stock Securities Management, Autumn, 2011
Rahnama Roudposthi, F. et al. (2013). Strategic Financial Management (Value Creation)
Ziodar, Mahdi (2005). Analyzing the Empirical Relationship between Volume, Stock Returns, and Return Volatility at Tehran Stock Exchange. Master’s Thesis, Tarbiat Modares University
Muhammad Ali Zadeh, Saeed (2002). Analyzing the Dynamic Relationship between the Transactions of Natural-Legal Investors and Stock Returns at Tehran Stock Exchange, Master’s Thesis, University of Tehran
Baklaci, H. and Kasman, A. (2008).  An Empirical Analysis of Trading Volume and Return Volatility Relationship in the Turkish Stock Market.http://eab.ege.edu.tr/pdf/6_2/C6-S2-M11.pdf.
Blume, L., Easley, D., & O'Hara, M. (1994). Market statistics and technical analysis: The role of volume. Journal of Finance, 49, 153–181.
Campbell, J. Y., Grossman, S. J., & Wang, J. (1993). Trading volume and serial correlation in stock returns. Quarterly Journal of Economics, 108, 905–939.
Copeland, T. E. (1976). A model of asset trading under the assumption of sequential information arrival. Journal of Finance, 31,1149–1168.
Darrat, A. F., Rahman, S., & Zhong, M. (2003). Intraday trading volume and return volatility of the DJIA stocks: A note. Journal of Banking and Finance, 27, 2035–2043.
Gervais, S., & Odean, T. (2001). Learning to be overconfident. Review of Financial Studies, 14, 1–27.
Ghysels, E., Gourieá, C., & Jasiak, J. (2000). Causality between returns and traded volumes. Annales d'Economie et d. Statistique, 60, 189–206.
Griffin, J. M., Nardari, F., & Stulz, R. M. (2007). Do investors trade more when stocks have performed well? Evidence from 46 countries. Review of Financial Studies, 20, 905–951.
Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price–volume relation. Journal of Finance, 49, 1639–1664.
Karpoff, J. M. (1988). Costly short sales and the correlation of returns with volume. Journal of Financial Research, 11, 173–188.
Lamoureux, C. G., & Lastrapes, W. D. (1990). Heteroskedasticity in stock return data: Volume versus GARCH effects. Journal of Finance,45, 221–229.
Lee, C. M. C., & Swaminathan, B. (2000). Price momentum and trading volume. Journal of Finance, 55, 2017–2069.
Malliaris, A. G., & Urrutia, J. L. (1998). Volume and price relationships: Hypotheses and testing for agricultural futures. Journal of Futures Markets, 18, 53–72.
Pascual, L., Romo, J. and Ruiz, E. (2006). Bootstrap Prediction for Returns and Volatilities in GARCH Models.  Computational Statistics & Data Analysis. 50, 2293 – 2312.
R. S. Tsay, Analysis of financial time series vol. 543: Wiley. com, 2005.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. Journal of Finance, 40, 777–791.
Smirlock, M., & Starks, L. (1985). A further examination of stock price changes and transaction volume. Journal of Financial Research, 8, 217–225.
Wang, J. (1994). A model of competitive stock trading volume. Journal of Political Economy, 102, 127–168.
W.-I. Chuang, H.-H. Liu, and R. Susmel, "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, vol. 23, pp. 1-15, 2012.

Iranian Journal of Finance

Volume 2, Issue 4
Autumn 2018
Pages 27-40

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