Effect of Trading Volume on Market Returns of Equity Securities Market in Kenya

Effect of Trading Volume on Market Returns of Equity Securities Market in Kenya

Mwiti Jedidah Karwitha, Willy Muturi, Oluoch J. Oluoch

School of Business, Jomo Kenyatta University of Agriculture and Technology P.O Box 62000-00200 Nairobi, Kenya


The study aimed to establish the effect of trading volume on market returns of securities traded in Kenyan securities exchange market. The study used secondary data from all the firms listed in NSE during the period 2004 to 2016. The target population of the study consisted of the sixty 62 companies listed in Nairobi securities exchange market that is, both financial and non-financial companies. The study was a census study of all the sixty 2 companies listed in the Nairobi security exchange market for 13 years starting the year 2004 to the year 2016. The study started with descriptive and then diagnostic tests. The measures of central tendency used to test normality were mean, median, maximum and minimum value, standard deviation, skewness, kurtosis and Jarque-Bera (JB) test. The results from these tests showed that the variables were fairly normally distributed. The study further sought to investigate the stationality properties of market returns, trading volume. The study used five panel data unit root tests. Particularly the test were, Levin, Lin and Chu t, Breitung t-stat, Im, Pesaran and Shin W-stat developed, Fisher-type tests using augmented dickey fuller ADF and (Phillip and Peron) PP tests. The all these tests revealed that the variables were stationary on average. The study also sought to test the granger causality among the variable. The results from granger causality showed that some of the variables granger caused one another. The cointegration results showed that there was long-run equilibrium. The regression techniques used was Cross-section fixed (dummy variables) and Period fixed (dummy variables). The regression results revealed that the variables were statistically significant effect on market returns trading volume had a positive effect on the market returns. It is therefore in this light that the future research should consider other variables which would increase the predictive power of the model. The other relevant variables would be variables such as the size of the firm, market value of the firm and the macroeconomic variables such as exchange rate, inflation, money supply among others.

Keywords: Trading Volume, Market returns, unit root and cointegration

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How to cite this article:
Mwiti Jedidah Karwitha, Willy Muturi, Oluoch J. Oluoch. Effect of Trading Volume on Market Returns of Equity Securities Market in Kenya. Global journal of Economics and Business Administration, 2018,3: 12. DOI: 10.28933/gjeba-2018-09-2301


1. Baltagi, B. H., Bratberg, E., and Holmås, T. H. (2005). A panel data study of physicians’ labor supply: the case of Norway. Health Economics, 14(10), 1035-1045.
2. Breitung (2000),The Local Power of Some Unit Root Tests for Panel Data, Advances in Econometrics, Vol. 15: Nonstationary Panels, Panel Cointegration, and Dynamic Panels, Amsterdam: JAI Press, p. 161–178.
3. Chae, J., and Wang, A. (2003). Who makes markets? Do dealers provide or take liquidity. Unpublished working paper, Sloan School of Management, MIT.
4. Choi, I. (2001). Unit root tests for panel data. Journal of international money and Finance, 20(2), 249-272.
5. Choi, I. (2006). Combination unit root tests for cross-sectionally correlated panels. Econometric Theory and Practice: Frontiers of Analysis and Applied Research: Essays in Honor of Peter CB Phillips. Cambridge University Press, Chapt, 11, 311-333.
6. Christie, W. G. (1994). Why do Nasdaq market makers avoid odd-eighth quotes? Journal of Finance , 49, 1813-1840.
7. Cooper, D. R., Schindler, P. S., and Sun, J. (2006). Business research methods (Vol. 9). New York: McGraw-Hill Irwin.
8. Easley, D., & O’Hara, M. (2003). Microstructure and asset pricing. Handbook of the Economics of Finance, 1, 1021-1051.
9. Engle, R. F., and Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
10. Fama, E. (1970). Efficient Capital Markets: A Review of Theory and Empirical work. Journal of Finance , 25, 383-417.
11. Gujarati, D. N. (2003). Basic Econometrics. London: McGraw Hill.
12. Gujarati, D. N. Sangeetha (2012), Basic Econometrics.
13. Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal, 3(2), 148-161.
14. Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. Stata Journal, 7(3), 281.
15. Hsiao, C. (2004). Analysis of panel data (No. 54). Cambridge university press.
16. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74.
17. Karpoff, J. M. (1986). A theory of trading volume. The Journal of Finance, 41(5), 1069-1087.
18. Karpoff, J. M. (1986). A theory of trading volume. The Journal of Finance, 41(5), 1069-1087.
19. Kelley, E. K., and Tetlock, P. C. (2013). How wise are crowds? Insights from retail orders and stock returns. The Journal of Finance, 68(3), 1229-1265.
20. Kombo, D. K., and Tromp, D. L. (2010). Proposal and Thesis Writing. Pauline’s Publication Africa.
21. Kothari, C. R. (2009). Research Methodology Methods and Techniques 2nd Revised Edition. Nairobi: New Age International Publishers.
22. Levin, A., Lin, C. F., and Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1-24.
23. Lim, K. P., & Brooks, R. (2011). The evolution of stock market efficiency over time: a survey of the empirical literature. Journal of Economic Surveys, 25(1), 69-108.
24. Lim, K., and Brooks, R. (2011). The Evolution of Stock Market Efficiency over Time: A survey of the Empirical Literature. Journal of Economic Surveys , 25 (1), 69-108.
25. Maddala, G. S., and Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and statistics, 61(S1), 631-652.
26. Mugenda, A. G. (2010). Social Science Research. Nairobi: Kijabe Printing Press.
27. Ngugi, R. W., and Njiru, R. (2005). Growth of the Nairobi Stock Exchange Primary Market. Nairobi: Kenya Institute of Public Policy Research Analysis.
28. Pedroni, P. (1999). Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors, Oxford Bulletin of Economics and Statistics, 61, 653–70.
29. Pedroni, P. (2004). Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis, Econometric Theory, 20, 597–625.
30. Polit, D.F. and Hungler, B.P. 2013. Essentials of Nursing Research: Methods, Appraisal, and Utilization (8thedn). Philadelphia: Wolters Kluwer/Lippincott Williams and Wilkins.
31. Saikkonen, P. (1992). Estimation and testing of cointegrated systems by an autoregressive approximation. Econometric theory, 8(1), 1-27.
32. Sanjay Sehgal, Vibhuti and Vasishth, (2015). Past price changes, trading volume and prediction of portfolio returns: Evidence from select emerging markets. Journal of Advances in Management Research, Vol. 12 Issue: 3, pp.330-356, https://doi.org/10.1108/JAMR-10-2014-0056
33. Stock, J. H., and Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica: Journal of the Econometric Society, 783-820.
34. Stock, J. H., and Watson, M. W. (2001). Vector autoregressions. Journal of Economic perspectives, 15(4), 101-115.
35. Tapa, A., and Hussin, M. (2016). The Relationship between Stock Return and Trading Volume in Malaysian ACE Market. International Journal of Economics and Financial Issues, 6(7S), 271-278.
36. Tehranchian, A. M., Behravesh, M., and Hadinia, S. (2014). On the Relationship between Stock Returns and Trading Volume: A Case Study. European Online Journal of Natural and Social Sciences, 3(3), pp-425.
37. Yen, G., & Lee, C. F. (2008). Efficient market hypothesis (EMH): past, present and future. Review of Pacific Basin Financial Markets and Policies, 11(02), 305-329.
38. Yen, G., and Lee, C. F. (2008). Efficient market hypothesis (EMH): Past, Present and Future. Review of Pacific Basin Financial Markets and Policies , 11, 305-329.
39. Yonis, M. (2014). Trading Volume and Stock Return: Empirical Evidence for Asian Tiger Economies. Masters thesis.
40. Akileng, G., Ogwang, A. A., & Ssendyona, C. (2018). Determinants of performance of securities exchanges in East Africa. Journal of Finance and Investment Analysis, 7(3), 1-3.
41. Hsiao, C., and Pesaran, M. H. (2004). Random coefficient panel data models.
42. Hui-Ching,S.H. (2014).The causal relationships between stock returns, trading volume, and volatility: Empirical evidence from Asian listed real estate companies, International Journal of Managerial Finance, Vol. 10 Issue: 2, pp.218-240, https://doi.org/10.1108/IJMF-10-2013-0103
43. Abdullahi,S.A. Kouhy,R. and Muhammad,Z. (2014).Trading volume and return relationship in the crude oil futures markets, Studies in Economics and Finance, Vol. 31 Issue: 4, pp.426-438, https://doi.org/10.1108/SEF-08-2012-0092
44. Girard,E. and Omran,M. (2009).On the relationship between trading volume and stock price volatility in CASE, International Journal of Managerial Finance, Vol. 5 Issue: 1, pp.110-134, https://doi.org/10.1108/17439130910932369
45. Faff, R.W. and McKenzie,M.D. (2007).The relationship between implied volatility and autocorrelation, International Journal of Managerial Finance, Vol. 3 Issue: 2, pp.191-196, https://doi.org/10.1108/17439130710738736

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