Relationship Between Trading Volume and Stock Return Volatility: Evidence From Nairobi Securities Exchange

Abstract

Trading volume and volatility are two key concepts in finance. The relationship between volume and volatility provides an insight into structure of financial markets, since the predicted price-volume relation depends on information flow, size of the market and short selling constraints. Therefore, the objective of this study is to examine the nature of relationship between trading volume and stock return volatility in the Nairobi Securities Exchange. The research design was a correlational study and the population of study consisted of all the 20 companies forming the NSE 20-share index. Daily closing stock prices of all the companies comprising the NSE 20-share index and daily trade volume as a proxy for information arrival were used in the analysis for the period January 2008 to December 2013. Daily realized volatility was computed using standard deviation and realized volatility at different time horizons – weekly and monthly in this study, was calculated using simple averages. The study applied ordinary least squares regression and autoregression on the data. The study examined this relationship using the Heterogeneous Autoregressive Realized Volatility (HAR-RV) model of Corsi (2004) and extended this model as HARX-RV model following Aguilar and Ringgenberg (2011) by adding the trade volume as a proxy for the information arrival in the HAR-RV model. The study found the F-statistic to be 39.4597 for the HAR-RV model which indicates that the model is statistically significant. Results from HAR-RV model show that volatility of stock returns is persistent in NSE and the persistence reduces when volume is added to the model. The F-statistic is 30.0461 for the HARX-RV model which indicates that the model is implying that major variations of returns are explained by variables other than trading volume. It was concluded that there is a weak relation between trading volume and the stock return volatility of firms listed at the NSE. It is however recommended that a study of similar nature to be carried out on all the listed companies using a longer time period, to give a more varied and valid conclusion. This conclusion regarding the NSE is consistent with other studies conducted locally and within Africa (Gworo, 2012; Achieng, 2013; Mutalib, 2012), but inconsistent with the studies related to other emerging markets, specifically the Asian and Chinese market (Tripathy, 2011; Pathirawasam, 2011; Wang et. al, 2012) which found that volume represents the most predicted variable of increasing price volatility, and both volume and prices are integrated with each other.