The Effect of Capital Structure on Stock Returns for Firms Listed on the Nairobi Securities Exchange

Abstract

The goal of the study was to investigate the effect of capital structure on stock returns for firms listed on the Nairobi Securities Exchange. The period of focus was from 1st January 2011 to 31st December 2015. The study adopted a causal research design and multiple regression analysis was used to investigate this effect at 95% confidence level. Other independent variables adopted in the study were profitability measured by earnings per share, firm size measured by firms’ total assets and liquidity measured by the average annual trading as a quotient of the outstanding shares in number. Secondary data was utilized for both the dependent and independent variables. The data was obtained from Nairobi Securities Exchange (NSE) historical data on price changes and volume between 1st January 2011 and 31st December 2015 and the 2016 NSE handbook financial reviews per company. Regression analysis results disclosed that overall, capital structure has a positive bearing on stock returns for firms listed on the Nairobi Securities Exchange within the period the study was carried out. The sectorial analysis also showed that capital structure has a positive effect on stock returns in the different sectors except for the agricultural sector, investment and telecommunication sectors. The results are however not statistically significant and can therefore not be used to meaningfully explain changes in stock returns for firm’s listed on the Nairobi Securities Exchange. Nevertheless, the results were found to be statistically significant for the telecommunication sector even though only one firm was reviewed in the sector. Overall, in addition to the positive effect of capital structure on stock returns, profitability and stock liquidity had a positive impact while firm size had a negative impact on a firm’s stock returns. None of the variables were deduced to be statistically significant and the model adopted only accounted for 4.4% variation in stock returns. Other factors not factored in the model employed in the study thus account for 95.6% of the variation in stock returns. Correlation analysis pointed at weak positive correlations between stock returns and all the independent variables. The correlation was only found to be statistically significant between stock returns and stock liquidity. The researcher recommends research on other variables not employed in this study that could account for the 95.6% variation that has not been accounted for by the model adopted. The period of the study can also be extended in future research and different proxies for measuring different variables employed in the same study to eliminate the weaknesses that associated with particular proxies for the independent variables.