Abstract
Firms can be distinguished from one another on the basis of different financial and non-financial factors including firm size, firm value, leverage, earnings per share, cash flow and firm structure. These factors are unique to individual firms and influence the perception of investors towards the future performance of the firms. The aim of the study is to examine the impact of, Firm value, Earnings per share and Firm size on stock return for non-financial listed firms in Kenya. This study used census and covered all non-financial listed firms at the NSE between the years 2008 to 2016. The choice of this period was informed by various reforms undertaken at the NSE. These includes a rise in initial public offers (IPOs), additional offers (AOs), right issues, bonus issues and stock splits. These reforms have had great influence on stock returns. There are 44 non-financial listed firms in the Nairobi Securities Exchange. A number of studies in the empirical literature have documented that firm earnings scaled by market value of equity are related to average return. This study is meant to assess the sensitivity of empirical results of firm value, earnings per share and firm size on stock return for non-financial listed firms in Kenya. The study contributed to the body of knowledge in that non-financial listed firms have gained practical insights into the impact of firm factors under consideration on stock return thereby enriching their knowledge on how to increase overall positive results. The study was based on the problem that whereas there were various firm factors attributed to each firm, it was not clear how, firm value, earnings per share and firm size affect stock return for non-financial listed firms on stock markets particularly those with factors like in Nairobi Securities exchange. This was particularly because existing Empirical literature was scarce in this case. Panel regression model was applied to test the significance of the independent variables on dependent variable and unit root test, Co integration and granger causality test was applied for empirical testing of the data. Descriptive statistics was used to describe basic features of the data in the study.