Effects of Estimating Systematic Risk in Equity Stocks in the Nairobi Securities Exchange (NSE) (An Empirical Review of Systematic Risks Estimation)

Abstract

Capital Markets have become an integral part of the Kenyan economy. The manner in which securities are priced in the capital market has attracted the attention of many researchers for long. This study sought to investigate the effects of estimating of Systematic risk in equity stocks of the various sectors of the Nairobi Securities Exchange (NSE. The study will be of benefit to both policy makers and investors to identify the specific factors affecting stock prices. To the investors it will provide useful and adequate information an understanding on the relationship between risk and return as a key piece in building ones investment philosophy. To the market regulators to establish the NSE performance against investors’ perception of risks and returns and hence develop ways of building investors’ confidence, the policy makers to review and strengthening of the legal and regulatory framework. The paper examines the merged 12 sector equity securities of the companies listed at the market into 4sector namely Agricultural; Commercial and Services; Finance and Investment and Manufacturing and Allied sectors. This study Capital Asset Pricing Model (CAPM) of Sharpe (1964) to vis-a-vis the market returns. Monthly basis secondary data from the period January 2009 through December 2012 was used model the study from Stocks of the various sectors of the NSE. A simple regression model approach was used where stock was taken as dependent variable while systematic risk as independent variable and used. The study found out that there were effects market sector betas and returns. Second there is a relationship between systematic risk and stock market return in sectors because systematic risk and stock market return exhibits a strong negative autocorrelation, indicating that the stock market return is a function of more variable than systematic risk. The study rejects the first null hypothesis for all the four sectors and finds that beta is a statistically significant indicator of market risk for those sectors. The study also found out that agricultural sector was most risky sector with the highest volatility while the Finance and Investment sector is the least risky during the study period. Industrial and allied as well as the finance and investment sectors had less volatile returns than the overall NSE. From the findings of sectors studied it can be concluded that the various equity in NSE each of the have unique factors that influence market risk relative to the all the companies listed at the NSE.