Modeling and Forecasting Stock Market Volatility at Nairobi Securities Exchange

Abstract

The purpose of this study was to model and forecast the stock market volatility at Nairobi Securities Exchange since modeling and forecasting stock market volatility has been the subject of vast theoretical and empirical inquiry. The NSE 20 Share Index was used to generate the daily returns for the market. The study covered ten years of stock market indices and the series of returns (Rt) were generated using the natural logarithm of (Pt/Pt-1). The study used both symmetric and asymmetric GARCH family specifications to model volatility at NSE. The stock market is inefficient in its weak form. The NSE 20 Share Index return was leptokurtosis and skewed to the left, hence it was not normally distributed. It also exhibited serial correlation. The unit root test showed that daily returns are integrated order of one, I(1), which implies that the daily returns are mean reverting in their first difference form. The study indicates that the variance of the returns was not constant. It was time varying, which can be specified as a process of conditional heteroskedasticity. From the parameters estimated using GARCH, GJR GARCH, EGARCH and GARCH M model the returns in stock market exhibit volatility persistency and clustering effect, leverage effect and asymmetric response to external shocks. Further the market is not efficient in pricing risk. Therefore, from the empirical evidence of this study it was possible to deduce that the NSE is not efficient in its weak form and exhibits the stylized facts of financial markets. Keywords: EMH, GARCH, NSE, Stock Market Volatility.