DETERMINANTS OF STOCK MARKET INDEX: QUANTILE REGRESSION APPROACH

Abstract

Quantile regression is considered a methodological improvement and preferred to ordinary least squares regression (OLS) because it can depict a more detailed picture of the relationship between variables by estimating multiple slopes along the entire response distribution. In the study, quan- tile regression estimation is used to investigate the significant effects of external reserves, exchange rate and inflation rate on stock market index in Nigeria. The study revealed the violation of the assumptions of normality, homoscedasticity and independence of regressors using normality curve, time series plot plot and variance inflation factors (VIF) respectively, followed by the estimation of quantile slopes and relative effectiveness of the model in explaining the data at each quantile. The result of the study showed that all the regressors are related to stock market index and significant at 0.25th quantile while the external reserves only is positively related to stock market and statistically significant at all quantile levels, also it mostly contributed to the explanation of the variation in stock market index. The stock market index has been the tool used by investors to describe the market and compare on specific investments, its determinants like the interest rate needs to be set right in order to boost the performance of the stock market.