Fitting the Nigeria Stock Market Return Series Using GARCH Models

Abstract

This study investigated the performance of eleven competing time series GARCH models for fitting the rate of returns data, monthly observations on the index returns series of the market over the period of January 1996 to December 2015 was used. From the results obtained from the Log Likelihood (Log L), Schwarzs Bayesian Criterion (SBC) and the Akaike Information Criterion (AIC) values it was found that the models identified was not the same for the two periods (Training and Testing period) that is for Training period were CGARCH (1,1) and EGARCH (1,1) while for Testing period were ARCH (1) and GARCH (2,1) . The two extreme classes of models are identified to represent the best and the worst groups respectively. The overall effect of this will tend to increase the volatility of the market returns. The paper therefore recommended that the Nigeria government should as a matter of urgency take appropriate positive measure s through the security and exchange commission to regulate the market volatility so that the provided market index could be safely used as predictive index for measuring the performance of the firms and as a guide for investment purpose.