Document Type : Full Length Article
Department of Statistics University of Nigeria
Department of Statistics, Faculty of Science, University of Ibadan
Department of Statistics, Faculty of Science, University of Ibadan, Nigeria
The forecasting performance of different class of volatility models was compared in this work using the daily adjusted close price of traded stocks of the Nigerian Stock Exchange (NSE) from December 10, 2013 to February 07, 2019. The GARCH and EGARCH models were selected from the GARCH models whereas the GAS and EGAS were selected from the GAS models. Two different distributions were assumed for the innovations of the volatility models and forecasts measure was obtained. Based on the forecasts measure which are Mean Error (ME) and Theil Inequality (TI) obtained, the ability the models to forecast future volatilities was achieved. The outcome of this research showed that the GAS model performed better when compared to the GARCH model under the two distributional assumptions in terms of ability to forecast future volatilities of the close price NSE stocks. However, the EGARCH performed better when student-t distribution was assumed.