On the Hybrid of Arima and Garch Model in Modelling Volatilities in Nigeria Stock Exchange

Abstract

This work examined the implementation of combination of the most effective univariate time series model, ARIMA models with the superior volatility models GARCH, in examining the daily stocks returns of 2910 observations.  Augmented dickey Fuller and Phillips Perron test were used to check the stationarity of the series. The series were confirmed stationary after the first difference. Comparison of forecasting accuracy of the hybridization between ARIMA Model and Generalized Autoregressive Conditional Heteroscedastic (GARCH) processes was done using the secondary data of All share Index of Nigeria Stock Exchange series obtained from National Bureau of Statistics and World Bank Statistics Database dated, from January 2012 to October 2023.The empirical results of 2910 daily series monthly revealed that the  ARIMA (1,1,1)-GARCH (1,1) model gives the optimum results in modelling the Nigeria Stock exchange returns compared to conditional mean model ARIMA (1,1,1).