Forecasting malaysian gold using GARCH model

Abstract

The purpose of the current study is to forecast the prices of Kijang Emas, the official Malaysian gold bullion. Two methods are considered, which are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Using Akaike's information criterion (AIC) as the goodness of fit measure and mean absolute percentage error (MAPE) as the forecasting performance measure, the study concludes that GARCH is a more appropriate model. Analysis are carried out by using the E-views software. © 2013 Pung Yean Ping et al.