| Summary: | The monthly economic time series commonly contains the volatility periods and it is suitable to apply the Heteroscedastic model to it where the conditional variance is not constant throughout the time trend. The aim of this study is to model and forecast the currency in circulation (CIC) in Malaysia over the time period, from January 1998 to January 2016. Two methods are considered, which are Autoregressive Conditional Heteroscedastic (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Using the Root Mean Square Error (RMSE) as the forecasting performance measure, this study concludes that GARCH is a more appropriate model compared to ARCH.
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