On parameter estimation for malaysian gold prices modelling and forecasting

Abstract In developing a time series model, parameter estimation is one of the crucial steps. Common methods of estimation include method of moment (MME), ordinary least square estimation (OLS) and maximum likelihood estimation (MLE). The purpose of the current study is to model and forecast the prices of Malaysian gold called kijang emas using Box-Jenkins methodology. To find the best model, parameter estimates using OLS and MLE were computed. Based on the Akaike information criteria (AIC) and mean absolute percentage error (MAPE), the model estimated with OLS was found to perform better. Keywords : parameter estimation, ordinary least square estimation, maximum likelihood estimation 1 Introduction Kijang Emas is the official Malaysian gold bullion coin minted by the Royal Mint of Malaysia. Kijang emas prices are volatile with huge price swings. Volatility refers to a condition where the conditional variance changes between extremely high and low values. The forecasting of