Abstract
All investors are very keen to know about the trend of the Gold price, whether it will rise or fall. In recent times, the price of Gold has become a hot topic for everyone, it fluctuates rapidly from last some months. In this study, we propose a time series model for forecasting the daily Gold price and use the data set of United State Dollars per ounce from Jan 02, 2014 to Jul 03, 2015 for the said purpose. By using the Box-Jenkins methodology, Autoregressive Integrated Moving Average (ARIMA) model is selected and the model selection criterion (AIC and SBC) shows that ARIMA (1,1,0) and (0,1,1) are close to each other for forecasting the daily Gold price. The forecasted values reveal that ARIMA (0,1,1) is more efficient than ARIMA (1,1,0) on the base of model selection criteria’s, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE).