Abstract
Many investors prefer the gold market due to its history and maturity. However, understanding how to make correct investments in a fluctuating gold market would be the main challenge when investing in the gold market. If one can understand the factors that affect the gold price, one would be able to make better forecast on the future gold price through an appropriate model. This research adopts ARIMA model and regression model towards the forecast of gold price using the data from January, 1998 to July, 2010 that includes sliver price, US dollar exchange rate, consumer price index, Dow Jones Industrial Average, unemployment rate of G7 countries. Both regression model and ARIMA model are identified through Best Subsets Regress, and time series patterns, respectively. The research result from regression model indicates that gold price is affected significantly by silver price and US dollar exchange rate. In addition, it finds that ARIMA(0,2,1) is an appropriate ARIMA model in the prediction of gold price. Using the R-square and Mean Square Error (MSE) as indicators, we find ARIMA (0,2,1) model has higher R-square value and lower MSE, making it a better model in the prediction of gold price. Prediction on the period of August-September, 2010 are conducted and their results compared with the actual values for August-September, 2010 to assess the predictability of the model.
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