International Journal of Advances in Applied Sciences (IJAAS) Vol. 1, No. 4, December 2012, pp. 153~158 ISSN: 2252-8814  153 Journal homepage: http://iaesjournal.com/online/index.php/IJAAS ARIMA Model for Gold Bullion Coin Selling Prices Forecasting Lazim Abdullah * * Departement of Mathematics, University Malaysia Terengganu Article Info ABSTRACT Article history: Received Jul 22, 2012 Revised Oct 23, 2012 Accepted Nov 14, 2012 Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. Auto-Regressive Integrated Moving Average (ARIMA) models are one of the most important time series models used in financial market forecasting over the past three decades but not very often used to forecast gold prices. This paper attempts to address the forecasting of gold bullion coin selling prices. The forecasting models ARIMAs are applied to forecast the gold bullion coin prices. The result suggests that ARIMA (2, 1, 2) is the most suitable model to be used for forecasting gold bullion coin prices. Closer examination suggests that the gold bullion coin selling prices are in upward trends and could be considered as a worthy investment. Keyword: Forecasting Stationary Estimation Auto Regressive Moving Average Golg Prices Copyright © 2012 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Lazim Abdullah, Department of Mathematics, University Malaysia Terengganu, 21030 Kuala Terengganu, Malaysia. Email: lazim_m@umt.edu.my 1. INTRODUCTION Central bank of Malaysia has recognized that gold bullion coins are legal tender coins whose market price depends on their gold content rather than on their face value. Gold bullion coins are traded daily throughout the world and their price depends on the prevailing international gold price. Investors are encouraged to invest in gold bullion coins because its price depends on the international gold price and not very subjected to inflation. With investing in gold bullion, investors may reduce the risk of losing their cash such as in the case of a sudden slide in the stock market or increased inflation rate. Gold can be considered as an option to protect against any eventuality since it is pretty immune from national and regional economies. Most of investors would like to keep a portion of their total assets in gold because it is low-to-negative correlation with stocks and bonds thereby make it an excellent portfolio diversifier. Gold investors may depend on historical data of gold price to forecast future prices prior to making their investment decision. The main reason for forecasting is to minimize risk when making a decisive move. Forecasting is a process in management to assist decision making. It is also described as the process of estimation in unknown future situations. In a more general term it is commonly known as prediction which refers to estimation of time series or longitudinal type data. The most popular model for this method is the Box-Jenkins model introduced by [1]. Box-Jenkins has suggested the time-series autoregressive integrated moving average (ARIMA) model for forecasting. Like any other such methods, it requires historical time series data on the variable under forecasting. It assumes that the future values of a time series have a clear and definite functional relationship with current, past values and white noise. Kumar et al. [2] stated that the ARIMA offers a good technique for predicting the magnitude of any variables. The model has been successfully tested in many forecasting. In fishery industries, Lloret, et al. [3] suggests ARIMA models as the most appropriate to forecast fishery landings in the Hellenic marine waters, since systematic biological time-