Forecasting Malaysia gold’s price by using neural networks / Norpah Mahat, Aini Mardhiah Yusuf and Siti Sarah Raseli

• Main Authors: Mahat, Norpah, Yusuf, Aini Mardhiah, Raseli, Siti Sarah
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA, Perlis 2019
• Subjects: Precious metals. Bullion; Time-series analysis; Neural networks (Computer science)
• Online Access: http://ir.uitm.edu.my/id/eprint/41822/1/41822.pdf; http://ir.uitm.edu.my/id/eprint/41822/; https://jurnalintelek.uitm.edu.my/index.php/main

Gold and all kinds of gold alloys are commonly used in the manufacture of jewelry, coins and in exchange for trade in many countries. In addition, gold can conduct electricity efficiently and withstand corrosion. This has made gold becomes an important industrial metal in the late 20th century. It is also important for the investors and public to know the trend of changes on gold’s price in order to assist them in making a good decision on their business. This research is done to forecast the Malaysia gold’s price by using artificial Neural Network (NN). The forecasting models are implemented by using Alyuda Neurointelligence software. A monthly gold’s price data from January 2013 until March 2018 is used and applied to the models and comparing their error measures. The results show that the Conjugate Gradient Algorithm (CGA) is chosen as the best neural network algorithm to forecast gold price since it has a higher value of correlation and R square with the best architecture design [2-5-1]. Then, the future price of gold starting from April 2018 until December 2018 is forecasted by using the best model.