Title :
Gold price prediction using radial basis function neural network
Author :
Hussein, Shamsul Faisal Mohd ; Shah, Mohd Badril Nor ; Jalal, Mohd Razi Abd ; Abdullah, Shahrum Shah
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. Malaysia (UTM), Skudai, Malaysia
Abstract :
Gold is a precious metal once widely used as a standard for monetary exchange but was replaced by paper currency mostly used today. However interest in gold trading and investment has resurfaced recently in Malaysia probably due to its price stability. Samples of gold that are used as investment include the Kijang Emas, Public Dinar and the Public Gold which are currently available to the general public in Malaysia. This project will involve developing a system to aid a gold investor in deciding the best time in the future to buy or sell gold. The system developed is based on existing gold data time series and algorithms based on Artificial Neural Networks. The system should be able to give daily prediction to its users.
Keywords :
gold; investment; pricing; radial basis function networks; time series; Malaysia; artificial neural networks; gold data time series; gold price prediction; gold trading; investment; monetary exchange; public dinar; radial basis function neural network; Artificial neural networks; Forecasting; Gold; Radial basis function networks; Testing; Time series analysis; Training data;
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0003-3
DOI :
10.1109/ICMSAO.2011.5775457