Forecasting Gold Price using Data Mining Techniques by Considering New Factors

• Main Authors: A.R. Hatamlou, M. Deljavan
• Format: Article
• Language: English
• Published: Shahrood University of Technology 2019-07-01
• Series: Journal of Artificial Intelligence and Data Mining
• Subjects: gold price forecast; data mining; time series; neural networks; regression
• Online Access: http://jad.shahroodut.ac.ir/article_1262_c0e3e477464bd17e86b6e558947ce238.pdf

Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase of forecast accuracy. In this paper, different factors were studied in comparison to the previous studies on gold price forecast. In terms of time span, the collected data were divided into three groups of daily, monthly and annually. The conducted tests using new factors indicate accuracy improvement up to 2% in neural networks methods, 7/3% in time series method and 5/6% in linear regression method.