Title of article
Forecasting Gold Price using Data Mining Techniques by Considering New Factors
Author/Authors
Hatamlou, A Department of Computer Science - Khoy Branch - Islamic Azad University - Khoy, Iran , Deljavan, M Department of Computer Science - Khoy Branch - Islamic Azad University - Khoy, Iran
Pages
10
From page
411
To page
420
Abstract
Gold price forecast is of great importance. Many models have been 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 in the forecast accuracy. In this work, different factors were studied in comparison with the previous studies on gold price forecast. In terms of time span, the collected data was divided into the three groups of daily, monthly, and annually. The conducted tests using new factors indicated an accuracy improvement of up to 2% in the neural networks methods, 7/3% in the time series method, and 5/6% in the linear regression method.
Keywords
Regression , Neural Networks , Time Series , Data Mning , Gold price Forecast
Journal title
Astroparticle Physics
Serial Year
2019
Record number
2453030
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