Forecasting copper price using gene expression programming | ||
| Journal of Mining and Environment | ||
| مقاله 6، دوره 9، شماره 2، تیر 2018، صفحه 349-360 اصل مقاله (1.53 M) | ||
| نوع مقاله: Case Study | ||
| شناسه دیجیتال (DOI): 10.22044/jme.2017.6195.1435 | ||
| نویسنده | ||
| H. Dehghani* | ||
| Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran | ||
| چکیده | ||
| Forecasting the prices of metals is important in many aspects of economics. Metal prices are also vital variables in financial models for revenue evaluation, which forms the basis of an effective payment regime using resource policymakers. According to the severe changes of the metal prices in the recent years, the classic estimation methods cannot correctly estimate the volatility. In order to solve this problem, it is necessary to use the artificial algorithms, which have a good ability to predict the volatility of various phenomena. In the present work, the gene expression programming (GEP) method was used to predict the copper price volatility. In order to understand the ability of this method, the results obtained were compared with the other classical prediction methods. The results indicated that the GEP method was much better than the time series and multivariate regression methods in terms of the prediction accuracy. | ||
| کلیدواژهها | ||
| Copper price؛ Gene expression programming؛ Forecasting؛ time series | ||
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آمار تعداد مشاهده مقاله: 1,559 تعداد دریافت فایل اصل مقاله: 1,663 |
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