کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5053373 1476515 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Oil price forecasting using gene expression programming and artificial neural networks
ترجمه فارسی عنوان
پیش بینی قیمت نفت با استفاده از برنامه نویسی بیان ژن و شبکه های عصبی مصنوعی
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
چکیده انگلیسی


- The gene expression programming (GEP) and artificial neural network (NN) models are used to predict oil prices.
- ARIMA models are employed to benchmark evolutionary models.
- The GEP model outperforms the NN and the ARIMA models in terms of several performance statistics.

This study aims to forecast oil prices using evolutionary techniques such as gene expression programming (GEP) and artificial neural network (NN) models to predict oil prices over the period from January 2, 1986 to June 12, 2012. Autoregressive integrated moving average (ARIMA) models are employed to benchmark evolutionary models. The results reveal that the GEP technique outperforms traditional statistical techniques in predicting oil prices. Further, the GEP model outperforms the NN and the ARIMA models in terms of the mean squared error, the root mean squared error and the mean absolute error. Finally, the GEP model also has the highest explanatory power as measured by the R-squared statistic. The results of this study have important implications for both theory and practice.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Economic Modelling - Volume 54, April 2016, Pages 40-53
نویسندگان
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