Journal
RESOURCES POLICY
Volume 45, Issue -, Pages 37-43Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.resourpol.2015.03.004
Keywords
Neural networks; Autoregressive integrated moving average (ARIMA); Time series analysis; Copper; Price forecasting; New York Commodity Exchange (COMEX)
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This paper examines the forecasting performance of ARIMA and two different kinds of artificial neural networks models (multilayer perceptron and Elman) using published data of copper spot prices from the New York Commodity Exchange, (COMEX). The empirical results obtained showed a better performance of both neural networks models over the ARIMA. The findings of this research are in line with some previous studies, which confirmed the superiority of neural networks over ARIMA models in relative research areas. (C) 2015 Elsevier Ltd. All rights reserved.
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