Applying Artificial Neural Networks to Forecast European Union Allowance Prices: The Effect of Information from Pollutant-Related Sectors

Miguel A. Jaramillo-Morán and Agustín García
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Miguel A. Jaramillo-Morán: Department of Electrical Engineering, Electronics and Automation, School of Industrial Engineering, University of Extremadura, Avda. Elvas s/n, 06006 Badajoz, Spain

Energies, 2019, vol. 12, issue 23, 1-18

Abstract: In this paper, we forecast the price of CO 2 emission allowances using an artificial intelligence tool: neural networks. We were able to provide confident predictions of several future prices by processing a set of past data. Different model structures were tested. The influence of subjective economic and political decisions on price evolution leads to complex behavior that is hard to forecast. We analyzed correlations with different economic variables related to the price of CO 2 emission allowances and found the behavior of two to be similar: electricity prices and iron and steel prices. They, along with CO 2 emission allowance prices, were included in the forecasting model in order to verify whether or not this improved forecasting accuracy. Only slight improvements were observed, which proved to be more significant when their respective time series trends or fluctuations were used instead of the original time series. These results show that there is some sort of link between the three variables, suggesting that the price of CO 2 emission allowances is closely related to the time evolution of the price of electricity and that of iron and steel, which are very pollutant industrial sectors. This can be regarded as evidence that the CO 2 market is working properly.

Keywords: European Union Allowances; price of CO 2 emission allowances; neural networks; forecasting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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