Short-term European Union Allowance price forecasting with artificial neural networks

Agustín García,Miguel A Jaramillo-Morán

doi:10.9770/jesi.2020.8.1(18)

Abstract

The European Union Emissions Trading Scheme (EU ETS) was created to reduce greenhouse gas emissions. Companies producing carbon emissions have to manage associated cash flows by buying or selling carbon allowances. Moreover, future carbon prices could affect company decision making on decarbonization technology investments. In this paper, we forecasted short-term future carbon allowance prices using an artificial intelligence tool: a neural network. The resulting mean error was 1.7617 %. This is indicative of very good performance for a time series whose evolution is influenced by subjective economic and political decisions. The inclusion in the forecasting model of variables possibly directly related to the evolution of the price of CO2 emission allowances did not improve prediction accuracy. Therefore, we can assume that emission allowances evolve following a random path. The neural network provided reliable predictions which agents selling or buying allowances can use to make their decisions.

Highlights

The European Union introduced the emissions trading system (EU ETS) in 2005 in order to reduce greenhouse gas emissions which are very much responsible for climate change
We selected a multilayer perceptron (MLP) with one hidden layer to carry out the forecasting process in this paper, because, as stated above, it has been proven to be a powerful and reliable forecasting tool to predict time series and one hidden layer is enough to guarantee that the network can efficiently approximate the time series behavior
In this paper a type of neural network known as multilayer perceptron has been used to forecast carbon allowance prices

Summary

Introduction

The European Union introduced the emissions trading system (EU ETS) in 2005 in order to reduce greenhouse gas emissions which are very much responsible for climate change. The EU ETS is a market mechanism that determines a price for CO2 emissions and tries to create incentives to reduce emissions from industrial sectors This system allows companies producing carbon emissions to effectively manage associated costs by buying or selling emission allowances. Free allowance allocation is a key factor that could have curbed the effectiveness of the EU ETS in Phases I and II, countering its ability to generate climate-related innovations (Joltreau and Sommerfeld, 2019). In this respect, increased auctioning in Phase III could stimulate low carbon emission innovations. Zeng and Zhu (2019) analyzed the effect of market power in the emission trading market on technology adoption. Zhang et al (2019) pointed out that an ETS pilot project has achieved the Porter effect in China, whereas Wang et al (2019) found empirical evidence supporting the fact that the pilot ETS project had a significant causal impact on the reduction of CO2 intensity

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