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Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances
The growing interest and direct impact of carbon trading in the economy have drawn an increasing attention to the evolution of the price of CO2 allowances (European Union Allowances, EUAs) under the European Union Emissions Trading Scheme (EU ETS). As a novel financial market, the dynamic analysis o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10172064/ https://www.ncbi.nlm.nih.gov/pubmed/37359707 http://dx.doi.org/10.1007/s13412-023-00838-5 |
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author | Villar-Rubio, Elena Huete-Morales, María-Dolores Galán-Valdivieso, Federico |
author_facet | Villar-Rubio, Elena Huete-Morales, María-Dolores Galán-Valdivieso, Federico |
author_sort | Villar-Rubio, Elena |
collection | PubMed |
description | The growing interest and direct impact of carbon trading in the economy have drawn an increasing attention to the evolution of the price of CO2 allowances (European Union Allowances, EUAs) under the European Union Emissions Trading Scheme (EU ETS). As a novel financial market, the dynamic analysis of its volatility is essential for policymakers to assess market efficiency and for investors to carry out an adequate risk management on carbon emission rights. In this research, the main autoregressive conditional heteroskedasticity (ARCH) models were applied to evaluate and analyze the volatility of daily data of the European carbon future prices, focusing on the last finished phase of market operations (phase III, 2013–2020), which is structurally and significantly different from previous phases. Some empirical findings derive from the results obtained. First, the EGARCH (1,1) model exhibits a superior ability to describe the price volatility even using fewer parameters, partly because it allows to collect the sign of the changes produced over time. In this model, the Akaike information criterion (AIC) is lower than ARCH (4) and GARCH (1,1) models, and all its coefficients are significative (p < 0.02). Second, a sustained increase in prices is detected at the end of phase III, which makes it possible to foresee a stabilization path with higher prices for the first years of phase IV. These changes will motivate both companies and individual energy investors to be proactive in making decisions about the risk management on carbon allowances. |
format | Online Article Text |
id | pubmed-10172064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-101720642023-05-14 Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances Villar-Rubio, Elena Huete-Morales, María-Dolores Galán-Valdivieso, Federico J Environ Stud Sci Research Article The growing interest and direct impact of carbon trading in the economy have drawn an increasing attention to the evolution of the price of CO2 allowances (European Union Allowances, EUAs) under the European Union Emissions Trading Scheme (EU ETS). As a novel financial market, the dynamic analysis of its volatility is essential for policymakers to assess market efficiency and for investors to carry out an adequate risk management on carbon emission rights. In this research, the main autoregressive conditional heteroskedasticity (ARCH) models were applied to evaluate and analyze the volatility of daily data of the European carbon future prices, focusing on the last finished phase of market operations (phase III, 2013–2020), which is structurally and significantly different from previous phases. Some empirical findings derive from the results obtained. First, the EGARCH (1,1) model exhibits a superior ability to describe the price volatility even using fewer parameters, partly because it allows to collect the sign of the changes produced over time. In this model, the Akaike information criterion (AIC) is lower than ARCH (4) and GARCH (1,1) models, and all its coefficients are significative (p < 0.02). Second, a sustained increase in prices is detected at the end of phase III, which makes it possible to foresee a stabilization path with higher prices for the first years of phase IV. These changes will motivate both companies and individual energy investors to be proactive in making decisions about the risk management on carbon allowances. Springer US 2023-05-11 /pmc/articles/PMC10172064/ /pubmed/37359707 http://dx.doi.org/10.1007/s13412-023-00838-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Villar-Rubio, Elena Huete-Morales, María-Dolores Galán-Valdivieso, Federico Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title | Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title_full | Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title_fullStr | Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title_full_unstemmed | Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title_short | Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances |
title_sort | using egarch models to predict volatility in unconsolidated financial markets: the case of european carbon allowances |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10172064/ https://www.ncbi.nlm.nih.gov/pubmed/37359707 http://dx.doi.org/10.1007/s13412-023-00838-5 |
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