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The role of online news sentiment in carbon price prediction of China’s carbon markets

Carbon trading as a vital tool to reduce carbon dioxide emissions has developed rapidly in recent years. Reasonable prediction of the carbon price can improve the risk management in the carbon trading market and make healthy development of the carbon trading market. This paper aims to enhance the pr...

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Detalles Bibliográficos
Autores principales: Liu, Muyan, Ying, Qianwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838308/
https://www.ncbi.nlm.nih.gov/pubmed/36627425
http://dx.doi.org/10.1007/s11356-023-25197-0
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author Liu, Muyan
Ying, Qianwei
author_facet Liu, Muyan
Ying, Qianwei
author_sort Liu, Muyan
collection PubMed
description Carbon trading as a vital tool to reduce carbon dioxide emissions has developed rapidly in recent years. Reasonable prediction of the carbon price can improve the risk management in the carbon trading market and make healthy development of the carbon trading market. This paper aims to enhance the predictive performance of carbon price in the China’s carbon markets, especially the China’s national carbon market, by adding the online news sentiment index which is a kind of unconstructed data, to a deep learning model using traditionally constructed predictors innovatively. Long short–term memory (LSTM) network was applied as the primary model to predict carbon price and random forest as the additional experiment to validate the effectiveness of online news sentiment. The results in the China’s national carbon market and Hubei pilot carbon market both proved that the model including the sentiment index performed better than the model does not, and the improvement was significant.
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spelling pubmed-98383082023-01-17 The role of online news sentiment in carbon price prediction of China’s carbon markets Liu, Muyan Ying, Qianwei Environ Sci Pollut Res Int Research Article Carbon trading as a vital tool to reduce carbon dioxide emissions has developed rapidly in recent years. Reasonable prediction of the carbon price can improve the risk management in the carbon trading market and make healthy development of the carbon trading market. This paper aims to enhance the predictive performance of carbon price in the China’s carbon markets, especially the China’s national carbon market, by adding the online news sentiment index which is a kind of unconstructed data, to a deep learning model using traditionally constructed predictors innovatively. Long short–term memory (LSTM) network was applied as the primary model to predict carbon price and random forest as the additional experiment to validate the effectiveness of online news sentiment. The results in the China’s national carbon market and Hubei pilot carbon market both proved that the model including the sentiment index performed better than the model does not, and the improvement was significant. Springer Berlin Heidelberg 2023-01-11 2023 /pmc/articles/PMC9838308/ /pubmed/36627425 http://dx.doi.org/10.1007/s11356-023-25197-0 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Liu, Muyan
Ying, Qianwei
The role of online news sentiment in carbon price prediction of China’s carbon markets
title The role of online news sentiment in carbon price prediction of China’s carbon markets
title_full The role of online news sentiment in carbon price prediction of China’s carbon markets
title_fullStr The role of online news sentiment in carbon price prediction of China’s carbon markets
title_full_unstemmed The role of online news sentiment in carbon price prediction of China’s carbon markets
title_short The role of online news sentiment in carbon price prediction of China’s carbon markets
title_sort role of online news sentiment in carbon price prediction of china’s carbon markets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838308/
https://www.ncbi.nlm.nih.gov/pubmed/36627425
http://dx.doi.org/10.1007/s11356-023-25197-0
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