Influences of sentiment from news articles on EU carbon prices

Jing Ye and Minggao Xue

Energy Economics, 2021, vol. 101, issue C

Abstract: In this paper, we calculate the carbon tone index that reflects sentiment in news articles through a self-built dictionary. We study the effect of carbon tone index on carbon price return in the period from September 19, 2017 to October 9, 2020. In addition, we employ the Latent Dirichlet Allocation (LDA) method to explore the differential influences of different topic carbon tone indexes on carbon prices. The market confidence boosted by the approved Market Stability Reserve (MSR) policy led to a continuous increase in volume in 2018. Using two subsample periods divided by the implementation of MSR, we explore the problem whether the increased high volume changed the speed of information absorption in carbon market. Quantile regression with control variables (coal, oil, natural gas, electricity and stock prices) is used to test the robustness of the estimated results. The empirical results show that carbon tone index is closely associated with changes in carbon prices and the efficiency of carbon market is improved after MSR. Finally, we use all carbon tone indexes at the 10% significance level in eight predictive models and show the economic value of the optimal predictive model. In summary, carbon tone index has a strong predictive power for carbon prices.

Keywords: Textual analysis; Carbon pricing; Carbon tone index; LDA; Carbon price prediction (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988321002929
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:101:y:2021:i:c:s0140988321002929

DOI: 10.1016/j.eneco.2021.105393

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().