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Improvement of carbon price prediction with social factors and mixed-frequency unstructured data | Synapse
March 3, 2026
Improvement of carbon price prediction with social factors and mixed-frequency unstructured data
JK
Jinghao Kang
FY
Fengyu Yang
Jiangnan University
SL
Shi‐Min Li
Shenzhen Polytechnic
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Puntos clave
Improved carbon price prediction incorporates social factors, indicating a significant increase in accuracy for forecasts.
The models achieve predictive gains by integrating mixed-frequency unstructured data alongside traditional indicators.
Utilizing predictive modeling techniques enhances the understanding of the relationship between social dynamics and market behavior.
These findings support the need for a multifaceted approach to carbon pricing strategies, acknowledging social influences.
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Kang et al. (Thu,) studied this question.
synapsesocial.com/papers/69a76778badf0bb9e87e1067
https://doi.org/https://doi.org/10.1016/j.eneco.2026.109190
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