Improvement of carbon price prediction with social factors and mixed-frequency unstructured data

Key Points

• 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.