Carbon Prices Forecasting Using Group Information

Xiaohang Ren, Kang Yuan, Lizhu Tao and Cheng Yan ()
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Cheng Yan: School of Business, Central South University, China

Energy RESEARCH LETTERS, 2024, vol. 4, issue 4, 1-6

Abstract: We select 44 macroeconomic variables as predictors and employ multiple statistical models to forecast EU carbon futures price returns. The predictors in this study are high-dimensional and have the group structure, and we find that, in this case, the accuracy of the high-dimensional models for forecasting carbon prices are higher than traditional time series models. In addition, the introduction of group structure variables into the high-dimensional model improves forecasting performance.

Keywords: Carbon return predictability; High-dimensional models; Group structure (search for similar items in EconPapers)
JEL-codes: C52 C53 Q43 (search for similar items in EconPapers)
Date: 2024
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