Climate risk and energy futures high frequency volatility prediction

Xue Gong, Ping Lai, Mengxi He and Danyan Wen

Energy, 2024, vol. 307, issue C

Abstract: This study explores the impact of climate risk on the volatility of energy futures, including heating oil, crude oil, and natural gas. In particularly, employing the heterogeneous autoregressive model and its extensions, we find that incorporating climate risk information significantly improves predictive accuracy for high-frequency volatility of energy futures both in- and out-of-sample. These results are robust across different forecasting mechanisms and periods. Additionally, we demonstrate that climate risk provides incremental information compared with existing predictors of energy futures volatility, leading to improved prediction accuracy when combining various predictors. Finally, we demonstrate that considering climate risk can lead to increased economic gains for investors in heating oil and crude oil markets. Our findings provide valuable insights for market participants in the realms of energy portfolio selection and risk management.

Keywords: High-frequency data; Climate risk; Volatility prediction; Energy futures; Forecast combination (search for similar items in EconPapers)
JEL-codes: G15 G17 Q47 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:307:y:2024:i:c:s0360544224022400

DOI: 10.1016/j.energy.2024.132466

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