Forecasting EUA futures volatility with geopolitical risk: evidence from GARCH-MIDAS models

Hengzhen Lu, Qiujin Gao (), Ling Xiao and Gurjeet Dhesi
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Hengzhen Lu: Nanjing University of Aeronautics and Astronautics
Qiujin Gao: Royal Holloway, University of London
Ling Xiao: Royal Holloway, University of London
Gurjeet Dhesi: Bucharest University of Economic Studies

Review of Managerial Science, 2024, vol. 18, issue 7, No 6, 1917-1943

Abstract: Abstract This paper examines whether the information contained in geopolitical risk (GPR) can improve the forecasting power of price volatility for carbon futures traded in the EU Emission Trading System. We employ the GARCH-MIDAS model and its extended forms to estimate and forecast the price volatility of carbon futures using the most informative GPR indicators. The models are examined for both statistical and economic significance. According to the results of the Model Confidence Set tests for the full-sample and sub-sample data, we find that the extended model, which accounts for the threat of geopolitical risk, exhibits superior forecasting ability for the full-sample data, while the model that includes drastic changes in geopolitical risk in Phase II and the model that considers serious geopolitical risk in Phase III have the best predictive power. Moreover, all GPR-related variables we use contribute to increasing economic gains. In particular, the threat of geopolitical risk contains valuable information for future EUA futures volatility and can provide the highest economic gains. Therefore, carbon market investors and policymakers should pay great attention to geopolitical risk, especially its threat, in risk and portfolio management.

Keywords: Volatility forecasting; Geopolitical risk index; Carbon futures; GARCH-MIDAS models; Economic gain (search for similar items in EconPapers)
JEL-codes: C32 G17 Q47 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11846-023-00722-0

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