Modeling climate policy uncertainty into cryptocurrency volatilities

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@Article{Ding:2025:irfa,

• author = "Shusheng Ding and Xiangling Wu and Tianxiang Cui and John W. Goodell and Anna Min Du",
• title = "Modeling climate policy uncertainty into cryptocurrency volatilities",
• journal = "International Review of Financial Analysis",
• year = "2025",
• volume = "102",
• pages = "104030",
• keywords = "genetic algorithms, genetic programming, Cryptocurrency markets, Climate policy uncertainty, Volatility forecasting",
• ISSN = "1057-5219",
• URL = "https://www.sciencedirect.com/science/article/pii/S1057521925001176",
• DOI = "doi:10.1016/j.irfa.2025.104030",
• abstract = "Climate change is a highly controversial topic within the socioeconomic context. Climate Policy Uncertainty (CPU) arises from the process of climate policies formulation and implementation. This uncertainty impacts financial market volatilities, including cryptocurrency markets. In this paper, we demonstrate the substantial role of CPU in forecasting volatilities in cryptocurrency markets using Genetic Programming (GP). Our study shows that different cryptocurrency markets respond differently to CPU across time scales. Our paper contributes to the literature by illustrating the impact of CPU on cryptocurrency market volatilities and analyses it across different time horizons. Second, we build three volatility forecasting models for different cryptocurrency markets by incorporating CPU, which outperform traditional models. Our models can thereby illuminate portfolio construction and hedging strategies, providing valuable insights for investors and policymakers",

}

Genetic Programming entries for Shusheng Ding Xiangling Wu Tianxiang Cui John W Goodell Anna Min Du

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