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<p>This research investigates the dynamics of extreme risk spillovers between commodity markets (energy, metals, and agriculture) and the green finance from November 2013 to December 2023. We enhance traditional risk measurement models by combining Generative Adversarial Networks (GANs) from deep learning with the GARCH model to generate model-estimated distributions, thus avoiding errors associated with manually specified parameters, and then conduct a conditional quantile analysis. Empirical results indicate a significant extreme risk correlation and asymmetry between these markets. The downside risk spillover effect from the commodity market to the green finance market is more pronounced than the upside risk. Notably, the metal commodity market, particularly gold and copper, exhibits the highest extreme risk spillover effect on the green finance market, whereas the agricultural product market demonstrates a relatively weaker effect. Moreover, we observe that the green bond market shows substantial resilience to commodity market fluctuations, while the clean and renewable energy sector is more vulnerable to such fluctuations. Additionally, financial stress and the USD index emerge as key factors influencing the systemic risk between the commodity markets and green finance markets.</p>

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Extreme Risk Spillover from Commodity Markets to Green Finance Markets: New Evidence Utilizing GAN and GARCH Model

  • 期刊论文

  • 发表日期：

    2025年6月4日

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  • Jiaojiao Yang,
  • Xiuguo Gong,
  • Ancheng Fang

摘要

This research investigates the dynamics of extreme risk spillovers between commodity markets (energy, metals, and agriculture) and the green finance from November 2013 to December 2023. We enhance traditional risk measurement models by combining Generative Adversarial Networks (GANs) from deep learning with the GARCH model to generate model-estimated distributions, thus avoiding errors associated with manually specified parameters, and then conduct a conditional quantile analysis. Empirical results indicate a significant extreme risk correlation and asymmetry between these markets. The downside risk spillover effect from the commodity market to the green finance market is more pronounced than the upside risk. Notably, the metal commodity market, particularly gold and copper, exhibits the highest extreme risk spillover effect on the green finance market, whereas the agricultural product market demonstrates a relatively weaker effect. Moreover, we observe that the green bond market shows substantial resilience to commodity market fluctuations, while the clean and renewable energy sector is more vulnerable to such fluctuations. Additionally, financial stress and the USD index emerge as key factors influencing the systemic risk between the commodity markets and green finance markets.