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<p>The resilience of the green bond market amidst escalating geopolitical risks (GPR) and economic policy uncertainties (EPU) is a critical concern for global financial stability. However, traditional models fail to capture its asymmetric risk transmission under extreme conditions. This study addresses this gap by employing a Quantile Vector Autoregression-Dynamic (QVAR-DY) spillover framework, integrated with dynamic rolling windows and frequency-domain decomposition, to analyze monthly data from China’s green bond market (January 2010 to December 2024). The results reveal profound asymmetries: green bonds act predominantly as a net risk receiver during extreme downside markets. At the same time, GPR and EPU consistently function as net transmitters, with total spillover intensity surging by approximately 15% during crises. Notably, we identify a “conditional resilience” of green bonds—they can temporarily become net risk exporters under strong positive policy signals (e.g., post-COP26). The transmission mechanisms are also scale-dependent: short-term spillovers are driven by investor sentiment, while long-term patterns are anchored by structural factors and “patient capital.” These findings challenge the static view of green bonds as safe havens, underscoring the necessity of state-dependent, multi-horizon risk monitoring. We advocate for dynamic macro-prudential frameworks and asymmetric risk management strategies to enhance market stability and guide sustainable investment.</p>

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Analysis of dynamic network spillover effects in the green bond market amid geopolitical risks and economic policy uncertainties

  • 期刊论文

  • 发表日期：

    2026年4月1日

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  • Chunyan Jiang,
  • Wanqi Li,
  • Runze Ding

摘要

The resilience of the green bond market amidst escalating geopolitical risks (GPR) and economic policy uncertainties (EPU) is a critical concern for global financial stability. However, traditional models fail to capture its asymmetric risk transmission under extreme conditions. This study addresses this gap by employing a Quantile Vector Autoregression-Dynamic (QVAR-DY) spillover framework, integrated with dynamic rolling windows and frequency-domain decomposition, to analyze monthly data from China’s green bond market (January 2010 to December 2024). The results reveal profound asymmetries: green bonds act predominantly as a net risk receiver during extreme downside markets. At the same time, GPR and EPU consistently function as net transmitters, with total spillover intensity surging by approximately 15% during crises. Notably, we identify a “conditional resilience” of green bonds—they can temporarily become net risk exporters under strong positive policy signals (e.g., post-COP26). The transmission mechanisms are also scale-dependent: short-term spillovers are driven by investor sentiment, while long-term patterns are anchored by structural factors and “patient capital.” These findings challenge the static view of green bonds as safe havens, underscoring the necessity of state-dependent, multi-horizon risk monitoring. We advocate for dynamic macro-prudential frameworks and asymmetric risk management strategies to enhance market stability and guide sustainable investment.