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<p>Against the backdrop of accelerating global financial integration, China's new energy market has experienced exponential growth. This study aims to explore the time-varying interdependencies between China's new energy market and multiple critical macroeconomic determinants—including the status of sustainable development, commodity markets, and uncertainty factors—to reveal systemic risk transmission pathways and inform market stability policies. By integrating nonlinear Granger causality tests with Bayesian Large Time-Varying Parameter Vector Autoregression models, we capture intricate dynamic interaction mechanisms often overlooked within conventional linear, low-dimensional variable analysis frameworks. Results indicate that green bonds and technological progress exert positive effects on new energy market returns, whereas ESG (National Securities Environmental, Social, and Governance 300 Index) equities and green electricity markets are prone to generate negative shocks to the new energy market due to policy and supply-demand imbalances. Although rising crude oil prices typically guide capital flows towards renewable energy, WTI (West Texas Intermediate) crude oil offers unreliable hedging due to high volatility, with gold exhibiting similar characteristics. Notably, a significant bidirectional non-linear causal relationship exists between uncertainty factors and market volatility, intensifying during major events. The interaction between China's new energy market and macroeconomic factors reveals multi-layered dependencies and time-varying characteristics.</p>

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Risk-volatility interdependence in China's new energy market: evidence from critical macroeconomic determinants

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Yuanying Jiang,
  • Yan Chen,
  • Hao Nong

摘要

Against the backdrop of accelerating global financial integration, China's new energy market has experienced exponential growth. This study aims to explore the time-varying interdependencies between China's new energy market and multiple critical macroeconomic determinants—including the status of sustainable development, commodity markets, and uncertainty factors—to reveal systemic risk transmission pathways and inform market stability policies. By integrating nonlinear Granger causality tests with Bayesian Large Time-Varying Parameter Vector Autoregression models, we capture intricate dynamic interaction mechanisms often overlooked within conventional linear, low-dimensional variable analysis frameworks. Results indicate that green bonds and technological progress exert positive effects on new energy market returns, whereas ESG (National Securities Environmental, Social, and Governance 300 Index) equities and green electricity markets are prone to generate negative shocks to the new energy market due to policy and supply-demand imbalances. Although rising crude oil prices typically guide capital flows towards renewable energy, WTI (West Texas Intermediate) crude oil offers unreliable hedging due to high volatility, with gold exhibiting similar characteristics. Notably, a significant bidirectional non-linear causal relationship exists between uncertainty factors and market volatility, intensifying during major events. The interaction between China's new energy market and macroeconomic factors reveals multi-layered dependencies and time-varying characteristics.