A complex network analysis of risk spillover and linkage effects between green bonds and commodities under the characteristics of the Chinese market

This study focuses on the distinctive characteristics of the Chinese market environment and constructs a composite analytical framework integrating EGARCH, wavelet coherence, QVAR-DY. The unique advantage of this framework lies in its ability to simultaneously deconstruct the risk transmission pathways between green bonds and commodities across multiple dimensions, including "time domain-frequency domain," "mean-tail," and "static-dynamic." Systematic examination reveals significant time-frequency heterogeneity and state dependence in the risk linkage between the two markets: in the short term, it manifests as synchronous responses to high-frequency information; in the medium term, it is driven by economic events and policy factors; and in the long term, it is associated with macroeconomic cycles and the trend of green transformation. During extreme downside periods, green bonds predominantly act as net risk recipients, exhibiting pronounced sensitivity to shocks from energy and non-ferrous metals; under normal conditions, they demonstrate greater independence; whereas in extreme upside periods, risk inflows intensify, and from a long-term perspective, green bonds may transition into net risk transmitters, underscoring the reshaping effect of green transformation on demand expectations for commodities. The findings provide multidimensional evidence for understanding the risk transmission mechanisms between green finance and the real economy, offering valuable insights for risk management and policy formulation.