Risk Spillover Effects Among China’s Green Financial Markets Under Artificial Intelligence Shocks
Yan Wang, Jining Wang, Lei WangThis study examines risk spillovers among China’s green financial markets using the TVP-VAR-BK model. An Artificial Intelligence (AI) technology attention index is constructed and combined with an AI industry development index to capture AI shocks. The TVP-VAR-SV model is then employed to examine how these AI shocks interact with risk spillovers among China’s green financial markets. The results reveal that: (1) China’s green financial markets exhibit noticeable risk spillovers, mainly driven by short-term risk spillover, with considerable heterogeneity in markets’ roles as net risk transmitters and receivers across frequency horizons. (2) Risk spillovers are highly time-varying, increasing during periods of geopolitical tensions, public health crises, and industrial policy adjustments, but weakening as external conditions stabilize. Risk spillovers are predominantly short-term, except during the rapid development of generative AI, when noticeable long-term effects emerge. (3) The posterior mean responses of risk spillovers among China’s green financial markets to AI technology attention and AI industry development shocks exhibit time-varying characteristics and frequency-dependent heterogeneity, with predominantly positive and dynamic patterns. However, the 90% posterior credible intervals include zero during some periods, and these findings should therefore be interpreted as indicative dynamic patterns rather than conclusive evidence of effects credibly different from zero.