Cross-Market Risk Spillovers in China: A Multidimensional and Nonlinear Transmission Perspective

This paper investigates the non-linear characteristics and heterogeneous evolution of cross-market risk transmission in China by constructing a multi-layered analysis framework that integrates linear spillovers, non-linear transmission, and tail risk diffusion. By employing the Diebold–Yilmaz spillover index, effective transfer entropy (ETE), and quantile vector autoregression (QVAR), we systematically measure the dynamic connectedness structures and transmission pathways across key financial markets and strategic real-economy sectors. Our empirical results yield several critical insights. First, the Chinese cross-market risk network exhibits significant state-dependence and asymmetric features, where negative shocks generate stronger spillover intensities than positive ones, and systemic connectedness intensifies substantially under extreme quantile conditions, demonstrating pronounced non-linear amplification effects. Second, the high-tech sector acts as a persistent net source of non-linear information flow, which is consistent with the influence of industrial technology cycles on financial markets rather than constituting direct causal evidence. Third, the real estate market displays high network centrality, operating as a predominant net risk receiver and the ultimate heavy-bearing terminal of systemic stress. Finally, time-varying network analysis reveals that major external shocks markedly elevate network density and overall coupling, triggering synchronized risk resonance. These findings unveil the structural mechanics of risk diffusion under emerging market conditions, offering novel empirical evidence and structural insights for macroprudential regulation and cross-market risk governance.