A mutual information-based Graph-VARX network analysis of global risk spillovers in the Chinese equity market

External shocks such as oil-price movements, exchange-rate shifts, and global risk sentiment can affect not only aggregate equity performance but also how stress propagates across sectors. This paper aims to (i) map how these global shocks enter the Chinese equity market, (ii) identify which sectors amplify or buffer their transmission, and (iii) provide an interpretable framework that can support stress testing and portfolio risk monitoring. We adopt a complex-systems, network-based perspective and use information-theoretic dependence (mutual information) to learn time-varying inter-sector linkages. Global financial markets are increasingly interconnected, and external shocks transmit unevenly across sectors. We study how oil, currency, and volatility shocks propagate across Chinese equities using a novel Graph-VARX that combines vector autoregressions with network methods to capture both direct responses and inter-sector dependencies. The dataset merges daily sector returns with Brent/WTI prices, USD/CNY, and Volatility Index (VIX). Out-of-sample checks confirm stability (spectral radius ρ = 0.047) and accuracy (RMSE <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mo>≈</m:mo> <m:mn>0.012</m:mn> </m:math> ≈ 0.012 ; MAE <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mo>≈</m:mo> <m:mn>0.009</m:mn> </m:math> ≈ 0.009 ). Results show asymmetric transmission, with the exchange rate the dominant spillover channel. Scenario analysis suggests a +1.5 % RMB appreciation coincides with modest benchmark declines centered in Property and Information Technology, while a +15 % oil increase lifts Materials and Energy and only mildly supports the benchmark. Mutual-information filtering retains 39 of 156 sector links; Utilities, Consumer Staples, and Healthcare act as buffers. Currency dynamics, more than commodity cycles, shape systemic vulnerability and portfolio risks. Further studies extend Graph-VARX to firm-level panels and compare with other emerging markets to test whether hub–periphery patterns are China-specific.