This　study　constructs　spillover　indices　from　a　volatility　spillover　network　perspective　using　the　Quantile　Vector　Autoregression　(QVAR)　model,　capturing　the　RMB　exchange　rate＇s　tail　risk　and　time-frequency　effects　across　varying　shock　sizes.　Empirical　results　show　that　the　QVAR-based　spillover　index　more　effectively　captures　the　tail　risk　spillover　effects　across　different　quantiles.　In　the　time　domain,　spillovers　between　RMB　exchange　rates　are　dynamic　and　particularly　sensitive　to　extreme　contingencies.　In　the　frequency　domain,　RMB　exchange　rates　demonstrate　significant　spillovers,　primarily　at　low　frequencies.　During　extreme　upward　events,　dynamic　observations　show　high-frequency　spillovers　surpassing　low-frequency　ones　as　dominant　drivers　in　the　tail　spillovers　of　the　RMB　exchange　rate.　Additionally,　the　analysis　of　tail　dependence　indicators　indicates　a　strong　asymmetry　in　RMB　exchange　rate　correlations,　emphasizing　market　participants＇　heightened　sensitivity　to　unfavorable　shocks.　These　findings　can　serve　as　a　reference　for　policymakers　to　strengthen　risk　management　of　the　RMB　exchange　rate.