This　study　investigates　the　dynamic　return　dependence　between　China＇s　real　estate　and　financial　markets　using　a　quantile　coherency　framework.　Quantile　coherency　decomposes　tail　dependence　across　different　frequencies,　thereby　capturing　interdependencies　across　business　cycles.　We　compare　periods　before　and　after　two　major　shocks　-　the　2015　Stock　Market　Crash　and　the　COVID-19　pandemic　-　examining　both　long-run　and　short-run　dependence　to　reveal　how　extreme　negative,　normal,　and　positive　market　conditions　reshape　inter-sector　linkages.　To　assess　systemic　importance,　we　construct　quantile　coherency　networks　to　measure　the　overall　connectedness　structure　across　market　conditions　and　business　cycles　and　apply　an　Entropy-Weighted　TOPSIS　(EW-TOPSIS)　method　to　identify　key　firms　under　varying　market　conditions.　Our　findings　reveal　that　the　2015　crash　intensified　systemic　co-dependence　primarily　in　extreme　negative　and　positive　regimes,　whereas　the　COVID-19　pandemic　have　stronger　effects　during　normal　and　positive　conditions.　By　effectively　pinpointing　systemically　important　firms,　the　EW-TOPSIS　framework　underscores　the　centrality　of　the　banking　sector　and　highlights　the　role　of　the　real　estate　market　as　a　secondary　channel,　especially　during　short-term　business　cycles,　thereby　offering　guidance　for　targeted　risk　prevention　strategies.