This　paper　aims　to　uncover　patterns　of　financial　risk　spillover　between　Chinese　financial　institutions　and　investigate　influencing　factors　across　various　timescales　and　periods.　First,　we　decompose　the　transaction　prices　of　financial　institutions　using　the　maximal　overlap　discrete　wavelet　transform　(MODWT).　Using　the　copula　model,　we　construct　multiscale,　multiperiod　interconnected　networks　between　Chinese　financial　institutions　at　different　timescales.　Then,　we　measure　risk　spillover　between　financial　institutions　using　the　dynamic　Delta-conditional　value-at-risk　(Delta　CoVaR)　model.　Subsequently,　we　integrate　the　correlation　matrixes　into　a　spatial　econometric　model　to　explore　the　influencing　factors　of　risk　spillover　between　financial　institutions　at　different　timescales　and　in　different　periods　using　samples　of　27,　42　and　78　financial　institutions　listed　in　China　from　2008　to　2023.　Our　results　highlight　the　critical　role　of　banking　and　securities　institutions　in　transmitting　network　risk,　although　the　importance　of　banks　is　found　to　decrease　over　time.　During　financial　events,　the　clustering　trend　within　the　banking　industry　decreases.　A　rise　in　stock　market　returns,　the　size　of　financial　institutions,　market-to-book　ratios　or　financial　leverage　increases　the　risk　spillover　to　other　related　financial　institutions.　Conversely,　rising　asset　returns　lead　to　a　reduction　in　risk　spillover　to　other　related　financial　institutions.　Based　on　these　findings,　we　propose　recommendations　for　preventing　financial　risks.