This study investigates financial interconnectedness and systemic risk within the European financial sector, focusing on a network of 29 financial institutions between 2007 and 2024, using stock price data. Commonly used methodologies, such as the Spillover Index, leave important questions unanswered, particularly regarding the statistical significance of directional spillovers of shocks among individual institutions and the appropriate choice of rolling-window width for the total connectedness plot, that is used for assessing the extent and nature of the time-varying spillovers. The goal of the study is to determine the correct window width for the Spillover Index methodology, based on the statistical significance of spillover effects. The authors leverage the Dynamic Conditional Correlation (DCC)-GARCH to examine pairwise dynamic correlations, offering evidence into the persistence and strength of linkages that complement the Spillover Index approach. Furthermore, the authors propose a novel “Average Dynamic Correlation” plot derived from the DCC-GARCH results, providing an alternative visualization of network-wide connectedness that is conceptually comparable to the “Net Volatility Spillovers” plots but grounded in a different measure of co-movement. Analysis of pairwise dynamic correlations reveals evidence of stronger long-term financial linkages compared to short-term ones within the network of European financial institutions, with a few cases of disconnectedness, where no short- or long-term impact is significant. This finding complements the practical application of the Spillover Index methodology, suggesting wider rolling-window widths better capture enduring total connectedness in the European financial system. This study thus offers both critical methodological refinements and a new analytical tool for assessing financial interconnectedness and systemic risk.