With the continuous development of the shipping market, the China Containerized Freight Index (CCFI) serves as an important indicator for measuring the state of the global container shipping market, and research on its fluctuation characteristics is conducted to help market participants better grasp market dynamics and formulate effective market strategies. To address the issue that CCFI fluctuations are influenced by multiple factors, this paper focused on the composition of the CCFI, selected five major representative routes. First, decomposed the freight index of each route using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm optimized by particle swarm adaptation. Second, reconstructed the components into high-frequency and low-frequency parts based on the variance contribution rate. Finally, the BEKK-GARCH model was used to analyze the volatility effects of the original series and the three groups of reconstructed series for the selected routes, and the volatility relationships between different route markets were obtained. The research results show that the impact of major events on CCFI fluctuations is profound, while the impact of short-term market behaviors and sudden events is smaller in magnitude, shorter in duration and higher in frequency; bidirectional spillover effects exist among the trend terms of the freight indices of all routes, and these effects are transmitted to one another.