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• A signal propagation model for financial granular network is constructed. • Theoretical proofs of fluctuation propagation on financial granular network. • Quantitative analysis of the fluctuation propagation in real financial data sets. Financial markets are usually affected by various factors, such as breaking news or the release of important economic data, which would interrupt normal fluctuations and cause the abruptly increasing of volatility. How the financial markets behave under the impact of sudden external stimulations is of great significance for the analysis and prediction of financial prices. In this article, combining the theory of complex networks with granular computing, the financial granular complex network is constructed, based on which the propagation of fluctuation patterns after the occurrence of abnormal changes are studied. Here, the so-called "abnormal changes" are defined as the sudden and fierce fluctuations of financial prices, which are the non-trivial phenomena commonly existing in financial markets. By constructing the dynamical equations of pattern propagation, the evolution trajectories and the intrinsic characteristic of abnormal volatility patterns in financial granular network are quantitatively and qualitatively discussed. Results reveals the behaviors of the financial granule networks after the occurrence of abnormal fluctuations, and the impact of network topology on the propagation of fluctuation patterns is proved theoretically. In order to verify the validity of theoretical analysis, the empirical studies are carried out by using the real financial data deriving from foreign exchange and stock markets. [ABSTRACT FROM AUTHOR]