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Based on the daily data of American and Chinese stock markets, the dynamicbehavior of a financial network with static and dynamic thresholds isinvestigated. Compared with the static threshold, the dynamic thresholdsuppresses the large fluctuation induced by the cross-correlation of individualstock prices, and leads to a stable topological structure in the dynamicevolution. Long-range time-correlations are revealed for the average clusteringcoefficient, average degree and cross-correlation of degrees. The dynamicnetwork shows a two-peak behavior in the degree distribution.

Adaptive financial networks with static and dynamic thresholds