  Based on the daily data of American and Chinese stock markets, the dynamic
behavior of a financial network with static and dynamic thresholds is
investigated. Compared with the static threshold, the dynamic threshold
suppresses the large fluctuation induced by the cross-correlation of individual
stock prices, and leads to a stable topological structure in the dynamic
evolution. Long-range time-correlations are revealed for the average clustering
coefficient, average degree and cross-correlation of degrees. The dynamic
network shows a two-peak behavior in the degree distribution.
