Abstract
Based on the daily data of the 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.
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