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.
@article{arxiv.1002.3432,
title = {Adaptive financial networks with static and dynamic thresholds},
author = {Tian Qiu and Bo Zheng and Guang Chen},
journal= {arXiv preprint arXiv:1002.3432},
year = {2015}
}