We proposed a method to find the community structure in a complex network by density-based clustering. Physical topological distance is introduced in density-based clustering for determining a distance function of specific influence functions. According to the distribution of the data, the...

By means of a visibility graph, we investigate six important exchange rate series. It is found that the series convert into scale-free and hierarchically structured networks. The relationship between the scaling exponents of the degree distributions and the Hurst exponents obeys the analytical...

Recent works show that complex network theory may be a powerful tool in time series analysis. We propose in this paper a reliable procedure for constructing complex networks from the correlation matrix of a time series. An original stock time series, the corresponding return series and its...

The de-trended cross-correlation analysis (DCCA) is converted to a new form, which turns out to be a periodic function modulated power-law, to evaluate discrete-scale long-range cross-correlation between time series. If the modulator is dominated with one frequency, the derived form will...