关键词: 股票市场；时间序列数据；复杂网络；分形特征

Abstract: Based on the closing price data of Shenzhen Component Index in Chinese stock market from 2000 to 2010, it turned the component index time series into complex networks by the visible diagram method, calculates, analyzed these complex networks' topological structure index, and found that these networks have the typical network characteristics of a small world and self-similarity, being scale-free. Finally, it gave an explanation in detail of this phenomenon. The study finds that a new perspective to explore the complexity of the financial system and its internal structure can be acquired by turning the financial time series into complex networks, which provides a new way of thinking to predict financial markets.

Key words: stock market; time series data; complex network; fractal characteristic