The Similality Of Volatility Network

The volatility of the stock market has been the focus of research, fluctuations in theoretical studies is quite mature. Alought many models focus on the distribution characteristics of financial data. Such as Fat-tail Distribution and Asymmetry Characteristics. Complex network theory has been developing rapidly since emergence,This paper elaborationes and analysises the similarity and self-similarity of the individual stock volatility network or stock market volatility network at micro and sub-macro level. Comparison the similarity and self-similarity between several stocks and index stocks. And investigate dropped or rise of the same from the time stock market index, try to study the similarity between two networks. This paper is divided into three parts, as follows:The first part mainly introduced the required background and theoretical knowledge about the similarity of volatility network. Including the volatility network of stock market in application research, basic theory of complex network, Related knowledge of stock market and similarity of complex network.The second part focuses on the description of self-similarity in various disciplines at present. Summarized the common characteristics of self-similarity, Then Given definition of self-similarity and simplify the method of calculation, This provides a better understanding of complex network more in-depth study of self-similarity of complex networks provides a ractical application of powerful analytical tool.The third part established complex network model with methods of coarse-grained. with a purpose to analyze some important topological and statistical characteristics, By means of measuring betweenness Centrality (BC) and transition probability, and reveal the regular pattern of the joint fluctuation of stock indices and transactions. And comparison the important state of stock markets. Then we compared the self-similarity of the networks in different time and the similarity between individual stocks and indexes in same time period, so as to illustrate some common features and Personality features of fluctuating networks in same time.In time with rise and drop has highly similar.