Firstly,on the basis of the weighted local-world network model,this paper proposes a weighted financial network model in a new local-world by combining complex networks and financial systems.The main idea is that both the growth way of index distribution and the connection way of two-way selection are added in the weighted local-world network.Using the mean field theory and the simula-tion to get the financial network node degree follows power law distribution and the distribution index is related to the parameters.And the proposed financial network model has hierarchical structure and different matched properties.Secondly,we analyze the financial risk problem with the epidemiological dynamics model of infectious diseases.On the basis of the standard SIRS model of non-right financial network,we propose a SIRS epidemic model and SIRS with direct immune behavior epidemic model,which have the nonlinear transmission capacity and weighted propagation rate.Using the mean-field theory,it is found that the two models can obtain the propagation threshold greater than zero by adjusting the size of the corresponding parameters.And they mainly related to the topology of the financial network and the transmission ability of the financial nodes.Direct immunity behavior can increase the spread of the threshold and narrow the scope of transmission,which can better control the spread of financial risks.Thirdly,based on the stock price data in Chinese stock market,the paper establishes a weighted complex network model of the stock market and analyzes the topological structure of the stock market.We find that here is a certain strong correlation between stocks in stock market.The distribution of nodes in stock network model has the power-law attribute.And the stock network model has the power-law attribute and the small-world character.We also use the SIRS model on weighted-scale financial network to analyze the stock market risk transfer problem,to study the circumstances under which stock risk will be disseminated and to make recommendations on risk early warning monitoring. |