Non-equilibrium Networks Evolution And Self-organization Criticism In Financial Markets

In 1967, Milgram proposed the theory of "six degrees of separation", and in 201 ,the average distance between two households on Facebook was only about 4.74. People live in a very complex and rapidly changing era. The Thai baht fluctuation in 1997 caused by monetary policy in Thailand, in just a few months, evolved into the Asian financial crisis. Just 10 years later, the subprime mortgage crisis eventually swept the world into a global financial crisis. In the current information age, the research on the complex and fragile network is becoming more and more urgent, and the challenges are extremely difficult.In this paper, we first introduce the Erdos-Renyi random model, exponential growth model and Barabasi-Albert scale-free random network model. The evolution process and properties of the physical quantities such as average degree and degree distribution function are derived. We can obtaine that the degree distribution function is exponential distribution in the evolution of non-preferential random network. In the linear precedence network, the average degree is k(s) (?) s-?,distribution function is P(k) (?) k-?, obeying the power-law distribution. That is a typical scale-free network, and obey this rule: ?(?-1) = 1 . For instance, in the B-A random network model, ?=3,?=1/2. Then the computer simulations were conducted. We find that the larger the random network, the smaller the fitting error.we try to present the price dynamics of financial markets through the self-organized criticality of complex networks. We will be divided into 3 different categories of investors: fundamentalist, chartists and random traders. And introduces two types of information impact: the influence of global financial markets and the influence of investors neighbors. When the information of one investors (except for the random traders) accumulated to a certain threshold, he will affect the investment behavior of the neighbors, thus forming an avalanche effect. This paper constructs a self-organized critical network model of financial market. In the market, we first consider only the fundamentalist and chartists without considering the presence of random traders, that is CF model. We can get the global price series, the normalized returns series and the degree distribution function of the normalized return. Then compared with the actual financial market price, the CF model is obvious fat tails distribution, which is consistent with the characteristics of the actual financial market. Then by changing the proportion of fundamentalist and chartists to change the market structure of population. We find that the proportion of these two groups and the size of the random network have little effect on the fat tail distribution. The financial market is mainly affected by the information.Therefore, the financial market must do a good job of information management and control, to ensure the accuracy and confidentiality of information. Leaks and false information are disruptive to fragile financial markets. It is suggested that the government should strengthen the opacity of information disclosure in order to stabilize financial markets. Finally, adding random traders, we find that little random traders have a very large impact on price series of the market. Random traders only from 1% change to 5% ,the standardized returns quickly stabilized and no longer show volatility and fat tail distribution. It can be seen that the influence of random traders is very obvious. That financial markets have a strong human nature. In the special period, the government can increase the number o random traders to stabilize the financial market.