Self-organizing Ising Model Of Artificial Financial Markets With Highly Clustered Model

Econophysics is an interdisciplinary formed in the 1990s when physicists introduced physical research methods into the field of economics in order to explain some abnormal statistical properties of real financial data which are difficult to describe by classical economics theory.At the beginning,most of researches of econophysics focused on statistical properties of real financial data.At that time,researchers used the theories and methods of physics,especially the tools and methods in statistical physics,to analyze the real financial data,especially the high-frequency data,and obtained many fascinating statistical properties of real financial data.On the other hand,using physical models to build macro or micro models to describe these phenomena is another emphases for research in econophysics.Particularly,the building of micro models to reveal the micro mechanism of some macro financial phenomena has attracted more and more researchers,which is also the main research direction we will devote on.We establish the model based on the tunable clustering scale-free network(HK model)and the self-organizing Ising model proposed by Sornette and Zhou.In HK model,the clustering coefficient(CC)can be tuned by changing the triangle formation probability among nodes(controlled by the parameter m_t).Meanwhile,the degree distribution of this network also satisfies the power-law distribution.In the self-organizing Ising model of financial market,an agent makes a decision to buy or sell a single asset based on the influence of the nearest neighbor,external news and private information.Then their decisions will cause the asset price change in the model.In this model,the influence coefficient of the nearest neighbor on an agent will be updated with time.Based on HK model and self-organizing Ising model,we established a self-organizing Ising model artificial financial market with tunable clustering scale-free underlying network which will have higher CC.Then,in the simulation of this model,we obtained the time series of the logarithmic price and the logarithmic return with different CC.In particular,when m_t=0.0,we reproduced the following stylized facts:the distribution of logarithmic returns satisfies the"leptokurtic and fat tail";the autocorrelation of logarithmic return shows short-range correlation;and the autocorrelation of absolute logarithmic return exhibits long-range correlation.Our work mainly divided into the following five parts:in the first part,we briefly introduced the background,main content and direction of econophysics,as long as the major work of this paper;in the second part,we introduced some basic knowledges in Econophysics and complex networks,we also gave a briefly intruduction to the development of the self-organizing Ising model used in this paper;in the third part,we introduced the establishment process of scale-free networks with tunable CC;in the fourth part,introduced the artificial financial market of Ising model with tunable CC;in the fourth part,we introduced setting of parameters used in our model and discussed the results;finally,we summarize all works.