Analysis Of Stock Price Fluctuation Based On Two-dimensional Stochastic Ising Spin Model

In recent years,due to the rapid development of computers,the stock market is regarded as a non-linear statistical dynamics system.The use of theoretical physical knowledge and various physical models such as the Ising model to study the price formation mechanism and market characteristics of the stock market has become a new study.hot spot.Driven by its application in financial markets,we studied the mean field equation of the extended version of the dynamic model Ising model,where the external(magnetic or news)field is endogenous as a state variable representing the smooth moving average of the past.This new The model represents a simplification of the interaction between transients.This article has completed the construction of a price formula based on the theory of the Ising spin model.The introduction section briefly introduces the research background and significance,research methods and innovations of this article.We analyze the changes in the thermodynamic properties of the spin system from the classic two-dimensional Ising model to the spin glass model,considering noise.The dependence of critical values(critical temperature,internal energy,entropy and specific heat)and ground state energy was found.Thus it is concluded that we should use the Ising model with low noise in the analysis of stock market volatility analysis.We study excess demand and supply to investigate the impact of the economic cycle(through the external economic realm)on stock price volatility.Then,the excess demand and supply extracted by Ising magnetization were used to predict stock prices based on the effects of time,market temperature,and economic fields,and hysteresis fields and corresponding parameters were plotted and discussed.It is found that the characteristics of the economic field and the market temperature have a competitive and significant effect on price changes,leading to different characteristics of stock price changes in the lagging line,which implies a multidimensional and complex relationship between input and output.An extended version of the dynamic average field Ising model is analyzed,and the relative importance of the instantaneous variable and past social opinions to form the next value of the state variable is quantified.The external field is endogenized to represent past smooth moving average state variables.The model captures,through simple settings,the imitation of interactions between instant social networks and past social coordination trends.Moreover,a thorough analysis of chaotic behavior is shown,which manifests itself within certain parameter ranges.Finally,we investigated four cases,where slow changes in control parameters would cause transitions through bifurcation boundaries.These schemes are provided as a possible simplified model for fluctuations in the stock market.In the experimental research part,using Matlab programming and computer simulation,the parameter seepage probability was simulated with different values,and the simulation sequence of the yield was obtained.At the same time,the real market Shanghai index SSE was added for research and comparison.The results show that this model can well simulate the fluctuation of stock prices.