Scientific Journal of KubSAU

The work used methods of system analysis, monographic, structural and logical, economic-statistical, mathematical continuous and discrete, settlement and constructive methods as well as software tools of linear cellular automata. Usage of each method was based on their functionality, thus ensuring the accuracy of the findings and scientific positions. In this article we attempt to predict the dynamic behavior of the financial market elements, to use on the basis of a linear cellular automaton computer tools and methods of nonlinear science for adequate numerical reflection measure various risks, primarily financial and economic risks, as well as to show the power of computer graphics, computer mathematics system linear cellular automata, to emphasize an important philosophical role of visualization. The authors of the work programmed linear cellular automaton based on Python 2.7 software platform in the form of application. The program validates the predictive model on the adequacy of the selected coloring, is forecast error and builds polygons predictive model and input data on the same graph. The proposed research area is relevant to the processes in the financial and economic system, bringing in useful innovative elements in the generalized forecast that do not exist in continuous classical methodology