Model for Predictive Analysis of International Trade Based on the Dynamics of Stock Indices (Example of Data from the USA, Canada and UK)

Abstract

Forecasting is one of the tools for assessing the functioning and development of processes, phenomena, objects. This tool has found its application in all areas of research. Among these areas of research, one should single out the direction that is associated with the economy. This is important because such studies help to assess the level of economic development, the welfare of mankind, to find ways for the further functioning and development of various processes, phenomena, objects. To solve the tasks set, various models are used that help to implement a certain forecast scheme. At the same time, the construction of such models involves the implementation of the corresponding stages of modeling. Such modeling steps help determine the type of the final model and implement the required predictive model. Therefore, we pay special attention to the individual stages of predictive modeling. The efficiency of building a predictive model is also determined by the applied problem that needs to be solved in the modeling process. In this paper, we consider the elements of a predictive model for the analysis of international trade. To do this, we use data on the dynamics of stock indices. In particular, we use the dynamics of stock indices, which describe the activities of banking institutions. To build individual elements of the predictive model, we use the apparatus of wavelet theory. Among the tools of wavelet theory, we use wavelet coherence. We also propose an approach for comparing different estimates of wavelet coherence. This approach is based on comparing the corresponding wavelet coherence estimates and visualizing the results. This allows you to better understand the mutual dynamics of stock indices and evaluate the dynamics of international trade. The paper presents various graphs and diagrams that help to understand the logic of the study and the results obtained.