Application of Neuron Networks to Analysis of Currency Rate

Abstract

The article analyzes the application of information technologies to the analysis of the stock market, namely to the study of the dynamics of the Ukrainian currency exchange rate, which will allow us to draw a conclusion about the market as a whole. Exploratory data analysis was used to familiarize and analyze financial data. It is an approach to summarizing, visualizing, and gaining insight into the important characteristics of a data set. When analyzing and predicting the dynamics of complex financial systems, one cannot do without such a powerful tool as the Python programming language and neural network technologies. Neural networks find new successful applications in the practice of management and decision-making, including in the financial and trade spheres, i.e. wherever it is necessary to find a certain hidden regularity and make a forecast of stock market tools aimed at achieving macroeconomic stabilization and dynamic development of the financial market. Forecasting is done the dynamics of stock market instruments, which allows to conduct analysis and make precautionary conclusions and proposals in order to minimize risks related to the pricing of derivatives that arise on the stock market. Neural networks were used to forecast the exchange rate, which allows you to minimize speculative changes in pricing, analyze stock market processes, and take specific steps to improve the situation in terms of optimizing financial strategies. As a result of the analysis, it can be noted that information technologies are widely used in financial spheres and activities. The effectiveness of the use of information technologies for data analysis and the ability of neural networks to one of the most sought-after tasks of financial activity - forecasting the future value of various instruments - have been proven . It can be argued that the best result is given by the combination of information technologies with expert systems, it allows to calculate the value of derivatives prices with great accuracy and to monitor changes in the speed of financial flows. The used technique allows to increase the accuracy of the forecast and to make informed management strategic decisions by the participants of the stock market.