Corporate information system for exchange rate analysis and commodity money forecasting
Zhengbing Hu, Dmytro I. Uhryn, Yuriy Ushenko, Oksana Yatsko, Oleksandr Kodrianu, Myroslav Kovalchuk, Yu. Ya. Tomka · 2024
An intelligent web portal for analysing and forecasting the exchange rate of commodity money has been developed. The result of this research is a comprehensive system that allows for the analysis of the commodity money market, including price forecasting and risk assessment. The study identified the prophet method for predicting the exchange rate of a commodity unit and the monte carlo method for predicting the value of an investment portfolio with various assets. These methods allow us to reliably determine future trends based on the analysis of available data. To implement the web portal, we used the streamlit framework, which allows us to quickly develop interactive web applications using machine learning and data analysis tools. The scikit-learn library was used to work with machine learning, which has a wide range of tools for applying classical machine learning methods. The yfinance library was also used to retrieve financial data from the Yahoo Finance web service.