INNOVATIVE ANALYSIS AND MONITORING OF FINANCIAL RESOURCES ON THE MOSCOW STOCK EXCHANGE

UDC 336.7
4DOI: 10.36871/2618­-9976.2024.09.007

Authors

Ivan S. Tuyakhov,
Student, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Yuriy Yu. Kochinev,
Doctor of Economic Sciences, Professor, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Alexander S. Sokolitsyn,
Doctor of Economic Sciences, Professor, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

Abstract

This article is devoted to the development and application of an abnormal volume Bot based on the Python programming language for automatic analysis of financial data of the Moscow Stock Exchange in real time. The paper describes four key stages of the bot's operation: determining the average monthly trading volume, obtaining realtime data, analyzing historical closed candlesticks and identifying anomalies in trading volumes. A specific example of using a bot using the example of a SIBN stock is given, demonstrating its ability to respond to abnormal events, such as the announcement of dividends. The effectiveness of the bot is shown by sending notifications to the Telegram channel, which provides traders with the necessary information to make informed decisions in the financial markets. The developed tool provides traders with the opportunity to quickly respond to changes in the market, identifying both potential opportunities and risks associated with financial assets. At the same time, the main focus is on data analysis and forecasting of market trends, which is an important aspect of modern financial analysis.

Keywords

Financial analysis, Trading, Investment, Automation, Anomaly, Algorithm, Market change, Forecasting, Response