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  • Development of an Algorithm and Proposals for Automating the Process of Building a Forecast for Stock Prices of Leading IT Companies

Development of an Algorithm and Proposals for Automating the Process of Building a Forecast for Stock Prices of Leading IT Companies

Student: Bychenko Darya

Supervisor: Victor Popov

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2020

In a financially unstable and high-risk market, such as the stock market, it is important to have a very accurate and reliable forecast of the future price movement trend. It is known that forecasting stock prices has always been relevant and attractive among analysts. Over the entire history of stock price forecasting, a sufficiently accurate algorithm has not been invented that could effectively predict the change in quotes. It is believed that the main problem of price forecasting is the difficulty of creating a model of stock market dynamics. In this paper, the first chapter highlights the theory of various forecasting methods, analyzes methods using literary sources, considers the stock market, and analyzes a new approach to the analysis of securities markets - fractal analysis. The second chapter of the work discusses forecasting methods for the collected data, methods for modeling them and the mechanism of work, as well as methods for calculating accuracy and methods for improving the forecast. The third chapter contains the practical part of the work, which develops a forecasting algorithm and simulates a business process to automate the process of forecasting stock prices. The final product of work can be used by investors, managers and traders to forecast stock prices in the real financial market to improve the efficiency and quality of investment decisions made by improving the process of building projections for future stock price values.

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