Abstract

The investment market is a complex competitive environment where speed and accuracy of decision-making play a crucial role. Understanding sentiment and asset behavior is key to forecasting and successful investment portfolio management. The results of information analysis confirm the hypothesis of the effectiveness of food market assets, and this in turn proves the possibility of increasing the portfolio's profitability by including food sector assets in it. Creation of an information analysis system for the purpose of segmentation of the contained portfolio is an urgent task, which will allow obtaining real and objective information about the potential risk and profitability of various assets. The paper provides an overview of specialized applied software products that are available on the Internet and are used to analyze financial data. An overview of modern information technologies, which allow convenient processing, visualization of data and forecasting of asset price movements, was carried out. An alternative version of the own information system of analysis is proposed, which focuses on the assets of the food sector. The main task of the created information system is to provide convenient tools for market data analysis, visualization and forecasting of price movements. The main functionalities of the created system are described, including a visual comparison of historical data, price movement forecasting using machine learning, and recommendations on the optimal content of the investment portfolio. The conducted example of the analysis demonstrates how the received information will help to reduce risks and increase the efficiency of decision-making, when managing a portfolio that contains assets of the food sector. The results of the work show that in the case of a small set of assets and, accordingly, restrictions on the diversification of capital investments, the use of such information systems in the field of food products is effective and profitable. The presented technique also demonstrates that an investor, even with non-professional knowledge in the field of programming and information and communication technologies, can effectively use them to create specialized systems for data analysis, visualization and forecasting.

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