Development and Design of an Expert System for Stock Price Analysis

Discusses the development of an expert system for stock market analysis using artificial intelligence technologies. The architecture of the system is presented, which includes a knowledge base, a logical inference mechanism, and a user interface. The key stages of development are described: from the collection and preprocessing of financial data to the implementation of analysis algorithms in Python using NumPy, Pandas libraries and machine learning methods. Special attention is paid to the analysis of existing solutions (WallStreetZen, SeekingAlpha) and the choice of tools (VS Code, QT Designer). Examples of the implementation of the main components of the system are given, including the processing of time series of stock quotes and visualization of results. The developed system demonstrates its effectiveness in solving forecasting problems and can be useful to financial market participants.