APPLICATION OF FUZZY SETS IN THE PROBLEM OF PREDICTING THE DYNAMICS OF SECURITIES BEHAVIOR

Solobuto Aleksei Viktorovich, Pavlov Valeriy Anatolyevich

This paper explores the application of fuzzy set theory as a tool for predicting the behavior of stock prices on the exchange. Fuzzy set theory is used to account for the uncertainty, incompleteness, and subjectivity of information inherent to the stock market, where price movements are often determined by numerous factors that cannot be precisely formalized. To implement this approach, informative features influencing stock prices were selected. Each of these features was associated with fuzzy terms (such as "low volume," "high price," "overbought," etc.), after which fuzzy inference rules were formulated to reflect expert-based or empirically identified relationships between the features and the expected price movement direction. Thus, fuzzy set theory represents a flexible and interpretable approach, especially useful in situations of high uncertainty and the need to incorporate expert intuition, which are typical in stock market analysis.

Keywords:stocks, fuzzy sets, membership function, classification task, indicators, fuzzy inference