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In the modern world, financial markets play an important role in the economy and people’s lives. They provide access to financial resources and are also a source of profit for many companies. However, instability in the financial markets can lead to serious consequences such as financial crises and loss of investor confidence. In this regard, modelling the financial market dynamics becomes increasingly relevant. This work considered the use of fuzzy mathematics for this purpose. Fuzzy mathematics is a branch of mathematics that studies methods and algorithms for dealing with fuzzy data and fuzzy objects. It allows to consider uncertainty and incompleteness of information, which is especially important in the financial markets where data is often incomplete and inaccurate. The purpose of this research is to establish the relationship between financial asset prices while using behavioural factors (investor sentiment), fundamental (market returns), and microstructural ones (company size, ratio of book and market values of the company). The application of fuzzy mathematics in financial modelling will improve the accuracy and reliability of forecasts as well as increase the stability of the model to various sources of uncertainty.
Polekhina et al. (Sat,) studied this question.