Abstract

Analyzing and forecasting financial and stock markets is a strategic goal for investors, analysts, traders, underwriters, top managers of agricultural companies, and other stakeholders to manage the efficiency of both corporate and individual activities. At the same time, methods of modeling market capitalization dynamics differ depending on which institutional group of investors use them, which often leads to contradictory results. In this context, the problem arises of systematizing and improving the theoretical framework for analyzing corporate agricultural enterprises' market capitalization dynamics. The study aims to generalize and systematize the theoretical framework for analyzing the dynamics of the stock market and market capitalization of corporate agricultural enterprises. The study used the following methods: systematization, generalization, monographic analysis, and synthesis. The content of the theories of random expectations, efficient stock market, reflexivity in the stock market, chaos and fractal geometry of price movements, psychological moods of investors, and catastrophes have been summarized. It has been argued and proved that all theories and methodological approaches to analyzing stock market dynamics and market capitalization of corporate agricultural enterprises are dialectically related, are in constant development, and are ultimately aimed at identifying and explaining the patterns of the phenomena and processes under study. It has been shown that quantitative analysis is a methodological superstructure to qualitative analysis aimed at substantiating the identified laws and regularities in the dynamics of price quotations, stock market development, the behavior of investors and stock traders, and market capitalization of corporate issuers. These patterns subsequently become the basis for refining the theoretical and methodological foundations for analyzing the dynamics of the stock market and market capitalization of enterprises, as well as for launching adaptive training and retraining algorithms for neural networks and artificial intelligence systems. Keywords: stock market, market capitalization, equity, behavioural finance, finance theory, corporate agricultural enterprise.

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