Modeling Share Prices Based on Investors’ Irrational Behavior

The subject of the research is the economic and socio-psychological aspects of investment behavior in the stock market, which is the most volatile segment of the stock market. The purpose of the study is to develop a methodology for assessing deviations in stock market prices from their rational (fundamental) values. Objectives: to reveal the essence of the market value of shares and its irrational component, which is a set of heuristic estimates of the future benefits of the share owner; to describe the stages of development of behavioral economics considering irrationality in consumer choice models; to analyze research in the field of irrational stock pricing and propose an algorithm for solving the problem. Relevance: Irrational valuation of financial assets can become a catalyst for economic crises. This is why distortions in consumer behavior require government supervision and regulation. Methodology: The authors employed Discounted Cash Flow Model, Logit model, the Least Squares Method, and Lasso Regularization. Research result: The author’s approach to assessing financial heuristics, including a set of indicators that reflect distortions in consumer behavior in the stock market. Based on the results of the study, we concluded that the market value can deviate significantly from rational expectations. We proved that there is a relationship between cognitive distortions and quotation dynamics. However, we found that the methods we considered do not allow us to determine the duration of irrational assessments. Scientific novelty: A new approach to modeling the irrational valuation of stocks has been developed based on the relationship between the deviation of stock prices from their fair values and indicators can be used to make heuristic estimates of future benefits from owning a particular stock. The practical significance: The use of the developed methodology can be beneficial for investors to accurately assess the fair value of their portfolios. Businesses can use it to create models of consumer behavior when developing of financial products. Mega-regulators can use it to analyze investment behavior factors and respond to market distortions in a timely manner.

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