MULTIFACTOR REGRESSION ANALYSIS FOR ASSESSING CURRENT AND PROJECTED STOCK RETURNS

The article examines the theoretical and methodological foundations of applying multifactor regression analysis to assess the current and forecasted returns on shares issued by companies in Uzbekistan's corporate sector. A methodological approach to developing regression models is proposed, encompassing the formation of a system of financial indicators, the selection of informative factors, multicollinearity analysis, and the estimation of model parameters using the ordinary least squares method. Using JSC "O'zRTXB" as an example, the study examines the applicability of the proposed approach to identifying relationships between an issuer's financial characteristics and the returns on its shares. The analysis demonstrates how regression modelling can quantify the identified relationships and provide a computational basis for forecasting share returns over subsequent periods. Directions for further methodological improvement are identified, including expanding the sample of issuers and validating the predictive capabilities of the models. The findings may be used to develop analytical tools for assessing the investment attractiveness of shares and supporting investment decision-making in Uzbekistan's capital market.

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