Methodological Aspects of Estimating the Value of Shares of Issuing Companies on the Stock Market

The purpose of the study . Development of a methodology for the estimated value of shares of issuing companies on the stock market based on the values of their investment criteria and indexes of net profit per share. Materials and methods . The study uses analytical and statistical data for the time period 1881-2022 on the market quotations of the S&P500 index and indexes of net profit of companies in terms of E, E6 and E10 shares (E6 and E10 are the moving average of E for the previous 6 and 10 years) for companies included in the calculation of the S&P500 index. Similar data for the time period 1998-2022 of the index-forming Russian companies Gazprom, Nornickel and Rosneft are also used. The research methodology includes statistical methods, methods of comparative analysis, comparison and generalization. Results . Based on the obtained data of regression dependence of the market quotations of the S&P500 index from 1881 to 2022 on the investment criteria of American companies S&P500/E and S&P500/E10, as well as on their net profit indexes in terms of E and E10 shares, it is shown that the objective financial and economic characteristics of companies mainly determine the market price of its shares. The regression dependence of the S&P500 on the E, E10 indexes and on the S&P/E10 investment criterion is characterized as high and very high. The presented S&P/E6 investment criterion, along with the S&P500/E10, has a very high impact on the S&P500 in comparison with other criteria and indexes (data from regression statistics during the dotcom crises from 2000 to 2005 and global crisis phenomena from 2007 to 2010). In most cases, it was revealed: high and very high dependence of the market value of shares of US and Russian issuing companies on the investment criteria P/E6 and P/E10; medium and weak dependence on the indexes E, E6 and E10; weak and very weak dependence on the investment criterion P/E. Conclusion . The results obtained show that to assess the reliable value of shares of issuing companies on the stock market, it is advisable to use the values of investment criteria P/E6 and P/E10. The practical significance of the study lies in testing the developed methodology for estimating the value of shares of issuing companies on the stock market. Stock market participants in choosing preferred investment strategies can use the results of the study. Based on the data obtained on a reliable assessment of the value of shares of issuing companies of the Russian stock market, regulatory organizations have the opportunity to formulate effective management of it in the context of existing negative geopolitical events.

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Publication Details

Journal
Statistics and Economics
Published
2024-10-21
DOI
https://doi.org/10.21686/2500-3925-2024-5-46-54
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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Methodological Aspects of Estimating the Value of Shares of Issuing Companies on the Stock Market

Evgenii Vladimirovich Dorokhov
Statistics and Economics
Financial Risk and Volatility Modeling
article

Methodological Aspects of Estimating the Value of Shares of Issuing Companies on the Stock Market

Evgenii Vladimirovich Dorokhov
article en

Abstract

The purpose of the study . Development of a methodology for the estimated value of shares of issuing companies on the stock market based on the values of their investment criteria and indexes of net profit per share. Materials and methods . The study uses analytical and statistical data for the time period 1881-2022 on the market quotations of the S&P500 index and indexes of net profit of companies in terms of E, E6 and E10 shares (E6 and E10 are the moving average of E for the previous 6 and 10 years) for companies included in the calculation of the S&P500 index. Similar data for the time period 1998-2022 of the index-forming Russian companies Gazprom, Nornickel and Rosneft are also used. The research methodology includes statistical methods, methods of comparative analysis, comparison and generalization. Results . Based on the obtained data of regression dependence of the market quotations of the S&P500 index from 1881 to 2022 on the investment criteria of American companies S&P500/E and S&P500/E10, as well as on their net profit indexes in terms of E and E10 shares, it is shown that the objective financial and economic characteristics of companies mainly determine the market price of its shares. The regression dependence of the S&P500 on the E, E10 indexes and on the S&P/E10 investment criterion is characterized as high and very high. The presented S&P/E6 investment criterion, along with the S&P500/E10, has a very high impact on the S&P500 in comparison with other criteria and indexes (data from regression statistics during the dotcom crises from 2000 to 2005 and global crisis phenomena from 2007 to 2010). In most cases, it was revealed: high and very high dependence of the market value of shares of US and Russian issuing companies on the investment criteria P/E6 and P/E10; medium and weak dependence on the indexes E, E6 and E10; weak and very weak dependence on the investment criterion P/E. Conclusion . The results obtained show that to assess the reliable value of shares of issuing companies on the stock market, it is advisable to use the values of investment criteria P/E6 and P/E10. The practical significance of the study lies in testing the developed methodology for estimating the value of shares of issuing companies on the stock market. Stock market participants in choosing preferred investment strategies can use the results of the study. Based on the data obtained on a reliable assessment of the value of shares of issuing companies of the Russian stock market, regulatory organizations have the opportunity to formulate effective management of it in the context of existing negative geopolitical events.

Statistics and EconomicsVol. 21(5)
Lomonosov Moscow State University (RU), Moscow State University (TJ)
Industry, innovation and infrastructure
Openalex Percentile: Top 73%
Financial Risk and Volatility Modeling
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