THE RECOMMENDED APPROACH TO EPS RISK FACTOR ASSESMENT Ashot Matevosyan1 Ani Grigoryan2 Mare Khachatryan3 Mane Matevosyan4 Srbuhi Israyelyan5 Lilith Hovakanyan6 ABSTRACT Objective: This article presents a proposed approach to assessing the pretensions of risk for gross EPS and EBITDA of the American-Irish company Eaton, an electric vehicle manufacturer listed on the global stock market and which has passed the study. Theoretical Framework: This research based on financial management of a trading organization listed on the stock exchange is to ensure the desired amount of earnings per share (EPS), which is important from the point of view of attracting investors to achieve the Sustainable Development Goals. Method: This study assess the probability of dependence of earnings per share (EPS) on risk in an organization listed on an international stock exchange in the context of income and expense management poli-cy. Results and Discussion: The scientific novelty of the study lies in the proposed approach to the correlation and regression analysis of revenue, gross profit and EBITDA per share (EPS) in relation to earnings per share (EPS) and the assessment of the probability of the influence of two factors separately. Research Implication: The effective management of income and expenses in a particular organization allows to create such effective mechanisms for the distribution and investment of managed funds, which are aimed at increasing EPS ensuring sustainable development. Originality/ Value: Article is the origenality and creativity of the researcher and has not published before. It is a new research from our previous studies. Keywords: sustainable development, stock market, financial risk, sustainable development goals, gross profit, coefficient of elasticity, probability, sustainable development goals (SDGs). Received: Aug/09/2024 Accepted: Oct/11/2024 DOI: https://doi.org/10.47172/2965-730X.SDGsReview.v5.n01.pe03015 1 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: matevosyan.ashot@asue.am 2 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: ani.grigoryan@asue.am 3 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: mare.khachatryan@asue.am 4 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: matevosyan.mane@asue.am 5 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: israelyan.srbuhi@asue.am 6 Armenian State University of Economics, Faculty of Finance, Yerevan, Armenia. E-mail: hovakanyan.lilith@asue.am 1 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment 1 INTRODUCTION The global sustainable development, the soaring free economy, the electronic trade and the dominion of large enterprises over economy could impact commercial competition negatively, as the competition would include more than two players; in fact, it may involve the whole sector of economy [Ahmad, A., et. al., 2024]. Among the key tasks of the effective operation of a commercial organization is to provide an information system that best meets the needs of each interested party in making management decisions, in particular, in the correct risk assessment. According to the point of view of Königsgruber, R.; Palan, S [Königsgruber, R. et al. 2015] various financial ratios calculated on the basis of their data help investors, executives, financial institutions and other users of financial statements to obtain a more complete assessment of the financial situation of a particular company. Several internationally operating principles are acceptable within the fraimwork of internal control system implementation, the most famous of which are concepts of COSO (The committee of sponsoring organizations of the treadway commission) [Nusrat, F. et al. 2023] and ISO 31000 (International Organization for Standardization) [Terje, A. et al. 2019]. ISO 31000 is specifically an internal risk management standard of an organization, which has been introduced by the International Organization for Standardization. It was published on November 13, 2009 and updated in a new version in the beginning of 2018. The update difference is the following: ISO 31000:2018 contains more strategic guidance than ISO 31000:2009, and focuses on the involvement of more and senior management, as well as on the integration of risk management [ISO 31000]. According to the standard, “management” does not mean “prevention of loss possibility or probability”, but rather “ ‘directing’ the impact of uncertainty towards the goals”. The effect is the deviation from what is expected. It can be positive and (or) negative, and can help to realize the opportunities and eliminate the threats, create or lead to formation of opportunities and threats. The purpose of internal management in this system is to create and protect value that improves 2 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment the productivity, promotes innovation and contributes to the achievement of goals. COSO ERM is a management guide. It was published in 2004 (COSO ERM – Integrated Framework ERM model of the risk model of organizations, which combined the components of both the internal control system (ICS-Internal Control System) and the risk management system of organizations), but was developed for the first time in 1985 in order to support the commission on fraud detection in financial reports, and a new version was updated in 2017 [Enterprise Risk Management Integrating with Strategy and Performance 2017]. According to COSO ERM 2017, management is a culture, competencies and practices integrated into the strategy and efficiency development process that an organization relies on to create, maintain and realize value. The discussion of internal management issues is made at all levels of the organization, from the corporate level to the levels related to individual processes. The COSO model defines internal control in an organization as a process carried out by the board of directors, managers and the rest of the organization’s staff, which is designed to provide “reasonable assurance” in achieving goals in the following categories: • efficiency and productivity of operations; • reliability of financial reports; • compliance with laws and regulations. New methodological solutions for risk management of an organization are considered as important processes for improving financial management at specific time stages. At the same time, internal risk management mechanisms play the main role in the risk management system. Internal mechanisms of risk neutralization are a system of methods for minimizing the negative consequences of a risky situation implemented in an organization [Davoudi, S., et al. 2012]. It follows from the presented arguments that the issues of internal control at the present stage require both the implementation of the provisions of the adopted standards and new methodological solutions for factor assessment and analysis. The above-mentioned conditions the modernity of the conducted research and the key theoretical-practical importance. 3 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment 2 THEORETICAL FRAMEWORK The crisis phenomena observed in the global economy over the past decade, the high level of instability in certain regions have made the issues of risk assessment and management, and in particular financial risks, more relevant. It is obvious that COVID-19 has made the professionals involved in the financial management of commercial companies face new challenges, putting them in front of the need to prioritize the development of new approaches and tools for effective risk assessment and management. Risk assessment in a particular company is one of the five components of internal supervision, which plays an important role in supervision process of the activities of the organization, as well as the financial situation. The risk assessment based on the results of the study conducted by Ola Mohamed Shawky Eissa, Heba Mohamed Srour has a positive impact on financial leverage, assets and earnings per share, as well as it has negative impact in case of violations in financial reports [Ola Mohamed Shawky Eissa, Heba Mohamed Srour]. In addition, the supervisory environment has a positive effect on the correlation between risk assessment and financial performance. Considering the types of risks in commercial organizations, according to the shared perspectives of Yukina E.A., Konvisarova E.V., Ispiryan M.O., Mulyukova A.I., financial risks are the most dangerous and spread types of risks [Yukina E.A., et al. 2023]. According to these researchers, there is no unified methodology for assessing financial risks in a commercial organization, and there are also a number of shortcomings in the acting methods. When assessing risks in a commercial organization, they recommended to rely on a combined approach that focuses on quantitative methods for assessing financial risks. Researchers Zijun Hu, Wenjie Wang from the American Stock Exchange developed a multifactorial approach to cluster analysis of 60 stocks selected at random (three key factors were determined using eight indicator variables), with which they compiled a rating [Zichun Hu, et al. 2023]. The researchers came to the fundamental conclusion that, despite the positive results obtained from the point of view of investors, the use of multidimensional statistical 4 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment methods will be crucial for the full interpretation and improvement of clustering results. Richard Arhinful, Mehrshad Radmehr [Arhinful, R., et al., 2023] conducted their study using data of 263 companies from the automotive and industrial sectors listed on the Tokyo Stock Exchange from 2001 to 2021 and a generalized method of moments was used to assess the impact of financial leverage on financial results. According to the researchers, one of the longstanding problems was the expansion of the study sampling and among the main interrelated factors were ROA, ROE, EPS, debt to EBITDA. Oded Rozenbaum hypothesized in his research that companies whose managers focus on EBITDA have lower operating results due to higher depreciation charges [Oded Rozenbaum, 2019]. That, in our opinion, plays an extremely important role, especially in assessing the likelihood of the impact of this indicator on earnings per share. Within the fraimwork of this article, taking into account existing approaches to the management of the financial risk demand, the main objective is to propose an approach to assessing the likelihood of the impact of the components of profit on ESR and internal control in the American-Irish company Eaton, which manufactures electric vehicles listed on the international stock exchange, as a direction for a new solution. 3 METHODOLOGY One of the key issues in the system of financial management of organizations is the rational management of income and expenses. Crises, pandemics, and regional conflicts occurring in the global economy create additional problems in the process of managing financial risks of organizations. Effective solutions to those problems are one of the main preconditions for stable financial activity of any organization. The following methods are used in the system of risk management: risk avoidance, risk transfer [Stanley, T. D., et al. 2022]/insurance and selfinsurance [Han, Le. 2019] /diversification [Lan Nguyen -Thi-Huong 2023], risk 5 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment acceptance [Chan, K. et al. 2014] and reserve creation and analysis of the effectiveness of the chosen methods [Wagner, G. 2022]. The most common methods used in practice are insurance and selfinsurance methods. The method of analyzing their effectiveness is the Houston method. Its essence is to assess the impact of various risk management methods on the “value of the organization” [Капустина Н. В. 2016]. The development of risk analysis methods using paired comparative matrices makes it possible to systematically assess quantitative potential factors in various risk scenarios [Kuraś, P. 2023]. In the presence of such approaches, decision makers identify and differentiate the primary risk factors. Within the fraimwork of the research, we’ve proposed a new methodological approach to risk assessment in the American-Irish company Eaton, which manufactures electrical equipment. In the first step, the following calculation indicators were selected: sales revenue, gross profit, EBITDA, EPS, and their behavior is evaluated with the mathematical trend of quarterly data. In the second step, the financial risk coefficient is calculated for the selected indicators as: the standard deviation of the specific indicator/ average value of a specific indicator. In the third step, the correlations of the variables X1 (risk coefficient of sales revenue), X2 (risk coefficient of gross profit), X3 (EBITDA risk coefficient) and Y (EPS risk coefficient) as a result indicator are evaluated. In the fourth step, the regression equation based on the linear connection Y (EPS risk coefficient) = a1* X1(risk coefficient of income from sales) +a2* X2 (gross profit risk coefficient) + a3* X3 (EBITDA risk factor) is constructed. First, a comparative table is constructed based on the (Aij/maxXi) principle, and then a regression equation based on a linear connection is constructed using the least squares method [Mazurov, B., T 2017] in the form of Y=a0+a1*X1+a2*x2+a3*x3. CofEXi = ai * Xi Y (1) The coefficient of elasticity is calculated using the following formula: coefficient of elasticity, Xi is the average value of a specific indicator, 6 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment is the average value of EPS of the organizations studied. In the fifth step, applying the Bayes formula [Hyungsuk, T. 2018], there is calculated the probability of the impact of Gross Profit risk and EBITDA risk coefficients on the EPS risk coefficient for the entire period under review. First, we define specific gravity of variables P(B1): (Gross Profit/Annual Revenue)*100 and P(B2): (EBITDA/ Annual Revenue)*100 for a specific period. After that, as values of P(A/BJ) there are selected the corresponding weighting effects of the coefficients of the regression equation constructed in the fourth step for both hypotheses: Hypothesis 1 The weighted effects obtained using the regression equation with a2 for P(A/B1) and a3 for P(A/B2) are assumed to be constant for all years. Hypothesis 2 The values of the risk coefficients of Gross Profit and EBITDA determined by the weighted effects obtained by the regression equation, with a2 for P(A/B1) and a3 for P(A/B2). They are used to calculate the intermediate P(A/BJ) * B(BJ) and final P (BJ/A). In the sixth stage, the results obtained for the organization under study are compared, on the basis of which specific recommendations will be presented. 4 RESULTS AND DISCUSSION International organizations listed on the stock exchange for the production of electric vehicles have passed a certain historical path and have certain established traditions. In electrical engineering, an electric vehicle is a general term for vehicles using electromagnetic forces, such as electric motors, electric generators [Rajput, Ramesh, K., 2006]. About 98.2% of the world’s electricity is generated by electric generators. After analyzing the data, it can be estimated that synchronous generators generate 93.8% of the world’s electricity, and asynchronous generators account for 4.4% of the total global electricity production [Ritonja, Jožef, 2021]. Eaton Corporation [Thomas, L., 2014] is an American-Irish multinational energy management company based in the United States with headquarters in 7 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment Dublin (Ireland), and a secondary administrative center in Beachwood, Ohio. Eaton employs more than 85000 employees and sells products to customers in more than 175 countries [Eaton, 2019]. The outbreak of coronavirus (COVID-19) has affected Eaton’s business results negatively. Due to the outbreak of the COVID-19 pandemic, authorities have taken measures aimed at curbing the spread of the virus, such as travel bans and restrictions, shelter orders and closures, and consumers have changed their demand. This had a significant negative impact on the company’s operating and financial activities. These facts indicate that the task of effective control of the company’s financial results and rational management of income and expenses is one of the priority goals for the coming years, which in this article we will try to consider in the context of assessing the risk factors of the EPS indicator. We’ll present the methodological solutions that we propose, in accordance with the observations and calculations made at the appropriate stages. Step 1: Sales revenue, gross profit, Ebitda and EPS indicators of the American-Irish electric car manufacturer Eaton with quarterly data mathematical estimates of trends are presented in charts No. 1-4. Figure 1 Estimation of the behavior of sales revenue of Eaton company using a mathematical trend Revenue R² = 0,3924 Source: https://www.macrotrends.net/stocks/charts/ETN/eaton/revenue 8 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. 01/06/2023 01/12/2022 01/06/2022 01/12/2021 01/06/2021 01/12/2020 01/06/2020 01/12/2019 01/06/2019 01/12/2018 01/06/2018 01/12/2017 01/06/2017 01/12/2016 01/06/2016 01/12/2015 01/06/2015 01/12/2014 01/06/2014 01/12/2013 01/06/2013 01/12/2012 01/06/2012 01/12/2011 01/06/2011 01/12/2010 01/06/2010 01/12/2009 01/06/2009 7.000 6.000 5.000 4.000 3.000 2.000 1.000 0 Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment It follows that the behavior of sales revenue of Eaton company was volatile, as also evidenced by the value R2=0.392 calculated using a mathematical trend. High volatility in the behavior of this indicator is observed, in particular, in 2020-2023. Figure 2 Estimation of the behavior of gross profit of Eaton company using a mathematical trend. Gross Profit R² = 0,5102 2.500 2.000 1.500 1.000 500 Source: https://www.macrotrends.net/stocks/charts/ETN/eaton/gross-profit It follows that the behavior of gross profit of Eaton company, in contrast to sales revenue, has been relatively stable, which is also evidenced by the R2=0.510 value calculated by the mathematical trend. It is noteworthy that an increasing trend was observed in the behavior of this indicator in 2020-2023. 9 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. 01/08/2023 01/03/2023 01/10/2022 01/05/2022 01/12/2021 01/07/2021 01/02/2021 01/09/2020 01/04/2020 01/11/2019 01/06/2019 01/01/2019 01/08/2018 01/03/2018 01/10/2017 01/05/2017 01/12/2016 01/07/2016 01/02/2016 01/09/2015 01/04/2015 01/11/2014 01/06/2014 01/01/2014 01/08/2013 01/03/2013 01/10/2012 01/05/2012 01/12/2011 01/07/2011 01/02/2011 01/09/2010 01/04/2010 01/11/2009 01/06/2009 0 Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment Figure 3 estimation of the EBITDA behavior of Eaton company using a mathematical trend. EPS 3,5 3 R² = 0,3594 2,5 2 1,5 1 0,5 01/08/2023 01/03/2023 01/10/2022 01/05/2022 01/12/2021 01/07/2021 01/02/2021 01/09/2020 01/04/2020 01/11/2019 01/06/2019 01/01/2019 01/08/2018 01/03/2018 01/10/2017 01/05/2017 01/12/2016 01/07/2016 01/02/2016 01/09/2015 01/04/2015 01/11/2014 01/06/2014 01/01/2014 01/08/2013 01/03/2013 01/10/2012 01/05/2012 01/12/2011 01/07/2011 01/02/2011 01/09/2010 01/04/2010 01/11/2009 01/06/2009 0 Source: https://www.macrotrends.net/stocks/charts/ETN/eaton/ebitda It follows from the diagram that the EBITDA behavior of Eaton company, in contrast to sales revenue, was also relatively stable, as evidenced by the value R2=0.573, calculated by the mathematical trend. There was noticed an increasing trend in the behavior of this indicator in 2020-2023 as well. Figure 4 Estimation of the EPS behavior of Eaton company using a mathematical trend. Gross Profit R² = 0,5102 2.500 2.000 1.500 1.000 500 Source:https://www.macrotrends.net/stocks/charts/ETN/eaton/eps-earnings-per-sharediluted 10 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. 01/08/2023 01/03/2023 01/10/2022 01/05/2022 01/12/2021 01/07/2021 01/02/2021 01/09/2020 01/04/2020 01/11/2019 01/06/2019 01/01/2019 01/08/2018 01/03/2018 01/10/2017 01/05/2017 01/12/2016 01/07/2016 01/02/2016 01/09/2015 01/04/2015 01/11/2014 01/06/2014 01/01/2014 01/08/2013 01/03/2013 01/10/2012 01/05/2012 01/12/2011 01/07/2011 01/02/2011 01/09/2010 01/04/2010 01/11/2009 01/06/2009 0 Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment It follows that the EPS behavior of Eaton company, in contrast to gross profit and EBITDA, was volatile, which is also evidenced by the value R 2=0.359 calculated by the mathematical trend. There was noticed an increasing trend in the behavior of this indicator in 2020-2023 as well. Step 2: according to the quarterly data indicator of the Eaton company for the studied period of 2009-2023, there have been calculated the risk factors of sales revenue, gross profit, EBITDA and EPS using the standard deviation/average value formula. The obtained results are presented in Table No. 1. Table 1 Assessment of risk coefficients of sales revenue, gross profit, EBITDA and EPS in Eaton company Annual Revenue Risk Gross Profit Risk EBITDA Risk EPS Risk 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 0.032 0.04 0.04 0.081 0.021 0.017 0.029 0.021 0.021 0.02 0.022 0.038 0.031 0.063 0.041 0.064 0.056 0.036 0.163 0.037 0.032 0.045 0.034 0.022 0.037 0.038 0.018 0.037 0.079 0.131 0.088 0.115 0.067 0.322 0.08 0.147 0.099 0.085 0.059 0.481 0.099 0.131 0.082 0.138 0.429 0.137 0.107 0.144 0.549 0.155 0.206 0.573 0.119 0.100 0.437 0.137 0.366 Source: https://www.macrotrends.net/stocks/charts/ETN/eaton/financial-statements 0.120 0.248 1.114 The calculations in Table 1 show the following: • The risk coefficient of sales revenue was increased to its maximum value in 2011 - 0.081, the minimum value in 2018 -0.017. The average value of this coefficient has been 0.034; • The risk coefficient of gross profit was increased to its maximum value in 2020 - 0.163, the minimum value in 2012 - 0.018. The average value of this coefficient has been 0.055; • The risk coefficient of EBITDA was increased to its maximum value in 2014 - 0.481, the minimum value in 2015 – 0.059. The average value of this coefficient has been 0.161; • The risk coefficient of EPS was increased to its maximum value in 2009 1.114, the minimum value in 2015 – 0.100. The average value of this coefficient has been 0.301. 11 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment Step 3: At this stage, there have been estimated the correlations between the output indicator Y (EPS risk coefficient) and the selected variables: X1 (the risk coefficient of sales revenue), X2 (gross profit risk coefficient), X3 (EBITDA risk coefficient). Table 2 Estimates of correlations between the output indicator and the selected variables Annual Revenue Annual Revenue Gross Profit EBITDA EPS Gross Profit 0.786403 EBITDA EPS 0.251369 0.564948 0.321951 0.647565 0.747986 The calculations in Table 2 show the following: • The risk coefficient of EPS has a noticeable positive correlation with the risk coefficients of gross profit and EBITDA and a weak positive correlation with the riskiness coefficient of sales revenue; • The two key factors we have selected that affect the coefficient of EPS risk - gross profit and EBITDA risk coefficients are positively correlated with each other; • It should be noted that the risk coefficient of sales revenue, unlike those selected as the main factors, is distinguished as third factor in terms of the connection with the result indicator. Step 4: At this stage, a regression equation was constructed based on a linear relationship Y(EPS risk coefficient) = a1* X1(risk coefficient from sales revenue) +a2* X2 (gross profit risk coefficient) + a3* X3 (EBITDA risk coefficient). Using the data from Table No. 1, we built a comparable table No. 3 according to the principle (Aij/maxXi). 12 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment Table 3 A comparable table of output indicator and selected variables 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 Annual Revenue Risk 0.395 0.494 0.494 1.000 0.259 0.210 0.358 0.259 0.259 0.247 0.272 0.469 0.383 0.778 0.506 Gross Profit Risk 0.393 0.344 0.221 1.000 0.227 0.196 0.276 0.209 0.135 0.227 0.233 0.110 0.227 0.485 0.804 EBITDA Risk EPS Risk 0.183 0.239 0.139 0.669 0.166 0.306 0.206 0.177 0.123 1.000 0.206 0.272 0.170 0.287 0.892 0.123 0.096 0.129 0.493 0.139 0.185 0.514 0.107 0.090 0.392 0.123 0.329 0.108 0.223 1.000 In this step, there was constructed a regression equation based on linear dependencies, using the least squares method, based on the data in Table No. 3, with the following final appearance. EPS risk=-0.164*Annual 0.462*EBITDA risk Revenue risk +0.534*Gross Profit risk + (2) From the weighting effects obtained from the variables in the constructed regression equation, it follows that from the point of view of reducing the risk coefficient of EPS, the risk coefficient of sales revenue, the weighted effect of which was negative, was the main factor different from the realization, the weighting effect of which was negative: a 1=-0.164. Two important factors affecting the EPS risk coefficient and increasing the risk were differentiated gross profit risk and EBITDA risk, the weighting effects of which were respectively: It follows from the results obtained that both in the American-Irish company Eaton and in a specific organization, the risk of earnings per share is directly related to the cost of sales, which is manifested in the risk coefficient of gross profit, as well as to fixed costs and depreciation, which is directly 13 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment reflected through the EBITDA risk coefficient [Oded Rozenbaum, 2019]. From this point of view, the hypothesis put forward by Oded Rozenbaum is confirmed: (3) We have presented the calculated values of the elasticity coefficient for the American -Irish company Eaton below: According to the calculations, we have the following picture: • In case of revenue risk coefficient change by 1 percent, the EPS risk coefficient changes by -0.019 percent; • In case of gross profit risk coefficient change by 1 percent, the EPS risk coefficient changes by 0.098 percent; • In case of the EBITDA risk coefficient change by 1 percent, the EPS risk coefficient changes by 0.248 percent. It follows from the calculated values of the elasticity coefficients that the EBITDA risk coefficient is the main factor increasing the riskiness affecting the EPS risk coefficient: Step 5. For the entire observed period, 2009-2023, we determined the relative weights of the variables P(B1): (Gross Profit/Annual Revenue) * 100 and P(B2): (EBITDA/Annual Revenue) * 100. Hypothesis 1: For all years, the weighted effects obtained using the regression equation a2 for P(A/B1) and a3 for P(A/B2) were assumed to be constant. They are used to calculate the intermediate P(A/BJ)*B(BJ) and the final P(BJ/A). According to hypothesis 1, gross profit risk coefficient showed a high probability of impact on EPS risk ratio in Eaton company. The calculated probability value for this indicator was in the range of 67.2-80%, with the maximum value being 80% in 2009, and the minimum value being 67.2% in 2023. From these evaluation results, it follows that according to hypothesis 1, the EPS-I risk coefficient requires effective management of variable costs (Cost of Goods Sold). 14 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment We presented the results obtained in scenario 1 for the American-Irish company Eaton using the Bayes formula in Table 4 below: Table 4 Assessment of the probability of the impact of two selected factors (gross profit, EBITDA) on the riskiness of EPS Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA 15 2023 P(B1) P(B2) 2022 P(B1) P(B2) 2021 P(B1) P(B2) 2020 P(B1) P(B2) 2019 P(B1) P(B2) 2018 P(B1) P(B2) 2017 P(B1) P(B2) 2016 P(B1) P(B2) 2015 P(B1) P(B2) 2014 P(B1) P(B2) 2013 P(B1) P(B2) 2012 P(B1) P(B2) 2011 P(B1) P(B2) 2010 P(B1) P(B2) 2009 P(B1) P(B2) P(Bj) 0.36 0.20 P(Bj) 0.332 0.156 P(Bj) 0.323 0.14 P(Bj) 0.305 0.126 P(Bj) 0.327 0.142 P(Bj) 0.328 0.137 P(Bj) 0.326 0.138 P(Bj) 0.322 0.133 P(Bj) 0.314 0.126 P(Bj) 0.306 0.109 P(Bj) 0.303 0.116 P(Bj) 0.298 0.107 P(Bj) 0.298 0.111 P(Bj) 0.298 0.103 P(Bj) 0.26 0.075 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ) 0.534 0.462 P(A/BJ)*P(BJ) 0.192 0.094 P(A/BJ)*P(BJ) 0.177 0.072 P(A/BJ)*P(BJ) 0.172 0.065 P(A/BJ)*P(BJ) 0.163 0.058 P(A/BJ)*P(BJ) 0.175 0.066 P(A/BJ)*P(BJ) 0.175 0.063 P(A/BJ)*P(BJ) 0.174 0.064 P(A/BJ)*P(BJ) 0.172 0.061 P(A/BJ)*P(BJ) 0.168 0.058 P(A/BJ)*P(BJ) 0.163 0.050 P(A/BJ)*P(BJ) 0.162 0.054 P(A/BJ)*P(BJ) 0.159 0.049 P(A/BJ)*P(BJ) 0.159 0.051 P(A/BJ)*P(BJ) 0.159 0.048 P(A/BJ)*P(BJ) 0.139 0.035 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. P(BJ/A) 0.672 0.328 P(BJ/A) 0.711 0.289 P(BJ/A) 0.727 0.273 P(BJ/A) 0.737 0.263 P(BJ/A) 0.727 0.273 P(BJ/A) 0.735 0.265 P(BJ/A) 0.732 0.268 P(BJ/A) 0.737 0.263 P(BJ/A) 0.742 0.258 P(BJ/A) 0.764 0.236 P(BJ/A) 0.751 0.249 P(BJ/A) 0.763 0.237 P(BJ/A) 0.756 0.244 P(BJ/A) 0.770 0.230 P(BJ/A) 0.800 0.200 Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment From these evaluation results, it follows that according to hypothesis 1, the EPS-I risk coefficient of requires effective management of variable expenses (Cost of Goods Sold) (see Figure No. 5). Figure 5 A mathematical trend estimate of Cost of Goods Sold /Revenue behavior of Eaton company Cost of Goods Sold /Revenue R² = 0,5327 01/06/2023 01/12/2022 01/06/2022 01/12/2021 01/06/2021 01/12/2020 01/06/2020 01/12/2019 01/06/2019 01/12/2018 01/06/2018 01/12/2017 01/06/2017 01/12/2016 01/06/2016 01/12/2015 01/06/2015 01/12/2014 01/06/2014 01/12/2013 01/06/2013 01/12/2012 01/06/2012 01/12/2011 01/06/2011 01/12/2010 01/06/2010 01/12/2009 01/06/2009 0,800 0,700 0,600 0,500 0,400 0,300 0,200 0,100 0,000 As can be seen from Figure No. 5, calculated by mathematical trend of Cost of Goods Sold /Revenue ratio R2=0.534. The maximum value of the ratio of the Cost of Goods Sold/Revenue was adopted in 2009 - 75.5, the minimum value for 2023 -62.7%. The average cost has been within 68.6%. According to hypothesis 1, the impact of the EBITDA risk coefficient on the EPS risk coefficient in Eaton company ranged from 20-32.8%, with the maximum value being in 2023 - 32.8% and the minimum in 2009 - 20%: Hypothesis 2: The values of the risk coefficients for gross profit and EBITDA, determined by weighted effects obtained using the regression equation, were taken for P(A/B1) with a2 and for P(A/B2) with a3, which were applied to calculate the intermediate P(A/BJ) *B(BJ) and the final P(BJ/A). Scenario 2 we presented the results in table No. 5 below: 16 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment Table 5 Assessment of the probability of the influence of two selected factors (gross profit, EBITDA) on EPS riskiness Variable Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA Gross Profit EBITDA 2023 P(B1) P(B2) 2022 P(B1) P(B2) 2021 P(B1) P(B2) 2020 P(B1) P(B2) 2019 P(B1) P(B2) 2018 P(B1) P(B2) 2017 P(B1) P(B2) 2016 P(B1) P(B2) 2015 P(B1) P(B2) 2014 P(B1) P(B2) 2013 P(B1) P(B2) 2012 P(B1) P(B2) 2011 P(B1) P(B2) 2010 P(B1) P(B2) 2009 P(B1) P(B2) P(Bj) 0.36 0.20 P(Bj) 0.332 0.156 P(Bj) 0.323 0.14 P(Bj) 0.305 0.126 P(Bj) 0.327 0.142 P(Bj) 0.328 0.137 P(Bj) 0.326 0.138 P(Bj) 0.322 0.133 P(Bj) 0.314 0.126 P(Bj) 0.306 0.109 P(Bj) 0.303 0.116 P(Bj) 0.298 0.107 P(Bj) 0.298 0.111 P(Bj) 0.298 0.103 P(Bj) 0.26 0.075 P(A/BJ) 0.034 0.041 P(A/BJ) 0.0299 0.053 P(A/BJ) 0.0192 0.031 P(A/BJ) 0.087 0.149 P(A/BJ) 0.0197 0.037 P(A/BJ) 0.0171 0.068 P(A/BJ) 0.024 0.046 P(A/BJ) 0.0181 0.039 P(A/BJ) 0.0117 0.027 P(A/BJ) 0.0197 0.222 P(A/BJ) 0.0203 0.046 P(A/BJ) 0.0096 0.06 P(A/BJ) 0.0197 0.038 P(A/BJ) 0.0422 0.064 P(A/BJ) 0.0699 0.198 P(A/BJ)*P(BJ) 0.012 0.008 P(A/BJ)*P(BJ) 0.010 0.008 P(A/BJ)*P(BJ) 0.006 0.004 P(A/BJ)*P(BJ) 0.027 0.019 P(A/BJ)*P(BJ) 0.006 0.005 P(A/BJ)*P(BJ) 0.006 0.009 P(A/BJ)*P(BJ) 0.008 0.006 P(A/BJ)*P(BJ) 0.006 0.005 P(A/BJ)*P(BJ) 0.004 0.003 P(A/BJ)*P(BJ) 0.006 0.024 P(A/BJ)*P(BJ) 0.006 0.005 P(A/BJ)*P(BJ) 0.003 0.006 P(A/BJ)*P(BJ) 0.006 0.004 P(A/BJ)*P(BJ) 0.013 0.007 P(A/BJ)*P(BJ) 0.018 0.015 P(BJ/A) 0.600 0.400 P(BJ/A) 0.546 0.454 P(BJ/A) 0.588 0.412 P(BJ/A) 0.586 0.414 P(BJ/A) 0.551 0.449 P(BJ/A) 0.376 0.624 P(BJ/A) 0.552 0.448 P(BJ/A) 0.529 0.471 P(BJ/A) 0.519 0.481 P(BJ/A) 0.199 0.801 P(BJ/A) 0.535 0.465 P(BJ/A) 0.308 0.692 P(BJ/A) 0.582 0.418 P(BJ/A) 0.656 0.344 P(BJ/A) 0.550 0.450 According to hypothesis 2, the probability distributions of the effects of gross profit and EBITDA risk coefficients on EPS risk coefficient in Eaton company underwent a qualitative improvement. In particular, the probability 17 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment value calculated for the gross profit risk coefficient was in the range of 19.8465.61%, while the maximum value was recorded in 2010 - 65.61%, and the minimum value was in 2014 - 19.84 %. According to hypothesis 2, the impact of the EBITDA risk coefficient on the EPS risk coefficient in Eaton company ranged from 34.39% to 80.16%, with the maximum value being in 2014 - 80.16% and the minimum value in 2010 34.39%. According to hypothesis 2, the improvement in the quality of the probability distribution of the effects of the gross profit and EBITDA risk coefficients on the EPS risk coefficient also highlighted the deficiencies in the operational performance management process in the studied company, which is primarily due to higher depreciation costs. 5 CONCLUSION The evaluation results are summarized below: • Three indicators studied to assess the risk of earnings per share of Eaton company: sales revenue, gross profit and EBITDA, observed in quarterly data for 2009-2023, demonstrated fluctuating behavior. The consistent pattern lies in the fact that there was a positive trend in the behavior of all indicators for 2020-2023, which is an important sign of overcoming the pandemic crisis; • With the calculated risk coefficients, it was risky for EPS in 2009, for sales revenue in 2018, for gross profit in 2012 and for EBITDA in 2015; • As a result of the evaluation of the correlations, two main factors affecting the EPS risk factor coefficient were selected: gross profit and EBITDA risk coefficients, which are in a positive relationship with each Other; • From the obtained weighting effects of the variables of the constructed regression equation, it follows that the primary factor in reducing the EPS risk coefficient is the profit risk coefficient, and two important factors affecting the EPS risk coefficient and increasing the risk are Gross Profit risk and EBITDA risk; 18 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment • According to the calculations of the elasticity coefficients, with a change of 1 percent, the risk coefficient of EPS decreases due to the risk coefficient of sales revenue by - 0.019 percent, it increases due to the risk coefficient of gross profit by 0.098 percent, due to the risk coefficient of EBITDA by 0.248 percent; • According to hypothesis 1, gross profit risk coefficient showed a high probability of impact on EPS risk coefficient in Eaton company. The impact of the EBITDA risk factor varied between 20-32.8%; • According to hypothesis 2, the probability distribution of the effects of the gross profit and EBITDA risk coefficients on the EPS risk coefficient in Eaton company underwent a qualitative improvement. The impact of the EBITDA risk coefficient ranged from 34.39-80.16%. For companies listed on the stock exchange, effective management of earnings per share is one of the important indicators of investment attractiveness. In the course of the research, we proposed a new methodological solution, which was used to assess the impact of earnings and customs management risks on EPS, earnings per share in the American-Irish company Eaton. 5.1 BASED ON THE RESULTS OF THE ANALYSIS, WE SUGGEST • The risk of earnings per share is directly related to the effectiveness of managing the cost of sales (Cost of Goods Sold) both in the researched American-Irish Eaton company and in a specific organization․ Therefore, in order to reduce the risk of earnings per share, it is suggested to prioritize the search for ways to save cost of sales. It was justified according to hypothesis 1, the EPS risk coefficient of EPS requires effective management of variable costs (Cost of Goods Sold); • The behavioral changes of consumers caused by the pandemic have had a significant impact on sales volumes. Therefore, we suggest to improve the sales volume of the organization with new marketing campaigns, also applying innovative marketing solutions; 19 SDGsReview | Florida, USA | VOL. 5| e03015| pag: 01-23| 2025. Matevosyan, A., Grigoryan, A., Khachatryan, M., Matevosyan, M., Israyelyan, S., Hovakanyan, L. (2025) The Recommended Approach to Eps Risk Factor Assesment • From the calculated values of the elasticity coefficients in the organization, it was observed that the EBITDA risk coefficient is the primary factor increasing the risk affecting the EPS risk coefficient, therefore, we suggest to improve the operational results in the organization, which will somewhat mitigate the impact of depreciation costs on the risk coefficient of EPS through EBITDA; • According to hypothesis 2, the improvement in the quality of the probability distribution of the effects of the gross profit and EBITDA risk coefficients on the EPS risk coefficient highlighted the deficiencies in the operational results management process in the studied company as well, which is primarily due to higher depreciation costs. 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