2408-9346Research result. Business and Service Technologies2408-93464023TRENDS IN THE DEVELOPMENT OF INDUSTRY AND REGIONAL MARKETS. BUSINESS TRANSFORMATION IN THE NEW REAL<strong>Evaluation of the Altman Z-Score Dynamics of an Average Agricultural Holding</strong><strong>Evaluation of the Altman Z-Score Dynamics of an Average Agricultural Holding</strong>MorhachovIllia V.MorhachovIllia V.ShevchenkoMaria N.ShevchenkoMaria N.ListopadovaYulia V.ListopadovaYulia V.ChugayDmitriy Yu.ChugayDmitriy Yu.ArtemenkoViktor А.ArtemenkoViktor А.202511400

The importance of domestic agricultural holdings to the national economy makes it important to analyze the feasibility of applying the Altman Z-score method to them. Unfortunately, such studies are rare. The aim of this study is to assess the dynamics of the Altman Z-score of an average agricultural holding. A sample-based observation method was used to develop an economic and mathematical model of the average agricultural holding. The sample size consisted of 110 organizations within the structures of the country&#39;s leading agricultural holdings. The dynamics of Altman Z-score values can be useful for monitoring the financial and economic status of the agro-industrial complex. Testing the model for the industry demonstrated the feasibility of this approach and the feasibility of its application. The Altman Z-score values relative to the economic and mathematical model of the average agricultural holding ranged from 1.5 to 1.95, indicating an orange risk zone. The average value for the 14 years analyzed was 1.7099. The value of the studied indicator for 2011-2024 allows us to classify domestic agricultural holdings, on average, into the orange risk zone with a high probability of bankruptcy. The results of the model testing further substantiate the importance of state support for the agro-industrial complex. The feasibility of analyzing the dynamics of the studied indicator at the macro and meso levels for the purpose of improving state regulation of the agro-industrial complex is substantiated. Such data can indicate periods of crisis in the activities of the analyzed entities. The dynamics of the quantitative values of the Altman Z-score allowed us to identify periods of crisis for the average agricultural holding in the country: 2013-2014, 2016-2017, 2022, and 2024. The dynamics of the indicator under study demonstrate the success of state regulation of the agro-industrial complex and agricultural holdings in particular, as they continue to operate successfully even while in the orange zone.

The importance of domestic agricultural holdings to the national economy makes it important to analyze the feasibility of applying the Altman Z-score method to them. Unfortunately, such studies are rare. The aim of this study is to assess the dynamics of the Altman Z-score of an average agricultural holding. A sample-based observation method was used to develop an economic and mathematical model of the average agricultural holding. The sample size consisted of 110 organizations within the structures of the country&#39;s leading agricultural holdings. The dynamics of Altman Z-score values can be useful for monitoring the financial and economic status of the agro-industrial complex. Testing the model for the industry demonstrated the feasibility of this approach and the feasibility of its application. The Altman Z-score values relative to the economic and mathematical model of the average agricultural holding ranged from 1.5 to 1.95, indicating an orange risk zone. The average value for the 14 years analyzed was 1.7099. The value of the studied indicator for 2011-2024 allows us to classify domestic agricultural holdings, on average, into the orange risk zone with a high probability of bankruptcy. The results of the model testing further substantiate the importance of state support for the agro-industrial complex. The feasibility of analyzing the dynamics of the studied indicator at the macro and meso levels for the purpose of improving state regulation of the agro-industrial complex is substantiated. Such data can indicate periods of crisis in the activities of the analyzed entities. The dynamics of the quantitative values of the Altman Z-score allowed us to identify periods of crisis for the average agricultural holding in the country: 2013-2014, 2016-2017, 2022, and 2024. The dynamics of the indicator under study demonstrate the success of state regulation of the agro-industrial complex and agricultural holdings in particular, as they continue to operate successfully even while in the orange zone.

average agricultural holdingagro-industrial complexAltman Z-scoresample observation methodeconomic and mathematical modelingbankruptcy probabilitygovernment regulation of the agro-industrial complexaverage agricultural holdingagro-industrial complexAltman Z-scoresample observation methodeconomic and mathematical modelingbankruptcy probabilitygovernment regulation of the agro-industrial complexСписок литературыAltman, E.I. (1976), &ldquo;Capitalization of Leases and the Predictability of Financial Rations&rdquo;, A Comment Accounting Review, Vol. 51, 2, pp. 408&ndash;412.Altman, E.I., Haldeman, R.G. and Narayanan, P. (1977), &ldquo;Zeta Analysis: A New Model to Identify Bankruptcy Risk of Corporation&rsquo;&rsquo;, Journal of Banking and Finance, June.Altman, E.I. (1983), Corporate Financial Distress, N.Y., John Wiley.Altman, E.I. (1984), &ldquo;Further Empirical Investigation of the Bankruptcy Cost Question&rdquo;, Journal of Finance. Sept., pp. 1067&ndash;1089.Altman, E.I. and Saunders, A. (1988), &ldquo;Credit Risk Measurement: Developments over the Last 20 Years&rdquo;, Journal of Banking and Finance, 21, pp. 1721&ndash;1742.Feyzrakhmanova, N.M. (2023), &ldquo;Applicability of Classical Bankruptcy Prediction Models (Altman, Fulmer and Tafler) to Domestic Agricultural Companies&rdquo;, OpenScience, Т. 5, 1, pp. 123-134. DOI 10.51632/2658-7939_2023_5_1_123. (in Russ).Financial performance of companies, Website, [Online], available at: https://www.list-org.com/ (Accessed 09.08.2025) (in Russ).G&ouml;kt&uuml;rk, İ. E. and Yal&ccedil;ınkaya, H.S. (2023), &ldquo;Application of the Altman Z&#39;&#39; Score Model in Forecasting the Financial Position of BIST Companies&rdquo;, Finance: Theory and Practice, Vol. 27, 2, pp. 192-202. DOI 10.26794/2587-5671-2023-27-2-192-202.Khanin, G. (2018) &ldquo;Alternative Assessment of the Altman Model for Gazprom Group for 2016: Facts and Hypotheses&rdquo;, Terra Economicus, Т. 16, 2, pp. 17-26. Doi 10.23683/2073-6606-2018-16-2-17-26. (in Russ).Morgachev, I.V., Chugai, D.Iu., Lebed, A.V. and Bystrova, T.S. (2024), &ldquo;Assessment of Management of Borrowed Funds of Agricultural Holdings in Russia&rdquo;, AIC: Economics, Management, 3. pp. 46-55. DOI 10.33305/243-46. (in Russ).Morhachov, I.V., Shevchenko, M.N., Listopadova, Iu.V. and Chugai, D.Iu. (2024), &ldquo;Assessment of the Dynamics and Efficiency of the Use of Assets of Agricultural Holdings of the Russian Federation&rdquo;, AIC: Economics, Management, 10, pp. 64-76. DOI 10.33305/2410-64. (in Russ).Patlasov, O. Yu. and Sergienko, O. V. (2007) &ldquo;Multiple Discriminant Analysis in Altman Bankruptcy Forecasting Models: Interpretations and Limitations of Use&rdquo;, Siberian Financial School, 1 (62), pp. 76-80. (in Russ).Pavlinov, D. and Savchina, O. (2024), &ldquo;The Application of the Altman Model to Assess the Financial Stability of the Russian Airlines&rdquo;, Transport Affairs of Russia, 8, pp. 7-11. (in Russ).Vinnikova, E.V. (2008), &ldquo;Justification of the use of Altman models in the analysis of the financial condition of enterprises of the health resort complex&rdquo;, Bulletin of the Rostov State University of Economics (RINH), 2 (26), pp. 137-143. (in Russ).Zubarev, I.S. (2020), &ldquo;Possibility of Altman Z-model to predict corporate financial difficulties of Russian companies&rdquo;, The Eurasian Scientific Journal, 3(12), [Online], Available at: https://esj.today/PDF/46ECVN320.pdf (Accessed 09.08.2025). (in Russ).