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Journal articles on the topic 'Bankruptcy probability forecasting'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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1

Blazhevich, O., A. Karachun, and A. Suleymanova. "Comparative analysis and application of methods for predicting bankruptcy." Bulletin of Science and Practice, no. 5 (May 14, 2017): 161–75. https://doi.org/10.5281/zenodo.579745.

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In article methods of forecasting of bankruptcy are considered, their classification, the characteristic, a design procedure is given, merits and demerits are resulted. On an example of data of the accounting reporting of the enterprise–bankrupt the probability of bankruptcy is certain by each of analyzed methods. The analysis of procedures is lead and the most precise models are revealed.
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2

Kazakova, N. A., A. F. Leshchinskaya, and A. E. Sivkova. "Assessment and forecasting bankruptcy risk of mining companies." Russian Journal of Industrial Economics 11, no. 3 (2018): 261–72. http://dx.doi.org/10.17073/2072-1633-2018-3-261-272.

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Comparative analysis of domestic and foreign methods of bankruptcy diagnostics allowed to offer key determinants for modeling the probability of bankruptcy taking into account the industry specificity of mining and metallurgical companies. On the basis of a generalization of the results of the correlation analysis, a high interrelation between indices of industrial production and indices – indicators of the probability of bankruptcy of these companies was revealed. The possibilities of monitoring the evaluation of indicators obtained on the basis of financial statements. Monitoring of calculat
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3

Maykova, Anastasia A., Elena V. Rytova, and Yulia A. Dubolazova. "BANKRUPTCY FORECAST OF RUSSIAN CONSTRUCTION COMPANIES FOR STABLE DEVELOPMENT OF THE REGIONAL ECONOMY." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 3/11, no. 156 (2025): 120–34. https://doi.org/10.36871/ek.up.p.r.2025.03.11.013.

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The issue of forecasting corporate bankruptcy has been relevant in recent years due to economic instability, geopolitical tensions, increased competition, the COVID-19 pandemic, and sanctions pressure. Corporate bankruptcy manifests itself in various forms and scales depending on the industry, region, and general economic situation in the country, and affects the state of the region. The purpose of the study is to develop a model for forecasting the probability of bankruptcy of companies involved in the construction industry. According to the modeling results, the overall predictive ability of
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4

БЖАССО, А. А. "ОЦЕНКА РИСКА НАСТУПЛЕНИЯ ВЕРОЯТНОСТИ БАНКРОТСТВА ОРГАНИЗАЦИИ НА ОСНОВЕ РОССИЙСКИХ И ЗАПАДНЫХ МОДЕЛЕЙ ПРОГНОЗИРОВАНИЯ БАНКРОТСТВА В ЦЕЛЯХ УСОВЕРШЕНСТВОВАНИЯ СТРАТЕГИИ ЕЕ УСТОЙЧИВОГО РАЗВИТИЯ". Экономика и предпринимательство, № 10(171) (7 жовтня 2024): 1422–27. http://dx.doi.org/10.34925/eip.2024.171.10.260.

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В статье описана деятельность компаний в современных условиях, их подверженность воздействию кризисных факторов, которые могут привести к вероятности банкротству. Дано определение и раскрыто понятие банкротства. Описаны существующие методы прогнозирования вероятности банкротства. Проведена оценка риска наступления вероятности банкротства организации на основе российских и западных моделей прогнозирования банкротства в целях усовершенствования стратегии устойчивого развития, на основе экономических показателей, ЗАО «Урупский ГОК». Обоснована необходимость прогнозирования вероятности наступления
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5

Hubanova, I. V. "Features of Modeling the Probability of Bankruptcy Using Discriminant Models with Application in Economic Forensics." Business Inform 2, no. 517 (2021): 88–93. http://dx.doi.org/10.32983/2222-4459-2021-2-88-93.

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The article is aimed at studying the methodologies of forecasting bankruptcy, their application in forensic economic expertise, which will allow to make managerial decisions substantiated from the point of view of financial security of an enterprise and create opportunities for stable functioning and development of the enterprise. All enterprises are affected by negative factors and may find themselves in a crisis situation. That is why the management of enterprise should apply all existing measures to prevent bankruptcy and overcome crisis situations. Any crisis situation can be corrected if
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6

Ivanova, E. "TO THE QUESTION OF IMPROVING THE METHODOLOGY OF FORECASTING BANKRUPTCY SMALL BUSINESS." EurasianUnionScientists 7, no. 9(78) (2020): 36–41. http://dx.doi.org/10.31618/esu.2413-9335.2020.7.78.1028.

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The aim of this paper is to identify the possibilities of applying of existing models for estimation of the probability of bankruptcy in domestic and foreign practice to predict the risk of default of small enterprises. The relevance of this research is due to the role the small businesses play in the social-economic development of regions and the country as a whole. The relationship between individual indicators of the region’s social-economic situation and the level of bankrupt enterprises in the total number of enterprises is shown. The differentiation of Russian regions in terms of social-
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7

KULAI, Svetlana V., and Evgenii E. SHVAKOV. "Development of MDA and Logit models to predict bankruptcy probability for Russian coal enterprises." Economic Analysis: Theory and Practice 24, no. 3 (2025): 194–216. https://doi.org/10.24891/ea.24.3.194.

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Subject. The study deals with forecasting the probability of bankruptcy for coal enterprises, represented by two variants of mathematical models: the MDA model and the logit model. Objectives. The aim is to develop a methodology for predicting the probability of bankruptcy based on data from Russian coal industry enterprises for 2014–2022. Methods. The study employs the coefficient method, correlation analysis, k-means method, cluster and factor analysis, MDA and logit models. Results. The development of models included several stages: formation of a basic system of financial coefficients; cre
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8

Levandovska, O. "APPLICATION OF ANALYTICAL TOOLS FOR EVALUATING THR PERFORMANCE OF A MANUFACTURING ENTERPRISE." Series: Economic science 5, no. 179 (2023): 9–14. http://dx.doi.org/10.33042/2522-1809-2023-5-179-9-14.

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The article focuses on the use of analytical tools, namely, methods of assessing the bankruptcy of an enterprise, developed by foreign authors. Calculations are made using various models, and it is proved that at the moment there is no "ideal" model that will take into account all the realities of the enterprise. The current unstable situation of Ukraine's economy, namely the full-scale invasion of the aggressor country by the Russian Federation, creates additional difficulties for enterprises for development and normal functioning, so the issue of timely performance assessment and efficiency
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9

Xiaosi, Xu, Chen Ying, and Zheng Haitao. "The comparison of enterprise bankruptcy forecasting method." Journal of Applied Statistics 38, no. 2 (2011): 301–8. http://dx.doi.org/10.1080/02664760903406470.

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10

Лоханова and Valyentina Lokhanova. "Forecasting in Crisis Management Organization." Administration 4, no. 4 (2016): 91–98. http://dx.doi.org/10.12737/22795.

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The relevance of scientific research in the field of crisis management due to the depressed state of the
 Russian economy, including its business sector. One of the important directions of the scientific school of the
 Department of corporate management is forecasting the development of the organization in crisis. The article
 defines the essence of anti-crisis forecasting, its objective, stages and influencing factors. Special attention
 is given to forecasting methods, their classification, selection criteria. The contribution of famous Russian
 and foreign scientist
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11

RZAEV, G., and I. DUBIK. "DIRECTION OF FINANCIAL ANALYSIS IN THE SECTION OF BANKRUPTCY PROBABILITY ASSESSMENT MODELS." Herald of Khmelnytskyi National University. Economic sciences 280, no. 2 (2020): 249–52. https://doi.org/10.31891/2307-5740-2020-280-2-44.

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The purpose of the article is to study modern foreign models for assessing the probability of bankruptcy of the enterprise and substantiate the areas of financial analysis for the financial condition. Some models for estimating the probability of bankruptcy are considered. The systematization of foreign forecasting models is carried out and some factors that form the models are considered. It is proved that the choice of assessment models is based on the peculiarities of the functioning of the economy. The expediency of conducting an analysis of financial reporting indicators is emphasized. Th
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12

KOTZERUBA, N.V. "Methodology for predicting the potential bankruptcy of an enterprise." Market Relations Development in Ukraine №9(256)2022 102 (December 15, 2022): 39–50. https://doi.org/10.5281/zenodo.7441787.

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The subject of the study is a set of methodical features of the implementation of the financial status and forecasting the threat of bankruptcy of the enterprise. The purpose of writing the article is to study the theoretical aspects of the analysis for the purpose of forecasting the bankruptcy of an enterprise based on the results of a decrease in its solvency. Methodology of the work – in the process of writing this article, general scientific and specific methods were used, in particular, economic and logical methods and methods of economic analysis; graphical and tabular methods were
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13

Zubrenkova, О. А., E. V. Lisenkova, and А. S. Ilin. "ASSESSMENT OF THE PROBABILITY OF FORECASTING BANKRUPTCY OF AGRICULTURAL ORGANIZATIONS." Фундаментальные исследования (Fundamental research), no. 12 2020 (2020): 74–79. http://dx.doi.org/10.17513/fr.42912.

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14

T. O. MELIKHOVA. "ANALYSIS OF THE FINANCIAL SITUATION AND THE IDENTIFICATION OF THREATS AS A MEANS OF FORECASTING THE PROBABILITY OF BANKRUPTCY OF AN INDUSTRIAL ENTERPRISE." REVIEW OF TRANSPORT ECONOMICS AND MANAGEMENT, no. 1(17) (June 24, 2019): 48–57. http://dx.doi.org/10.15802/rtem.v0i1(17).176496.

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The purpose. The work is devoted to the analysis of the financial condition and the identification of threats as a means of predicting the probability of bankruptcy an industrial enterprise. The methodology. To solve the tasks it`s proposed to apply the methodology for predicting the probability of bankruptcy of an enterprise. The results. The paper considers the existing indicators of financial analysis of an industrial enterprise which are often used in practice. They have certain drawbacks since it`s difficult to choose a convenient methodology for conducting financial analysis through thei
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15

Meena, Manish, Ashish Pandey, and Ajay Garg. "Machine Learning Models Comparison for Bankruptcy Predication for Indian Companies." Journal of Prediction Markets 18, no. 3 (2025): 3–18. https://doi.org/10.5750/jpm.v18i3.2166.

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It is essential to recognize that dynamics of bankruptcy events vary across regions and legal frameworks. In this context, the paper aims to fill the critical gap in literature by presenting an analysis of machine learning (ML) models for early detection of bankruptcy probability among Indian companies operating under the Insolvency and Bankruptcy Code (IBC) of 2016. This study distinguishes itself by leveraging an extensive dataset covering the period from FY 2016 to FY 2022, encompassing 65,583 entries for 7,008 unique corporations, including 257 bankrupt entities. This paper employs various
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16

Gorbatkov, S. A., F. S. Rastegaeva, S. A. Farkhieva, T. V. Nakonechnaya, and T. N. Shashkova. "NEURONET LOGISTIC DYNAMIC MODEL TO DIAGNOSE AND FORECAST THE STAGES OF DEVELOPING BANKRUPTCY OF CORPORATIONS." Humanities & Social Sciences Reviews 7, no. 3 (2019): 604–11. http://dx.doi.org/10.18510/hssr.2019.7391.

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Purpose of Study: The object of the study is the problem of financial management, in particular, the problem of forecasting the stage of developing bankruptcy of corporations-loaners and decision-making on the restructuring of credit debt.
 The subject of the research is the development of a dynamic model of bankruptcies with continuous time in conditions of high uncertainty and noise data, which allows diagnosing the stages of bankruptcy of the simulated object at any time (between the “time slices” in the data), as well as to predict the probability of bankruptcy in time ahead for a giv
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17

L. H, Solianyk, Shtefan N. M, and Nikolaienko A. O. "Fintech tools for predicting bankruptcy: integration of traditional and innovative approaches." Economic Bulletin of Dnipro University of Technology 81 (June 2023): 128–35. http://dx.doi.org/10.33271/ebdut/82.128.

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Methods. The theoretical and methodological basis of the study is the scientific developments of domestic and foreign scholars related to the issues of determining the role and features of using traditional discriminant models of bankruptcy forecasting and modern FinTech tools. The results of the study were obtained using the methods of abstraction; general and particular – in establishing the unity of existing traditional methods of bankruptcy forecasting and innovative FinTech technologies; the systematic method was used to systematise a wide range of FinTech tools specifically designed to p
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18

PETYK, Liubov, and Mykhailo PISIAK. "Methodological approaches to the diagnostic and assessment of the probability of business bankruptcy." Economics. Finances. Law 10/1, no. - (2022): 22–26. http://dx.doi.org/10.37634/efp.2022.10(1).5.

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Introduction. Methodological approaches to forecasting the financial state of enterprises from the point of view of possible bankruptcy are generalized and systematized. The classification of crisis diagnosis methods was studied and the stages of the crisis were considered. The modern practice of using foreign models for diagnosing the probability of the threat of insolvency of business entities is analyzed, with the identification of their advantages and disadvantages. Recommendations for improving approaches to assessing the probability of bankruptcy of national enterprises using foreign met
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19

Kupriushina, Olga M., and Nadezhda F. Scherbakova. "Applying forecast reporting to assess the probability of financial insolvency (bankruptcy)." Vestnik Voronezhskogo gosudarstvennogo universiteta. Ser.: Ekonomika i upravlenie = Proceedings of Voronezh State University. Series: Economics and Management, no. 2 (June 30, 2022): 71–82. http://dx.doi.org/10.17308/econ.2022.1/3916.

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Subject. During the pandemic, contacts between many organisations and their business partners were disrupted: their sales volumes and other sources of financing decreased and non-payments became more frequent. These reasons may result in an increased risk of financial insolvency for economic entities and may lead to bankruptcy. In this regard, financial forecasting is a way to avoid negative consequences.Purpose. The development of a universal analytical tool that allows predicting the probability of financial insolvency (bankruptcy) which has been tested within the PROTEK group of companies.
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20

Boyko, N. E., and E. A. Kalinina. "FORECASTING THE PROBABILITY OF BANKRUPTCY OF THE ENTERPRISE RAPID DIAGNOSTIC METHODS." Vestnik Volzhskogo universiteta im V N Tatishcheva 2, no. 1 (2022): 179–90. http://dx.doi.org/10.51965/20767919_2022_2_1_179.

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21

Калінеску, Тетяна Василівна, та Вікторія Володимирівна Височина. "ДІАГНОСТИКА ЙМОВІРНОСТІ БАНКРУТСТВА ПІДПРИЄМСТВ". TIME DESCRIPTION OF ECONOMIC REFORMS, № 1 (2 квітня 2024): 50–57. http://dx.doi.org/10.32620/cher.2024.1.06.

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Formulation of the problem. In the period of today's complex challenges - the conduct of military operations on the territory of Ukraine, the consequences of the pandemic, an unfavorable investment climate, and others - the detection of the probability of bankruptcy of enterprises is of particular importance. Timely detection of the onset of crisis phenomena using various methods and models and the adoption of precautionary measures ensure the avoidance of financial instability in the future. Therefore, conducting a timely diagnosis of the probability of bankruptcy is relevant, because there i
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22

Бжассо, А. А., and О. А. Котлярова. "The impact of the probability of bankruptcy of companies on the economy of the region during the crisis: problems and ways to solve them." Экономика и предпринимательство, no. 1(126) (March 12, 2021): 884–88. http://dx.doi.org/10.34925/eip.2021.126.01.173.

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В статье рассмотрено влияние кризисных факторов на экономику нашей страны и на экономику регионов, причины ухудшения финансового состояния организации и вероятность наступления банкротства компаний. Рассмотрены различные подходы и методы прогнозирования вероятности банкротства организаций. Описано практическое применение моделей прогнозирования вероятности наступления банкротства, на примере ЗАО «Урупский ГОК». Обоснована взаимосвязь финансовой устойчивости компаний, и успешного применение инструментов антикризисного управления региональной экономики. The article considers the impact of the cr
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23

Marsenne, Maureen, Tubagus Ismail, Muhamad Taqi, and Imam Abu Hanifah. "Financial distress predictions with Altman, Springate, Zmijewski, Taffler and Grover models." Decision Science Letters 13, no. 1 (2024): 181–90. http://dx.doi.org/10.5267/j.dsl.2023.10.002.

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Several models have been developed to predict financial difficulties and corporate bankruptcy. In this research various models were employed, including the Altman model (referred to as the Z-Score), the Springate model (known as the S-Score), the Zmijewski model (designated as the X-Score), and the Grover model (referred to as the G-Score). These techniques serve the purpose of evaluating the likelihood of encountering financial difficulties, which in turn determines the probability of PT Garuda Indonesia (Persero) Tbk going bankrupt. The study utilized secondary data sourced from financial st
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24

БЖАССО, А. А. "METHODS OF FORECASTING BANKRUPTCY OF COMPANIES: CLASSIFICATION, ESSENCE AND NECESSITY OF DEVELOPING METHODOLOGICAL APPROACHES FOR ASSESSING AND PREDICTING THE PROBABILITY OF BANKRUPTCY IN A CRISIS." Экономика и предпринимательство, no. 1(162) (February 11, 2024): 919–24. http://dx.doi.org/10.34925/eip.2024.162.1.178.

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В статье описана деятельность компаний в современных условиях с учетом влияния факторов внешней и внутренней среды, их подверженность воздействию кризисных факторов, которые могут привести к вероятности банкротству. Рассмотрены основные признаки наступления банкротства, дано определение и раскрыто понятие банкротства. Описаны существующие методы прогнозирования вероятности банкротства компаний, зарубежных и отечественных авторов, их классификация, сущность, сделаны выводы о их достоинствах и недостатках. Обоснована необходимость разработки методических подходов оценки и прогнозирования вероятн
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25

Краснобокая and Irina Krasnobokaya. "Statistical prediction of probability of financial insolvency of industrial enterprises in the conditions of import substitution." Central Russian Journal of Social Sciences 11, no. 4 (2016): 173–83. http://dx.doi.org/10.12737/21334.

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The problem of diagnosis and prevention of financial insolvency of the domestic enterprises is one of the central problems in the system of anti-crisis financial management. Taking into account the crisis in the economy and the cyclical increase in the number of bankruptcies, it is of particular relevance in theoretical and applied aspects. The most acute problem is the bankruptcy in the industry, the development of which is an essential factor in the growth of the national economy in the context of import substitution. 
 Every fifth domestic company is on track to bankruptcy. In this sit
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26

Vasylieva, N., N. Bolila, and T. Tsyfra. "Forecasting the level of rehabilitation capacity of the construction company." Ways to Improve Construction Efficiency 1, no. 49 (2022): 157–63. http://dx.doi.org/10.32347/2707-501x.2022.49(1).157-163.

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Theoretical bases that reveal the concept of enterprise reorganization are substantiated, the causes and consequences of reorganization are determined, the models of calculating the probability of bankruptcy are investigated. The works of leading scientists in the field of research of enterprise rehabilitation are analyzed. The main financial and economic indicators are considered, with the help of which it is possible to predict in advance the financial condition of a construction enterprise and its rehabilitation capacity. Factors that reduce the quality of enterprise management have been id
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27

ANTYPENKO, Nаdiia, and Maksym PROKOPENKO. "Methodological and theoretical fundamentals of bankruptcy probability assessment of "UkSATSE" enterprise." Economics. Finances. Law 5/2, no. - (2022): 5–9. http://dx.doi.org/10.37634/efp.2022.5(2).1.

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In the economic sciences today there is a large number of developments in the field of analysis and forecasting of insolvent companies, which in turn helps to find and assess the criteria for the probability of bankruptcy of insolvent entities on the example of state enterprise “Ukrainian State Air Traffic Services Enterprise (UkSATSE)”. This paper is devoted to the reflection of the main methods and models for estimating the probability of bankruptcy of the enterprise, which were proposed by foreign and domestic scientists. In particular, it is noted that the assessment of the threat of bankr
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28

Naumov, Ilya V., Anna A. Bychkov, and Natalia L. Nikulina. "Scenario-Based Forecasting of Bankruptcy Risks for Woodworking Industry Enterprises in the Sverdlovsk Region." Journal of Applied Economic Research 24, no. 2 (2025): 555–83. https://doi.org/10.15826/vestnik.2025.24.2.019.

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The woodworking industry in the Sverdlovsk region is a significant sector of the regional economy, contributing to the development of small and medium-sized businesses, attracting investments, and creating jobs. However, the high dependence on timber prices, transportation costs, and macroeconomic factors makes enterprises in industry vulnerable and increases their risk of bankruptcy. This article explores the application of regression and autoregressive ARIMA/ARMA models to develop predictive scenarios for changes in the probability of bankruptcy among enterprises in the industry. The study u
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AFANASEVA, K., M. PRIMAKOVA, and Z. SAGDILLAEVA. "FORECASTING THE PROBABILITY OF BANKRUPTCY IN THE CONTEXT OF CRISIS MANAGEMENT OF ORGANIZATIONS." Vestnik of Polotsk State University Part D Economic and legal sciences, no. 3 (December 18, 2023): 6–13. http://dx.doi.org/10.52928/2070-1632-2023-65-3-6-13.

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The article examines methodological approaches (regulated and author's) to identify signs of bankruptcy and analyze
 the financial condition, and identifies their significant disadvantages. The authors conducted a comparative analysis of the
 official methodology for determining the insolvency of organizations of the Republic of Belarus with other post–Soviet countries
 similar in terms of business conditions - the Russian Federation, the Republic of Uzbekistan, and Ukraine. The complexity
 and versatility of the problems associated with the methodological support of bankru
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30

Dominova, Inna, and Tetiana Kysil. "Assessment and forecasting of the probability of bankruptcy of banking institutions of Ukraine." Modeling and Information Systems in Economics, no. 99 (November 25, 2020): 70–83. http://dx.doi.org/10.33111/mise.99.6.

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31

Shumway, Tyler. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model." Journal of Business 74, no. 1 (2001): 101–24. http://dx.doi.org/10.1086/209665.

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32

Myagkova, Tat'yana, and Victoria Annenkova. "DEVELOPMENT OF MODELS FOR PREDICTING THE PROBABILITY OF BANKRUPTCY IN THE CONTEXT OF BUSINESS FINANCIAL SECURITY." Russian Journal of Management 8, no. 2 (2020): 126–30. http://dx.doi.org/10.29039/2409-6024-2020-8-2-126-130.

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Forecasting is one of the most important stages in planning future policies to ensure economic security. And countering the financial insolvency of an enterprise should begin with predicting the risk of this phenomenon. The risk of bankruptcy is predicted using domestic and foreign models for predicting potential threats to the organization's financial security. However, many of these models are outdated or not focused on the conditions of our country's economy, which affects the reliability of the results obtained and the effectiveness of decisions based on them. In this regard, there is an i
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33

Zakirova, D. F. "On predicting the probability of default of credit organizations in the Russian Federation." Russian Journal of Economics and Law 18, no. 1 (2024): 70–87. http://dx.doi.org/10.21202/2782-2923.2024.1.70-87.

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Objective: to form a model for predicting the default of credit organizations under the modern conditions of the banking sector functioning.Methods: unidimensional analysis of variance, regression analysis of binary choice models.Results: in the modern economy, the banking system stability largely affects not only the financial sector, but also the economic and investment climate in the country. Understanding of the banks’ influence on the economy necessitates the formation of appropriate effective forecasting systems that allow identifying problem banks before revoking their licenses is neces
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34

Kazakova, Nataliya, and Marina Bobkova. "Analysis and diagnostics of business risks of the company: forecasting and control of probability of bankruptcy." Russian Journal of Management 7, no. 4 (2020): 91–95. http://dx.doi.org/10.29039/2409-6024-2019-7-4-91-95.

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The article discusses the author’s methodology and analytical tools for assessing business risks and forecasting the business continuity (probability of bankruptcy) of companies with the possibility of its implementation in a computer environment. The proposed methodology consists of four stages: assessment of financial results; solvency assessment; identification, calculation and assessment of financial risks of the company's business continuity; forecasting changes in the level of risk of business continuity using the developed calculator for calculating risk factors indicators. This techniq
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Vorkunova, O. V., and N. V. Yarovа. "MONITORING THE PROBABILITY OF BANKRUPTCY AS A BASIS OF INNOVATIVE DEVELOPMENTOFPORTENTERPRISES." Development of Management and Entrepreneurship Methods on Transport (ONMU) 78, no. 1 (2022): 5–19. http://dx.doi.org/10.31375/2226-1915-2022-1-5-19.

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Thearticledealswithmonitoringthemanagementoftheprobabilityofbankruptcyofportenterprises.Inmarketconditions,enterprisesmustbeconfidentintheirreliability and economic stability, otherwise they get a situation of their own insolvency and havethe risk of obtaining the status of bankruptcy of the enterprise.In this regard, the heads ofenterprises, managers of different levels of management should carry out anti-crisis diagnosticsof the financial condition of their own enterprise in order to avoid possible bankruptcy, and in theeventofathreatofbankruptcy,findopportunitiesforthefinancialrecoveryofthe
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Murovana, Tetiana, and Vladyslav Paskhal. "Diagnosis of the crisis possibility and its effectiveness to maintain the financial stability of entrepreneurs." Economic Analysis, no. 29(4) (2019): 121–31. http://dx.doi.org/10.35774/econa2019.04.121.

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Introduction. Transformational changes in the national economy, its high level of dependence on the development trends of developed countries, and unstable financial situation require the search for effective tools for identifying and minimizing regulatory, financial, tax and reputational risks in business entities. The diagnosis of probability of crisis and bankruptcy is an effective tool for maintaining the financial stability of enterprises. Despite the large number of researchers and their achievements, the large number of methods and models for predicting the likelihood of bankruptcy, thi
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VEREVKA, Tat'yana V., and Angelina E. EPICHENKO. "Developing a model for predicting bankruptcy of construction industry enterprises." Economic Analysis: Theory and Practice 23, no. 5 (2024): 878–92. http://dx.doi.org/10.24891/ea.23.5.878.

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Subject. The article considers methods of forecasting bankruptcy of a construction industry enterprise. Objectives. The study aims to develop an industry model to forecast bankruptcy of construction companies. Methods. The study employs general scientific methods of cognition, like analysis, synthesis, comparison, generalization, observation. The main statistical and economic research method is linear multidimensional discriminant analysis (MDA), which is used to perform calculations in the program for statistical data processing, SPSS Statistics. Results. We selected optimal predictors for ea
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Babayev, Volodymyr M., Olena V. Dymchenko, Olha O. Rudachenko, Patrizia Gazzola, Eka Sepashvili, and Kateryna V. Shkurupiy. "Development of a Mechanism for Preventing Bankruptcy of Enterprises at the Regional and National Level." Mechanism of an Economic Regulation 2021, no. 3 (2021): 108–17. http://dx.doi.org/10.21272/mer.2021.93.10.

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The paper develops a mechanism for preventing bankruptcy of enterprises at the regional level, which allows management to make managerial decisions on time that will effectively assess the threat of bankruptcy and anticipate it in advance. The developed research mechanism includes 3 main stages: formation of the feature space; enterprise`s bankruptcy probability assessment; forecasting the state of the enterprise. One proved that every year most Ukrainian enterprises have insignificant incomes and receive huge losses, as a result an unemployment is growing in the country. Quarantine restrictio
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Lorca, Pedro, Manuel Landajo, and Javier De Andrés. "Nonparametric Quantile Regression-Based Classifiers for Bankruptcy Forecasting." Journal of Forecasting 33, no. 2 (2013): 124–33. http://dx.doi.org/10.1002/for.2280.

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40

Voiko, A. V. "Models for Predicting the Probability of Bankruptcy: Applying in Construction Companies." Accounting. Analysis. Auditing 8, no. 1 (2021): 13–23. http://dx.doi.org/10.26794/2408-9303-2021-8-1-13-23.

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The paper examines some foreign and domestic methods of forecasting bankruptcy of enterprises in order to apply them in the largest construction organizations in Russia. The empirical basis of the study is the construction companies that are comparable in size, revenue, and market share. Their annual financial statements preceding the analysis are the information base of calculations. The quality of forecasts has been checked on independent indicators’ calculations of financial analysis, as well as using data from financial markets and share prices under studied companies. The result of the re
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Kotseruba, Nataliia, and Іryna Krupelnytska. "FORECASTING THE PROBABILITY OF BANKRUPTCY OF THE ENTERPRISE ON THE BASIS OF IMPROVING ITS ANALYSIS." European Journal of Economics and Management 8, no. 3 (2022): 23–29. http://dx.doi.org/10.46340/eujem.2022.8.3.4.

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42

Nataliia, Koloshko. "ESTIMATE OF THE PROBABILITY OF BANKRUPTCY AS A METHOD FOR FORECASTING THE ENTERPRISE FINANCIAL CONDITION." Scientific Herald of Kherson State University: Economics Sciences 33 (March 25, 2019): 231–36. http://dx.doi.org/10.32999/ksu2307-8030/2019-33-46.

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Shkolnyk, Inna, Tomasz Pisula, Liliia Loboda, and Natalia Nebaba. "Financial crisis of real sector enterprises: an integral assessment." Investment Management and Financial Innovations 16, no. 4 (2019): 366–81. http://dx.doi.org/10.21511/imfi.16(4).2019.31.

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Successful crisis resolution of the enterprise depends heavily on its timely detection, which is facilitated by the use of forecasting models. This allows understanding the scale of the problems in a timely manner and developing the appropriate measures, applying various financial mechanisms to prevent it, and in case of occurrence, reducing the amount of losses. In this context, it is important to choose the most optimal informational model that would provide the most objective forecasts, considering the financial activity peculiarities of the analyzed enterprise. Given a wide list of models
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Opekunov, A. N., I. N. Kamardin, N. V. Nikitina, and N. V. Kamardina. "Formation of Analytical Tools of Anti-Crisis Business Regulation on the Basis of Logit-Models." SHS Web of Conferences 62 (2019): 03002. http://dx.doi.org/10.1051/shsconf/20196203002.

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Current trends in economic development emphasize the importance of crisis management at both the macro and microeconomic levels. The analysis of current problems of Russian enterprises has shown that at present some outdated approaches to this problem prevail in domestic science and practice. Therefore, a new scientific direction “Anti-crisis business regulation” is becoming increasingly important. In the world practice, the term crisis-management is not associated solely with the problems of bankruptcy. On the contrary, it is a broader concept that includes a range of problems. Therefore, the
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Zyukin, Danil Alekseevich, Alexey Anatolyevich Golovin, Olga Viktorovna Pshenichnikova, and Marina Nikolaevna Nadzhafova. "Assessing the functionality of models for predicting pharmaceutical companies." Revista Amazonia Investiga 9, no. 28 (2020): 272–80. http://dx.doi.org/10.34069/ai/2020.28.04.30.

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The article considers the problem of the functionality of existing bankruptcy forecasting models for the pharmaceutical industry, the significance of which is due to the strategic role of this industry in ensuring drug safety in Russia. In conditions of import dependence, it is possible to increase the competitiveness of domestic enterprises by investing in it, which actualizes the task of increasing their investment attractiveness, one of the main elements of which is long-term and predictable financial stability. The study shows that today the assessment of financial stability and the likeli
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Kovacova, Maria, and Tomas Kliestik. "Logit and Probit application for the prediction of bankruptcy in Slovak companies." Equilibrium 12, no. 4 (2017): 775–91. http://dx.doi.org/10.24136/eq.v12i4.40.

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Research background: Prediction of bankruptcy is an issue of interest of various researchers and practitioners since the first study dedicated to this topic was published in 1932. Finding the suitable bankruptcy prediction model is the task for economists and analysts from all over the world. forecasting model using. Despite a large number of various models, which have been created by using different methods with the aim to achieve the best results, it is still challenging to predict bankruptcy risk, as corporations have become more global and more complex.
 Purpose of the article: The ai
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Fantazzini, Dean. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models." Information 14, no. 5 (2023): 254. http://dx.doi.org/10.3390/info14050254.

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In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the daily range incorporates all the information provided in traditional daily datasets, including the open-high-low-close (OHLC) prices for each asset. We evaluated the accuracy of the probability of death estimated with the daily range against various forecasting models, including credit scoring models, machine learning models, and time-series-base
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Restaino, Marialuisa, and Marco Bisogno. "A Business Failure Index Using Rank Transformation." International Journal of Economics and Finance 11, no. 1 (2018): 56. http://dx.doi.org/10.5539/ijef.v11n1p56.

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The global financial crisis entails a renewed attention from financial institutions, academics, and practitioners to corporate distress analysis and its forecasting. This study aims to propose a model for predicting default risk based on a business failure index using rank transformation. The procedure suggested is able to capture firms’ financial difficulties and forecast bankruptcy through the construction of a failure index based on some relevant financial ratios. By means of the estimation of failure probability, it allows to classify and predict business distress in time to take
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Lagodiienko, N. V., V. S. Ivanchenkov, and I. I. Horobets. "https://www.business-inform.net/article/?year=2020&abstract=2020_12_0_265_270&lang=en." Business Inform 12, no. 515 (2020): 271–79. http://dx.doi.org/10.32983/2222-4459-2020-12-271-279.

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Ensuring the harmonious economic development of enterprises in leading sectors of the economy requires constant monitoring of the objectives and the availability of a plan to combat potential crises at various levels of management. The experience of implementing the tools of operational and strategic controlling in enterprises shows a significant increase in the level of competitiveness, improving the forecasting of rapid response to such a problem. The purpose of this article is development of an improved model of analysis and forecasting of the probability of crisis and bankruptcy for the en
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Ha, Hong Hanh, Ngoc Hung Dang, and Manh Dung Tran. "Financial distress forecasting with a machine learning approach." Corporate Governance and Organizational Behavior Review 7, no. 3 (2023): 90–104. http://dx.doi.org/10.22495/cgobrv7i3p8.

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A highlighted issue relating to the financial distress of public companies raises more debate from both academic and current practice perspectives as financial markets are currently a key source of growth for the local and international economies. In the context of advanced technology and the digital revolution, forecasting and early detection of financial distress are important methods that contribute to increasing confidence between investors and the market and help to make sound decisions promptly to avoid reaching bankruptcy (Fuentes et al., 2023). This study employs machine learning algor
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