Assessment of the relationship between liquidity and unprofitability of companies in preventing their bankruptcy

ПОЛЯКОВ, РОДІОН; Zayukov, Ivan

doi:10.21511/ppm.21(1).2023.13

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…Due to the impact of globalization and the consequences of the COVID-19 pandemic, it is no longer important to decide whether to predict bankruptcy at all but rather how to increase the accuracy of such predictions (Kitowski et al, 2022;Dinu & Bunea, 2022;Poliakov et al, 2023). The common element of most models is the prediction time horizon from 1 to 3 years.…”

Section: Introductionmentioning

confidence: 99%

Predicting bankruptcy using artificial intelligence: The case of the engineering industry

Letkovsky,

Jencova,

Vasanicova

et al. 2023

Economics &Amp; Sociology

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Bankruptcy prediction is a powerful early-warning tool and plays a crucial role in various aspects of financial and business management. It is vital for safeguarding investments, maintaining financial stability, making informed credit decisions, and contributing to the overall health of the economy. This paper aims to develop bankruptcy prediction models for the Slovak engineering industry and to compare their effectiveness. Predictions are generated using the classical logistic regression (LR) method as well as artificial intelligence (AI) techniques (artificial neural networks (ANN) and support vector machines (SVM)). Research sample consists of 825 businesses operating in the engineering industry (Manufacture of machinery and equipment n.e.c.; Manufacture of motor vehicles, trailers and semi-trailers; Manufacture of other transport equipment). The selection of eight financial indicators is grounded in prior research and existing literature. The results show high accuracy for all used methods. The SVM outcomes indicate a level of accuracy on the test set that is nearly indistinguishable from that of the ANN model. The use of AI techniques demonstrates their effective predictive capabilities and holds a significant position within the realm of tools for forecasting bankruptcy.

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Section: Introductionmentioning

confidence: 99%

Predicting bankruptcy using artificial intelligence: The case of the engineering industry

Letkovsky,

Jencova,

Vasanicova

et al. 2023

Economics &Amp; Sociology

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“…Розглядали проблематику законодавства про банкрутство та актуальні зміни до нього Васьковський О. [14], Островський С. [9].…”

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Банкрутство Українських Підприємств В Умовах Військової Агресії: Аналіз Основних Тенденцій

Вовк

2024

Електронний журнал "Ефективна економіка"

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Через загальну нестабільність економічної та політичної ситуації в Україні зумовлених повномасштабною збройною агресією росії, спостерігається загострення кризових явищ, погіршення умов ведення підприємницької діяльності, збільшується ризик банкрутства підприємств. У статті розглянуто трактування «банкрутства», доречність його ототожнення із дефініціями «неплатоспроможність» та «неспроможність». Висвітлено загальні причини настання банкрутства, зокрема вплив війни на діяльність суб'єктів господарювання. Досліджено помісячну інтенсивність відкриття проваджень про банкрутство за 2017-2023 рр. та проаналізовано кількість функціонуючих суб'єктів господарювання та частку збиткових, чисельність розглянутих справ про банкрутство, динаміку показників досудової санації, санації, ліквідації, відкритих проваджень у справі про неплатоспроможність та введених процедур погашення боргів боржника. Наведено коротку характеристику судових процедур, які застосовуються щодо боржника юридичної та фізичної особи. Також було розглянуто внесені під час воєнного стану зміни до законодавства про банкрутство. В результаті запропоновано кроки для покращення умов введення бізнесу і зниження ризику банкрутства, на державному, з врахуванням досвіду країн, що перебували в схожій ситуації, та підприємницькому рівнях. Due to the general instability of the economic and political situation in Ukraine caused by the full-scale armed aggression of Russia, there is an aggravation of crisis phenomena, deterioration of business conditions, and an increased risk of enterprise bankruptcy. The article examines the interpretation of «bankruptcy», the appropriateness of its identification with the definitions of «nonsolvency» and «insolvency». The general causes of bankruptcy are highlighted, in particular, the impact of war on the activities of business entities. The monthly intensity of opening bankruptcy proceedings for 2017-2023 was studied, and the number of operating business entities and the share of unprofitable ones, the number of considered bankruptcy cases, the dynamics of indicators of pre-trial rehabilitation, rehabilitation, liquidation, open insolvency proceedings and introduced repayment procedures were analyzed debts of the debtor. A brief description of the court procedures applied to the debtor of a legal entity and an individual is given. Changes to the bankruptcy legislation introduced during martial law were also considered. As a result, steps are proposed to improve the conditions for business introduction and reduce the risk of bankruptcy, at the state level, taking into account the experience of countries that were in a similar situation, and at the business level. The article assumes that the number of bankrupt business entities will increase due to the crisis situation in the country, difficult business conditions, and deterioration of the financial situation. On the one hand, bankruptcy is a solution to the problem of the insolvency of enterprises, it allows removing inefficient entities from the economic system, on the other hand,...

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The influence of interest rates on outstanding loans of enterprises on their structure in the bankruptcy warning system

Butyrskyi¹,

Lutkovska

ПОЛЯКОВ

et al. 2023

Problems and Perspectives in Management

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Small and medium-sized enterprises (SMEs) create more than half of the added value, providing about two-thirds of employment in most countries. However, they need more liquidity, access to credit resources, and significant outstanding loans. This study aims to identify the impact of interest rates on outstanding loans of enterprises on their structure as a way to prevent bankruptcy. The correlation-regression analysis used OECD statistical data for 2008‒2019 sampling individual countries; it showed an ambiguous situation between the interest rate and the share of outstanding loans of SMEs in the overall structure of outstanding loans. The paper verified constructed regression equations and estimated their parameters. The regression equations for Belgium, the Czech Republic, Estonia, and Latvia are statistically reliable. Thus, in Belgium and the Czech Republic, a negative relationship was recorded (r = –0.822; D = 0.675; r = –0.9274; D = 0.794; F-criterion &gt; Ft, respectively), and in Estonia and Latvia – a positive one (r = 0.876; D = 0.767; F-criterion &gt; F•Ft; r = 0.800; D = 0.641; F-criterion &gt; Ft , respectively). Australia, Italy, Slovakia, and France practically do not have a corresponding relationship. The regression equations make it possible to estimate the change in the level of interest rate on the share of outstanding loans of enterprises in the overall structure of outstanding loans, make predictions of the corresponding performance indicator, and develop measures of restoring the solvency of enterprises as an essential task of preventing their bankruptcy.

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Assessment of the relationship between liquidity and unprofitability of companies in preventing their bankruptcy

Cited by 4 publications

References 27 publications

Predicting bankruptcy using artificial intelligence: The case of the engineering industry

Predicting bankruptcy using artificial intelligence: The case of the engineering industry

Банкрутство Українських Підприємств В Умовах Військової Агресії: Аналіз Основних Тенденцій

The influence of interest rates on outstanding loans of enterprises on their structure in the bankruptcy warning system

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