Financial distress prediction in Slovakia: An application of the CART algorithm
M. Durica, J. Frnda, Lucia Švábová
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引用次数: 3
Abstract
The topic of predicting financial distress situation has been of interest to many economists and scientists from around the world for several years. As it turned out in practice, the application of existing prediction models to predict the financial difficulties of Slovak companies brings lower prediction accuracy, as these models were created in the conditions of another country. Therefore, the main aim of the article is to create the model for the prediction of the financial distress of the Slovak companies, based on the real conditions of Slovak economics. For this analysis, a dataset of the most important financial ratios that may affect the financial health of the Slovak companies was obtained from the Amadeus database, containing the data on more than 100,000 real companies operating in the Slovak economy in the period 2016 to 2018. For the creation of the models for the prediction of the financial distress of companies one year and Received: July, 2020 1st Revision: December, 2020 Accepted: March, 2021 DOI: 10.14254/20718330.2021/14-1/14 Journal of International Studies S ci en ti fi c P a pe rs © Foundation of International Studies, 2021 © CSR, 2021 Journal of International Studies Vol.14, No.1, 2021 202 two years in advance, the CART algorithm generating the binomial decision tree was used. The developed models achieve an overall accuracy of 87.3% and 91.9% and are very simple to the real application. The results from this prediction are important not only for companies themselves but also for all their stakeholders, as they could help the company to mitigate or eliminate the threat of financial distress and the other corporate risks related to such a situation in the company.
斯洛伐克的财务困境预测:CART算法的应用
多年来,预测金融危机一直是世界各地许多经济学家和科学家感兴趣的话题。实践证明,由于这些模型是在另一个国家的条件下建立的,因此使用现有的预测模型来预测斯洛伐克公司的财务困难会带来较低的预测精度。因此,本文的主要目的是基于斯洛伐克经济的实际情况,建立预测斯洛伐克公司财务困境的模型。为了进行这项分析,从Amadeus数据库中获得了可能影响斯洛伐克公司财务健康的最重要财务比率的数据集,其中包含2016年至2018年期间在斯洛伐克经济中运营的100,000多家实体公司的数据。创建模型的预测财务困境的公司一年,收到了:7月,2020年修订1:12月,2020年接受:三月,2021 DOI: 10.14254 / 20718330.2021 / 14-1/14国际研究杂志》的年代ci在ti fi c P pe rs©国际研究的基础,2021©CSR, 2021年国际研究杂志》第九卷,第一,2021 202提前两年,购物车使用算法生成二叉决策树。所建立的模型总体精度分别达到87.3%和91.9%,对实际应用非常简单。这一预测的结果不仅对公司本身很重要,而且对所有利益相关者都很重要,因为它们可以帮助公司减轻或消除财务困境的威胁,以及与公司这种情况相关的其他公司风险。
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