Bankruptcy Prediction Model Development and its Implications on Financial Performance in Slovakia

Dominika Gajdosikova, K. Valaskova
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Abstract

Abstract Research purpose. Financial distress being a global phenomenon makes it impact firms in all sectors of the economy and predicting corporate bankruptcy has become a crucial issue in economics. At the beginning of the last century, the first studies aimed to predict corporate bankruptcy were published. In Slovakia, however, several prediction models were developed with a significant delay. The main aim of this paper is to develop a model for predicting bankruptcy based on the financial information of 3,783 Slovak enterprises operating in the manufacturing and construction sectors in 2020 and 2021. Design / Methodology / Approach. A prediction model that uses the appropriate financial indicators as predictors may be developed using multiple discriminant analysis. Multiple discriminant analysis is currently used in prediction model development. In this case, financial health is assessed using several variables that are weighted in order to maximise the difference between the average value calculated in the group of prosperous and non-prosperous firms. When developing a bankruptcy prediction model based on multiple discriminant analysis, it is crucial to determine the independent variables used as primary financial health predictors. Findings. Due to the discriminant analysis results, the corporate debt level of the monitored firms may be regarded as appropriate. Despite the fact that the model identified 215 firms in financial distress due to an insufficient debt level, 3,568 out of 3,783 Slovak enterprises operating in the manufacturing and construction sectors did not have any problems with financing their debts. The self-financing ratio was identified in the developed model as the variable with the highest accuracy. Based on the results, the developed model has an overall discriminant ability of 93% since bankruptcy prediction models require strong discriminating abilities to be used in practice. Originality / Value / Practical implications. The principal contribution of the paper is its application of the latest available data, which could help in more accurate financial stability predictions for firms during the current difficult period. Additionally, this is a ground-breaking research study in Slovakia that models the financial health of enterprises in the post-pandemic period.
破产预测模型的发展及其对斯洛伐克财务绩效的影响
研究目的。金融危机是一种全球性的现象,它影响到所有经济部门的公司,预测公司破产已成为经济学中的一个关键问题。上世纪初,第一批旨在预测企业破产的研究发表了。然而,在斯洛伐克,几个预测模式的发展有很大的延迟。本文的主要目的是根据2020年和2021年在制造业和建筑业经营的3,783家斯洛伐克企业的财务信息,开发一个预测破产的模型。设计/方法论/方法。使用适当的财务指标作为预测指标的预测模型可以使用多重判别分析来开发。多元判别分析是目前应用于预测模型开发的一种方法。在这种情况下,使用几个变量来评估财务健康状况,这些变量经过加权,以便最大限度地提高在繁荣和不繁荣的公司组中计算的平均值之间的差异。在建立基于多元判别分析的破产预测模型时,确定作为主要财务健康预测因子的自变量是至关重要的。发现。根据判别分析结果,被监测企业的公司债务水平可以被认为是适当的。尽管该模型查明215家公司由于债务水平不足而陷入财政困境,但在3 783家从事制造业和建筑业的斯洛伐克企业中,有3 568家没有任何债务融资问题。在所建立的模型中,自筹资金比率被确定为精度最高的变量。结果表明,破产预测模型在实际应用中需要较强的判别能力,所建立的模型总体判别能力为93%。原创性/价值/实际意义。本文的主要贡献在于它对最新可用数据的应用,这有助于在当前困难时期对企业进行更准确的金融稳定性预测。此外,这是在斯洛伐克进行的一项开创性研究,对大流行后时期企业的财务健康状况进行了模拟。
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