Financial distress prediction in private firms: developing a model for troubled debt restructuring

IF 3.9 Q1 BUSINESS, FINANCE Journal of Applied Accounting Research Pub Date : 2023-11-20 DOI:10.1108/jaar-12-2022-0325
Asad Mehmood, Francesco De Luca
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Abstract

Purpose

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

Design/methodology/approach

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

Findings

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

Research limitations/implications

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

Practical implications

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

Originality/value

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

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私营企业财务困境预测:发展问题债务重组模型
本研究旨在建立一个基于财务变量的模型,以提高法国、西班牙和意大利私营企业财务困境预测的准确性。因此,财务困难的企业可以及时申请问题债务重组(TDR)以继续经营。设计/方法/方法本研究使用了312家陷入困境和312家非陷入困境的公司的样本。它包括60家法国公司、21家西班牙公司和231家意大利公司,包括陷入困境和非困境的公司。数据是从ORBIS数据库中提取的。首先,作者通过替换原来的Z”-Score模型中专门用于财务困境预测的比率,建立了一个新的模型,并基于线性判别分析(LDA)估计其系数。其次,利用改进的Z -Score模型,基于logistic回归模型,构建了陷入困境和非陷入困境企业的企业TDR概率指标。新模型(修正Z " -Score)在财务困境预测中具有更高的预测精度。此外,企业TDR概率指数准确地描述了两组陷入困境和非陷入困境的企业的概率趋势。研究局限/启示本研究的发现是结论性的。然而,样本量很小。因此,进一步的研究可以将本研究建立的预测模型的应用范围扩大到所有欧盟国家。本研究具有重要的现实意义。本研究响应欧盟指令呼吁,开发财务困境预测模型,允许债务人及时进行债务重组,从而继续其业务。因此,本研究可能对从业人员和企业利益相关者(如银行和其他债权人以及投资者)有用。独创性/价值本研究在几个方面对文献做出了重大贡献。首先,本研究基于公司破产和财务困境是不同事件的论点,开发了一个预测财务困境的模型。然而,最初的Z " -Score模型是用于故障预测的。此外,最近的文献建议修改和扩展预测模型。其次,采用三个国家的公司样本对新模型进行测试,这三个国家在TDR法律上有相似之处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
13.30%
发文量
44
期刊介绍: The Journal of Applied Accounting Research provides a forum for the publication of high quality manuscripts concerning issues relevant to the practice of accounting in a wide variety of contexts. The journal seeks to promote a research agenda that allows academics and practitioners to work together to provide sustainable outcomes in a practice setting. The journal is keen to encourage academic research articles which develop a forum for the discussion of real, practical problems and provide the expertise to allow solutions to these problems to be formed, while also contributing to our theoretical understanding of such issues.
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