Using Altman Z”-Score to Predict Financial Distress : Evidence from Lebanese Alpha Banks

Elia, Jean; Toros, Elena; Sawaya, Chadia; Balouza, Mohamed

doi:10.12816/0059150

Cited by 10 publications

(7 citation statements)

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“…The given research finding is consistent with the results concluded by Ullah et al ( 2021) who performed the study in banks at Pakistan and observed private banks were in a safe zone. On the other hand, the findings of the study is debatable to the study of Elia et al (2021) who attested the validity of Altman Z" score model on the Lebanese Alpha banks. Charitou et al (2004) urge the Altman's Z-score model as the tool to detect bankruptcy and equally employed by practitioners as well as the academics.…”

Section: Data Analysis and Resultsmentioning

confidence: 62%

“…Aziz and Dar (2006) suggest the early sign of financial failures help the firm undertaking timely initiation to check financial insolvency and protecting from potential bankruptcy. Further, Elia et al (2021) suggest the Z" score model as crucial indicator for auditors, financial managers, investors or lenders who use the banks' financial statements to make the right judgments in case of financial turmoil.…”

Section: Data Analysis and Resultsmentioning

confidence: 99%

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Exploring financial distress through Altman Z” score: example of selected private commercial banks in Nepal

Gyawali

2023

J. Emerging Mgt Stud.

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Purpose - This research aims to explore the financial distress of selected Nepalese commercial banks using Altman’s Z” score model. Design/methodology/approach - Based on quantitative research approach, this research has followed descriptive research design to assess financial distress. Amid of 24 private commercial banks, this study has selected 16 sample banks conveniently. Altman’s revised Z” score (1993) model has been used to draw inferences. The published annual financial report of respective banks of year 2019-20 was employed as secondary information. Findings and Conclusion - Among 16 sampled banks, 6 commercial banks are laid under zone of distress and 10 banks as in undecided zone. Similarly, this study has revealed the inefficiency of Z” score model in predicting financial distress. Originality/value - Commencing Altman’s Z” score model designed for non-manufacturing and companies of emerging market in relation to Nepalese commercial banks.

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Section: Data Analysis and Resultsmentioning

confidence: 62%

Section: Data Analysis and Resultsmentioning

confidence: 99%

Exploring financial distress through Altman Z” score: example of selected private commercial banks in Nepal

Gyawali

2023

J. Emerging Mgt Stud.

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“…e-ISSN: 2757 -5489 Elia et al (2021) was conducted to predict the financial distress of 10 Lebanese banks in the period of 2009-2018. In the study, Altman calculated Z Scores for non-manufacturing companies and emerging markets using equations.…”

Section: Literature Reviewmentioning

confidence: 99%

Determining Financial Distress With the Help of the Altman Z-Score Model

Say

2024

Toplum Ekonomi Ve Yönetim Dergisi

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Financial distress is a condition in which a company faces financial difficulties where its cash flows cannot meet its current obligations, such as trade payables or interest costs. Financial distress is the stages of deterioration in the financial condition of a company before bankruptcy or liquidation occurs. In this case, management cannot monitor the financial condition of the company, which causes increased business risk. Financial distress usually emerges with increasing liquidity pressures and then continues in the form of diminishing assets, the inability of the company to meet its financial obligations and dragging the company into bankruptcy. Considering the previous studies in the literature; many factors such as the size of the data used in the detection of financial distress, the type of sector from which it is obtained, the economic structure of the country affect the degree of success of the models. From this point of view, the main purpose of the study is to determine the financial failure degrees of the companies under the chemical, pharmaceutical, petroleum, rubber and plastic products sector classification, whose shares are traded in Borsa Istanbul. In this context, the Z Score Model developed by Altman was used. According to the results obtained from the study, most of the enterprises are either in the risky zone or in the gray zone for the studied 3-year period.

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“…They claim their results to have an accuracy ratio of 92% as compared to 60% ratio of Altman Z-score model. Elia et al (2021) attempt to prove the validity of Z-score model by predicting financial distress of banks in Lebanon. According to the results, most of the banks included in the study fall in the financial distress zone.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting Financial Failure using Altman’s Z-Score Model:Evidence from CommercialBanks in Pakistan

Khawaja

2023

ASSAP

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This paper aims to explore the predictability of financial failure in commercialbanks in Pakistan using Altman Z-score Model. Predicting the early financial failure indicates the concerned parties to intervene and take appropriate corrective actions before the bank finally fails. To achieve these objectives, the Altman Z-score model and current ratio tests are applied to the commercialbanks in Pakistan based on their financial statements and the analysis of the financial ratios during the period from 2016 to 2021. Theresults of the study show that Altman’s Z-Score model and current ratio appropriately predict the financial distress of commercialbanks in Pakistan, especially during the last two years. The results show that there isrisk of financial failure inalmost half of the commercialbanks of Pakistan.

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Using Altman Z”-Score to Predict Financial Distress : Evidence from Lebanese Alpha Banks

Cited by 10 publications

References 0 publications

Exploring financial distress through Altman Z” score: example of selected private commercial banks in Nepal

Exploring financial distress through Altman Z” score: example of selected private commercial banks in Nepal

Determining Financial Distress With the Help of the Altman Z-Score Model

Predicting Financial Failure using Altman’s Z-Score Model:Evidence from CommercialBanks in Pakistan

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