Application and Comparison of Altman and Ohlson Models to Predict  Bankruptcy of Companies

Karamzadeh, Mani Shehni

doi:10.19026/rjaset.5.4743

Cited by 23 publications

(23 citation statements)

References 12 publications

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“…Whenever financial ratios are utilized to analyze a company, it is important to note that no economic analysis technique is perfect (Gerantonis et al, 2009, Summers and Sweeney, 1998, Karamzadeh, 2013. For instance, the Z-Score is merely reliant on the underlying financial data reported by the company.…”

Section: Resultsmentioning

confidence: 99%

Predicting Corporate Failures Using Multi Discriminant Analysis and Current Ratio: An Empirical Application to Philippines Stock Exchange

Name¹,

Name²

2019

IJSR

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Corporate failure models can be broadly classified into two groups: quantitative models, which are mainly based on published financial information and qualitative models, which are based on an internal assessment of the company concerned. Both types attempt to determine characteristics, whether financial or non-financial, which can then be used to distinguish between surviving and failing companies. This study sought to predict companies that are potential to corporate financial distress utilizing the Altman Z-Score model and current ratio. Forty-five companies currently listed on the Philippine Stock Exchange were randomly selected, and their corresponding audited financial statements published online were downloaded and assessed using the financial ratios. Findings of the study revealed, 35 companies have been chosen potential for becoming financially distressed when subjected to the Altman Zscore model. On the other hand, 12 companies were also found experiencing financial difficulties based on current ratio analysis. Accordingly, these companies have classified either failure or non-failure based on Altman and current ratio. The study concluded both the Altman Z-Score Model and current ratio are financial analytical tools investors and financial analysts can use in assessing the financial health of the company before investing or buying the stock. For businesses having low or declining Z-index, requires an indepth analysis of the accounts in the financial statements to verify the cause of the problem or potential risk.

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Section: Resultsmentioning

confidence: 99%

Predicting Corporate Failures Using Multi Discriminant Analysis and Current Ratio: An Empirical Application to Philippines Stock Exchange

Name¹,

Name²

2019

IJSR

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“…To categorize the models it was evaluated that all the companies become successful in estimation. Karamzadeh (2013) Vol.11, No.19, 2019 7 companies listed at BEI and concluded that Grover model gives highest accuracy in predicting bankruptcy followed by Springate, Zmijewski and Altman models. Grice and Dugan (2003) examined Ohlson and Zmijewski models.…”

Section: Empirical Studies5mentioning

confidence: 99%

An Analysis of Assessment of Financial Distress in Textile Sector of Pakistan (2012-2018)

Khan¹

2019

EJBM

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As business expand in modern global economy, cutthroat competition also becomes a reality. It becomes more important for businesses not only to diversify but also to break through with their respective products on different markets through cost cutting techniques and technologies. For survival and carrying on business activities, an organization should have to manage their finances on priority matters that need utmost care and attention.

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“…Assessing the probability of failure by using 171 Journal of Technology Management for Growing Economies, Volume 8, Number 2, October 2017 Karamzadeh (2013) compared the predictive accuracy of Altman's model and Ohlson's model and it was observed that Altman model is a better predictor of bankruptcy and outperformed the Ohlson's model because correct classification rate of Altman model was found to be higher than Ohlson's model. Alareeni and Branson (2013) tested the Altman's Z-score model for manufacturing and non-manufacturing companies.…”

Section: Reveiw Of Literaturementioning

confidence: 99%

“…After the development of the Altman's model many authors or researchers developed their own models by using different variables and methodology. Many studies like Agarwal and Taffler (2005), Sarbapriya (2011), Rayalaseema and Muhammad (2012), Anjum (2012), Karamzadeh (2013), Altman et al (2014), Celli (2015) etc. tested the predictive accuracy of the Altman's model by applying it to the recent time period and it was found that Altman's model is still a powerful tool to predict the bankruptcy.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Probability of Failure by Using Altman’s Model and Exploring its Relationship with Company Size: An Evidence from Indian

Singla

Singh

2017

JTMGE

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Corporate failure is the situation when a firm becomes unable to pay debts when they come due and the market value of assets becomes lower than its total liabilities. The purpose of the paper is to explore the relationship between firm size and probability of failure for Indian steel sector companies by employing regression model. Altman's Z-score model has been used to derive the firm's probability of failure, whereas total assets and total sales are utilized as indicators for firm's size. The results indicate that size is inversely related to the probability of failure. With an increase in the size of the firm; probability of failure decreases and vice-versa. JEL Classification codes:

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Application and Comparison of Altman and Ohlson Models to Predict Bankruptcy of Companies

Cited by 23 publications

References 12 publications

Predicting Corporate Failures Using Multi Discriminant Analysis and Current Ratio: An Empirical Application to Philippines Stock Exchange

Predicting Corporate Failures Using Multi Discriminant Analysis and Current Ratio: An Empirical Application to Philippines Stock Exchange

An Analysis of Assessment of Financial Distress in Textile Sector of Pakistan (2012-2018)

Assessing the Probability of Failure by Using Altman’s Model and Exploring its Relationship with Company Size: An Evidence from Indian

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