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Predicting Corporate Financial Distress for Widely Held Large - Cap Companies in India : Altman Model vs. Ohlson Model


Affiliations
1 Associate Professor & Area Chair - Finance & Accounting Area, International Management Institute (IMI) - Bhubaneswar, Bhubaneswar - 751 003, Odisha, India

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In the present study, an attempt was made to compare the prediction accuracies of Altman's Z - score model and Ohlson's O - score model, primarily in predicting financial distress for widely held large cap companies in India. Over a period of 2000 to 2013, a sample of 15 financially distressed and a paired control sample of 30 financially non - distressed widely held large cap companies belonging to 15 different industries were taken up for the study. The comparative analysis of the rate of prediction accuracies of both the models unearthed that in predicting the financial distress for the companies, the prediction accuracy of Ohlson model was rather higher. In contrast, in predicting the overall financial health (both financial distress and non-distress) of the companies as well as in predicting the financial soundness (financial non-distress) of the companies, the prediction accuracy of the Altman model was found to be greater. However, the Pearson chi-square test of significance revealed that the prediction accuracy of the Altman model in predicting financial soundness of widely held large cap companies in India was statistically significantly higher than that of the Ohlson model. Furthermore, though both the models showed high levels of prediction accuracy in predicting financial health as well as financial distress of widely held large cap companies in India, their prediction accuracies did not vary significantly.

Keywords

Altman's Z - score model, bankruptcy, corporate failure, debt default, financial distress, leverage, logit analysis, multiple discriminant analysis, Ohlson's O - Score model, ratio analysis, solvency

C52, C53, G20, G32, G33, M40

Paper Submission Date : June 8, 2018 ; Paper sent back for Revision : July 14, 2018 ; Paper Acceptance Date : July 22, 2018

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  • Predicting Corporate Financial Distress for Widely Held Large - Cap Companies in India : Altman Model vs. Ohlson Model

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Authors

Ansuman Chatterjee
Associate Professor & Area Chair - Finance & Accounting Area, International Management Institute (IMI) - Bhubaneswar, Bhubaneswar - 751 003, Odisha, India

Abstract


In the present study, an attempt was made to compare the prediction accuracies of Altman's Z - score model and Ohlson's O - score model, primarily in predicting financial distress for widely held large cap companies in India. Over a period of 2000 to 2013, a sample of 15 financially distressed and a paired control sample of 30 financially non - distressed widely held large cap companies belonging to 15 different industries were taken up for the study. The comparative analysis of the rate of prediction accuracies of both the models unearthed that in predicting the financial distress for the companies, the prediction accuracy of Ohlson model was rather higher. In contrast, in predicting the overall financial health (both financial distress and non-distress) of the companies as well as in predicting the financial soundness (financial non-distress) of the companies, the prediction accuracy of the Altman model was found to be greater. However, the Pearson chi-square test of significance revealed that the prediction accuracy of the Altman model in predicting financial soundness of widely held large cap companies in India was statistically significantly higher than that of the Ohlson model. Furthermore, though both the models showed high levels of prediction accuracy in predicting financial health as well as financial distress of widely held large cap companies in India, their prediction accuracies did not vary significantly.

Keywords


Altman's Z - score model, bankruptcy, corporate failure, debt default, financial distress, leverage, logit analysis, multiple discriminant analysis, Ohlson's O - Score model, ratio analysis, solvency

C52, C53, G20, G32, G33, M40

Paper Submission Date : June 8, 2018 ; Paper sent back for Revision : July 14, 2018 ; Paper Acceptance Date : July 22, 2018




DOI: https://doi.org/10.17010/ijf%2F2018%2Fv12i8%2F130743