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VOL. 7, ISSUE 2 (2025)
Revising altman’s z-score cut-off point to enhance prediction accuracy: Evidence from India’s iron and steel industry
Authors
Pradip Bhabak
Abstract
The present study evaluates the effectiveness
of Altman’s Z-score model (1968), one of the most widely used distress
prediction tools globally, within the context of the Indian iron and steel
industry. The research also aims to refine the model’s cut-off point to
determine a more optimal Z-score specifically suited to India’s market. The
analysis focuses on 42 listed iron and steel companies—21 that failed and 21
that did not. The findings reveal that the original 1968 Z-score model offered
an accuracy rate of only 50% to 60% for different years prior to failure. In
contrast, the newly determined optimal Z-score demonstrated a remarkable
improvement in predictive accuracy, ranging from 79% to 90% for various years
before failure, highlighting its enhanced effectiveness in the Indian context.
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Pages:43-46
How to cite this article:
Pradip Bhabak "Revising altman’s z-score cut-off point to enhance prediction accuracy: Evidence from India’s iron and steel industry". International Journal of Finance and Commerce, Vol 7, Issue 2, 2025, Pages 43-46
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