Title: Prediction of financial distress in the Indian corporate sector: an improvement over Altman's Z-score model

Authors: Gurmeet Singh; Ravi Singla

Addresses: Chandigarh School of Business, CGC, Jhanjeri, India ' University School of Applied Management, Punjabi University, Patiala, India

Abstract: Financial distress is the situation when a firm faces difficulty regarding the payment of its financial obligations on due time which may result into business failure. Prediction of financial distress at an early stage can be used as a warning signal to take corrective actions and to avoid the future bankruptcy. Altman's Z-score model is widely used in practice to measure financial distress. This study has re-estimated the coefficients of Altman's model using recent data and has also developed a new model using logistic regression to predict financial distress. The accuracy of the two models is compared using testing sample and receiver operating characteristic (ROC). The results reveal that the newly developed model has achieved higher predictive accuracy than re-estimated Altman's model and hence can be more suitable to predict financial distress and to avoid future bankruptcy.

Keywords: Altman's model; business failure; financial distress prediction; financial ratios; logistic regression; receiver operating characteristic; ROC curve.

DOI: 10.1504/IJBCRM.2023.130287

International Journal of Business Continuity and Risk Management, 2023 Vol.13 No.1, pp.1 - 18

Received: 24 Sep 2021
Accepted: 07 Feb 2022
Published online: 17 Apr 2023 *