Articlediamond2016

Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies

42 citations0/0 files storedFinancial Innovation

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

Abstract

The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy.

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References

1973The Pricing of Options and Corporate Liabilities 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1974ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES*1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 1999Modeling Term Structures of Defaultable Bonds 1976VALUING CORPORATE SECURITIES: SOME EFFECTS OF BOND INDENTURE PROVISIONS

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2019Predicting bankruptcy in construction business: Traditional model validation and formulation of a new model 2025Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework 2021Bankruptcy prediction for private firms in developing economies: a scoping review and guidance for future research

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