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Volume 3, Issue 1

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Volume 3, Issue 1

Predicting Corporate Failure


Meena Sharma and Vandna Saini

  1. University Business School, Panjab University, Chandigarh, Punjab
  2. SUS college of Research and Technology, Tangori, Punjab

Corporate failure is a serious problem being confronted by the corporate world. This issue has been a subject of intensive research and discussion by economists, bankers, creditors, equity shareholders, accountants, marketing and management experts. The present study aims at developing a model for prediction of corporate failure on the basis of financial ratios. The study is based on the data of selected firms from chemical industry (with equal number of failed and non failed firms). The discriminant analysis has been used to discriminate between failed and non failed firms. It is concluded that some of the financial ratios can significantly differentiate between failed and non failed firms. The finding will be useful for the banks and other financial institutions in designing a suitable credit appraisal and monitoring system for their loans. This model could guide the policy makers to prepare an early warning system to avoid bankruptcy.


Corporate Failure, Distress Analysis, Financial Ratios, Discriminate Analysis, Credit Analysis and Appraisal

  1. Aggarwal, P. (2003). Corporate Sickliness and Revival in India. An Empirical study, University Business School Punjab University Chandigarh.
  2. Attman, E.I. (1968). ‘Financial Ratio, discriminant analysis and prediction of corporate bankruptcy’, Journal of finance, Vol. 23, No. 4, pp. 589-609.
  3. Beaver, W.H. (1966). ‘Financial Ratios as predictors of failure’, Journal of Accounting Research, Vol. 4, pp. 71-111.
  4. David, K.H., Shin, T. and Kim, C. (2008). ‘Insolvency prediction Model using Multivariate Discriminant Analysis and Artificial Neural Network for The Finance Industry in Nagaland’, International Journal of Business and Management, Vol. 3, No. 1, pp. 19-27.
  5. Deakin, E.B. (1972). ‘A Discriminant Analysis of Predication of Business Failure’, Journal of Accounting Research, Vol. 10, spring, pp. 167- 169.
  6. Gunawardana, K. and Puagwatana, S. (2005). ‘Logistic Regression Model for Business Failure Prediction of Technology Industry in Thailand’, International Journal of the computer and Management, Vol. 13, No. 2, pp. 47-53.
  7. Gupta, L.C. (1979). Financial Ratios as for Warning Indicator of Corporate Sickness, ICICI, Bombay.
  8. Hainz, C. and Fidrmuc, J. (2010). ‘Default Rates in the Loan Market for SMES: Evidence from Slovakia’, Economic System, Vol. 34, Issue 2, pp. 133-147.
  9. Jiming, L. and Weiwei, D. (2011). ‘An Empirical Study on the Corporate Financial Distress Prediction Modes: Evidence from Chinas Manufacturing Industry’, International Journal of Digital Content Technology and Its Application, Vol. 5, No. 6.
  10. Kaveri, V.S. (1980). Financial Ratio as a Predictor of Borrowed Health: With Special Reference to Small Scale Industries in India, Sultan Chand, New Delhi.
  11. Khan, Bhunia and Mukhuti (2011). ‘Prediction of financial distress’, Asian Journal of Business Management, Vol. 3, No. 3, pp. 210-218.
  12. Kjatwani, H. and Arora, M. (2006). ‘Constructing a Loan Default Model for Indian Bank using CIBIL Data’, IIMB Management Review, Vol. 18, No. 2, pp. 127-135.
  13. Libby, R. (1975). ‘Accounting Ratios and the Prediction of Failure: Some Behavioral Evidence’, Journal of Accounting Research, Vol. 13, No. 1, pp. 150-161.
  14. Lin, T.H. (2009). ‘A Cross Model Study of Corporate Financial Distress Prediction in Taiwan’, New Computing, Vol. 72, Issue 16-18, pp. 3507-3576.
  15. Mishra, D.P. (1993). ‘Predicting Corporate Sickness using Cash Flow Analysis’, Vikalpa, Vol. 18, No. 3, pp. 13-19.
  16. Singh, N. and Prasain, G.P. (2010). ‘Sickness Small Scale Industries: Causes and Remedies – A Case Study of Manipur’, Management Coverage, Vol. 1, No. 1, pp. 82-89.