A Review of Financial Distress Prediction Models: Logistic Regression and Multivariate Discriminant Analysis

Authors

  • Ehsan ul Hassan School of Economics, Finance and Banking, Universiti Utara Malaysia
  • Zaemah Zainuddin School of Economics, Finance and Banking, Universiti Utara Malaysia
  • Sabariah Nordin School of Economics, Finance and Banking, Universiti Utara Malaysia

DOI:

https://doi.org/10.52962/ipjaf.2017.1.3.15

Keywords:

Financial Distress Prediction, Logistic Regression, Multivariate Discriminant Analysis, Bankruptcy

Abstract

In corporate finance, the early prediction of financial distress is considered more important as another occurrence of business risks. The study presents a review of literature for early prediction of financial bankruptcy. It contributes to the formation of a systematic review of the literature regarding previous studies done in the field of bankruptcy. It addresses two most commonly used financial distress prediction models, i.e. multivariate discriminant analysis and logit. Models are discussed with their advantages and disadvantages. After methodological review, it seems that logit regression model (LRM) is more advantageous than multivariate discriminant analysis (MDA) for better prediction of financial bankruptcy. However, accurate prediction of bankruptcy is beneficial to improve the regulation of companies, to form policies for companies and to take any precautionary measures if any crisis is about to come in future.

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Published

2017-07-01

How to Cite

Hassan, E. ul, Zainuddin, Z., & Nordin, S. (2017). A Review of Financial Distress Prediction Models: Logistic Regression and Multivariate Discriminant Analysis. Indian-Pacific Journal of Accounting and Finance, 1(3), 13–23. https://doi.org/10.52962/ipjaf.2017.1.3.15

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Section

Main Section