Default Risk Prediction in Firms via Statistical Techniques – A review
DOI:
https://doi.org/10.48165/gmj.2023.conf6Keywords:
default risk prediction, discriminant analysis, logistic regressionAbstract
The current study presents the literature review of default risk prediction studies for the period 1930-2022. The rising corporate default is a reason of concern for banks and companies. It has particularly attracted the attention of researchers since the global crisis of 2008-09. The review is based on statistical techniques including discriminant analysis, multiple discriminant analysis, logistic regression, conditional logistic regression and probit regression. The review targets the following aspects of the studies: country origin, period of study, financial indicators used and accuracy of results. Analysis of review depicts that logistic regression (LR) is the most applied technique among statistical techniques to predict corporate failure. However, focus has now been shifting to intelligent techniques in 21st centuary.
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