Predicting default by indian firms using statistical methods

This study assesses the classification accuracies of two statistical methods namely, multiple discriminant analysis and logistic regression approach in default prediction. It uses a small sample of 32 India firms listed on Bombay Stock Exchange for the sample period of six years over 2010-11 to 2015-16. Two models have been built using the two statistical methods. Results of the study clearly indicate that there are no significant differences in the classification accuracies because of change in statistical methods. Different statistical measures clearly suggest that the two developed models have comparative classification accuracies in default prediction. However, the specification and robustness of logit model is found to be on lower side than that of the discriminant model contrary to large numbers of studies. The weaker model specification of logistic model may be result of small sample size.