Subject(s) - financial distress , linear discriminant analysis , predictive power , context (archaeology) , discriminant function analysis , discriminant , distress , financial ratio , business failure , multiple discriminant analysis , artificial intelligence , computer science , statistics , machine learning , business , mathematics , psychology , finance , geography , financial system , philosophy , archaeology , epistemology , psychotherapist
The present study is crucial importance to build up a model to develop the predictive abilities for company failures in a later time frame with different financial, business and operating conditions in the Indian context. A total of sixty-four private sector pharmaceutical companies were analyzed with sixteen financial ratios using multiple discriminant analysis. A strong discriminant function was constructed with seven ratios found to be significant in discriminating power and the classification results showed high predictive accuracy rates of between 88% and 94% for each of the five years prior to actual failure. This study also indicated that even with more advanced statistical tools more popularly used recently, MDA is still a very reliable and potent statistical tool.