Estimation and comparison of corporate financial distress models on performance of major crude oil companies listed in S & P BSE oil and gas index

Abstract

Crude oil price has held the attraction of academicians as well as practitioners over the last few decades as it is the life line of the world economy. In this article we examine the outer performance of six major distinct companies listed in S&P BSE Oil and Gas Index with the help of Altman Z score and Springate S score and examine the precisions of the above two models. The model consists of different financial ratios to ascertain the likelihood of corporate financial distress. Two different binary logistic regressions were constructed with the help of selected financial ratios for determining the performance of the company into two categories “non-distress and distress” based on the above two models for each year. The classification result showed a high predictive accuracy of 100.00% correct classification rate for original grouped data as well as for Altman and Springate model. The study also showed that, binomial logistic regression can be used by Investment Companies, Financial Manager, Investors and Researchers for investment as well as policy implications.