An Empirical Analysis of Default Risk for Listed Companies in India: A Comparison of Two Prediction Models

Vandana Gupta

doi:10.5539/ijbm.v9n9p223

Abstract

The objective of this study is to examine the performance of two default prediction models: the Z-score modelusing discriminant analysis, and the logit model on a dataset of 60 defaulted and 60 solvent companies. Financialratios obtained from corporate balance sheets are used as independent variables while solvent/defaulted company(ratings assigned) is the dependent variable. Furthermore, for logistic regressions, an attempt is made to combinemacro variables and dummy industry variables along with accounting ratios. The predictive ability of theproposed Z score model is higher when compared to both the Altman original Z-score model and the Altmanmodel for emerging markets. The research findings establish the superiority of logit model over discriminantanalysis and demonstrate the significance of accounting ratios in predicting default.

Highlights

Every business entity undertakes a variety of operational activities to carry on business
The model with predictors shows a significant increase to 99% from 50% in our base model with only the constant and no predictor variables
As a step, accounting ratios are included along with industry dummy variables and macro-economic variables, the research findings show In Table 13, we report results from logit regressions with the inclusion of macro-economic variables

Summary

Introduction

Every business entity undertakes a variety of operational activities to carry on business. The outcome of at least some of such activities may be unpredictable. This introduces an element of risk for every organization. Among the different risks that an organization is faced with, credit risk is perhaps one of the oldest financial risks, though there have not been many instruments to manage and hedge this type of risk till recently. The focus had been primarily on market risk and bulk of the academic research was focused on this risk. There has been an upsurge in research on credit risk with increasing emphasis being given to its modeling and evaluation

Objectives

Results

Conclusion