Business Distress Prediction Using Bayesian Logistic Model for Indian Firms

Arvind Shrivastava, Kuldeep Kumar, Nitin Kumar

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)
186 Downloads (Pure)


The objective of the study is to perform corporate distress prediction for an emerging economy, such as India, where bankruptcy details of firms are not available. Exhaustive panel dataset extracted from Capital IQ has been employed for the purpose. Foremost, the study contributes by devising novel framework to capture incipient signs of distress for Indian firms by employing a combination of firm specific parameters. The strategy not only enables enlarging the sample of distressed firms but also enables to obtain robust results. The analysis applies both standard Logistic and Bayesian modeling to predict distressed firms in Indian corporate sector. Thereby, a comparison of predictive ability of the two approaches has been carried out. Both in-sample and out of sample evaluation reveal a consistently better predictive capability employing Bayesian methodology. The study provides useful structure to indicate the early signals of failure in Indian corporate sector that is otherwise limited in literature.

Original languageEnglish
Article number113
Number of pages15
Issue number4
Publication statusPublished - 9 Oct 2018


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