Business Distress Prediction Using Bayesian Logistic Model for Indian Firms

Arvind Shrivastava, Kuldeep Kumar and Nitin Kumar
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Arvind Shrivastava: Reserve Bank of India, Mumbai 400051, India
Kuldeep Kumar: Bond Business School, Bond University, Gold Coast 4229, Australia
Nitin Kumar: Reserve Bank of India, Mumbai 400051, India

Risks, 2018, vol. 6, issue 4, 1-15

Abstract: 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.

Keywords: financial distress; firms; Bayesian analysis; logistic model (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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