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Journal cover: Journal of Risk Finance, The

Journal of Risk Finance, The

ISSN: 1526-5943
Incorporates: Balance Sheet

Online from: 1999

Subject Area: Accounting and Finance

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Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches


Document Information:
Title:Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches
Author(s):Arindam Bandyopadhyay, (National Institute of Bank Management (NIBM), Kondhwe Khurd, Pune, India)
Citation:Arindam Bandyopadhyay, (2006) "Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches", Journal of Risk Finance, The, Vol. 7 Iss: 3, pp.255 - 272
Keywords:Bonds, Emerging markets, India, Modelling
Article type:Research paper
DOI:10.1108/15265940610664942 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – This paper aims at developing an early warning signal model for predicting corporate default in emerging market economy like India. At the same time, it also aims to present methods for directly estimating corporate probability of default (PD) using financial as well as non-financial variables.

Design/methodology/approach – Multiple Discriminate Analysis (MAD) is used for developing Z-score models for predicting corporate bond default in India. Logistic regression model is employed to directly estimate the probability of default.

Findings – The new Z-score model developed in this paper depicted not only a high classification power on the estimated sample, but also exhibited a high predictive power in terms of its ability to detect bad firms in the holdout sample. The model clearly outperforms the other two contesting models comprising of Altman's original and emerging market set of ratios respectively in the Indian context. In the logit analysis, the empirical results reveal that inclusion of financial and non-financial parameters would be useful in more accurately describing default risk.

Originality/value – Using the new Z-score model of this paper, banks, as well as investors in emerging market like India can get early warning signals about the firm's solvency status and might reassess the magnitude of the default premium they require on low-grade securities. The default probability estimate (PD) from the logistic analysis would help banks for estimation of credit risk capital (CRC) and setting corporate pricing on a risk adjusted return basis.



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