Predicting financial distress: revisiting the option-based model

Autor: Yogesh Maheshwari, Khushbu Agrawal
Rok vydání: 2016
Předmět:
Zdroj: South Asian Journal of Global Business Research. 5:268-284
ISSN: 2045-4457
DOI: 10.1108/sajgbr-04-2015-0030
Popis: Purpose – The purpose of this paper is to assess the significance of the Merton distance-to-default (DD) in predicting defaults for a sample of listed Indian firms. Design/methodology/approach – The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It employs two alternative statistical techniques, namely, logistic regression and multiple discriminant analysis. Findings – The option-based DD is found to be statistically significant in predicting defaults and has a significantly negative relationship with the probability of default. The DD retains its significance even after the addition of Altman’s Z-score. This further establishes its robustness as a significant predictor of default. Originality/value – The study re-establishes the utility of the Merton model in India using a simplified version of the Merton model that can be easily operationalized by practitioners, reasonably larger sample size and is done in a more recent period covering the post global financial crisis period. The findings could be valuable to banks, financial institutions, investors and managers.
Databáze: OpenAIRE