Variable selection and corporate bankruptcy forecasts

Shaonan Tian, Yan Yu and Hui Guo

Journal of Banking & Finance, 2015, vol. 52, issue C, 89-100

Abstract: We investigate the relative importance of various bankruptcy predictors commonly used in the existing literature by applying a variable selection technique, the least absolute shrinkage and selection operator (LASSO), to a comprehensive bankruptcy database. Over the 1980–2009 period, LASSO admits the majority of Campbell et al. (2008) predictive variables into the bankruptcy forecast model. Interestingly, by contrast with recent studies, some financial ratios constructed from only accounting data also contain significant incremental information about future default risk, and their importance relative to that of market-based variables in bankruptcy forecasts increases with prediction horizons. Moreover, LASSO-selected variables have superior out-of-sample predictive power and outperform (1) those advocated by Campbell et al. (2008) and (2) the distance to default from Merton’s (1974) structural model.

Keywords: Discrete hazard model; Financial ratios; LASSO; Market information (search for similar items in EconPapers)
JEL-codes: C25 G17 G33 M41 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (78)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:52:y:2015:i:c:p:89-100

DOI: 10.1016/j.jbankfin.2014.12.003

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