Predicting corporate bankruptcy: What matters?
Leon Li and
Robert Faff
International Review of Economics & Finance, 2019, vol. 62, issue C, 1-19
Abstract:
or market-based information should be employed to predict corporate default is a long-standing debate in finance research. Incorporating a regime-switching mechanism, we establish a hybrid bankruptcy prediction model with non-uniform loadings in both accounting- and market-based approaches to reexamine the issue. We find the following. Creditors should increase the loading on market-based information when large and liquid corporations are considered. Conversely, for companies with incremental information involved in accounting reporting proxied by discretionary accruals, banks could emphasize accounting ratio-based variables more than they are already emphasized. Since managerial discretion in accounting numbers could serve as a tool to bring undisclosed information about the firm to the public, the weight on accounting-based information could be increased for firms with high information asymmetry. In addition, the loading on market-based (accounting-based) information should be increased (decreased) during periods of financial crisis, defined by negative gross domestic product growth.
Keywords: Regime-switching system; Z-score; Distance to default; Bankruptcy (search for similar items in EconPapers)
JEL-codes: C51 G33 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (15)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S105905601830203X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:62:y:2019:i:c:p:1-19
DOI: 10.1016/j.iref.2019.02.016
Access Statistics for this article
International Review of Economics & Finance is currently edited by H. Beladi and C. Chen
More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).