Financial Mechanisms of Corporate Bankruptcy: Are They Different or Similar Across Crises?

Katsuyuki Tanaka, Takuo Higashide, Takuji Kinkyo and Shigeyuki Hamori ()
Additional contact information
Katsuyuki Tanaka: Data Science and AI Innovation Research Promotion Center Shiga University, 1-1, Baba, Hikone 522-8522, Shiga, Japan
Takuo Higashide: au Asset Management Corporation, 3-2-1, Nishikanga, Chiyoda 101-0065, Tokyo, Japan
Takuji Kinkyo: Graduate School of Economics, Kobe University, 2-1 Rokkodai, Nada-Ku 657-8501, Kobe, Japan
Shigeyuki Hamori: Graduate School of Economics, Kobe University, 2-1 Rokkodai, Nada-Ku 657-8501, Kobe, Japan

Risks, 2025, vol. 13, issue 8, 1-27

Abstract: One primary objective of the early warning system literature is to construct more accurate financial vulnerability prediction models and investigate the mechanisms and key factors that differentiate healthy from vulnerable financial states. Despite the importance of identifying and predicting financial vulnerabilities, existing research does not fully explain whether—and how—the financial behavior associated with corporate bankruptcy differs across crises. This study investigates (1) whether the financial mechanisms of corporate bankruptcy differ across three crises—the Global Financial Crisis, the European debt crisis, and the COVID-19 crisis; (2) whether these crises differ from tranquil periods before the Global Financial Crisis and after the European debt crisis; and (3) how these differences manifest. To conduct this analysis, we introduce a unique framework based on a random forest model, utilizing a corporate bankruptcy dataset spanning 2002–2023. The results show that the bankruptcy mechanisms during the Global Financial Crisis and the European debt crisis are not significantly different, whereas the COVID-19 crisis exhibits distinct characteristics. Additionally, we find that “Credit period days,” “Collection period days,” “Gross margin,” and “Solvency ratio (asset-based)” are key financial factors distinguishing these events.

Keywords: economic crises; data science; machine learning; company bankruptcy (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/13/8/158/pdf (application/pdf)
https://www.mdpi.com/2227-9091/13/8/158/ (text/html)

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:gam:jrisks:v:13:y:2025:i:8:p:158-:d:1728687

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().