Predicting Financial Distress with the CCB Bankruptcy Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F21%3A50018292" target="_blank" >RIV/62690094:18450/21:50018292 - isvavai.cz</a>
Result on the web
<a href="https://www.abacademies.org/articles/predicting-financial-distress-with-the-ccb-bankruptcy-model-11378.html" target="_blank" >https://www.abacademies.org/articles/predicting-financial-distress-with-the-ccb-bankruptcy-model-11378.html</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Predicting Financial Distress with the CCB Bankruptcy Model
Original language description
The aim of this research was to present a new methodology for the assessment of financial health of a company, called the Come Clean Bankruptcy (CCB) model. The ultimate objective of the model is to detect the signs of impending bankruptcy based on a set of selected financial indicators reflecting the capital structure, liquidity and overall growth of the company. The CCB model was applied on a data sample comprising 199 entities operating in the textile/clothing industry in the Czech Republic. The outputs were compared with the actual development of those companies in 2013-2020 in order to assess whether the model can be effectively employed in practice.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50205 - Accounting
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Academy of Accounting and Financial Studies Journal
ISSN
1096-3685
e-ISSN
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Volume of the periodical
25
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
1-12
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85112645137