Estimating credit rating models by a logistic regression approach

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F12%3A86079917" target="_blank" >RIV/61989100:27510/12:86079917 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Estimating credit rating models by a logistic regression approach
Original language description
Managing credit risk is an important part of risk management and this area has attracted a huge attention in last decades, especially in the context of recent financial crisis. An increasing need to actively and effectively manage credit risk across manysectors of the economy has resulted in more sophisticated and readily available tools and techniques. The main principle of these models is to give basic information about the company?s operating characteristics; to identify alert factors and assign a rating classification. Quantitative models provide rating based on publically available financial information only. The paper is aimed at the estimation of credit rating models using a large sample of European companies. By means of a multinomial logisticregression approach, two models are estimated in this paper, both of them with high classification ability. Results of the analysis confirm the importance of profitability, capitalization and interest coverage for credit rating assignmen
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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