recenzní posudek článku NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“

KALOUDA, František. recenzní posudek článku NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“ (review report of the article NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“). 12/1. Ostrava: VŠB-Technická univerzita Ostrava, 2011, 2 pp. ECON 12/1. ISSN 1803-3865.

Basic information

Original name

recenzní posudek článku NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“

Name in Czech

recenzní posudek článku NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“

Name (in English)

review report of the article NOVOTNÁ, M.: „Estimating credit rating models by a logistic regression approach“

Authors

KALOUDA, František (203 Czech Republic, guarantor, belonging to the institution)

Edition

12/1. Ostrava, 2 pp. ECON 12/1, 2011

Publisher

VŠB-Technická univerzita Ostrava

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Other information

Language

Czech

Type of outcome

Účelové publikace

Field of Study

50200 5.2 Economics and Business

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

RIV identification code

RIV/00216224:14560/11:00054281

Organization unit

Faculty of Economics and Administration

ISSN

Keywords (in Czech)

rating důvěryhodnosti bankrot finanční indikáto modelování ratingová agantura

Keywords in English

credit rating default financial indicator modelling rating agency

Tags

International impact, Reviewed

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Abstract

V originále

Managing credit risk is an important part of risk management and this area has attracted a huge attention, especially in the context of recent financial crisis. An increasing need to actively and effectively manage credit risk across many sectors of the economy has resulted in more sophisticated tools and techniques - models. The main principle of these models is to give basic information about the company’s operating characteristics. 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. Results of the analysis confirm the importance of profitability, capitalization and interest coverage for credit rating assignment.

In English

Managing credit risk is an important part of risk management and this area has attracted a huge attention, especially in the context of recent financial crisis. An increasing need to actively and effectively manage credit risk across many sectors of the economy has resulted in more sophisticated tools and techniques - models. The main principle of these models is to give basic information about the company’s operating characteristics. 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. Results of the analysis confirm the importance of profitability, capitalization and interest coverage for credit rating assignment.