Estimating credit rating models by a logistic regression approach

Kód výsledku v 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>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Estimating credit rating models by a logistic regression approach

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Estimating credit rating models by a logistic regression approach

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ECON '12

ISSN

1803-3865

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

84-93

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—