About: Comparison of Credit Scoring Models on Probability of Default Estimation for US Banks

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Description	This paper is devoted to the estimation of the probability of default (PD) as a crucial parameter in risk management, requests for loans, rating estimation, pricing of credit derivatives and many others key financial fields. Particularly, in this paper we will estimate the PD of US banks by means of the statistical models, generally known as credit scoring models. First, in theoretical part, we will briefly introduce the two main categories of credit scoring models, which will be afterwards used in application part – linear discriminant analysis and regression models (logit and probit), including testing the statistical significance of estimated parameters. In the main part of the paper we will work with the sample of almost three hundred U.S. commercial banks which will be separate into two groups (non-default and default) on the basis of historical information. Subsequently, we will stepwise apply the mentioned above scoring models on this sample to derive several models for estimation of PD. Further we will apply these models to the control sample to determine the most appropriate model. This paper is devoted to the estimation of the probability of default (PD) as a crucial parameter in risk management, requests for loans, rating estimation, pricing of credit derivatives and many others key financial fields. Particularly, in this paper we will estimate the PD of US banks by means of the statistical models, generally known as credit scoring models. First, in theoretical part, we will briefly introduce the two main categories of credit scoring models, which will be afterwards used in application part – linear discriminant analysis and regression models (logit and probit), including testing the statistical significance of estimated parameters. In the main part of the paper we will work with the sample of almost three hundred U.S. commercial banks which will be separate into two groups (non-default and default) on the basis of historical information. Subsequently, we will stepwise apply the mentioned above scoring models on this sample to derive several models for estimation of PD. Further we will apply these models to the control sample to determine the most appropriate model. (en)
Title	Comparison of Credit Scoring Models on Probability of Default Estimation for US Banks Comparison of Credit Scoring Models on Probability of Default Estimation for US Banks (en)
skos:prefLabel	Comparison of Credit Scoring Models on Probability of Default Estimation for US Banks Comparison of Credit Scoring Models on Probability of Default Estimation for US Banks (en)
skos:notation	RIV/61989100:27510/13:86082949!RIV14-MSM-27510___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(EE2.3.20.0296), S
http://linked.open...iv/cisloPeriodika	2
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Gurný, Petr Gurný, Martin
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Ekonomická fakulta
http://linked.open...dnocenehoVysledku	66168
http://linked.open...ai/riv/idVysledku	RIV/61989100:27510/13:86082949
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Probit Regression.; Logistic Regression; Linear Discriminant Analysis; Credit Scoring Models; Probability of Default (PD) (en)
http://linked.open.../riv/klicoveSlovo	Logistic Regression Credit Scoring Models Linear Discriminant Analysis Probability of Default (PD) Probit Regression.
http://linked.open...odStatuVydavatele	CZ - Česká republika
http://linked.open...ontrolniKodProRIV	[7E0E0AEFAA17]
http://linked.open...i/riv/nazevZdroje	Prague Economic Papers
http://linked.open...in/vavai/riv/obor	AH
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Research team for modelling of economic and financial processes at VSB-TU Ostrava
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	22
http://linked.open...iv/tvurceVysledku	Gurný, Petr Gurný, Martin
http://linked.open...ain/vavai/riv/wos	000321990300002
issn	1210-0455
number of pages	19 (xsd:int)
http://localhost/t...ganizacniJednotka	27510

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