This HTML5 document contains 43 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n20http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
n7http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F61989100%3A27510%2F12%3A86082805%21RIV14-MSM-27510___/
dctermshttp://purl.org/dc/terms/
n14http://purl.org/net/nknouf/ns/bibtex#
n13http://localhost/temp/predkladatel/
n19http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n12http://linked.opendata.cz/resource/domain/vavai/subjekt/
n11http://linked.opendata.cz/ontology/domain/vavai/
n17https://schema.org/
shttp://schema.org/
n5http://linked.opendata.cz/ontology/domain/vavai/riv/
skoshttp://www.w3.org/2004/02/skos/core#
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n9http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n8http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n21http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n6http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n10http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F61989100%3A27510%2F12%3A86082805%21RIV14-MSM-27510___
rdf:type
skos:Concept n11:Vysledek
dcterms:description
The objective of the paper is to apply three selected approaches for credit rating prediction, linear discriminant analysis, multinomial logistic regression and decision trees. The models are based on data of European companies’ financial indicators and MORE rating. A special attention is paid to comparison of models and interpretation of results. The analysis is also focused on the identification of variables with the most significant impact on credit rating assessment. The estimated models can be used for credit rating prediction and can serve as a useful tool in the investment decision process. The objective of the paper is to apply three selected approaches for credit rating prediction, linear discriminant analysis, multinomial logistic regression and decision trees. The models are based on data of European companies’ financial indicators and MORE rating. A special attention is paid to comparison of models and interpretation of results. The analysis is also focused on the identification of variables with the most significant impact on credit rating assessment. The estimated models can be used for credit rating prediction and can serve as a useful tool in the investment decision process.
dcterms:title
The use of different approaches for credit rating prediction and their comparison The use of different approaches for credit rating prediction and their comparison
skos:prefLabel
The use of different approaches for credit rating prediction and their comparison The use of different approaches for credit rating prediction and their comparison
skos:notation
RIV/61989100:27510/12:86082805!RIV14-MSM-27510___
n11:predkladatel
n12:orjk%3A27510
n5:aktivita
n21:S
n5:aktivity
S
n5:dodaniDat
n10:2014
n5:domaciTvurceVysledku
n19:2689510
n5:druhVysledku
n18:D
n5:duvernostUdaju
n8:S
n5:entitaPredkladatele
n7:predkladatel
n5:idSjednocenehoVysledku
176337
n5:idVysledku
RIV/61989100:27510/12:86082805
n5:jazykVysledku
n16:eng
n5:klicovaSlova
prediction; modelling; logistic regression; discriminant analysis; decision trees; Credit rating
n5:klicoveSlovo
n9:decision%20trees n9:modelling n9:Credit%20rating n9:prediction n9:discriminant%20analysis n9:logistic%20regression
n5:kontrolniKodProRIV
[1A4B988C5F7E]
n5:mistoKonaniAkce
Ostrava
n5:mistoVydani
Ostrava
n5:nazevZdroje
Řízení a modelování finančních rizik : sborník příspěvků z 6. mezinárodní vědecké konference : 10.-11. září 2012, Ostrava, Česká republika
n5:obor
n6:AH
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
1
n5:rokUplatneniVysledku
n10:2012
n5:tvurceVysledku
Novotná, Martina
n5:typAkce
n20:EUR
n5:wos
000317528600049
n5:zahajeniAkce
2012-09-10+02:00
s:numberOfPages
10
n14:hasPublisher
Vysoká škola báňská - Technická univerzita Ostrava
n17:isbn
978-80-248-2835-0
n13:organizacniJednotka
27510