Probabilistic Neural Networks for Credit Rating Modelling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F10%3A39881988" target="_blank" >RIV/00216275:25410/10:39881988 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Probabilistic Neural Networks for Credit Rating Modelling
Original language description
This paper presents the modelling possibilities of probabilistic neural networks to a complex real-world problem, i.e. credit rating modelling. First, current approaches in credit rating modelling are introduced. Then, probabilistic neural networks are designed to classify US companies and municipalities into rating classes. The input variables are extracted from financial statements and statistical reports in line with previous studies. These variables represent the inputs of probabilistic neural networks, while the rating classes from Standard and Poor's and Moody's rating agencies stand for the outputs. Classification accuracies, misclassification costs, and the contributions of input variables are studied for probabilistic neural networks comparedto other neural networks models. The results show that the rating classes assigned to bond issuers can be classified accurately with probabilistic neural networks using a limited subset of input variables.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
AE - Management, administration and clerical work
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GP402%2F09%2FP090" target="_blank" >GP402/09/P090: Modelling of Municipal Finance by Computational Intelligence Methods</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference on Neural Computation 2010
ISBN
978-989-8425-32-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
International Joint Conference on Computational Intelligence
Place of publication
Setúbal
Event location
Valencia
Event date
Oct 24, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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