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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    AE - Management, administration and clerical work

  • OECD FORD branch

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

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

  • 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