Neural Networks
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Computational Economics - Computational Studies at Stanford
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
On the Convergence of Pattern Search Algorithms
SIAM Journal on Optimization
Grammatical Evolution And Corporate Failure Prediction
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Computers and Operations Research - Special issue: Emerging economics
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Support Vector Machines for Pattern Classification (Advances in Pattern Recognition)
Support Vector Machines for Pattern Classification (Advances in Pattern Recognition)
Application of support vector machines to corporate credit rating prediction
Expert Systems with Applications: An International Journal
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Is this brand ephemeral? A multivariate tree-based decision analysis of new product sustainability
Decision Support Systems
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks
Decision Support Systems
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Predicting bond ratings using publicly available information
Expert Systems with Applications: An International Journal
Modelling sovereign credit ratings: Neural networks versus ordered probit
Expert Systems with Applications: An International Journal
A hybrid KMV model, random forests and rough set theory approach for credit rating
Knowledge-Based Systems
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Credit rating using a hybrid voting ensemble
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Credit risk assessment and decision making by a fusion approach
Knowledge-Based Systems
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The paper presents the modelling possibilities of neural networks on a complex real-world problem, i.e. municipal credit rating modelling. First, current approaches in credit rating modelling are introduced. Second, previous studies on municipal credit rating modelling are analyzed. Based on this analysis, the model is designed to classify US municipalities (located in the State of Connecticut) into rating classes. The model includes data pre-processing, the selection process of input variables, and the design of various neural networks' structures for classification. The selection of input variables is realized using genetic algorithms. The input variables are extracted from financial statements and statistical reports in line with previous studies. These variables represent the inputs of neural networks, while the rating classes from Moody's rating agency stand for the outputs. In addition to exact rating classes, data are also labelled by four basic rating classes. As a result, the classification accuracies and the contributions of input variables are studied for the different number of classes. The results show that the rating classes assigned to bond issuers can be classified with a high accuracy rate using a limited subset of input variables.