Radial basis functions networks to hybrid neuro-genetic RBFNs in financial evaluation of corporations
Authors: Loukeris, Nikolaos 
Issue Date: 1-Jul-2008
Conference: 12th WSEAS international conference on Computers, 23-25 July 2008, Heraklion, Greece 
Book: Proceedings of the 12th WSEAS international conference on Computers 
Abstract: 
Financial management maximise investors' return, seeking for stocks with increasing expected corporate value. Hidden information is included in vast accounting data and financial indices that are available in international financial markets. Methods of Econometrics and Artificial Intelligence- mainly in the field of Neural Networks- provide classifications of companies regarding their economic health. Radial Basis Function networks are examined in a hybrid form of Neural Network optimised with Genetic Algorithms and in a regular Neural Net form, to determine efficient methods of Financial Analysis. The regular Radial Basis Function network with 3 layers, Genetic Algorithms in all the layers and Cross Validation is superior to all the neuro-genetic forms of RBF in Financial Analysis.
ISBN: 978-960-6766-85-5
DOI: 10.5555/1513605.1513743
URI: https://uniwacris.uniwa.gr/handle/3000/2200
Type: Conference Paper
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου

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