Radial basis functions networks to hybrid neuro-genetic RBFNs in financial evaluation of corporations

  • Authors:
  • Loukeris Nikolaos

  • Affiliations:
  • University of Essex

  • Venue:
  • ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

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.