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Let Financial Data Speak for Themselves

  • Carlos Serrano-Cinca
Part of the Springer Finance book series (FINANCE)

Abstract

Carlos Serrano-Cinca of the University of Zaragoza in Spain discusses five different applications of unsupervised neural networks and self-organizing maps (SOM) using financial data: (i) analysis of financial statements and information for the formulation of corporate strategy; (ii) visual diagnosis of the financial situation of companies; (iii) establishment of bond ratings; (iv) analysis of the economic convergence of European countries using macro-economic indicators; and (v) self-organizing maps as decision support systems. The wide variety of financial applications presented by Carlos Serrano-Cinca shows that SOM is an important tool for initial data analysis.

Keywords

European Union Linear Discriminant Analysis Synaptic Weight European Union Member State Saving Bank 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Carlos Serrano-Cinca

There are no affiliations available

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