Statistical Data Mining and ArtificialNeural Networks:A Case of Studyin Financial Modeling

  1. Pedro García-Laencina 1
  2. M. Ángeles Varela-Jul 1
  3. José L. Roca-González 1
  4. Carmen de Nieves-Nieto 1
  5. Joaquín Roca-Dorda 1
  1. 1 Universidad Politécnica de Cartagena
    info

    Universidad Politécnica de Cartagena

    Cartagena, España

    ROR https://ror.org/02k5kx966

Book:
Industrial Engineering: Innovative Networks: 5th International Conference on Industrial Engineering and Industrial Management "CIO 2011", Cartagena, Spain, September 2011, Proceedings
  1. Suresh P. Sethi (dir. congr.)
  2. Marija Bogataj (dir. congr.)
  3. Lorenzo Ros-McDonnell (dir. congr.)

Publisher: Springer-Verlag Reino Unido

ISBN: 978-1-4471-2321-7

Year of publication: 2012

Pages: 69-78

Type: Book chapter

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Abstract

Nowadays, an organization or institution works with a huge amount of information about itself and its environment. This data has the potential to predict the evolution of interesting va riables or trends in the outside environment. Data mining isthe process that uses a variety of data analysis tools to discover meaningful patterns, trends and relationships in data that may be used to make valid predictions. In the lastdecades, artificial neural network-based technology stands out as one of the most suitable approaches. The goals of this work are to give a comprehensive analysis ofthe data mining process, to present the last advances on neural networks and its application for modeling financial data. In particular, an efficient neural network model is constructed for modeling the return on assets from other financial variables

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