Neural Networks for Economic Forecasting

  • Massimo Salzano
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

After a survey of literature, we analyse the main experiences of economic forecasting using NN. The review aims at two purposes: it provides a general summary of the work in ANN forecasting done to date and it furnishes guidelines for neural network modelling. Particular attention is given to the peculiarity of economic data (high noise, non stationary, and small sample size signals) and to the contrast between model and data driven approaches. We discuss fundamental limitations and inherent difficulties when using neural networks for the economic forecasting. Recently, the traditional analogy with biological nervous systems has been considered insufficient. A deeper understanding of theoretical foundations of these models is required. Some hints for assessing the correctness of NN implementation and their contribution to a better forecast are reported.

Keywords

Entropy Autocorrelation Tempo Metaphor Milton 

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Copyright information

© Springer-Verlag London Limited 1999

Authors and Affiliations

  • Massimo Salzano
    • 1
  1. 1.Dip. Scienze EconomicheUniversity of SalernoFisciano, SalernoItaly

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