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Are the Neural Networks ‘Immune’ from Database's Properties?

Emilian Dobrescu, Dumitru Nastac, Elena Pelinescu, Are the Neural Networks ‘Immune’ from Database's Properties?. TUCS Technical Reports 1093, TUCS, 2013.

Abstract:

Our purpose is to verify the predictive performances of the artificial neural networks (ANNs) under volatile statistics and possibly misspecified system. Daily forecasts of exchange rate using exclusively primary available information for an emergent economy (such as the Romanian one) could be a proper experimental ground with such a goal. The present paper extends the previous authors’ research (Dobrescu et al., 2006; Nastac et al., 2007) on the same issue to improve the accuracy of exchange rate forecasting by using a set of neural predictors in cascade, instead of a single one. The results show that the presented model, despite its proved advantages, could not avoid the translation into residuals of the high serial correlation present in the primary database.

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BibTeX entry:

@TECHREPORT{tDoNaPe13a,
  title = {Are the Neural Networks ‘Immune’ from Database's Properties?},
  author = {Dobrescu, Emilian and Nastac, Dumitru and Pelinescu, Elena},
  number = {1093},
  series = {TUCS Technical Reports},
  publisher = {TUCS},
  year = {2013},
}

Belongs to TUCS Research Unit(s): Computational Biomodeling Laboratory (Combio Lab)

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