Modelización y predicción de series de tiempo financieras utilizando redes neuronales

Authors

  • Gustavo Maradona
  • Hugo Balacco

Keywords:

JEL: C4

Abstract

The purpose of this work is to model and predict Financials Time Series by using neural networks. In order to achieve this aim, a recurrent total neural network with two hidden layers has been chosen; one layer for the linear threshold function and the other for the arctangent function. The series used in this research paper are the MERVAL index (Argentina) and the DOW JONES (USA). These results are based on information obtained over a period that goes from 1995 to 2006. The presentation will deal with the comparison of alternative techniques and the results obtained by other research workers.

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Published

2011-12-30

How to Cite

Maradona, G., & Balacco, H. (2011). Modelización y predicción de series de tiempo financieras utilizando redes neuronales. Económica, 57, p. 3–24. Retrieved from https://revistas.unlp.edu.ar/Economica/article/view/5361

Issue

Vol. 57 (2011)

Section

Articles

License

The material published in the journal is distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. This license requires proper credit to be given, a link to the license to be provided, and changes to be indicated. It does not permit commercial use of the work, and if the work is remixed, transformed, or otherwise modified, distribution of such modification is not allowed.