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Predicción de series temporales con redes neuronales: una aplicación a la inflación colombiana

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Author Info
Juan Camilo Santana ()
Abstract

Evaluar la capacidad de las redes neuronales en la predicción de series temporales es de sumo interés. Una aplicación que pronostique valores futuros de la serie de inflación colombiana permite mostrar que las redes neuronales pueden ser más precisas que las metodologías Sarima de Box-Jenkins y el suavizamiento exponencial. Además, los resultados revelan que la combinación de pronósticos hacen uso de las redes neuronales tiende a mejorar la capacidad de predicción.

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File URL: http://www.ciencias.unal.edu.co/publicaciones/estadistica/rce/V29/V29_1_77Santana.pdf
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Article provided by REVISTA COLOMBIANA DE ESTADISTICA in its journal Revista Colombiana de Estadística.

Volume (Year): (2006)
Issue (Month): ()
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Handle: RePEc:col:000163:004048

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March. [Downloadable!] (restricted)
  2. Martha Misas & Enrique López & Pablo Querubín, . "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 199, Banco de la Republica de Colombia. [Downloadable!]
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  3. Munir A. Jalil. B & Martha Misas, 2006. "Evaluación de pronósticos del tipo de cambio utilizando," BORRADORES DE ECONOMIA 002636, BANCO DE LA REPÚBLICA. [Downloadable!]
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This page was last updated on 2009-11-27.

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