SciELO - Scientific Electronic Library Online

 
vol.25 número3Guía para la evaluación de la Usabilidad en los Entornos Virtuales de Aprendizaje (EVA)Procedimientos de Ensayo para Conexiones tipo Clavija en Estructuras de Madera índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Información tecnológica

versión On-line ISSN 0718-0764

Resumen

VILLADA, Fernando; ARROYAVE, Daniel  y  VILLADA, Melissa. Oil Price Forecast using Artificial Neural Networks. Inf. tecnol. [online]. 2014, vol.25, n.3, pp.145-154. ISSN 0718-0764.  http://dx.doi.org/10.4067/S0718-07642014000300017.

An artificial neural network model to forecast oil international price is proposed in this work. To develop the model, price data taken from the literature for the WTI reference oil (West Texas Intermediate) traded mainly in New York Mercantile Exchange are used. Four network structures, including the daily price series in the first one, the price series plus the dollar index DXY in the second one, the price series plus the S&P500 index in the third one and the price series plus the DXY and S&P500 indexes in the fourth one are used. Different neural networks configurations are analyzed using a series of six months, where data for five months are used for training patterns and the next month is left for testing the predictive capabilities of the model. The effect of including investors risk aversion using the DXY and S&P500 indexes as alternative input patterns is also analyzed. The results show good performance of the neural networks both during learning and prediction.

Palabras clave : oil exchange market; artificial neural networks; price forecasting.

        · resumen en Español     · texto en Español     · Español ( pdf )