Resumo

VELASQUEZ HENAO, Juan David  e  ALDANA DUMAR, Mario Alberto. MODELLING OF THE COLOMBIAN COFFEE PRICE IN THE NEW YORK STOCK EXCHANGE USING ARTIFICIAL NEURAL NETWORKS. Rev.Fac.Nal.Agr.Medellín [online]. 2007, vol.60, n.2, pp. 4129-4144. ISSN 0304-2847.

In this paper, the monthly average price of the Colombian coffee in the New York Stock Exchange, is modelling by means of several alternative models. The preferred model is composed by a lineal autoregressive component plus a multilayer perceptron neural network with two neurons in the hidden layer, that allow us to representing the dynamic following by the expected value of the price time series; while, the dynamic of the residuals is specified by an autoregressive conditional heterocedastic model of first order. The normalized residuals of the preferred model are uncorrelated, homocedastic and are distributed following a normal distribution. The results indicate that the current price depend of the prices in the previous four months.

Palavras-chave : Coffee price; nonlinear models; artificial neural networks; time series.