MODELADO DEL PRECIO DEL CAFÉ COLOMBIANO EN LA BOLSA DE MODELADO DEL PRECIO DEL CAFÉ COLOMBIANO EN LA BOLSA DE MODELADO DEL PRECIO DEL CAFÉ COLOMBIANO EN LA BOLSA DE MODELADO DEL PRECIO DEL CAFÉ COLOMBIANO EN LA BOLSA DE NUEVA YORK USANDO REDES NEURONALES ARTIFICIALES NUEVA YORK USANDO REDES NEURONALES ARTIFICIALES NUEVA YORK USANDO REDES NEURONALES ARTIFICIALES NUEVA YORK USANDO REDES NEURONALES ARTIFICIALES

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.