Recently, various variants of the self-organsing map (SOM) have been proposed for modelling and predicting time series. However, most of them are based on lattice structure. In this paper, a hybrid neural model combining neural gas (NG) and mixture autoregressive models is developed for forecasting foreign exchange (FX) rates. It takes advantage of some NG features (i.e. neighbourhood rankings)