In order to fully understand the changes in gas component prices and, more importantly, to predict future prices and their effect on both production and investment decisions, it is vital that we model them appropriately. The approach shown in this paper that uses a time series with unobservable components is employed with a stochastic underlying trend and seasonality, using monthly data (January 1995 to November 2006) for the propane, butane and naphtha traded in the north European market. We test the predictive power of fitted models using various hold-out samples. The in-sample and out-ofsample results indicate that gas component prices follow stochastic processes, with levels and slopes shifting continuously and unpredictably over time while seasonal patterns seem to be fixed. This suggests a random walk with fixed seasonal parameters for the time series. Predicting gas component prices for horizons relevant for gas processing production and investment decisions will therefore be a very challenging task.