Sliding simulation: A new approach to time series forecasting

This paper proposes a new approach to time series forecasting based upon three premises. First, a model is selected not by bow well it fits historical data but on its ability to accurately predict out-of-sample actual data. Second, a model/method is selected among several run in parallel using out-of-sample information. Third, models/methods are optimized for eacb forecasting horizon separately, making it possible to have different models/methods to predict each of tbe m horizons. Tbis approach outperforms the best method of the Af-Competition by a large margin wben tested empirically with the 111 series subsample of the Af-Competition data.