Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors

In this paper, we discuss how extrapolation can be advanced by using some of the most successful elements and paradigms from the forecasting literature. We propose a new hybrid method that utilises: a) the decomposition approach of the Theta method, but instead of considering a linear trend we allow for nonlinear trends, b) rather than employing the extrapolation method on the raw data, we first apply smoothing to the data, and c) when seasonality is present, we employ the shrinkage approach to the derived indices instead of simply applying classical seasonal decomposition. We empirically evaluate the new proposition in the M3-Competition data with very promising results in terms of forecast accuracy.