Multi-Series Heuristics for Exponential Smoothing

In this paper several heuristics are proposed for calculating the smoothing parameter in exponential smoothing when forecasts of many 'closely' related series are required on a regular basis. The methods are evaluated using both synthetic and real data. They not only compare favourably against several other known forecasting techniques but they are also simple and computationally efficient.