6.1 Change and Noise
One of the most effective and robust methods for time series forecasting is exponential smoothing. This result has been established in the so-called M-competitions, in which more than 20 forecasting methods were compared for their performance across over 3,000 time series from different industries and contexts (Makridakis and Hibon 2000). The good news is that exponential smoothing is not only an effective, versatile, and robust method but is also, at its core, intuitive and easy to understand and interpret. Another important aspect of the method is that the data storage and computational requirements for exponential smoothing are minimal, and the method can thus be applied with ease to a ...
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