In business forecasting it is quite common to deal with seasonal time series. Although several methodologies have been developed to identify when to use a seasonal model, less effort has been invested in identifying whether a time series exhibits additive or multiplicative seasonality. Perhaps here it is useful to remember the distinction between the two.
The “Judgmental model selection for time series forecasting” experiment is now successfully completed! In total, 905 people started the experiment, from which 693 completed the task. Thank you all for your participation in this judgmental experiment. Your contribution to this research is much appreciated. The experiment itself completed by two approaches: Judgmental model selection, where
Model selection for forecasting problems has attracted much attention during the last 30 years. Many research studies have examined theoretically and empirically different statistical selection methodologies to identify the ‘optimal’ model. The model selection problem is of major practical importance, because if selections are to be done perfectly, substantial gains will achieved in terms of
We are inviting you to participate in a web-based judgmental forecasting exercise. You are asked to select the best model, based on your judgment, for 32 time series. The exercise consists of four rounds. Each round will contain 8 series and will be followed by a short questionnaire, while different types of information will be