Forecasting the M4 competition weekly data: Forecast Pro’s winning approach
| Autor: | Eric Stellwagen, Sarah Goodrich Darin |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Operations research
Computer science Process (engineering) 05 social sciences ComputingMilieux_GENERAL Competition (economics) Business forecasting ComputerApplications_MISCELLANEOUS 0502 economics and business Key (cryptography) 050207 economics Business and International Management Baseline (configuration management) Performance metric Selection algorithm 050205 econometrics |
| Zdroj: | International Journal of Forecasting. 36:135-141 |
| ISSN: | 0169-2070 |
| DOI: | 10.1016/j.ijforecast.2019.03.018 |
| Popis: | Forecast Pro forecasted the weekly series in the M4 competition more accurately than all other entrants. Our approach was to follow the same forecasting process that we recommend to our users. This approach involves determining the Key Performance Metric (KPI), establishing baseline forecasts using our automated expert selection algorithm, reviewing those baseline forecasts and customizing forecasts where needed. This article explores why this approach worked well for weekly data, discusses the applicability of the M4 competition to business forecasting and proposes some potential improvements for future competitions to make them more relevant to business forecasting. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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