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Evaluating quantile forecasts in the M5 uncertainty competition

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  • Chen, Zhi
  • Gaba, Anil
  • Tsetlin, Ilia
  • Winkler, Robert L.

Abstract

Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the forecasting performance of the quantile forecasts at different aggregation levels and at different quantile levels. We contrast this with some theoretical predictions, and discuss potential implications and promising future research directions for the practice of probabilistic forecasting.

Suggested Citation

  • Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "Evaluating quantile forecasts in the M5 uncertainty competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1531-1545.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:4:p:1531-1545
    DOI: 10.1016/j.ijforecast.2022.03.004
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    1. Te Bao & Brice Corgnet & Nobuyuki Hanaki & Katsuhiko Okada & Yohanes E. Riyanto & Jiahua Zhu, 2022. "Financial Forecasting in the Lab and the Field: Qualified Professionals vs. Smart Students," ISER Discussion Paper 1156r, Institute of Social and Economic Research, Osaka University, revised Sep 2024.

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