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Faculty & Research


Evaluating Quantile Forecasts in the M5 Uncertainty Competition

Journal Article
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. The authors contrast this with some theoretical predictions, and discuss potential implications and promising future research directions for the practice of probabilistic forecasting.

Professor of Decision Sciences

Professor of Decision Sciences