Quantile Forecasts#
Forecasts of specific quantiles of the outcome distribution.
Important
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What it is#
A quantile forecast expresses the prediction not as one number but as one or more conditional quantiles of the future value’s distribution — for example the 10th, 50th and 90th percentiles. The 0.5 level is the median; a pair like 0.1 / 0.9 brackets the outcome, saying it is unlikely (\(\le\) 10%) to fall below the lower or above the upper. Formally the \(\tau\)-quantile forecast satisfies
Why use them#
They convey uncertainty and asymmetry directly: you can act differently when under- and over-shooting carry different costs, without assuming a parametric (e.g. Gaussian) shape for the distribution.
How they’re scored#
Quantile forecasts are evaluated with the pinball (quantile) loss, matched to each level; the CRPS (Continuous Ranked Probability Score) generalizes it by integrating the pinball loss across all quantiles, giving a single distributional score.
Theme: Risk & Probabilistic Forecasting · All terminology
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Mind map — connected ideas
Quantile Regression · Prediction Intervals (PI) · Probabilistic Forecasts · Quantile Level · Predicting Percentiles · Point Forecasts
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More in Risk & Probabilistic Forecasting
Continuous Probabilistic Forecasts · Continuous Ranked Probability Score (CRPS) · Deterministic forecasts · Full Distribution · Pinball Loss (a.k.a. Quantile Loss) · Point Forecasts · Predicting Percentiles · Prediction Intervals (PI) · Probabilistic Forecasts · Probabilistic Scoring · Probability Forecasts · Quantile Level · Quantile Regression · Return Distribution
See also
Source article Adapted (context, re-expressed) in our own words from: Quantile Forecasts (insightful-data-lab.com).