Quantile Forecast Evaluation

Quantile Forecast Evaluation is a formal metric within forecast error analysis that assesses the accuracy of quantile forecasts by comparing predicted quantiles to empirical outcomes using specialized loss functions, such as the asymmetric linear loss in the quantile scoring rule, thereby distinguishing it from point or probabilistic forecast evaluation methods.

55

Publications

2.8K

Citations

160

Authors

115

Institutions

Publications per year

2017–2026

30

Authors

160

  1. JW
    James W. Taylor

    University of Wisconsin–Madison, United States

    3 publications · 205 citations

    3

    h-index

  2. RL
    Robert L. Winkler

    Duke University, United States

    3 publications · 286 citations

    3

    h-index

  3. GJ
    Georg J. Mayr

    Universität Innsbruck, Austria

    2 publications · 65 citations

    2

    h-index

  4. GK
    Georges Kariniotakis

    Centre Procédés, Energies Renouvelables et Systèmes Energétiques, France

    2 publications · 376 citations

    2

    h-index

  5. PP
    Pierre Pinson

    Technical University of Denmark, Denmark

    2 publications · 301 citations

    2

    h-index

1–5 of 160

Venues

  1. International Journal of Forecasting

    5 publications · 197 citations

    5

    h-index

  2. 3

    h-index

  3. Resources Policy

    3 publications · 185 citations

    3

    h-index

  4. SSRN Electronic Journal

    Repository · 2 publications · 79 citations

    2

    h-index

  5. Journal of Forecasting

    2 publications · 77 citations

    2

    h-index

1–5