A Set of New Tools to Measure the Effective Value of Probabilistic Forecasts of Continuous Variables

Josselin Le Gal La Salle (), Mathieu David and Philippe Lauret
Additional contact information
Josselin Le Gal La Salle: lPIMENT Laboratory, University of La Reunion, 15, Avenue René Cassin, CEDEX, 97715 Saint-Denis, France
Mathieu David: lPIMENT Laboratory, University of La Reunion, 15, Avenue René Cassin, CEDEX, 97715 Saint-Denis, France
Philippe Lauret: lPIMENT Laboratory, University of La Reunion, 15, Avenue René Cassin, CEDEX, 97715 Saint-Denis, France

Forecasting, 2025, vol. 7, issue 2, 1-18

Abstract: In recent years, the prominence of probabilistic forecasting has risen among numerous research fields (finance, meteorology, banking, etc.). Best practices on using such forecasts are, however, neither well explained nor well understood. The question of the benefits derived from these forecasts is of primary interest, especially for the industrial sector. A sound methodology already exists to evaluate the value of probabilistic forecasts of binary events. In this paper, we introduce a comprehensive methodology for assessing the value of probabilistic forecasts of continuous variables, which is valid for a specific class of problems where the cost functions are piecewise linear. The proposed methodology is based on a set of visual diagnostic tools. In particular, we propose a new diagram called EVC (“Effective economic Value of a forecast of Continuous variable”) which provides the effective value of a forecast. Using simple case studies, we show that the value of probabilistic forecasts of continuous variables is strongly dependent on a key variable that we call the risk ratio. It leads to a quantitative metric of a value called the OEV (“Overall Effective Value”). The preliminary results suggest that typical OEVs demonstrate the benefits of probabilistic forecasting over a deterministic approach.

Keywords: value of forecast; probabilistic forecasting; uncertainty management; quantile score (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2571-9394/7/2/30/pdf (application/pdf)
https://www.mdpi.com/2571-9394/7/2/30/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jforec:v:7:y:2025:i:2:p:30-:d:1682859

Access Statistics for this article

Forecasting is currently edited by Ms. Joss Chen

More articles in Forecasting from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().