Proper scoring rules for evaluating asymmetry in density forecasting

Matteo Iacopini (), Francesco Ravazzolo and Luca Rossini

No No 06/2020, Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School

Abstract: This paper proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It extends the proposed score and defines a weighted version, which emphasizes regions of interest, such as the tails or the center of a variable s range. A test is also introduced to statistically compare the predictive ability of different forecasts. The ACPS is of general use in any situation where the decision maker has asymmetric preferences in the evaluation of the forecasts. In an artificial experiment, the implications of varying the level of asymmetry in the ACPS are illustrated. Then, the proposed score and test are applied to assess and compare density forecasts of macroeconomic relevant datasets (US employment growth) and of commodity prices (oil and electricity prices) with particular focus on the recent COVID-19 crisis period.

Keywords: asymmetric continuous probablistic score; asymmetric loss; proper score; density forecast; predictive distribution; weighted score; probabilistic forecast (search for similar items in EconPapers)
Pages: 33 pages
Date: 2020-09
New Economics Papers: this item is included in nep-for
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https://hdl.handle.net/11250/2678134

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Working Paper: Proper scoring rules for evaluating asymmetry in density forecasting (2020)
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