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dc.contributor.authorIacopini, Matteo
dc.contributor.authorRavazzolo, Francesco
dc.contributor.authorRossini, Luca
dc.identifier.citationJournal of business & economic statistics. Online First 11 Mar 2022en_US
dc.description.abstractThis article proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It generalizes 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. The (weighted) ACPS extends the symmetric (weighted) CRPS by allowing for asymmetries in the preferences underlying the scoring rule. A test is used 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 (U.S. employment growth) and of commodity prices (oil and electricity prices) with particular focus on the recent COVID-19 crisis period.en_US
dc.publisherTaylor & Francis Onlineen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.subjectAsymmetric continuous probabilistic scoreen_US
dc.subjectAsymmetric lossen_US
dc.subjectDensity forecasten_US
dc.subjectPredictive distributionen_US
dc.subjectProbabilistic forecasten_US
dc.subjectProper scoreen_US
dc.subjectWeighted scoreen_US
dc.titleProper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functionsen_US
dc.title.alternativeProper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functionsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.rights.holderThe Authorsen_US
dc.source.journalJournal of business & economic statisticsen_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal