Proper scoring rules for evaluating asymmetry in density forecasting

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Tác giả: Matteo Iacopini, Francesco Ravazzolo, Luca Rossini

Ngôn ngữ: eng

Ký hiệu phân loại: 525.12 Earth (Astronomical geography)

Thông tin xuất bản: 2020

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 164700

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.
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