Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context

Jie Cheng ()
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Jie Cheng: Keele University

Computational Economics, 2024, vol. 64, issue 6, No 18, 3617-3643

Abstract: Abstract Scoring rules are commonly applied to assess the accuracy of density forecasts in both univariate and multivariate settings. In a financial risk management context, we are mostly interested in a particular region of the density: the (left) tail of a portfolio’s return distribution. The dependence structure between returns on different assets (associated with a given portfolio) is usually time-varying and asymmetric. In this paper, we conduct a simulation study to compare the discrimination ability between the well-established scores and their threshold-weighted versions with selected regions. This facilitates a comprehensive comparison of the performance of scoring rules in different settings. Our empirical applications also confirm the importance of weighted-threshold scores for accurate estimates of Value-at-risk and related measures of downside risk.

Keywords: Density forecast evaluation; Copula; Weighted score; Multivariate forecasting; Multivariate scoring rule; Asymmetric dependence structure (search for similar items in EconPapers)
JEL-codes: C53 G11 G17 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10614-024-10571-y

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