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Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall

Esther B. Del Brio, Andrés Mora-Valencia and Javier Perote ()

International Review of Financial Analysis, 2020, vol. 70, issue C

Abstract: This paper calibrates risk assessment of alternative methods for modeling commodity ETFs. We implement recently proposed backtesting techniques for both value-at-risk (VaR) and expected shortfall (ES) under parametric and semi-nonparametric techniques. Our results indicate that skewed-t and Gram-Charlier distributional assumptions present the best relative performance for individual Commodity ETFs for those confidence levels recommended by Basel Accords. In view of these results, we recommend the application of leptokurtic distributions and semi-nonparametric techniques to mitigate regulation concerns about global financial stability of commodity business.

Keywords: Value-at-risk; Expected shortfall; Backtesting; Gram-Charlier expansion (search for similar items in EconPapers)
JEL-codes: C46 C58 G17 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.irfa.2017.11.007

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