Semi-nonparametric risk assessment with cryptocurrencies

Inés Jiménez, Andrés Mora-Valencia and Javier Perote

Research in International Business and Finance, 2022, vol. 59, issue C

Abstract: This paper establishes a brand-new perspective of analyzing the risk of crypto assets through a semi-nonparametric approach, discussing its theoretical advantages and testing its performance compared to parametric approaches and in terms of backtesting techniques and different risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. Our comprehensive analysis for six cryptocurrencies shows that flexible semi-nonparametric approaches outperform risk measures of most crypto assets (particularly Bitcoin) and tend to provide the most conservative risk assessment. Furthermore, we propose the Median Shortfall as a robust-to-outliers and reliable risk measure for cryptocurrencies and discuss on the choice of the appropriate probability levels according to the assumed distribution. The evidence supports that Median Shortfall at 98.31 % and 98.51 % confidence levels as accurate alternatives to Value-at-Risk at 99 % and Expected Shortfall at 97.5 %.

Keywords: Gram Charlier series; Value-at-Risk; Expected shortfall; Median shortfall; Backtesting; Cryptocurrencies (search for similar items in EconPapers)
JEL-codes: C01 C12 C13 C14 C16 C53 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:59:y:2022:i:c:s0275531921001884

DOI: 10.1016/j.ribaf.2021.101567

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