Value-at-Risk Effectiveness: A High-Frequency Data Approach with Semi-Heavy Tails
Mario Ivan Contreras-Valdez,
Sonal Sahu,
José Antonio Núñez-Mora
et al.
Abstract:In the broader landscape of cryptocurrency risk management, this study delves into the nuanced estimation of Value-at-Risk (VaR) for a uniformly weighted portfolio of cryptocurrencies, employing the bivariate Normal Inverse Gaussian distribution renowned for its semi-heavy tails. Utilizing high-frequency data spanning between 1 January 2017 and 25 October 2022, with a primary focus on Bitcoin and Ethereum, our research seeks to accentuate the resilience of VaR methodology as a paramount risk assessment tool. T… Show more
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