Cryptocurrencies are risky currencies due to their extreme price volatilities and requires an estimation of coherent risk measures for an effective portfolio optimization and risk management. We focus on seven cryptocurrencies (Bitcoin, Ethereum, Litecoin, Ripple, Das, Monero, and Steller) and provide empirical application of Fissler and Ziegel joint loss dynamic models (FZL) for joint Value-at-Risk (VaR) and Expected Shortfall (ES) in a cryptocurrency context at ? = 0.01 and ? = 0.025 risk levels. Results show Ethereum and Steller as less risky currencies followed by Monero, Das, Litecoin, Bitcoin, and largest for Ripple suggesting that Ethereum and Steller requires the least capital to absorb losses. Following this result, we argue that market participants interested in cryptocurrencies can follow the rankings in this study to hedge, calculate margins, and capital requirement to maximize utility whiles minimizing risk to ensure financial stability in the global economy.

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Keywords

Cryptocurrencies; FZL; Value-at-Risk; Expected Shortfall; GAS framework