Optimizing the market-risk of major cryptocurrencies using CVaR measure and copula simulation

Abstract

In this paper, we utilize the conditional value-at-risk to quantify the risk exposure and the generalized Pareto distribution copula technique to analyse extreme events which helps in finding out the efficient portfolio selection. The sample data covers nine cryptocurrencies covering the period from September 2016 to August 2018. Our results using the efficient frontier indicate that if a minimum variance portfolio is constructed using chosen cryptocurrencies, investment in Bitcoin is preferred being the least risky currency on the bottom of the efficient frontier. These results find prime importance for investors and risk managers.