Quantile Methods for Assessing Investment Risk in Cryptocurrencies

In this study, the daily returns of the ten largest-cap cryptocurrencies have been analyzed. It is shown that the returns of cryptocurrencies most often follow a Laplace distribution. Analytical expressions have been obtained for assessing the investment risk of cryptocurrencies using the VaR method. Numerical risk estimates have been calculated using VaR and CVaR methods. Our analysis indicates that the Conditional Value at Risk (CVaR) is 40-45% higher than the Value at Risk (VaR), suggesting that the VaR method underestimates potential losses.