Extreme value analysis of high‐frequency cryptocurrencies

Abstract

Abstract Using extreme value analysis, we investigate the tail risk behavior of the high‐frequency (hourly) log returns of four most popular cryptocurrencies. The analysis is conducted on high‐frequency returns data, estimating value at risk and expected shortfall with varying thresholds. We find that Ripple is the most risky cryptocurrency exhibiting the largest potential gain or loss for both positive and negative (hourly) log returns at every percentile and threshold. Bitcoin is the least risky cryptocurrency.