CMStatistics 2018: Start Registration
View Submission - CFE
Title: Conditional tail-risk in cryptocurrency markets Authors:  Nicola Borri - LUISS University (Italy) [presenting]
Abstract: The CoVaR risk-measure is used to estimate the conditional tail-risk in the markets for bitcoin, ether, ripple and litecoin and find that these cryptocurrencies are highly exposed to tail-risk within cryptomarkets while they are not exposed to tail-risk with respect to other global assets, like the U.S. equity market or gold. Although cryptocurrencies are highly correlated one with the other, both unconditionally and conditionally, we find that idiosyncratic risk can be significantly reduced and that portfolios of cryptocurrencies offer better risk-adjusted and conditional returns than the individual cryptocurrencies. These results indicate that portfolios of cryptocurrencies could offer attractive returns and hedging properties when included in investors' portfolios.