Tail Risk Measurement in Crypto-Asset Markets

Abstract

The paper examines the relationships among market assets during stressful times, using two recently proposed econometric modeling techniques for tail risk measurement: the extreme downside hedge (EDH) and the extreme downside correlation (EDC). We extend both measures taking into account the sensitivity of asset's return to innovations not only from the overall market index, but also from its components, by means of network modelling. Applying our proposal to the cryptocurrencies market, we find that crypto-assets can be clustered in two groups: speculative assets, such as Bitcoin, which are mainly "givers" of tail contagion; and technical assets, such as Ethereum, which are mainly "receivers" of contagion.

Keywords: Crypto-Assets, Extreme Downside Hedge, Extreme Downside Correlation, Network Models, Systematic Risk, Systemic Risk

JEL Classification: JEL: C31, C58, G01, G12