Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis - Rui Ren; Michael Althof; Wolfgang Karl Härdle (Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", 2020)
Cryptocurrencies are gaining momentum in investor attention, are about to become a new asset class, and may provide a hedging alternative against the risk of devaluation of fiat currencies following the COVID-19 crisis. In order to provide a thorough understanding of this new asset class, risk indicators need to consider tail risk behaviour and the interdependencies between the cryptocurrencies not only for risk management but also for portfolio optimization. The tail risk network analysis framework proposed in the paper is able to identify individual risk characteristics and capture spillover effect in a network topology. Finally we construct tail event sensitive portfolios and consequently test the performance during an unforeseen COVID-19 pandemic.
Keywords: C00; 330; Cryptocurrencies; Network Dynamics; Portfolio Optimization; Quantile Regression; Systemic Risk; Financial Risk Meter