Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/230834 
Year of Publication: 
2020
Series/Report no.: 
IRTG 1792 Discussion Paper No. 2020-028
Publisher: 
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", Berlin
Abstract: 
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.
Subjects: 
Cryptocurrencies
Network Dynamics
Portfolio Optimization
Quantile Regression
Systemic Risk
Financial Risk Meter
JEL: 
C00
Document Type: 
Working Paper

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