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Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis

Author

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  • Ren, Rui
  • Althof, Michael
  • Härdle, Wolfgang Karl

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.

Suggested Citation

  • Ren, Rui & Althof, Michael & Härdle, Wolfgang Karl, 2020. "Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis," IRTG 1792 Discussion Papers 2020-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    • Handle: RePEc:zbw:irtgdp:2020028
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    References listed on IDEAS

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    8. Alla Petukhina & Simon Trimborn & Wolfgang Karl Härdle & Hermann Elendner, 2021. "Investing with cryptocurrencies – evaluating their potential for portfolio allocation strategies," Quantitative Finance, Taylor & Francis Journals, vol. 21(11), pages 1825-1853, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Wang, Ruting & Althof, Michael & Härdle, Wolfgang Karl, 2023. "A financial risk meter for China," Emerging Markets Review, Elsevier, vol. 56(C).
    2. Wang, Ruting & Althof, Michael & Härdle, Wolfgang, 2021. "A financial risk meter for China," IRTG 1792 Discussion Papers 2021-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    5. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    6. Theodore Pelagidis & Eleftheria Kostika, 2022. "Investigating the role of central banks in the interconnection between financial markets and cryptoassets," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 481-507, September.

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    More about this item

    Keywords

    Cryptocurrencies; Network Dynamics; Portfolio Optimization; Quantile Regression; Systemic Risk; Financial Risk Meter;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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