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Tail Risk Measurement In Crypto-Asset Markets

Author

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  • Daniel Felix Ahelegbey

    (Università di Pavia)

  • Paolo Giudici

    (Università di Pavia)

  • Fatemeh Mojtahedi

    (Sari Agricultural Sciences and Natural Resources University)

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.

Suggested Citation

  • Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2020. "Tail Risk Measurement In Crypto-Asset Markets," DEM Working Papers Series 186, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:demwp0186
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    Cited by:

    1. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
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    3. Fatemeh Mojtahedi & Seyed Mojtaba Mojaverian & Daniel F. Ahelegbey & Paolo Giudici, 2020. "Tail Risk Transmission: A Study of the Iran Food Industry," Risks, MDPI, vol. 8(3), pages 1-17, July.
    4. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    5. Samia Nasreen & Aviral Kumar Tiwari & Seong-Min Yoon, 2021. "Dynamic Connectedness and Portfolio Diversification during the Coronavirus Disease 2019 Pandemic: Evidence from the Cryptocurrency Market," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    6. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    7. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    8. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    10. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2022. "Crypto Asset Portfolio Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    11. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).
    12. Goodell, John W. & Alon, Ilan & Chiaramonte, Laura & Dreassi, Alberto & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Risk substitution in cryptocurrencies: Evidence from BRICS announcements," Emerging Markets Review, Elsevier, vol. 54(C).
    13. González-Sánchez, Mariano & Nave Pineda, Juan M., 2023. "Where is the distribution tail threshold? A tale on tail and copulas in financial risk measurement," International Review of Financial Analysis, Elsevier, vol. 86(C).
    14. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).
    15. Wang, Qunwei & Liu, Mengmeng & Xiao, Ling & Dai, Xingyu & Li, Matthew C. & Wu, Fei, 2022. "Conditional sovereign CDS in market basket risk scenario: A dynamic vine-copula analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).

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    More about this item

    Keywords

    Crypto-assets; Extreme downside hedge; Extreme downside correlation; Network Models; Systematic risk; Systemic risk.;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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