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An application of extreme value theory to cryptocurrencies

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  • Gkillas, Konstantinos
  • Katsiampa, Paraskevi

Abstract

We study the tail behaviour of the returns of five major cryptocurrencies. By employing an extreme value analysis and estimating Value-at-Risk and Expected Shortfall as tail risk measures, we find that Bitcoin Cash is the riskiest, while Bitcoin and Litecoin are the least risky cryptocurrencies.

Suggested Citation

  • Gkillas, Konstantinos & Katsiampa, Paraskevi, 2018. "An application of extreme value theory to cryptocurrencies," Economics Letters, Elsevier, vol. 164(C), pages 109-111.
  • Handle: RePEc:eee:ecolet:v:164:y:2018:i:c:p:109-111
    DOI: 10.1016/j.econlet.2018.01.020
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    References listed on IDEAS

    as
    1. Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
    2. Gkillas (Gillas), Konstantinos & Tsagkanos, Athanasios & Siriopoulos, Costas, 2016. "The risk in capital controls," Finance Research Letters, Elsevier, vol. 19(C), pages 261-266.
    3. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    4. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    5. Ibragimov, Rustam & Prokhorov, Artem, 2016. "Heavy tails and copulas: Limits of diversification revisited," Economics Letters, Elsevier, vol. 149(C), pages 102-107.
    6. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    7. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    8. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    9. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    10. Longin, Francois, 2005. "The choice of the distribution of asset returns: How extreme value theory can help?," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 1017-1035, April.
    11. Joerg Osterrieder & Julian Lorenz, 2017. "A Statistical Risk Assessment Of Bitcoin And Its Extreme Tail Behavior," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 1-19, March.
    12. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    13. Phillip, Andrew & Chan, Jennifer S.K. & Peiris, Shelton, 2018. "A new look at Cryptocurrencies," Economics Letters, Elsevier, vol. 163(C), pages 6-9.
    14. Longin, François & Pagliardi, Giovanni, 2016. "Tail relation between return and volume in the US stock market: An analysis based on extreme value theory," Economics Letters, Elsevier, vol. 145(C), pages 252-254.
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    More about this item

    Keywords

    Cryptocurrency; Bitcoin; Extreme value analysis; Value-at-Risk; Expected shortfall;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • F38 - International Economics - - International Finance - - - International Financial Policy: Financial Transactions Tax; Capital Controls
    • G01 - Financial Economics - - General - - - Financial Crises

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