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Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?

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  • Bikramaditya Ghosh
  • Spyros Papathanasiou
  • Georgios Pergeris

Abstract

Many studies have associated cryptocurrencies with bubbles, especially during stressed market conditions such as the recent outbreak of the second wave of COVID‐19. Although the majority of studies have focused on Bitcoin, we investigate the predictability of bubble formation in the cryptocurrency market by using the log‐periodic power law and we uncover some important stylized facts of this market. Our sample consists of data for a selection of 15 cryptocurrencies for the period between 1 January 2021 and 1 September 2021 which coincides with the second wave of COVID‐19. We analyse 86 speculative bubbles, and we find that the cryptocurrency market has three times higher drawdown over equities during stressed market conditions.

Suggested Citation

  • Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    • Handle: RePEc:bla:ecnote:v:51:y:2022:i:3:n:e12207
    DOI: 10.1111/ecno.12207
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    as
    1. Vladimir Filimonov & Didier Sornette, 2011. "A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model," Papers 1108.0099, arXiv.org, revised Jun 2013.
    2. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    3. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    4. Samitas, Aristeidis & Papathanasiou, Spyros & Koutsokostas, Drosos & Kampouris, Elias, 2022. "Volatility spillovers between fine wine and major global markets during COVID-19: A portfolio hedging strategy for investors," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 629-642.
    5. Belbute, José M. & Pereira, Alfredo M., 2015. "An alternative reference scenario for global CO2 emissions from fuel consumption: An ARFIMA approach," Economics Letters, Elsevier, vol. 136(C), pages 108-111.
    6. Flage, R. & Aven, T., 2015. "Emerging risk – Conceptual definition and a relation to black swan type of events," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 61-67.
    7. Taleb, Nassim Nicholas, 2007. "Black Swans and the Domains of Statistics," The American Statistician, American Statistical Association, vol. 61, pages 198-200, August.
    8. Aldasoro, Iñaki & Gambacorta, Leonardo & Giudici, Paolo & Leach, Thomas, 2022. "The drivers of cyber risk," Journal of Financial Stability, Elsevier, vol. 60(C).
    9. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Pawe{l} O'swik{e}cimka, 2016. "World Financial 2014-2016 Market Bubbles: Oil Negative - US Dollar Positive," Papers 1606.01218, arXiv.org.
    10. Anders Johansen & Didier Sornette, 2010. "Shocks, Crashes and Bubbles in Financial Markets," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 53(2), pages 201-253.
    11. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    12. Taisei Kaizoji & Michiyo Kaizoji, 2003. "Empirical Laws Of A Stock Price Index And A Stochastic Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 303-312.
    13. Max J. Krause & Thabet Tolaymat, 2018. "Author Correction: Quantification of energy and carbon costs for mining cryptocurrencies," Nature Sustainability, Nature, vol. 1(12), pages 814-814, December.
    14. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    15. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    16. Adrian (Wai-Kong) Cheung & Eduardo Roca & Jen-Je Su, 2015. "Crypto-currency bubbles: an application of the Phillips-Shi-Yu (2013) methodology on Mt. Gox bitcoin prices," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2348-2358, May.
    17. Bikramaditya Ghosh & Spyros Papathanasiou & Vandita Dar & Konstantinos Gravas, 2022. "Bubble in Carbon Credits during COVID-19: Financial Instability or Positive Impact (“Minsky” or “Social”)?," JRFM, MDPI, vol. 15(8), pages 1-16, August.
    18. W. -X. Zhou & D. Sornette, 2003. "Renormalization Group Analysis of the 2000-2002 anti-bubble in the US S&P 500 index: Explanation of the hierarchy of 5 crashes and Prediction," Papers physics/0301023, arXiv.org, revised Aug 2003.
    19. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    20. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    21. Filimonov, V. & Sornette, D., 2013. "A stable and robust calibration scheme of the log-periodic power law model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3698-3707.
    22. Elie Bouri & Luis A. Gil‐Alana & Rangan Gupta & David Roubaud, 2019. "Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 412-426, January.
    23. Max J. Krause & Thabet Tolaymat, 2018. "Quantification of energy and carbon costs for mining cryptocurrencies," Nature Sustainability, Nature, vol. 1(11), pages 711-718, November.
    24. Xiong, Jinwu & Liu, Qing & Zhao, Lei, 2020. "A new method to verify Bitcoin bubbles: Based on the production cost," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    25. Sornette, Didier & Johansen, Anders, 1998. "A hierarchical model of financial crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 261(3), pages 581-598.
    26. Geuder, Julian & Kinateder, Harald & Wagner, Niklas F., 2019. "Cryptocurrencies as financial bubbles: The case of Bitcoin," Finance Research Letters, Elsevier, vol. 31(C).
    27. Yao, Can-Zhong & Li, Hong-Yu, 2021. "A study on the bursting point of Bitcoin based on the BSADF and LPPLS methods," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    28. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    29. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    30. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    31. T. Kaizoji, 2006. "A precursor of market crashes: Empirical laws of Japan's internet bubble," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 123-127, March.
    32. Taisei Kaizoji, 2005. "A Precursor of Market Crashes," Papers physics/0510055, arXiv.org, revised Mar 2006.
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