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How the Cryptocurrency Market Has Performed during COVID 19? A Multifractal Analysis

Author

Listed:
  • E. Mnif

    (LARTIGE - Laboratoire de recherche en Technologie de l’Information, Gouvernance et Entrepreneuriat - Université de Sfax - University of Sfax)

  • A. Jarboui

    (Université de Sfax - University of Sfax)

  • K. Mouakhar

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

Abstract

Cryptocurrency markets are complex systems based on speculation. Where investors interact using strategies that generate some biases responsible for endogenous instabilities. This paper investigated the herding biases by quantifying the self-similarity intensity of cryptocurrency returns' during the COVID-19 pandemic. The main purpose of this work was to study the level of cryptocurrency efficiency through multifractal analysis before and after the coronavirus pandemic. The empirical results proved that COVID-19 has a positive impact on the cryptocurrency market efficiency. © 2020 Elsevier Inc.

Suggested Citation

  • E. Mnif & A. Jarboui & K. Mouakhar, 2020. "How the Cryptocurrency Market Has Performed during COVID 19? A Multifractal Analysis," Post-Print hal-04457136, HAL.
    • Handle: RePEc:hal:journl:hal-04457136
    DOI: 10.1016/j.frl.2020.101647
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    Citations

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    Cited by:

    1. Saji Thazhungal Govindan Nair, 2021. "On extreme value theory in the presence of technical trend: pre and post Covid-19 analysis of cryptocurrency markets," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 14(4), pages 533-561, December.
    2. Amel Farhat & Amal Hili, 2024. "The performance of compliant stocks during the Covid-19 crisis," Journal of Asset Management, Palgrave Macmillan, vol. 25(1), pages 70-95, February.
    3. Efstathios Polyzos & Ghulame Rubbaniy & Mieszko Mazur, 2024. "Efficient Market Hypothesis on the blockchain: A social‐media‐based index for cryptocurrency efficiency," The Financial Review, Eastern Finance Association, vol. 59(3), pages 807-829, August.
    4. Bouteska, Ahmed & Abedin, Mohammad Zoynul & Hajek, Petr & Yuan, Kunpeng, 2024. "Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods," International Review of Financial Analysis, Elsevier, vol. 92(C).
    5. Liu, Jian & Julaiti, Jiansuer & Gou, Shangde, 2024. "Decomposing interconnectedness: A study of cryptocurrency spillover effects in global financial markets," Finance Research Letters, Elsevier, vol. 61(C).
    6. Kai Meng & Khalid Khan, 2024. "Is cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2225-2246, June.
    7. Xinyu Huang & Weihao Han & David Newton & Emmanouil Platanakis & Dimitrios Stafylas & Charles Sutcliffe, 2023. "The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 800-825, May.
    8. dos Santos Maciel, Leandro, 2023. "Brazilian stock-market efficiency before and after COVID-19: The roles of fractality and predictability," Global Finance Journal, Elsevier, vol. 58(C).

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