IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v607y2022ics0378437122007762.html
   My bibliography  Save this article

The resilience of cryptocurrency market efficiency to COVID-19 shock

Author

Listed:
  • Fernandes, Leonardo H.S.
  • Bouri, Elie
  • Silva, José W.L.
  • Bejan, Lucian
  • de Araujo, Fernando H.A.

Abstract

We examine the price disorder and informational efficiency of five cryptocurrencies (Bitcoin, BNB, Cardano, Ethereum, and XRP) before and during the COVID-19 pandemic. In this sense, we estimate the permutation entropy and Fisher information measure (FIM). We use these complexity measures to construct the Shannon–Fisher causality plane (SFCP) to map these cryptocurrencies and their respective locations in a two-dimensional plane and then apply the sliding time window approach to study the temporal evolution of informational efficiency. All cryptocurrencies exhibit high but slightly varying informational efficiency during both periods. Cardano was the most efficient cryptocurrency. These results might point to the increasing maturity and lower potential for price predictability, which matter to cryptocurrencies’ usage for liquidity risk diversification strategy.

Suggested Citation

  • Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007762
    DOI: 10.1016/j.physa.2022.128218
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122007762
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.128218?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tiwari, Aviral Kumar & Jana, R.K. & Das, Debojyoti & Roubaud, David, 2018. "Informational efficiency of Bitcoin—An extension," Economics Letters, Elsevier, vol. 163(C), pages 106-109.
    2. Xiang Wu & Liang Wu & Shujuan Chen, 2022. "Long memory and efficiency of Bitcoin during COVID-19," Applied Economics, Taylor & Francis Journals, vol. 54(4), pages 375-389, January.
    3. 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.
    4. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    5. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    6. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    7. Higor Y. D. Sigaki & Matjaz Perc & Haroldo V. Ribeiro, 2019. "Clustering patterns in efficiency and the coming-of-age of the cryptocurrency market," Papers 1901.04967, arXiv.org.
    8. Leonardo H. S. Fernandes & Fernando H. A. De Araujo & Jos㉠W. L. Silva & Igor E. M. Silva & Benjamin Miranda Tabak, 2022. "Evaluating The Efficiency Of Brazilian Stock Market Indices: The Case Of Covid-19," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(01), pages 1-11, February.
    9. Vidal-Tomás, David & Ibañez, Ana, 2018. "Semi-strong efficiency of Bitcoin," Finance Research Letters, Elsevier, vol. 27(C), pages 259-265.
    10. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    11. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    12. Akihiko Noda, 2021. "On the evolution of cryptocurrency market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 28(6), pages 433-439, March.
    13. Kakinaka, Shinji & Umeno, Ken, 2022. "Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: An asymmetric multifractal analysis approach," Finance Research Letters, Elsevier, vol. 46(PA).
    14. Aurelio F. Bariviera & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "A permutation Information Theory tour through different interest rate maturities: the Libor case," Papers 1509.00217, arXiv.org.
    15. Nguyen, Khanh Quoc, 2022. "The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods," Finance Research Letters, Elsevier, vol. 46(PA).
    16. Scharnowski, Stefan, 2021. "Understanding Bitcoin liquidity," Finance Research Letters, Elsevier, vol. 38(C).
    17. Werner Kristjanpoller & Leonardo H. S. Fernandes & Benjamin M. Tabak, 2022. "Examining The Fractal Market Hypothesis Considering Daily And High Frequency For Cryptocurrency Assets," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(03), pages 1-20, May.
    18. Aurelio F. Bariviera & Luciano Zunino & Osvaldo A. Rosso, 2018. "An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers," Papers 1808.01926, arXiv.org.
    19. Ustaoglu, Erkan, 2022. "Safe-haven properties and portfolio applications of cryptocurrencies: Evidence from the emerging markets," Finance Research Letters, Elsevier, vol. 47(PB).
    20. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    21. Ghabri, Yosra & Guesmi, Khaled & Zantour, Ahlem, 2021. "Bitcoin and liquidity risk diversification," Finance Research Letters, Elsevier, vol. 40(C).
    22. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    23. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    24. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    25. Shahzad, Syed Jawad Hussain & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2019. "Is Bitcoin a better safe-haven investment than gold and commodities?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 322-330.
    26. Ghassan Dibeh & Haidar Harmanani, 2012. "A Stochastic Chartist–Fundamentalist Model with Time Delays," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 105-113, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sayed Mohammad Mousavi & Yazdan Shahin Rad, 2023. "Challenges and Legal Aspects of Financing Projects Through Cryptocurrencies in Iran," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 13(4), pages 127-151.
    2. Zarifhonarvar, Ali, 2022. "The Effect of Covid Pandemic on Cryptocurrency Markets; A Literature Review," EconStor Preprints 266369, ZBW - Leibniz Information Centre for Economics.
    3. Ghosh, Bikramaditya & Bouri, Elie & Wee, Jung Bum & Zulfiqar, Noshaba, 2023. "Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs," Research in International Business and Finance, Elsevier, vol. 65(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    3. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    4. Fernandes, Leonardo H.S. & de Araujo, Fernando H.A. & Silva, José W.L. & Tabak, Benjamin Miranda, 2022. "Booms in commodities price: Assessing disorder and similarity over economic cycles," Resources Policy, Elsevier, vol. 79(C).
    5. Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
    6. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Pal, Debdatta & Mitra, Subrata K., 2019. "Hedging bitcoin with other financial assets," Finance Research Letters, Elsevier, vol. 30(C), pages 30-36.
    8. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    9. Mensi, Walid & Ur Rehman, Mobeen & Maitra, Debasish & Hamed Al-Yahyaee, Khamis & Sensoy, Ahmet, 2020. "Does bitcoin co-move and share risk with Sukuk and world and regional Islamic stock markets? Evidence using a time-frequency approach," Research in International Business and Finance, Elsevier, vol. 53(C).
    10. Mensi, Walid & Sensoy, Ahmet & Aslan, Aylin & Kang, Sang Hoon, 2019. "High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    11. 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.
    12. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.
    13. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    14. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    15. Al-Nassar, Nassar S. & Boubaker, Sabri & Chaibi, Anis & Makram, Beljid, 2023. "In search of hedges and safe havens during the COVID─19 pandemic: Gold versus Bitcoin, oil, and oil uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 318-332.
    16. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    17. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Masih, Mansur, 2022. "COVID-19 government interventions and cryptocurrency market: Is there any optimum portfolio diversification?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    18. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    19. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    20. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007762. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.