IDEAS home Printed from https://ideas.repec.org/a/arp/bmerar/2022p17-27.html
   My bibliography  Save this article

Can Digital Currencies Serve as Safe Havens in the Post-Covid Era?

Author

Listed:
  • A. Désiré Adom

    (Eastern Illinois University, Department of Economics, United States)

Abstract

The exponential growth of digital currencies in general and cryptocurrencies, in particular, has seemingly broken every record in the book. This has generated in the process a tremendous amount of interest in both developed and developing countries from scholars, academics, politicians, decision-makers and other stakeholders. Considering an applied methodology about asymmetric volatility with Exponential General Auto-regressive Conditional heteroscedasticity (EGARCH), this research work explores the fundamentals of the behavior of cryptocurrencies comparatively to a benchmark of key assets. To achieve its goal, this study uses two classes of assets. On the one hand, the first class (Class I) includes seven ?  Bitcoin, Ethereum, Binance, Dogecoin, Tether, Ripple, and Cardano ? of the top 10 cryptocurrencies, which, as of July 2021, commanded more than $1.5 trillion in market capitalization. On the other hand, the second class (Class II) is comprised of three traditionally established, well-known and “safe†assets, namely, gold, the 3-month US treasury bill and the 30-year US treasury bond. Using thousands of datapoints, empirical findings regarding volatilities, returns, clustering and leverage effects of the two asset classes do not reveal any startling contrasts to warrant an outright dismissal of crypto-assets as viable repositories of purchasing power and value. However, the pace in the move towards a full “safe haven†status will hinge upon the introduction of a clear regulatory and legislative framework in the US and other major countries to instill more confidence and certainty about crypto assets in a post-Covid era.

Suggested Citation

  • A. Désiré Adom, 2022. "Can Digital Currencies Serve as Safe Havens in the Post-Covid Era?," Business, Management and Economics Research, Academic Research Publishing Group, vol. 8(2), pages 17-27, 06-2022.
  • Handle: RePEc:arp:bmerar:2022:p:17-27
    DOI: 10.32861/bmer.82.17.27
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/bmer8(2)17-27.pdf
    Download Restriction: no

    File URL: https://www.arpgweb.com/journal/8/archive/06-2022/2/8
    Download Restriction: no

    File URL: https://libkey.io/10.32861/bmer.82.17.27?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
    ---><---

    References listed on IDEAS

    as
    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Gamba-Santamaria, Santiago & Gomez-Gonzalez, Jose Eduardo & Hurtado-Guarin, Jorge Luis & Melo-Velandia, Luis Fernando, 2017. "Stock market volatility spillovers: Evidence for Latin America," Finance Research Letters, Elsevier, vol. 20(C), pages 207-216.
    3. Steven E. Kozlowski & Michael R. Puleo & Jizhou Zhou, 2021. "Cryptocurrency return reversals," Applied Economics Letters, Taylor & Francis Journals, vol. 28(11), pages 887-893, June.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    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. Andrea Bucci, 2020. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 502-531.
    2. Zhao, Zifeng & Zhang, Zhengjun & Chen, Rong, 2018. "Modeling maxima with autoregressive conditional Fréchet model," Journal of Econometrics, Elsevier, vol. 207(2), pages 325-351.
    3. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.
    4. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Shogbuyi, Abiodun & Steeley, James M., 2017. "The effect of quantitative easing on the variance and covariance of the UK and US equity markets," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 281-291.
    6. Justice Matarutse, 2014. "Volatility characteristics of stocks underlying Exchange Traded Funds in South Africa," Journal of Economics and Behavioral Studies, AMH International, vol. 6(10), pages 829-839.
    7. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2016. "The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects," The Japanese Economic Review, Springer, vol. 67(3), pages 280-294, September.
    8. Tingting Cao & Weiqing Sun & Cuiping Sun & Lin Hao, 2022. "Unique futures in China: studys on volatility spillover effects of ferrous metal futures," Papers 2206.15039, arXiv.org.
    9. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    10. Runumi Das & Arabinda Debnath, 2022. "Analyzing the COVID-19 Pandemic Volatility Spillover Influence on the Collaboration of Foreign and Indian Stock Markets," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 14(2), pages 411-452, June.
    11. Walid Abass Mohammed, 2021. "Volatility Spillovers among Developed and Developing Countries: The Global Foreign Exchange Markets," JRFM, MDPI, vol. 14(6), pages 1-30, June.
    12. Apostolou, Apostolos & Beirne, John, 2017. "Volatility spillovers of Federal Reserve and ECB balance sheet expansions to emerging market economies," Working Paper Series 2044, European Central Bank.
    13. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    14. Allen, David E. & McAleer, Michael & Powell, Robert J. & Singh, Abhay K., 2017. "Volatility Spillovers from Australia's major trading partners across the GFC," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 159-175.
    15. Frankovic, Jozo & Liu, Bin & Suardi, Sandy, 2022. "On spillover effects between cryptocurrency-linked stocks and the cryptocurrency market: Evidence from Australia," Global Finance Journal, Elsevier, vol. 54(C).
    16. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    17. M. Hakan Eratalay & Evgenii V. Vladimirov, 2020. "Mapping the stocks in MICEX: Who is central in the Moscow Stock Exchange?," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 28(4), pages 581-620, October.
    18. Ziadat, Salem Adel & Herbst, Patrick & McMillan, David G., 2020. "Inter- and intra-regional stock market relations for the GCC bloc," Research in International Business and Finance, Elsevier, vol. 54(C).
    19. Leung, Henry & Schiereck, Dirk & Schroeder, Florian, 2017. "Volatility spillovers and determinants of contagion: Exchange rate and equity markets during crises," Economic Modelling, Elsevier, vol. 61(C), pages 169-180.
    20. Lumengo Bonga-Bonga & Tebogo Maake, 2021. "The Relationship between Carry Trade and Asset Markets in South Africa," JRFM, MDPI, vol. 14(7), pages 1-13, July.

    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:arp:bmerar:2022:p:17-27. 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/index.php?ic=journal&journal=8&info=aims .

    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.