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Cryptocurrencies, Diversification and the COVID-19 Pandemic

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  • Allen, David

Abstract

The paper features an analysis of cryptocurrencies and the impact of the COVID- 19 pandemic on their effectiveness as a portfolio diversification tool. It does so by exploring the correlations between the continuously compounded returns on Bitcoin, Ethereum and the S&P500 Index, using a variety of parametric and non-parametric techniques. These methods include linear standard metrics such as the application of ordinary least squares regression (OLS) and the Pearson, Spearman, and Kendall's tau measures of association. In addition, nonlinear, non-parametric measures such as the Generalised Measure of Correlation (GMC), and non-parametric copula estimates are applied. The results across this range of measures are consistent. The metrics suggest that whilst the shock of the COVID-18 pandemic does not appear to have increased the correlations between the crypto currency series, it does appear to have increased the correlations between the returns on crypto currencies and those on the S&P500 Index. This suggests that investment in cryptocurrencies is not likely to offer key diversification strategies in times of crisis, on the basis of evidence provided by this crisis

Suggested Citation

  • Allen, David, 2021. "Cryptocurrencies, Diversification and the COVID-19 Pandemic," MPRA Paper 111735, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:111735
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    Cited by:

    1. Hrishikesh Vinod, 2023. "Causality Estimation in Panel Data," Fordham Economics Discussion Paper Series dp2023-09er:dp2023-09, Fordham University, Department of Economics.
    2. Xu, Lei & Kinkyo, Takuji, 2023. "Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    3. Marcin Wątorek & Jarosław Kwapień & Stanisław Drożdż, 2022. "Multifractal Cross-Correlations of Bitcoin and Ether Trading Characteristics in the Post-COVID-19 Time," Future Internet, MDPI, vol. 14(7), pages 1-15, July.
    4. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    5. Ivan Mužić & Ivan Gržeta, 2022. "Expectations of Macroeconomic News Announcements: Bitcoin vs. Traditional Assets," Risks, MDPI, vol. 10(6), pages 1-15, June.
    6. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2022. "Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time," Papers 2208.01445, arXiv.org.

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    More about this item

    Keywords

    Bitcoin; Ethereum; Copula; kernel estimation; non-parametric; GMC;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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