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COVID-19 and the volatility interlinkage between bitcoin and financial assets

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  • Aktham Maghyereh

    (United Arab Emirates University)

  • Hussein Abdoh

    (The Citadel: The Military College of South Carolina)

Abstract

We investigate the effects of COVID-19 on volatility connectedness between bitcoin and five traditional financial assets from the gold, oil, foreign exchange, stock, and bond markets, employing high-frequency data. The empirical analyses are carried out using the wavelet coherence approach and dynamic frequency-domain connectedness method. Our results generally indicate that the volatility dynamics between bitcoin and the financial assets are weak or negative before the pandemic while they become positive during the pandemic times for most of the assets. Further, the volatility connectedness for bitcoin-gold and bitcoin-foreign exchange pairs is most significant in the short term, while it is significant in the intermediate term for bitcoin-oil and bitcoin-equity pairs during the pandemic. We examine optimal portfolios to hedge Bitcoin shocks at multiple investment horizons during the pandemic. We find that most of these financial assets perform as a good hedger against Bitcoin shocks in the short and long term but not in the medium term.

Suggested Citation

  • Aktham Maghyereh & Hussein Abdoh, 2022. "COVID-19 and the volatility interlinkage between bitcoin and financial assets," Empirical Economics, Springer, vol. 63(6), pages 2875-2901, December.
    • Handle: RePEc:spr:empeco:v:63:y:2022:i:6:d:10.1007_s00181-022-02223-7
    DOI: 10.1007/s00181-022-02223-7
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    3. Dora Almeida & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2023. "Impact of the COVID-19 Pandemic on Cryptocurrency Markets: A DCCA Analysis," FinTech, MDPI, vol. 2(2), pages 1-17, May.
    4. Karol Szafranek & Michał Rubaszek & Gazi Salah Uddin, 2023. "The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets," KAE Working Papers 2023-095, Warsaw School of Economics, Collegium of Economic Analysis.
    5. Yen, Kuang-Chieh & Nie, Wei-Ying & Chang, Hsuan-Ling & Chang, Li-Han, 2023. "Cryptocurrency return dependency and economic policy uncertainty," Finance Research Letters, Elsevier, vol. 56(C).
    6. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    7. Li Wei & Ming-Chih Lee & Wan-Hsiu Cheng & Chia-Hsien Tang & Jing-Wun You, 2023. "Evaluating the Efficiency of Financial Assets as Hedges against Bitcoin Risk during the COVID-19 Pandemic," Mathematics, MDPI, vol. 11(13), pages 1-19, June.
    8. Mutaju Isaack Marobhe & Jonathan Mukiza Peter Kansheba, 2023. "High frequency volatility spillover between oil and non-energy commodities during crisis and tranquil periods," SN Business & Economics, Springer, vol. 3(4), pages 1-27, April.
    9. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2022. "Bitcoin Prices and the Realized Volatility of US Sectoral Stock Returns," Working Papers 202224, University of Pretoria, Department of Economics.
    10. Di, Michael & Xu, Ke, 2022. "COVID-19 vaccine and post-pandemic recovery: Evidence from Bitcoin cross-asset implied volatility spillover," Finance Research Letters, Elsevier, vol. 50(C).
    11. Qiao, Xingzhi & Zhu, Huiming & Zhang, Zhongqingyang & Mao, Weifang, 2022. "Time-frequency transmission mechanism of EPU, investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
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    More about this item

    Keywords

    COVID-19; Wavelet coherence; Volatility interdependence; Bitcoin; Dynamic Frequency-domain connectedness;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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