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High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis

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  • Katsiampa, Paraskevi
  • Yarovaya, Larisa
  • Zięba, Damian

Abstract

In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-tradable crypto assets using high-frequency data for the period from January 2019 to December 2020. We apply the Diagonal-BEKK model to data from the pre-COVID and COVID-19 periods, and identify significant changes in patterns of co-movements and correlations during the pandemic period. We also employ the Minimum Spanning Tree (MST) and Planar Maximally Filtered Graph (PMFG) methods to study the changes of the crypto asset network structure after the COVID-19 outbreak. While the influential role of Bitcoin in the digital asset ecosystem has been confirmed, our novel findings reveal that due to recent developments in the blockchain ecosystem, crypto assets that can be categorised as dApps and protocols have become more attractive to investors than pure cryptocurrencies.

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  • Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:intfin:v:79:y:2022:i:c:s1042443122000610
    DOI: 10.1016/j.intfin.2022.101578
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    Cited by:

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    3. Zhao, Yuan & Liu, Nan & Li, Wanpeng, 2022. "Industry herding in crypto assets," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    5. Zarifhonarvar, Ali, 2022. "The Effect of Covid Pandemic on Cryptocurrency Markets; A Literature Review," EconStor Preprints 266369, ZBW - Leibniz Information Centre for Economics.
    6. Yousaf, Imran & Yarovaya, Larisa, 2022. "The relationship between trading volume, volatility and returns of Non-Fungible Tokens: evidence from a quantile approach," Finance Research Letters, Elsevier, vol. 50(C).
    7. Ali, Shoaib & Ijaz, Muhammad Shahzad & Yousaf, Imran, 2023. "Dynamic spillovers and portfolio risk management between defi and metals: Empirical evidence from the Covid-19," Resources Policy, Elsevier, vol. 83(C).
    8. Chen, Ning & Li, Shaofang & Lu, Shuai, 2023. "The extreme risk connectedness of the global financial system: G7 and BRICS evidence," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    9. Rehman, Mobeen Ur & Katsiampa, Paraskevi & Zeitun, Rami & Vo, Xuan Vinh, 2023. "Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies," Emerging Markets Review, Elsevier, vol. 55(C).
    10. 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.
    11. Ivanovski, Kris & Hailemariam, Abebe, 2023. "Forecasting the stock-cryptocurrency relationship: Evidence from a dynamic GAS model," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 97-111.
    12. Chancharat, Surachai & Sinlapates, Parichat, 2023. "Dependences and dynamic spillovers across the crude oil and stock markets throughout the COVID-19 pandemic and Russia-Ukraine conflict: Evidence from the ASEAN+6," Finance Research Letters, Elsevier, vol. 57(C).

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    More about this item

    Keywords

    COVID-19; High-frequency co-movements; Bitcoin; Protocols; Cryptocurrencies;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G1 - Financial Economics - - General Financial Markets

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