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Interlinkages of cryptocurrency and stock markets during COVID-19 pandemic by applying a TVP-VAR extended joint connected approach

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  • Le Thanh Ha

Abstract

Purpose - The purpose of this paper is to study the interlinkages between the cryptocurrency and stock market by characterizing their connectedness starting from January 1, 2018 to December 31, 2021. Design/methodology/approach - The author employs a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach. Findings - The pandemic shocks appear to have influences on the system-wide dynamic connectedness, which reaches a peak during the COVID-19 pandemic. Net total directional connectedness suggests that each cryptocurrency and stock have a heterogeneous role, conditional on their internal characteristics and external shocks. In particular, Bitcoin and Binance Coin are reported as the net receiver of shocks, while the role of Ethereum shifts from receivers to transmitters. As for the stock market, the US stock market stays persistent as net transmitters of shocks, while the Asian stock market (including Hong Kong and Shanghai) are the two consistent net receivers. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the impact most severe at the beginning of 2020. Practical implications - Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value - The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages among these two markets. The author employs the TVP-VAR combined with an extended joint connectedness approach.

Suggested Citation

  • Le Thanh Ha, 2022. "Interlinkages of cryptocurrency and stock markets during COVID-19 pandemic by applying a TVP-VAR extended joint connected approach," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(3), pages 407-428, March.
  • Handle: RePEc:eme:jespps:jes-01-2022-0055
    DOI: 10.1108/JES-01-2022-0055
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Zhao, Xin & Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Vasa, László & Shahzad, Umer, 2023. "Interoperability of the revolutionary blockchain architectures and Islamic and conventional technology markets: Case of Metaverse, HPB, and Bloknet," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 112-131.
    2. Mei-jun, Ling & Guang-xi, Cao, 2024. "Dynamics of asymmetric multifractal cross-correlations between cryptocurrencies and global stock markets: Role of gold and portfolio implications," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    3. Mishra, Aswini Kumar & Arunachalam, Vairam & Olson, Dennis & Patnaik, Debasis, 2023. "Dynamic connectedness in commodity futures markets during Covid-19 in India: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 82(C).
    4. Ha, Le Thanh, 2024. "Dynamic spill-over influences of FinTech innovation development on renewable energy volatility during the time of war in pandemic: A novel insight from a wavelet model," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 515-529.

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    More about this item

    Keywords

    Stock market; COVID-19 pandemic; Cryptocurrency; TVP-VAR; Dynamic connectedness; Joint connectedness; C32; F3; G12; Q43;
    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
    • F3 - International Economics - - International Finance
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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