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The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods

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  • Nguyen, Khanh Quoc

Abstract

This research examined the impact of the stock market on Bitcoin during COVID-19 and other uncertainty periods. Based on the quantile regression results, during periods of high uncertainty, such as COVID-19, the S&P 500 returns significantly affected Bitcoin returns. Moreover, this research applied the VAR (1)–GARCH (1, 1) model to investigate the spillover effect from the stock market to Bitcoin. According to the findings, the shocks from the stock market also influenced Bitcoin's volatility during COVID-19 and other periods of turmoil.

Suggested Citation

  • Nguyen, Khanh Quoc, 2022. "The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods," Finance Research Letters, Elsevier, vol. 46(PA).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pa:s1544612321003238
    DOI: 10.1016/j.frl.2021.102284
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    Cited by:

    1. Ovidiu-Constantin BUNGET & Georgiana-Iulia LAZEA (TRIFA), 2023. "Comparative Analysis Cryptocurrencies Versus Stocks," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 4(11), pages 49-65, November.
    2. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2024. "A Bayesian approach for the determinants of bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 91(C).
    3. Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Lee, Yen-Sheng & Vo, Ace & Chapman, Thomas A., 2022. "Examining the Maturity of Bitcoin Price through a Catastrophic Event: The Case of Structural Break Analysis During the COVID-19 Pandemic," Finance Research Letters, Elsevier, vol. 49(C).
    5. Wu, Xiangling & Ding, Shusheng, 2023. "The impact of the Bitcoin price on carbon neutrality: Evidence from futures markets," Finance Research Letters, Elsevier, vol. 56(C).
    6. Li, Shi, 2022. "Spillovers between Bitcoin and Meme stocks," Finance Research Letters, Elsevier, vol. 50(C).
    7. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
    8. Apostolos Ampountolas, 2023. "The Effect of COVID-19 on Cryptocurrencies and the Stock Market Volatility -- A Two-Stage DCC-EGARCH Model Analysis," Papers 2307.09137, arXiv.org.
    9. Luca Mungo & Silvia Bartolucci & Laura Alessandretti, 2023. "Cryptocurrency co-investment network: token returns reflect investment patterns," Papers 2301.02027, arXiv.org, revised Jan 2023.
    10. Lioba Heimbach & Vabuk Pahari & Eric Schertenleib, 2024. "Non-Atomic Arbitrage in Decentralized Finance," Papers 2401.01622, arXiv.org, revised Apr 2024.
    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. 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.

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    More about this item

    Keywords

    Bitcoin; Uncertainty; Conditional variance; COVID-19; Safe-haven;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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