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The Effect of COVID-19 on Cryptocurrencies and the Stock Market Volatility: A Two-Stage DCC-EGARCH Model Analysis

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  • Apostolos Ampountolas

    (School of Hospitality Administration, Boston University, Boston, MA 02215, USA
    Department of Mathematics, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge UB8 3PH, UK)

Abstract

This research examines the correlations between the return volatility of cryptocurrencies, global stock market indices, and the spillover effects of the COVID-19 pandemic. For this purpose, we employed a two-stage multivariate volatility exponential GARCH (EGARCH) model with an integrated dynamic conditional correlation (DCC) approach to measure the impact on the financial portfolio returns from 2019 to 2020. Moreover, we used value-at-risk (VaR) and value-at-risk measurements based on the Cornish–Fisher expansion (CFVaR). The empirical results show significant long- and short-term spillover effects. The two-stage multivariate EGARCH model’s results show that the conditional volatilities of both asset portfolios surge more after positive news and respond well to previous shocks. As a result, financial assets have low unconditional volatility and the lowest risk when there are no external interruptions. Despite the financial assets’ sensitivity to shocks, they exhibit some resistance to fluctuations in market confidence. The VaR performance comparison results with the assets portfolios differ. During the COVID-19 outbreak, the Dow (DJI) index reports VaR’s highest loss, followed by the S&P500. Conversely, the CFVaR reports negative risk results for the entire cryptocurrency portfolio during the pandemic, except for the Ethereum (ETH).

Suggested Citation

  • Apostolos Ampountolas, 2023. "The Effect of COVID-19 on Cryptocurrencies and the Stock Market Volatility: A Two-Stage DCC-EGARCH Model Analysis," JRFM, MDPI, vol. 16(1), pages 1-17, January.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:1:p:25-:d:1022549
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    References listed on IDEAS

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    1. Uddin, Gazi Salah & Yahya, Muhammad & Goswami, Gour Gobinda & Lucey, Brian & Ahmed, Ali, 2022. "Stock market contagion during the COVID-19 pandemic in emerging economies," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 302-309.
    2. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    5. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    6. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    7. Kejia Yan & Huqin Yan & Rakesh Gupta, 2022. "Are GARCH and DCC Values of 10 Cryptocurrencies Affected by COVID-19?," JRFM, MDPI, vol. 15(3), pages 1-25, March.
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    Cited by:

    1. Mukul Bhatnagar & Sanjay Taneja & Ramona Rupeika-Apoga, 2023. "Demystifying the Effect of the News (Shocks) on Crypto Market Volatility," JRFM, MDPI, vol. 16(2), pages 1-16, February.
    2. Apostolos Ampountolas, 2023. "Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models: Evidence from European Financial Markets and Bitcoins," Forecasting, MDPI, vol. 5(2), pages 1-15, June.
    3. Apostolos Ampountolas, 2023. "Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models Evidence from European Financial Markets and Bitcoins," Papers 2307.08853, arXiv.org.

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