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The COVID-19 effects on cryptocurrency markets: robust evidence from time-frequency analysis

Author

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  • Ngo Thai Hung

    (University of Finance-Marketing)

Abstract

This study contributes to the related literature on the COVID-cryptocurrency relationship by examining its dynamics in the time-frequency space. The application of wavelet frameworks to the news-based COVID-19 sentiment index introduced by Buckman et al. (2020) is what distinguishes our approach. Our empirical results suggest a bidirectional relationship between the two variables in the short and medium run. Specifically, negative co-movement between them was found during the COVID-19 crisis. In addition, the COVID-19 sentiment index has a higher causal effect and a significant connection with the selected cryptocurrency prices. News-based sentiment indexes can provide fresh insight into future developments in the cryptocurrency markets.

Suggested Citation

  • Ngo Thai Hung, 2022. "The COVID-19 effects on cryptocurrency markets: robust evidence from time-frequency analysis," Economics Bulletin, AccessEcon, vol. 42(1), pages 109-123.
    • Handle: RePEc:ebl:ecbull:eb-21-00769
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    References listed on IDEAS

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    1. Mnif, Emna & Jarboui, Anis & Mouakhar, Khaireddine, 2020. "How the cryptocurrency market has performed during COVID 19? A multifractal analysis," Finance Research Letters, Elsevier, vol. 36(C).
    2. Ghulame Rubbaniy & Ali Awais Khalid & Aristeidis Samitas, 2021. "Are Cryptos Safe-Haven Assets during Covid-19? Evidence from Wavelet Coherence Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(6), pages 1741-1756, May.
    3. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    4. Hee Soo Lee, 2020. "Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    5. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    6. Pradipta Kumar Sahoo, 2021. "COVID-19 pandemic and cryptocurrency markets: an empirical analysis from a linear and nonlinear causal relationship," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 38(2), pages 454-468, March.
    7. 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).
    8. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    9. van der Wielen, Wouter & Barrios, Salvador, 2021. "Economic sentiment during the COVID pandemic: Evidence from search behaviour in the EU," Journal of Economics and Business, Elsevier, vol. 115(C).
    10. Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    11. Olaolu Richard Olayeni, 2016. "Causality in Continuous Wavelet Transform Without Spectral Matrix Factorization: Theory and Application," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 321-340, March.
    12. Corbet, Shaen & Larkin, Charles & Lucey, Brian, 2020. "The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies," Finance Research Letters, Elsevier, vol. 35(C).
    13. Lahmiri, Salim & Bekiros, Stelios, 2020. "The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    14. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    15. Umar, Zaghum & Gubareva, Mariya & Teplova, Tamara, 2021. "The impact of Covid-19 on commodity markets volatility: Analyzing time-frequency relations between commodity prices and coronavirus panic levels," Resources Policy, Elsevier, vol. 73(C).
    16. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
    17. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    18. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    19. Hung, Ngo Thai & Vo, Xuan Vinh, 2021. "Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 76(C).
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    1. Osman, Myriam Ben & Urom, Christian & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Economic sentiment and the cryptocurrency market in the post-COVID-19 era," International Review of Financial Analysis, Elsevier, vol. 91(C).

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    More about this item

    Keywords

    COVID-19; cryptocurrency markets; wavelet analysis; news-based sentiment index.;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets

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