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Connectedness between Gold and Cryptocurrencies in COVID-19 Pandemic: A Frequency-Dependent Asymmetric and Causality Analysis

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  • Zynobia Barson
  • Peterson Owusu Junior
  • Anokye M. Adam
  • Emmanuel Asafo-Adjei
  • Mariya Gubareva

Abstract

We employ a frequency-dependent asymmetric and causality analysis to investigate the connectedness between gold and cryptocurrencies during the COVID-19 pandemic. Hence, the variational mode decomposition-based quantile regression is utilised. Findings from the study divulge that the variational mode functions at the lower quantiles are mostly significant and negative indicating that gold acts as a safe haven, a diversifier at most market conditions with insignificant coefficients, and a hedge at normal market conditions for most cryptocurrencies at various investment horizons. Particularly, hedging benefits mostly occur in the short- and medium-term for Bitcoin and Ripple, as well as Bitcoin and Dogecoin in the long-term with gold. This implies that there is high persistence in the hedging properties of gold with Bitcoin, followed by Ripple. We notice more significant relationship between gold and some cryptocurrencies in the long-term of the COVID-19 pandemic relative to the medium-term emphasising the delayed responses of prices to information. Investors are recommended to be observant and mindful of investing in these markets due to the different dynamics.

Suggested Citation

  • Zynobia Barson & Peterson Owusu Junior & Anokye M. Adam & Emmanuel Asafo-Adjei & Mariya Gubareva, 2022. "Connectedness between Gold and Cryptocurrencies in COVID-19 Pandemic: A Frequency-Dependent Asymmetric and Causality Analysis," Complexity, Hindawi, vol. 2022, pages 1-17, April.
    • Handle: RePEc:hin:complx:7648085
    DOI: 10.1155/2022/7648085
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    Cited by:

    1. Thobekile Qabhobho, 2023. "Assessing the Asymmetric Effect of Local Realized Exchange Rate Volatility and Implied Volatilities in Energy Market on Exchange Rate Returns in BRICS," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 231-239, March.
    2. F. Leung & M. Law & S. K. Djeng, 2024. "Deterministic modelling of implied volatility in cryptocurrency options with underlying multiple resolution momentum indicator and non-linear machine learning regression algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    3. Kyei, Collins Baffour & Cantah, William Godfred & Junior Owusu, Peterson, 2023. "Effect of commodity prices on financial soundness; insight from adaptive market hypothesis in the Ghanaian setting," Resources Policy, Elsevier, vol. 86(PA).
    4. Ebenezer Boateng & Emmanuel Asafo-Adjei & John Gartchie Gatsi & ªtefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2022. "Multifrequency-based non-linear approach to analyzing implied volatility transmission across global financial markets," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 699-743, September.

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