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Does volatility in cryptocurrencies drive the interconnectedness between the cryptocurrencies market? Insights from wavelets

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Listed:
  • Samuel Kwaku Agyei
  • Anokye Mohammed Adam
  • Ahmed Bossman
  • Oliver Asiamah
  • Peterson Owusu Junior
  • Roberta Asafo-Adjei
  • Emmanuel Asafo-Adjei

Abstract

We present a multi-scale and time-frequency analysis of the degree of integration and the lead-lag relationship between six cryptocurrencies (i.e., Bitcoin, Bitcoincash, Ethereum, Litecoin, Ripple, and Tether) and the cryptocurrency-implied volatility index (VCRIX). As a result, the wavelet techniques—bi-wavelet, partial wavelet, bivariate contemporary correlations (BCC), wavelet multiple correlations (WMC) and wavelet multiple cross-correlations (WMCC) are applied. Findings from the study provide that the interdependencies between the cryptocurrencies and VCRIX are high and mostly positive across investment horizons. Furthermore, the comovements between the cryptocurrencies designate long memory dynamics. The high comovements between cryptocurrencies are highly influenced by idiosyncratic shocks they possess rather than the VCRIX. In addition, the BCC and the WMC indicate that there is a high integration among all the cryptocurrencies. Categorically, the VCRIX could not lead or lag the interdependencies among the cryptocurrencies in the WMCC analysis. Findings from the study, therefore, divulge that investing in a single or few cryptocurrencies is highly risky due to the adverse impact of the VCRIX on individual cryptocurrencies. In general, investors should effectively hedge against volatilities in the cryptocurrency markets due to the significant predictive ability of VCRIX as an effective proxy.

Suggested Citation

  • Samuel Kwaku Agyei & Anokye Mohammed Adam & Ahmed Bossman & Oliver Asiamah & Peterson Owusu Junior & Roberta Asafo-Adjei & Emmanuel Asafo-Adjei, 2022. "Does volatility in cryptocurrencies drive the interconnectedness between the cryptocurrencies market? Insights from wavelets," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2061682-206, December.
    • Handle: RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2061682
    DOI: 10.1080/23322039.2022.2061682
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    Citations

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    Cited by:

    1. Bossman, Ahmed & Gubareva, Mariya & Agyei, Samuel Kwaku & Vo, Xuan Vinh, 2024. "Time-frequency comovements between environmental cryptocurrency sentiment and faith-based sectoral stocks," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 699-719.
    2. Kingstone Nyakurukwa & Yudhvir Seetharam, 2023. "Higher moment connectedness of cryptocurrencies: a time-frequency approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 793-814, September.
    3. Bossman, Ahmed & Umar, Zaghum & Teplova, Tamara, 2022. "Modelling the asymmetric effect of COVID-19 on REIT returns: A quantile-on-quantile regression analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    4. Umar, Zaghum & Bossman, Ahmed & Choi, Sun-Yong & Vo, Xuan Vinh, 2023. "Are short stocks susceptible to geopolitical shocks? Time-Frequency evidence from the Russian-Ukrainian conflict," Finance Research Letters, Elsevier, vol. 52(C).
    5. Sayed Mohammad Mousavi & Yazdan Shahin Rad, 2023. "Challenges and Legal Aspects of Financing Projects Through Cryptocurrencies in Iran," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 13(4), pages 127-151.
    6. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    7. Ogunsanya, Ibukun & Wasiu Adamson, Temitope, 2024. "Exchange Rate Movement And Stock Returns In Most Capitalised Economies In Sub-Saharan Africa," Ilorin Journal of Economic Policy, Department of Economics, University of Ilorin, vol. 11(1), pages 18-37, June.
    8. Agyei, Samuel Kwaku & Umar, Zaghum & Bossman, Ahmed & Teplova, Tamara, 2023. "Dynamic connectedness between global commodity sectors, news sentiment, and sub-Saharan African equities," Emerging Markets Review, Elsevier, vol. 56(C).
    9. 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.
    10. Thobekile Qabhobho & Anokye M. Adam & Emmanuel Asafo-Adjei, 2023. "Do Local and International Shocks Matter in the Interconnectedness amid Exchange Rates and Energy Commodities? Insights into BRICS Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 666-678, November.
    11. 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.
    12. Thobekile Qabhobho & Anokye M. Adam & Anthony Adu-Asare Idun & Emmanuel Asafo-Adjei & Ebenezer Boateng, 2023. "Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 272-283, March.
    13. Chioma Nwosu Peace & Bosha Ernest Oryiman & Abubakar Ibrahim Sani, 2023. "Digital Currency and Financial Markets in Nigeria: Impact and Policy Implications," Financial Economics Letters, Anser Press, vol. 2(3), pages 22-36, December.
    14. Bossman, Ahmed & Agyei, Samuel Kwaku, 2022. "Interdependence structure of global commodity classes and African equity markets: A vector wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).

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