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Volatility changes in cryptocurrencies: evidence from sparse VHAR-MGARCH model

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  • Seungwon Lee
  • Changryong Baek

Abstract

This study examines the volatility changes of 20 cryptocurrencies from January 2018 to May 2021 using sparse VHAR-MGARCH model. Our proposed model incorporates the high-dimensionality and time-varying conditional heterogeneity of cryptocurrency markets. We examined the time-varying spillover index, dynamic correlation structure, and connectivity between cryptocurrencies. Our empirical analysis clearly shows that there was a volatility shift on 13 March 2020, due to a market crash caused by COVID-19. This naturally divides the data into three periods: pre-crisis, during the crisis, and post-crisis regimes. The pre-crisis regime exhibited long-term cyclic fluctuations in the spillover index. However, after the market crash, the spillover index remained at a very high level with almost no interconnections between cryptocurrencies. The post-crisis regime showed quite a few irregular and sharp spikes in the spillover index, together with record-breaking prices and volumes.

Suggested Citation

  • Seungwon Lee & Changryong Baek, 2023. "Volatility changes in cryptocurrencies: evidence from sparse VHAR-MGARCH model," Applied Economics Letters, Taylor & Francis Journals, vol. 30(11), pages 1496-1504, June.
    • Handle: RePEc:taf:apeclt:v:30:y:2023:i:11:p:1496-1504
    DOI: 10.1080/13504851.2022.2064417
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