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

Seungwon Lee and Changryong Baek

Applied Economics Letters, 2023, vol. 30, issue 11, 1496-1504

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.

Date: 2023
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DOI: 10.1080/13504851.2022.2064417

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