Regime switching and causal network analysis of cryptocurrency volatility: evidence from pre-COVID and post-COVID analysis

Parthajit Kayal () and Sumanjay Dutta
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Parthajit Kayal: Madras School of Economics (MSE), Behind Government Data Centre
Sumanjay Dutta: Indian Institute of Science

Digital Finance, 2024, vol. 6, issue 2, No 5, 319-340

Abstract: Abstract This paper investigates the volatility dynamics of Bitcoin, Ethereum, and Litecoin both before and after the COVID-19 pandemic. Employing an asymmetric two-state MS-MGARCH model, we identify a regime change in their volatility dynamics, providing a foundation for examining pre- and post-COVID volatility spillovers. Using the BEKK-GARCH model, we statistically confirm a spillover and quantify the correlation strength among the cryptocurrencies through the Windowed Scalogram Difference approach. Additionally, the cross-quantilogram approach is utilized to identify potential causal networks among the cryptocurrencies. The study unveils bidirectional shock transmission and volatility spillovers between Bitcoin and Ethereum, as well as Bitcoin and Litecoin, underscoring their interconnected nature. Furthermore, bidirectional volatility connections between Litecoin and Ethereum are uncovered. These findings enhance our comprehension of cryptocurrency volatility, emphasizing the influence of historical shocks and prior volatility on present dynamics. The study has practical implications for investors, traders, and policymakers, offering valuable insights for risk management in the cryptocurrency market, thus contributing to the advancement of knowledge in cryptocurrency dynamics and supporting more informed decision-making in this continually evolving financial landscape.

Keywords: Volatility; Cryptocurrencies; COVID-19; Spillovers; Correlation; Causal networks (search for similar items in EconPapers)
JEL-codes: C32 G15 G17 G41 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42521-023-00104-x

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