Extreme frequency connectedness, determinants and portfolio analysis of major cryptocurrencies: insights from quantile time-frequency approach
Date
2025
Authors
Bhattacherjee, P.
Mishra, S.
Kang, S.H.
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Journal article
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Quarterly Review of Economics and Finance, 2025; 100:1-27
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The study examines the extreme time-frequency connectedness among 12 major cryptocurrencies for the period from February 26, 2018, to February 6, 2024. We employ the novel TVP-VAR approach proposed by Chatziantoniou et al. (2022), and three portfolio construction methods (i.e., MVP, MCP and MCoP). The results reveal interesting insights. First, it unveils the diverse sensitivities of individual cryptocurrencies to total return shocks, with short-term events exerting a predominant influence compared to long-term shocks.
Notably, most cryptocurrencies act as net transmitters of shocks, reflecting their susceptibility to external market fluctuations. Second, the variations in the behavior of cryptocurrencies are observed during extreme market conditions and crisis periods, such as the COVID-19 pandemic and the Russia-Ukraine conflict. Furthermore, the outcomes of the portfolio construction process provide light on the efficacy of hedging as well as the performance of the portfolio. Notably, the minimum correlation portfolio (MCP) strategy outperforms other techniques, highlighting its superiority in terms of optimizing portfolio performance.
Lastly, we report that macroeconomic factors and asset-based volatility are the significant drivers of cryptocurrency contagion. However, the degree and direction of their impact vary across market conditions and time-frequency horizons. These findings have important policy ramifications since they point to the necessity of strong regulatory frameworks and risk management techniques to reduce systemic risks and protect the financial stability of the bitcoin market.
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Copyright 2025 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.