Purpose – This study aims to reassess the dynamics of major cryptocurrencies sur-rounding recent economic and geopolitical events. By employing wavelet analysis and quantile regression methods, it seeks to understand the behavior of cryptocurrencies before, during, and after the COVID-19 pandemic. Research methodology – This research employs the Least Asymmetric Daubechies (LA8) wavelet function to decompose log-returns of major cryptocurrencies into various frequency scales. Additionally, it utilizes wavelet coherence and quantile-on-quantile regression techniques to analyze daily price data spanning from July 2017 to May 2024. Findings – The findings reveal a strong long-term association among cryptocurrencies, with a decline in medium-term correlations. Bitcoin exhibits synchronization with major cryptocurrencies, excluding Tether, while BTC-ETH and BTC-BNB display a rapid, interconnected behavior alongside their fundamental links. Moreover, empirical evidence indicates Bitcoin’s heterogeneous nexus with other alternatives, showcasing greater sensitivity to positive extremes over negative ones. Research limitations – The study’s scope is delimited by the selected time frame (July 2017 to May 2024) for data analysis, potentially limiting insights into longer-term trends. Additionally, the reliance on specific methodologies like wavelet analysis might introduce constraints in capturing the entirety of cryptocurrency dynamics, leaving room for alternative interpretations or unexplored aspects. Practical implications – Results suggest that understanding the varying correlations among major cryptocurrencies during different market phases could aid investors and policymakers in devising more nuanced strategies. Recognizing the sensitivity of Bitcoin’s connections with alternatives to market trends could inform risk management approaches, particularly in navigating extreme market conditions. Originality/Value – The originality of this study lies in its comprehensive examination of cryptocurrency dynamics across varying time scales, utilizing wavelet analysis and quantile regression techniques. The findings offer valuable insights into the complex interconnections among cryptocurrencies, especially in terms of their sensitivity to different market conditions, providing a nuanced perspective for investors, analysts, and policymakers navigating the crypto landscape.
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