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Quantile analysis of Bitcoin returns: uncovering market dynamics

Author

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  • Monia Antar

Abstract

Purpose - This study delves into Bitcoin’s return dynamics to address its pronounced volatility, particularly in extreme market conditions. We analyze a broad range of explanatory variables, including traditional financial indicators, innovative cryptocurrency-specific metrics and market sentiment gauges. We uniquely introduce the Conference Board Leading Economic Indicator (LEI) to the cryptocurrency research landscape. Design/methodology/approach - We employ quantile regression to examine Bitcoin’s daily and monthly returns. This approach captures timescale dependencies and evaluates the consistency of our findings across different market conditions. By conducting a thorough analysis of the entire return distribution, we aim to reveal how various factors influence Bitcoin’s behavior at different risk levels. The research incorporates a comprehensive set of explanatory variables to provide a holistic view of Bitcoin’s market dynamics. Additionally, by segmenting the study period, we assess the consistency of the results across diverse market regimes. Findings - Our results reveal that factors driving Bitcoin returns vary significantly across market conditions. For instance, during downturns, an increase in transaction volume is linked to lower Bitcoin returns, potentially indicating panic selling. When the market stabilizes, a positive correlation emerges, suggesting healthier ecosystem activity. Active addresses emerge as a key predictor of returns, especially during bearish phases, and sentiment indicators such as Wikipedia views reveal shifting investor optimism, depending on market trends. Monthly return analysis suggests Bitcoin might act as a hedge against traditional markets due to its negative correlation with the S&P 500 during normal conditions. Practical implications - The study’s findings have significant implications for investors and policymakers. Understanding how different factors influence Bitcoin returns in varying market conditions can guide investment strategies and regulatory approaches. Originality/value - A novel contribution of this study is the identification of Bitcoin’s sensitivity to broader economic downturns as demonstrated by the negative correlation between LEI and returns. These insights not only deepen our understanding of Bitcoin market behaviour but also offer practical implications for investors, risk managers and policymakers navigating the evolving cryptocurrency landscape.

Suggested Citation

  • Monia Antar, 2024. "Quantile analysis of Bitcoin returns: uncovering market dynamics," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 26(1), pages 122-146, December.
  • Handle: RePEc:eme:jrfpps:jrf-05-2024-0154
    DOI: 10.1108/JRF-05-2024-0154
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    More about this item

    Keywords

    Cryptocurrency; EPU index; Google trends; VIX; Conference board leading indicator; Trade difficulty; Hash rate; G10; G15; G23;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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