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Crypto-environment network connectivity and Bitcoin returns distribution tail behaviour

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  • Caferra, Rocco
  • Morone, Andrea
  • Potì, Valerio

Abstract

This study explores whether and to what extent cryptocurrency ecosystem network connectivity predicts Bitcoin returns across quantiles of the return distribution. The facets of cryptocurrency ecosystem network connectivity we consider include connectivity between the on- and off-chain segments of the Bitcoin market, the intensity and synchronization of social and traditional crypto-focused media activity, the intensity of network correlations between cryptocurrencies. We identify tail behaviour predictors employing a quantile regression approach. The results demonstrate the effectiveness of several connectivity measures in predicting both price spikes and downfalls, but in a different way before and during the COVID-19 outbreak.

Suggested Citation

  • Caferra, Rocco & Morone, Andrea & Potì, Valerio, 2022. "Crypto-environment network connectivity and Bitcoin returns distribution tail behaviour," Economics Letters, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:ecolet:v:218:y:2022:i:c:s0165176522002555
    DOI: 10.1016/j.econlet.2022.110734
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    References listed on IDEAS

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    1. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta & Albert J. Menkveld, 2023. "Equilibrium Bitcoin Pricing," Journal of Finance, American Finance Association, vol. 78(2), pages 967-1014, April.
    2. Caferra, Rocco, 2020. "Good vibes only: The crypto-optimistic behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    3. Lin William Cong & Ye Li & Neng Wang, 2021. "Tokenomics: Dynamic Adoption and Valuation [The demand of liquid assets with uncertain lumpy expenditures]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1105-1155.
    4. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    5. Markus Brunnermeier & Emmanuel Farhi & Ralph S J Koijen & Arvind Krishnamurthy & Sydney C Ludvigson & Hanno Lustig & Stefan Nagel & Monika Piazzesi, 2021. "Review Article: Perspectives on the Future of Asset Pricing [Do survey expectations of stock returns reflect risk-adjustments?]," The Review of Financial Studies, Society for Financial Studies, vol. 34(4), pages 2126-2160.
    6. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2022. "Common Risk Factors in Cryptocurrency," Journal of Finance, American Finance Association, vol. 77(2), pages 1133-1177, April.
    7. Borri, Nicola, 2019. "Conditional tail-risk in cryptocurrency markets," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 1-19.
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    Cited by:

    1. Li, Yi & Lucey, Brian & Urquhart, Andrew, 2023. "Can altcoins act as hedges or safe-havens for Bitcoin?," Finance Research Letters, Elsevier, vol. 52(C).
    2. Fakhfekh, Mohamed & Bejaoui, Azza & Bariviera, Aurelio F. & Jeribi, Ahmed, 2024. "Dependence structure between NFT, DeFi and cryptocurrencies in turbulent times: An Archimax copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    3. Cascavilla, Alessandro, 2023. "Between money and speculative asset: the role of financial literacy on the perception towards Bitcoin in Italy," MPRA Paper 118472, University Library of Munich, Germany.
    4. Cascavilla, Alessandro, 2024. "Between money and speculative asset: The role of financial literacy on the perception towards Bitcoin in Italy," Journal of Economic Psychology, Elsevier, vol. 102(C).

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    More about this item

    Keywords

    Cryptocurrencies; Network analysis; Quantile regression;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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