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Tail dependence in the return-volume of leading cryptocurrencies

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  • Naeem, Muhammad
  • Bouri, Elie
  • Boako, Gideon
  • Roubaud, David

Abstract

We analyze the average and extreme dependence between returns and trading volumes of three main cryptocurrencies (Bitcoin, Ethereum and Litecoin) via GARCH-copula models. The copula models used allow for checking the dependence structure under various market conditions. The results indicate that the Student-t and time varying symmetrized Joe Clayton (SJC) copulas are the best choices for the three cryptocurrencies. The tail dependence of return-volume is asymmetric under Gumbel, Clayton and SJC copulas. Meanwhile, extreme returns are associated with extreme trading volumes, and tail dependence is stronger when returns and volumes are high than when returns and volume are low.

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  • Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).
    • Handle: RePEc:eee:finlet:v:36:y:2020:i:c:s1544612319306087
    DOI: 10.1016/j.frl.2019.101326
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    Cited by:

    1. Lars Hornuf & Paul P. Momtaz & Rachel J. Nam & Ye Yuan, 2023. "Cybercrime on the Ethereum Blockchain," CESifo Working Paper Series 10598, CESifo.
    2. Xiao Li & Linda Du, 2023. "Bitcoin daily price prediction through understanding blockchain transaction pattern with machine learning methods," Journal of Combinatorial Optimization, Springer, vol. 45(1), pages 1-24, January.
    3. Urom, Christian & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Dynamic dependence and predictability between volume and return of Non-Fungible Tokens (NFTs): The roles of market factors and geopolitical risks," Finance Research Letters, Elsevier, vol. 50(C).
    4. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2023. "An analysis of the return–volume relationship in decentralised finance (DeFi)," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 236-254.
    5. Hoang, Lai T. & Baur, Dirk G., 2022. "Loaded for bear: Bitcoin private wallets, exchange reserves and prices," Journal of Banking & Finance, Elsevier, vol. 144(C).
    6. Bouri, Elie & Kamal, Elham & Kinateder, Harald, 2023. "FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies," Finance Research Letters, Elsevier, vol. 56(C).
    7. Ahn, Yongkil, 2022. "Asymmetric tail dependence in cryptocurrency markets: A Model-free approach," Finance Research Letters, Elsevier, vol. 47(PB).
    8. Anh Ngoc Quang Huynh & Duy Duong & Tobias Burggraf & Hien Thi Thu Luong & Nam Huu Bui, 2022. "Energy Consumption and Bitcoin Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 79-93, March.
    9. Karishma Ansaram & Paolo Mazza, 2022. "Dependence structure among carbon markets around the world: New evidence from GARCH-copula analysis," Working Papers 2022-ACF-03, IESEG School of Management.
    10. Yousaf, Imran & Yarovaya, Larisa, 2022. "The relationship between trading volume, volatility and returns of Non-Fungible Tokens: evidence from a quantile approach," Finance Research Letters, Elsevier, vol. 50(C).
    11. Adedeji Daniel Gbadebo, 2023. "Dynamic Asymmetric Causality of Bitcoin’s Price-Volume Relation," SAGE Open, , vol. 13(4), pages 21582440231, December.
    12. Poddar, Abhishek & Misra, Arun Kumar & Mishra, Ajay Kumar, 2023. "Return connectedness and volatility dynamics of the cryptocurrency network," Finance Research Letters, Elsevier, vol. 58(PB).
    13. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    14. Rodriguez, E. & Alvarez-Ramirez, J., 2021. "Time-varying cross-correlation between trading volume and returns in US stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).

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