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Extreme return-volume relationship in cryptocurrencies: Tail dependence analysis

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  • Muhammad Naeem
  • Kashif Saleem
  • Sheraz Ahmed
  • Naeem Muhammad
  • Faisal Mustafa
  • Papavassiliou Vassilios

Abstract

We explore extreme return-volumes dependence among different cryptocurrencies such as Bitcoin, Ethereum, Ripple, and Litecoin by using the Copula approach. We use Student-t, Frank, Clayton, Survival Clayton, Gumbel, and SJC copulas. We filter out margins by using the EGARCH model for return series and GARCH model for volume series. Evidence of significant symmetric dependence between return-volume is not found due to insignificance of student-t and Frank copula parameters. In a return-volume relationship, coefficients of lower tail dependence are significant for Bitcoin, Ripple, and Litecoin which means that low returns are followed by low volumes. Lower tail dependence for the return-volume relationship is stronger than the upper tail dependence for Bitcoin, Ripple, and Litecoin. Moreover, for negative return-volume, left tail dependence coefficients are significant for Ripple and Litecoin, which means that high returns are followed by low volumes for Ripple and Litecoin. Our investigation shows that investors (buyer or seller) are very careful in extreme market conditions for both Ripple and Litecoin. Extreme upper tail and lower tail dependence coefficients are insignificant for Ethereum.

Suggested Citation

  • Muhammad Naeem & Kashif Saleem & Sheraz Ahmed & Naeem Muhammad & Faisal Mustafa & Papavassiliou Vassilios, 2020. "Extreme return-volume relationship in cryptocurrencies: Tail dependence analysis," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1834175-183, January.
    • Handle: RePEc:taf:oaefxx:v:8:y:2020:i:1:p:1834175
    DOI: 10.1080/23322039.2020.1834175
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    Cited by:

    1. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
    2. Chan, Stephen & Chu, Jeffrey & Zhang, Yuanyuan & Nadarajah, Saralees, 2022. "An extreme value analysis of the tail relationships between returns and volumes for high frequency cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Dias, Ishanka K. & Fernando, J.M. Ruwani & Fernando, P. Narada D., 2022. "Does investor sentiment predict bitcoin return and volatility? A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 84(C).

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