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Volatility and dependence in cryptocurrency and financial markets: a copula approach

Author

Listed:
  • Liu Jinan

    (Department of Economics, University of Nebraska, Omaha, USA)

  • Serletis Apostolos

    (Department of Economics, University of Calgary, Calgary, Canada)

Abstract

We use a semiparametric GARCH-in-Mean copula model to examine the volatility dynamics and tail dependence between cryptocurrency markets and financial markets. We do not find any statistically significant tail dependence between the financial and cryptocurrency markets, but we find lower tail dependence between Bitcoin and stock returns. There is lower tail dependence among Bitcoin, Ethereum, and Litecoin, and the lower tail dependence between Ethereum and Litecoin returns is the strongest. The GARCH-in-Mean model shows that the uncertainty effect on cryptocurrency returns is not statistically significant, while uncertainty has a negative and statistically significant effect on Bitcoin returns. The fact that there is no tail dependence between cryptocurrency and the interest rate or the effective exchange rate of U.S. dollar suggests that cryptocurrency could offer safe haven, defined as an asset that is uncorrelated with stocks and bonds.

Suggested Citation

  • Liu Jinan & Serletis Apostolos, 2024. "Volatility and dependence in cryptocurrency and financial markets: a copula approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(1), pages 119-149, February.
    • Handle: RePEc:bpj:sndecm:v:28:y:2024:i:1:p:119-149:n:6
    DOI: 10.1515/snde-2022-0029
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    More about this item

    Keywords

    Bitcoin price; copula; cryptocurrency price; GARCH-in-Mean model;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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