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Volatility co-movement between Bitcoin and Ether


  • Katsiampa, Paraskevi


Using a bivariate Diagonal BEKK model, this paper investigates the volatility dynamics of the two major cryptocurrencies, namely Bitcoin and Ether. We find evidence of interdependencies in the cryptocurrency market, while it is shown that the two cryptocurrencies' conditional volatility and correlation are responsive to major news. In addition, we show that Ether can be an effective hedge against Bitcoin, while the analysis of optimal portfolio weights indicates that Bitcoin should outweigh Ether. Understanding volatility movements and interdependencies in cryptocurrency markets is important for appropriate investment management, and our study can thus assist cryptocurrency users in making more informed decisions.

Suggested Citation

  • Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
  • Handle: RePEc:eee:finlet:v:30:y:2019:i:c:p:221-227
    DOI: 10.1016/

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    References listed on IDEAS

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    Cited by:

    1. Stefano Martinazzi & Daniele Regoli & Andrea Flori, 2020. "A Tale of Two Layers: The Mutual Relationship between Bitcoin and Lightning Network," Risks, MDPI, Open Access Journal, vol. 8(4), pages 1-1, December.
    2. Qiao, Xingzhi & Zhu, Huiming & Hau, Liya, 2020. "Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723,
    4. Beatriz Vaz de Melo Mendes & André Fluminense Carneiro, 2020. "A Comprehensive Statistical Analysis of the Six Major Crypto-Currencies from August 2015 through June 2020," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(9), pages 1-1, August.
    5. Aslanidis, Nektarios & Bariviera, Aurelio F. & Martínez-Ibañez, Oscar, 2019. "An analysis of cryptocurrencies conditional cross correlations," Finance Research Letters, Elsevier, vol. 31(C), pages 130-137.
    6. Merediz-Solà, Ignasi & Bariviera, Aurelio F., 2019. "A bibliometric analysis of bitcoin scientific production," Research in International Business and Finance, Elsevier, vol. 50(C), pages 294-305.
    7. Artem Meshcheryakov & Stoyu Ivanov, 2020. "Ethereum as a Hedge: The intraday analysis," Economics Bulletin, AccessEcon, vol. 40(1), pages 101-108.
    8. M. Bel'en Arouxet & Aurelio F. Bariviera & Ver'onica E. Pastor & Victoria Vampa, 2020. "Covid-19 impact on cryptocurrencies: evidence from a wavelet-based Hurst exponent," Papers 2009.05652,
    9. Maurice Omane-Adjepong & Imhotep Paul Alagidede, 2020. "Dynamic Linkages and Economic Role of Leading Cryptocurrencies in an Emerging Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 537-585, December.
    10. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

    More about this item


    Bitcoin; Ether; Cryptocurrency; Diagonal BEKK; Multivariate GARCH; Conditional volatility;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets


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