IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_8324.html
   My bibliography  Save this paper

Cyber Attacks, Spillovers and Contagion in the Cryptocurrency Markets

Author

Listed:
  • Guglielmo Maria Caporale
  • Woo-Young Kang
  • Fabio Spagnolo
  • Nicola Spagnolo

Abstract

This paper examines mean and volatility spillovers between three major cryptocurrencies (Bitcoin, Litecoin and Ethereum) and the role played by cyber attacks. Specifically, trivariate GARCH-BEKK models are estimated which include suitably defined dummies corresponding to different types, targets and number per day of cyber attacks. Significant dynamic linkages (interdependence) among the three cryptocurrencies under investigation are found in most cases when cyber attacks are taken into account, Bitcoin appearing to be the dominant one. Further, Wald tests for parameter shifts during episodes of turbulence resulting from cyber attacks provide evidence that the latter affect the transmission mechanism between cryptocurrency returns and volatilities (contagion). More precisely, cyber attacks appear to strengthen cross-market linkages, thereby reducing portfolio diversification opportunities for cryptocurrency investors. Finally, the conditional correlation analysis confirms the previous findings.

Suggested Citation

  • Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2020. "Cyber Attacks, Spillovers and Contagion in the Cryptocurrency Markets," CESifo Working Paper Series 8324, CESifo.
  • Handle: RePEc:ces:ceswps:_8324
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp8324.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Schilling, Linda & Uhlig, Harald, 2019. "Some simple bitcoin economics," Journal of Monetary Economics, Elsevier, vol. 106(C), pages 16-26.
    2. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    3. Elie Bouri & Naji Jalkh & Peter Molnár & David Roubaud, 2017. "Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?," Applied Economics, Taylor & Francis Journals, vol. 49(50), pages 5063-5073, October.
    4. Boako, Gideon & Tiwari, Aviral Kumar & Roubaud, David, 2019. "Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market," International Economics, Elsevier, vol. 158(C), pages 77-90.
    5. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    6. Guglielmo Caporale & Nikitas Pittis & Nicola Spagnolo, 2006. "Volatility transmission and financial crises," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 30(3), pages 376-390, September.
    7. Biais, Bruno & Bisière, Christophe & Bouvard, Matthieu & Casamatta, Catherine & Menkveld, Albert J., 2018. "Equilibrium Bitcoin Pricing," TSE Working Papers 18-973, Toulouse School of Economics (TSE).
    8. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    9. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    10. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    11. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(1), pages 81-127.
    12. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
    13. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    14. C. Alexander & M. Dakos, 2020. "A critical investigation of cryptocurrency data and analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 173-188, February.
    15. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
    16. Bouri, Elie & Gupta, Rangan & Tiwari, Aviral Kumar & Roubaud, David, 2017. "Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions," Finance Research Letters, Elsevier, vol. 23(C), pages 87-95.
    17. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    18. Bação Pedro & Duarte António Portugal & Sebastião Helder & Redzepagic Srdjan, 2018. "Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?," Scientific Annals of Economics and Business, Sciendo, vol. 65(2), pages 97-117, June.
    19. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2020. "Non-linearities, cyber attacks and cryptocurrencies," Finance Research Letters, Elsevier, vol. 32(C).
    20. Caporale, Guglielmo Maria & Cipollini, Andrea & Spagnolo, Nicola, 2005. "Testing for contagion: a conditional correlation analysis," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 476-489, June.
    21. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    22. Fry, John, 2018. "Booms, busts and heavy-tails: The story of Bitcoin and cryptocurrency markets?," Economics Letters, Elsevier, vol. 171(C), pages 225-229.
    23. Liu, Weiyi, 2019. "Portfolio diversification across cryptocurrencies," Finance Research Letters, Elsevier, vol. 29(C), pages 200-205.
    24. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
    25. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    26. Wenjun Feng & Yiming Wang & Zhengjun Zhang, 2018. "Can cryptocurrencies be a safe haven: a tail risk perspective analysis," Applied Economics, Taylor & Francis Journals, vol. 50(44), pages 4745-4762, September.
    27. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    28. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    29. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    30. Max Raskin & David Yermack, 2016. "Digital Currencies, Decentralized Ledgers, and the Future of Central Banking," NBER Working Papers 22238, National Bureau of Economic Research, Inc.
    31. Borri, Nicola, 2019. "Conditional tail-risk in cryptocurrency markets," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 1-19.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    mean and volatility spillovers; contagion; cryptocurrencies; cyber attacks;

    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
    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_8324. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Klaus Wohlrabe). General contact details of provider: http://edirc.repec.org/data/cesifde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.