IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v38y2021ics154461231930755x.html
   My bibliography  Save this article

Tail-risk spillovers in cryptocurrency markets

Author

Listed:
  • Xu, Qiuhua
  • Zhang, Yixuan
  • Zhang, Ziyang

Abstract

This paper analyzes the tail-risk interdependence among 23 cryptocurrencies and identifies the systemically important cryptocurrencies using the TENET approach proposed by Fan et al. (2018) and finds that (i) significant risk spillover effect exists; (ii) the degree of the total connectedness of all the sampled cryptocurrencies increases steadily over time; (iii) Bitcoin is the largest systemic risk receiver; (iv) Ethereum is the largest systemic risk emitter.

Suggested Citation

  • Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
  • Handle: RePEc:eee:finlet:v:38:y:2021:i:c:s154461231930755x
    DOI: 10.1016/j.frl.2020.101453
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461231930755X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2020.101453?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    4. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    5. Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
    6. Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
    7. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    8. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    9. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    10. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    11. 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.
    12. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
    13. Bouri, Elie & Azzi, Georges & Dyhrberg, Anne Haubo, 2017. "On the return-volatility relationship in the Bitcoin market around the price crash of 2013," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-16.
    14. Zięba, Damian & Kokoszczyński, Ryszard & Śledziewska, Katarzyna, 2019. "Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 102-125.
    15. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    16. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    17. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.
    18. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    19. Yan Fan & Wolfgang Karl Härdle & Weining Wang & Lixing Zhu, 2018. "Single-Index-Based CoVaR With Very High-Dimensional Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 212-226, April.
    20. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    21. 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.
    22. Guesmi, Khaled & Saadi, Samir & Abid, Ilyes & Ftiti, Zied, 2019. "Portfolio diversification with virtual currency: Evidence from bitcoin," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 431-437.
    23. 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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charfeddine, Lanouar & Benlagha, Noureddine & Khediri, Karim Ben, 2022. "An intra-cryptocurrency analysis of volatility connectedness and its determinants: Evidence from mining coins, non-mining coins and tokens," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. BRIK, Hatem & El OUAKDI, Jihene & FTITI, Zied, 2022. "Roles of stable versus nonstable cryptocurrencies in Bitcoin market dynamics," Research in International Business and Finance, Elsevier, vol. 62(C).
    3. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    4. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    5. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    6. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 1-13.
    7. Samet Gunay & Kerem Kaskaloglu & Shahnawaz Muhammed, 2021. "Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
    8. Jiang, Wen & Xu, Qiuhua & Zhang, Ruige, 2022. "Tail-event driven network of cryptocurrencies and conventional assets," Finance Research Letters, Elsevier, vol. 46(PB).
    9. 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).
    10. Etienne Harb & Charbel Bassil & Talie Kassamany & Roland Baz, 2024. "Volatility Interdependence Between Cryptocurrencies, Equity, and Bond Markets," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 951-981, March.
    11. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    12. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2021. "Cyber-attacks, spillovers and contagion in the cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    13. Umar, Zaghum & Trabelsi, Nader & Alqahtani, Faisal, 2021. "Connectedness between cryptocurrency and technology sectors: International evidence," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 910-922.
    14. Demiralay, Sercan & Golitsis, Petros, 2021. "On the dynamic equicorrelations in cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 524-533.
    15. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    16. Silky Vigg Kushwah & Shab Hundal & Payal Goel, 2024. "Unveiling Interconnectedness and Volatility Transmission: A Novel GARCH Analysis of Leading Global Cryptocurrencies," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 132-139, May.
    17. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Spillovers and multiscale relationships among cryptocurrencies: A portfolio implication using high frequency data," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 449-479.
    18. Hsu, Shu-Han & Sheu, Chwen & Yoon, Jiho, 2021. "Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    19. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    20. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.

    More about this item

    Keywords

    Cryptocurrency; CoVaR; Tail-risk; TENET; LASSO;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:eee:finlet:v:38:y:2021:i:c:s154461231930755x. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.