IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v56y2023ics1544612323004713.html
   My bibliography  Save this article

FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies

Author

Listed:
  • Bouri, Elie
  • Kamal, Elham
  • Kinateder, Harald

Abstract

We examine the dynamic lower tail dependence and downside risk spillover between the FTX Token and seven major cryptocurrencies using Rotated Gumbel copula and GARCH copula quantile regression-based ∆CoVaR models. Daily data is analyzed from May 1, 2020 to December 31, 2022. The results show a strong evidence of risk spillover effects from FTX Token to crypto markets. Solana, followed by Cardano, displays the largest downside risk spillover. Tether and Bitcoin are affected least by the FTX fallout, receiving the lowest downside risk spillovers. Furthermore, the dynamic risk spillover effects are heterogeneous over time and comparatively different for each cryptocurrency.

Suggested Citation

  • Bouri, Elie & Kamal, Elham & Kinateder, Harald, 2023. "FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies," Finance Research Letters, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323004713
    DOI: 10.1016/j.frl.2023.104099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323004713
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2023.104099?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. Ahn, Yongkil, 2022. "Asymmetric tail dependence in cryptocurrency markets: A Model-free approach," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    4. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).
    5. Kumar, Anoop S. & Anandarao, S., 2019. "Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 448-458.
    6. Khalfaoui, Rabeh & Gozgor, Giray & Goodell, John W., 2023. "Impact of Russia-Ukraine war attention on cryptocurrency: Evidence from quantile dependence analysis," Finance Research Letters, Elsevier, vol. 52(C).
    7. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, vol. 7(3), pages 111-125, August.
    8. Chuffart, Thomas, 2022. "Interest in cryptocurrencies predicts conditional correlation dynamics," Finance Research Letters, Elsevier, vol. 46(PA).
    9. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).
    12. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    13. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    14. Mensi, Walid & El Khoury, Rim & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 65(C).
    15. Akyildirim, Erdinc & Conlon, Thomas & Corbet, Shaen & Goodell, John W., 2023. "Understanding the FTX exchange collapse: A dynamic connectedness approach," Finance Research Letters, Elsevier, vol. 53(C).
    16. Ben Ameur, Hachmi & Jawadi, Fredj & Jawadi, Nabila & Cheffou, Abdoulkarim Idi, 2020. "Assessing downside and upside risk spillovers across conventional and socially responsible stock markets," Economic Modelling, Elsevier, vol. 88(C), pages 200-210.
    17. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    18. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bastidon, Cécile & Jawadi, Fredj, 2024. "Trade fragmentation and volatility-of-volatility networks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    2. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    3. Gorman, Michael & Hughen, W. Keener, 2024. "Does bitcoin still enhance an investment portfolio in a post Covid-19 world?," Finance Research Letters, Elsevier, vol. 62(PB).
    4. Sakariyahu, Rilwan & Lawal, Rodiat & Adigun, Rasheed & Paterson, Audrey & Johan, Sofia, 2024. "One crash, too many: Global uncertainty, sentiment factors and cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 94(C).
    5. Poddar, Abhishek & Misra, Arun Kumar & Mishra, Ajay Kumar, 2023. "Return connectedness and volatility dynamics of the cryptocurrency network," Finance Research Letters, Elsevier, vol. 58(PB).
    6. Zhang, Lei & Bouri, Elie & Chen, Yan, 2023. "Co-jump dynamicity in the cryptocurrency market: A network modelling perspective," Finance Research Letters, Elsevier, vol. 58(PB).
    7. Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Miguel Ángel Echarte Fernández & David Sanz-Bas, 2024. "Bitcoin’s bubbly behaviors: does it resemble other financial bubbles of the past?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.

    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. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
    2. Fakhfekh, Mohamed & Bejaoui, Azza & Bariviera, Aurelio F. & Jeribi, Ahmed, 2024. "Dependence structure between NFT, DeFi and cryptocurrencies in turbulent times: An Archimax copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    3. Boubaker, Sabri & Karim, Sitara & Naeem, Muhammad Abubakr & Rahman, Molla Ramizur, 2024. "On the prediction of systemic risk tolerance of cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. Chowdhury, Md Iftekhar Hasan & Hasan, Mudassar & Bouri, Elie & Tang, Yayan, 2024. "Emotional spillovers in the cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    5. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    6. Ahmed BenSaïda, 2023. "The linkage between Bitcoin and foreign exchanges in developed and emerging markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    7. Umar, Zaghum & Usman, Muhammad & Choi, Sun-Yong & Rice, John, 2023. "Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios," Research in International Business and Finance, Elsevier, vol. 65(C).
    8. Poddar, Abhishek & Misra, Arun Kumar & Mishra, Ajay Kumar, 2023. "Return connectedness and volatility dynamics of the cryptocurrency network," Finance Research Letters, Elsevier, vol. 58(PB).
    9. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    10. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    11. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    12. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    13. Eross, Andrea & McGroarty, Frank & Urquhart, Andrew & Wolfe, Simon, 2019. "The intraday dynamics of bitcoin," Research in International Business and Finance, Elsevier, vol. 49(C), pages 71-81.
    14. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    15. 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.
    16. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    17. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    18. Xun Lu & Kin Lai & Liang Liang, 2014. "Portfolio value-at-risk estimation in energy futures markets with time-varying copula-GARCH model," Annals of Operations Research, Springer, vol. 219(1), pages 333-357, August.
    19. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    20. Rehman, Mobeen Ur, 2020. "Do bitcoin and precious metals do any good together? An extreme dependence and risk spillover analysis," Resources Policy, Elsevier, vol. 68(C).

    More about this item

    Keywords

    FTX collapse; Cryptocurrencies; Downside risk spillover; ∆CoVaR; GARCH copula quantile regression;
    All these keywords.

    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:56:y:2023:i:c:s1544612323004713. 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.