IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v69y2024ipas1062940823001596.html
   My bibliography  Save this article

Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework

Author

Listed:
  • Chen, Bin-xia
  • Sun, Yan-lin

Abstract

Existing research pays less attention to the risk characteristics and connectedness of higher moments of cryptocurrencies. We dynamically analyze the risk characteristics of cryptocurrencies and their connectedness at four levels: return, volatility, skewness, and kurtosis. First, there are price bubbles in five popular cryptocurrencies, with long bubble periods during the COVID-19 epidemic. The volatility, skewness and kurtosis of cryptocurrencies are characterized by high persistence, with the exception of BNB. Second, the connectedness between the five cryptocurrencies is significant at higher moment conditions. The results for time-varying connectedness show that the total spillover of volatility, skewness and kurtosis varies over a wider range than returns, and that the total spillover of returns, volatility and skewness peaks during COVID-19. According to the pairwise results, there is strong connectedness between Ether and Bitcoin at the level of returns, volatility, skewness, and kurtosis, which is more significant at higher moments. Third, the role of cryptocurrencies changes not only over time, but also over order moments. The cryptocurrency market experienced significant volatility during 2018 and the first half of 2019, with Bitcoin being the most significant net exporter of returns and volatility spillovers. Cardano is a net exporter of both skewness and kurtosis spillover, and it is highly persistent with respect to volatility, skewness, and kurtosis. Overall, the leader in risk spillover at all order moments is Ether, and the net receiver is BNB.

Suggested Citation

  • Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    • Handle: RePEc:eee:ecofin:v:69:y:2024:i:pa:s1062940823001596
    DOI: 10.1016/j.najef.2023.102036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940823001596
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2023.102036?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.

    More about this item

    Keywords

    Cryptocurrency market; GARCHSK model; TVP-VAR model; Higher moment connectedness; Non-linear Granger causality;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ecofin:v:69:y:2024:i:pa:s1062940823001596. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/inca/620163 .

    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.