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

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  • 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
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    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

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