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Intraday spillovers in high-order moments among main cryptocurrency markets: the role of uncertainty indexes

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Abstract

This study examines hourly realized volatility and high-order moments (realized kurtosis, realized skewness, and Jumps) spillovers among leading cryptocurrency markets (Bitcoin [BTC], Ethreum [ETH], Litecoin [LTC], Ripple [XRP], Bitcoin Cash [BCH]) using the time-varying parameter vector autoregression (TVP-VAR)-based connectedness method of (Antonakakis, N., & Gabauer, D., (2017). Refined Measures of Dynamic Connectedness Based On TVP-VAR. Technical Report. Munich: University Library of Munich.). Further, we investigate the impacts of uncertainty indices of stocks, gold, and oil on spillover size by employing a quantile regression framework. The results show that cryptocurrency connectedness increased during COVID-19 and returned to pre-pandemic levels once the stock markets recovered. BTC and XRP are net receivers of realized spillovers, whereas the remaining markets are net transmitters in the system. Under high-order moments, BTC is a net receiver of spillovers in Kurtosis and Jumps and shifts to a net contributor in kurtosis. ETH (XRP) is a net transmitter (receiver) of spillovers at high moments, except for jumps. LTC (BCH) is a net transmitter (receiver) of spillovers in the system, irrespective of high-order moments. From the hedging analysis, we document the hedging ability of the XRP against price fluctuations in BTC and ETH assets. Furthermore, quantile regression analysis reveals that cryptocurrency markets react asymmetrically to uncertainties during bullish and bearish regimes and exhibit potential hedge and safe haven properties.

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Fig. 1

Source: Authors’ calculation

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Data availability

Data available on request from the authors.

Notes

  1. We present the net spillover of realized kurtosis, skewness and jumps in Appendix A1 to A3.

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Funding

This work was supported by a 2-Year Research Grant of Pusan National University. 

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Authors and Affiliations

  1. Department of Economics and Finance, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman

    Walid Mensi

  2. Department of Finance and Accounting, University of Tunis El Manar and IFGT, Tunis, Tunisia

    Walid Mensi

  3. Gulati Institute of Finance and Taxation, Thiruvananthapuram, Kerala, India

    Anoop S. Kumar

  4. Jeonbuk State Institute, Jeonju, Jeonbuk, Korea

    Hee-Un Ko

  5. School of Business, Pusan National University, Jangjeon2-Dong, Ge-umjeong-Gu, Busan, 609-735, Korea

    Sang Hoon Kang

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Appendix

Appendix

See Figs. 5, 6, 7 and 8 here.

Fig. 5
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Net spillovers of realized kurtosis

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Fig. 6
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Net spillovers for realized skewness

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Fig. 7
figure 7

Net spillover for jumps

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Fig. 8
figure 8figure 8

Graphs in the quantile regression coefficients. Red lines indicate a 95% confidence band (color figure online)

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Mensi, W., Kumar, A.S., Ko, HU. et al. Intraday spillovers in high-order moments among main cryptocurrency markets: the role of uncertainty indexes. Eurasian Econ Rev (2024). https://doi.org/10.1007/s40822-024-00263-1

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