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

Author

Listed:
  • Walid Mensi

    (Sultan Qaboos University
    University of Tunis El Manar and IFGT)

  • Anoop S. Kumar

    (Gulati Institute of Finance and Taxation)

  • Hee-Un Ko

    (Jeonbuk State Institute)

  • Sang Hoon Kang

    (Pusan National University)

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.

Suggested Citation

  • Walid Mensi & Anoop S. Kumar & Hee-Un Ko & Sang Hoon Kang, 2024. "Intraday spillovers in high-order moments among main cryptocurrency markets: the role of uncertainty indexes," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(2), pages 507-538, June.
    • Handle: RePEc:spr:eurase:v:14:y:2024:i:2:d:10.1007_s40822-024-00263-1
    DOI: 10.1007/s40822-024-00263-1
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    as
    1. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
    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. Elsayed, Ahmed H. & Gozgor, Giray & Yarovaya, Larisa, 2022. "Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Faruk Balli & Anne de Bruin & Md Iftekhar Hasan Chowdhury & Muhammad Abubakr Naeem, 2020. "Connectedness of cryptocurrencies and prevailing uncertainties," Applied Economics Letters, Taylor & Francis Journals, vol. 27(16), pages 1316-1322, September.
    5. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    6. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    7. Cagli, Efe Caglar & Mandaci, Pinar Evrim, 2023. "Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets," Emerging Markets Review, Elsevier, vol. 55(C).
    8. Nabila Boukef Jlassi & Ahmed Jeribi & Amine Lahiani & Salma Mefteh-Wali, 2023. "Subsample analysis of stock market – cryptocurrency returns tail dependence: A copula approach for the tails," Post-Print hal-04353030, HAL.
    9. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    10. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    11. Mensi, Walid & Hammoudeh, Shawkat & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Volatility spillovers between oil and equity markets and portfolio risk implications in the US and vulnerable EU countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    12. Neto, David, 2022. "Revisiting spillovers between investor attention and cryptocurrency markets using noisy independent component analysis and transfer entropy," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    13. Jozef Barunk & Evzen KoÄ enda & Lukáš Váchaa, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, , vol. 36(3), pages 309-330, July.
    14. Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015. "Does realized skewness predict the cross-section of equity returns?," Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
    15. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Precious metals, oil, and ASEAN stock markets: From global financial crisis to global health crisis," Resources Policy, Elsevier, vol. 73(C).
    16. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
    17. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    18. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    19. Khamis Hamed Al-Yahyaee & Walid Mensi & Hee-Un Ko & Massimiliano Caporin & Sang Hoon Kang, 2021. "Is the Korean housing market following Gangnam style?," Empirical Economics, Springer, vol. 61(4), pages 2041-2072, October.
    20. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    21. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2022. "Explainable artificial intelligence for crypto asset allocation," Finance Research Letters, Elsevier, vol. 47(PB).
    22. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Al-Jarrah, Idries Mohammad Wanas & Kang, Sang Hoon, 2019. "Time frequency analysis of the commonalities between Bitcoin and major Cryptocurrencies: Portfolio risk management implications," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 283-294.
    23. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    24. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    25. 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.
    26. Kumar, Sanjeev & Jain, Reetika & Narain, & Balli, Faruk & Billah, Mabruk, 2023. "Interconnectivity and investment strategies among commodity prices, cryptocurrencies, and G-20 capital markets: A comparative analysis during COVID-19 and Russian-Ukraine war," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 547-593.
    27. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    28. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    29. Nader Trabelsi, 2018. "Are There Any Volatility Spill-Over Effects among Cryptocurrencies and Widely Traded Asset Classes?," JRFM, MDPI, vol. 11(4), pages 1-17, October.
    30. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    31. Jlassi, Nabila Boukef & Jeribi, Ahmed & Lahiani, Amine & Mefteh-Wali, Salma, 2023. "Subsample analysis of stock market – cryptocurrency returns tail dependence: A copula approach for the tails," Finance Research Letters, Elsevier, vol. 58(PA).
    32. Mensi, Walid & Hamed Al-Yahyaee, Khamis & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Dynamic spillover and connectedness between oil futures and European bonds," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    33. María de la O González & Francisco Jareño & Frank S. Skinner, 2020. "Nonlinear Autoregressive Distributed Lag Approach: An Application on the Connectedness between Bitcoin Returns and the Other Ten Most Relevant Cryptocurrency Returns," Mathematics, MDPI, vol. 8(5), pages 1-22, May.
    34. Rehman, Mobeen Ur & Vinh Vo, Xuan, 2020. "Cryptocurrencies and precious metals: A closer look from diversification perspective," Resources Policy, Elsevier, vol. 66(C).
    35. 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.
    36. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    37. Zhang, Hongwei & Jin, Chen & Bouri, Elie & Gao, Wang & Xu, Yahua, 2023. "Realized higher-order moments spillovers between commodity and stock markets: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 30(C).
    38. Hasan, Mudassar & Naeem, Muhammad Abubakr & Arif, Muhammad & Yarovaya, Larisa, 2021. "Higher moment connectedness in cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    39. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
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    More about this item

    Keywords

    Cryptocurrencies; Spillovers in high moments; High frequency; Hedging;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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