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

被引:2
|
作者
Mensi, Walid [1 ,2 ,3 ]
Kumar, Anoop S. [4 ]
Ko, Hee-Un [5 ]
Kang, Sang Hoon [6 ]
机构
[1] Sultan Qaboos Univ, Coll Econ & Polit Sci, Dept Econ & Finance, Muscat, Oman
[2] Univ Tunis Manar, Dept Finance & Accounting, Tunis, Tunisia
[3] IFGT, Tunis, Tunisia
[4] Gulati Inst Finance & Taxat, Thiruvananthapuram, Kerala, India
[5] Jeonbuk State Inst, Dept Nanosci & Nanotechnol, Jeonju, Jeonbuk, South Korea
[6] Pusan Natl Univ, Sch Business, Jangjeon2 Dong, Busan 609735, South Korea
关键词
Cryptocurrencies; Spillovers in high moments; High frequency; Hedging; G14; G15; IMPULSE-RESPONSE ANALYSIS; VOLATILITY CONNECTEDNESS; BITCOIN; GOLD; RETURN; OIL; INTEGRATION; INVESTMENT; COMMODITY;
D O I
10.1007/s40822-024-00263-1
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
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页码:507 / 538
页数:32
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