Volatility Spillovers among Cryptocurrencies

被引:7
|
作者
Smales, Lee A. [1 ]
机构
[1] Univ Western Australia, UWA Business Sch, Perth, WA 6009, Australia
关键词
cryptocurrency; volatility spillovers; vector autoregression (VAR); bitcoin; multivariate GARCH (MGARCH); MARKET EVIDENCE; BITCOIN; CONNECTEDNESS; GARCH;
D O I
10.3390/jrfm14100493
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
The cryptocurrency market has experienced stunning growth, with market value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, and stablecoins. Our results demonstrate that conditional correlations are time-varying, peaking during the COVID-19 pandemic sell-off of March 2020, and that both ARCH and GARCH effects play an important role in determining conditional volatility among cryptocurrencies. We find a bi-directional relationship for returns and long-term (GARCH) spillovers between BTC and ETH, but only a unidirectional short-term (ARCH) spillover effect from BTC to ETH. We also find spillovers from BTC and ETH to USDT, but no influence running in the other direction. Our results suggest that USDT does not currently play an important role in volatility transmission across cryptocurrency markets. We also demonstrate applications of our results to hedging and optimal portfolio construction.
引用
收藏
页数:12
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