Volatility and dependence in cryptocurrency and financial markets: a copula approach

IF 0.7 4区 经济学 Q3 ECONOMICS
Jinan Liu, Apostolos Serletis
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引用次数: 1

Abstract

Abstract We use a semiparametric GARCH-in-Mean copula model to examine the volatility dynamics and tail dependence between cryptocurrency markets and financial markets. We do not find any statistically significant tail dependence between the financial and cryptocurrency markets, but we find lower tail dependence between Bitcoin and stock returns. There is lower tail dependence among Bitcoin, Ethereum, and Litecoin, and the lower tail dependence between Ethereum and Litecoin returns is the strongest. The GARCH-in-Mean model shows that the uncertainty effect on cryptocurrency returns is not statistically significant, while uncertainty has a negative and statistically significant effect on Bitcoin returns. The fact that there is no tail dependence between cryptocurrency and the interest rate or the effective exchange rate of U.S. dollar suggests that cryptocurrency could offer safe haven, defined as an asset that is uncorrelated with stocks and bonds.
加密货币和金融市场的波动性和依赖性:一种联结方法
摘要我们使用均值copula模型中的半参数GARCH来检验加密货币市场和金融市场之间的波动动力学和尾部依赖性。我们没有发现金融和加密货币市场之间有任何统计上显著的尾部依赖性,但我们发现比特币和股票回报之间的尾部依赖度较低。比特币、以太坊和莱特币之间存在较低的尾部依赖性,以太坊和比特币回报之间的较低尾部依赖性最强。GARCH in Mean模型表明,不确定性对加密货币回报的影响在统计上并不显著,而不确定性对比特币回报有负面和统计显著的影响。加密货币与美元利率或有效汇率之间不存在尾部依赖性,这一事实表明,加密货币可以提供避风港,被定义为与股票和债券无关的资产。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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