Konstantinos Gkillas, Maria Tantoula, Manolis Tzagarakis
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引用次数: 0
Abstract
We analyze properties identified in the price volatility of Bitcoin and some of the leading cryptocurrencies namely Litecoin, Ripple, and Ethereum. We employ Heterogeneous Autoregressive models (HAR) in both a univariate and multivariate level of analysis. First, the significance of heterogeneity and jumps is examined, considering the ability of several univariate HAR models, to predict realized volatility of cryptocurrencies. Second, we examine the relevance of realized volatility jumps and covariances in the transmission of volatility spillovers among cryptocurrencies. We perform a comparative spillover analysis of the multivariate HAR models in two versions, considering variances only and covariances as well. Our results indicate that covariances and jumps inclusion lead to an increase in spillovers. The time-varying spillover analysis indicates higher dependency between Bitcoin and the other cryptocurrencies mostly at short frequencies.
我们分析了比特币和一些主要加密货币(即莱特币、瑞波币和以太坊)的价格波动特性。我们采用异质自回归模型(HAR)进行单变量和多变量分析。首先,考虑到几个单变量 HAR 模型预测加密货币已实现波动率的能力,我们研究了异质性和跳跃的重要性。其次,我们研究了已实现波动率跳跃和协方差在加密货币间波动溢出效应传播中的相关性。我们对两个版本的多变量 HAR 模型进行了溢出比较分析,分别只考虑了方差和协方差。我们的结果表明,包含协方差和跳跃会导致溢出效应增加。时变溢出效应分析表明,比特币与其他加密货币之间的依赖性较高,主要表现在短频率上。