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Complexity traits and synchrony of cryptocurrencies price dynamics
Decisions in Economics and Finance ( IF 1.4 ) Pub Date : 2021-02-16 , DOI: 10.1007/s10203-021-00319-w
Davide Provenzano , Rodolfo Baggio

In this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composition of communities. To the aim of our analysis, such result proves that price and volume dynamics of the cryptocurrencies were characterized by cyclical patterns of similar wavelength and amplitude over the time period considered. Yet, the value of the slope parameter associated with the exponential distributions fitted to the data suggests a higher stability and predictability for Bitcoin and Litecoin than for Ethereum. The study of synchrony between the time series investigated displayed a different degree of synchronization between the three cryptocurrencies before and after a collapse event. These results could be of interest for investors who might prefer to switch from one cryptocurrency to another to exploit the potential opportunities of profit generated by the dynamics of price and volumes in the market of virtual currencies.



中文翻译:

加密货币的复杂性特征和同步价格动态

在这项研究中,我们对动态进行了特征描述,并分析了2015年9月1日至2020年3月31日这三种加密货币(比特币,以太坊和莱特币)的每日收盘价和交易量的时间序列的同步度(以美元为单位)时间序列首先通过水平可见性算法映射到一个复杂的网络中,以揭示其时间特征和动力学的结构。然后,研究了时间序列的同步性,以确定被研究的加密货币同时共起泡的可能性。调查结果揭示了三种虚拟货币在社区的数量和内部组成方面具有相似的复杂结构。为了我们的分析目的,这样的结果证明,在所考虑的时间段内,加密货币的价格和数量动态具有相似的波长和幅度的周期性特征。然而,与拟合到数据的指数分布相关的斜率参数的值表明,比特币和莱特币的稳定性和可预测性高于以太坊。研究的时间序列之间的同步性研究显示,崩溃事件前后三种加密货币之间的同步程度不同。这些结果可能对那些可能希望从一种加密货币转换为另一种加密货币以利用虚拟货币市场中价格和交易量动态所产生的潜在获利机会的投资者感兴趣。与数据拟合的指数分布相关的斜率参数的值表明,与以太坊相比,比特币和莱特币的稳定性和可预测性更高。研究的时间序列之间的同步性研究显示,崩溃事件前后三种加密货币之间的同步程度不同。这些结果可能对那些可能希望从一种加密货币转换为另一种加密货币以利用虚拟货币市场中价格和交易量动态所产生的潜在获利机会的投资者感兴趣。与数据拟合的指数分布相关的斜率参数的值表明,与以太坊相比,比特币和莱特币的稳定性和可预测性更高。研究的时间序列之间的同步性研究显示,崩溃事件前后三种加密货币之间的同步程度不同。这些结果可能对那些可能希望从一种加密货币转换为另一种加密货币以利用虚拟货币市场中价格和交易量动态所产生的潜在获利机会的投资者感兴趣。

更新日期:2021-03-14
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