Drożdż Stanisław, Kwapień Jarosław, Oświęcimka Paweł, Stanisz Tomasz, Wątorek Marcin
Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, Poland.
Faculty of Computer Science and Telecommunication, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland.
Entropy (Basel). 2020 Sep 18;22(9):1043. doi: 10.3390/e22091043.
Social systems are characterized by an enormous network of connections and factors that can influence the structure and dynamics of these systems. Among them the whole economical sphere of human activity seems to be the most interrelated and complex. All financial markets, including the youngest one, the cryptocurrency market, belong to this sphere. The complexity of the cryptocurrency market can be studied from different perspectives. First, the dynamics of the cryptocurrency exchange rates to other cryptocurrencies and fiat currencies can be studied and quantified by means of multifractal formalism. Second, coupling and decoupling of the cryptocurrencies and the conventional assets can be investigated with the advanced cross-correlation analyses based on fractal analysis. Third, an internal structure of the cryptocurrency market can also be a subject of analysis that exploits, for example, a network representation of the market. In this work, we approach the subject from all three perspectives based on data from a recent time interval between January 2019 and June 2020. This period includes the peculiar time of the Covid-19 pandemic; therefore, we pay particular attention to this event and investigate how strong its impact on the structure and dynamics of the market was. Besides, the studied data covers a few other significant events like double bull and bear phases in 2019. We show that, throughout the considered interval, the exchange rate returns were multifractal with intermittent signatures of bifractality that can be associated with the most volatile periods of the market dynamics like a bull market onset in April 2019 and the Covid-19 outburst in March 2020. The topology of a minimal spanning tree representation of the market also used to alter during these events from a distributed type without any dominant node to a highly centralized type with a dominating hub of USDT. However, the MST topology during the pandemic differs in some details from other volatile periods.
社会系统的特点是拥有庞大的联系网络和各种因素,这些因素会影响系统的结构和动态变化。其中,人类活动的整个经济领域似乎是相互关联最为紧密且最为复杂的。所有金融市场,包括最新的加密货币市场,都属于这一领域。加密货币市场的复杂性可以从不同角度进行研究。首先,可以通过多重分形形式体系来研究和量化加密货币与其他加密货币以及法定货币之间汇率的动态变化。其次,可以利用基于分形分析的先进互相关分析来研究加密货币与传统资产之间的耦合和解耦情况。第三,加密货币市场的内部结构也可以成为分析的对象,例如利用市场的网络表示形式。在这项工作中,我们基于2019年1月至2020年6月最近一段时间间隔的数据,从上述三个角度来探讨这个问题。这段时期包括新冠疫情这一特殊时期;因此,我们特别关注这一事件,并研究其对市场结构和动态的影响程度。此外,所研究的数据还涵盖了其他一些重大事件,如2019年的双牛市和熊市阶段。我们表明,在整个考虑的时间段内,汇率回报具有多重分形特征,带有双分形的间歇性特征,这可能与市场动态变化中最动荡的时期相关,如2019年4月的牛市开端和2020年3月的新冠疫情爆发。市场最小生成树表示的拓扑结构在这些事件期间也会发生变化,从没有任何主导节点的分布式类型转变为以USDT为主导中心的高度集中类型。然而,疫情期间的最小生成树拓扑结构在某些细节上与其他动荡时期有所不同。