Kwapień Jarosław, Wątorek Marcin, Drożdż Stanisław
Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, Poland.
Faculty of Computer Science and Telecommunications, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland.
Entropy (Basel). 2021 Dec 13;23(12):1674. doi: 10.3390/e23121674.
Time series of price returns for 80 of the most liquid cryptocurrencies listed on Binance are investigated for the presence of detrended cross-correlations. A spectral analysis of the detrended correlation matrix and a topological analysis of the minimal spanning trees calculated based on this matrix are applied for different positions of a moving window. The cryptocurrencies become more strongly cross-correlated among themselves than they used to be before. The average cross-correlations increase with time on a specific time scale in a way that resembles the Epps effect amplification when going from past to present. The minimal spanning trees also change their topology and, for the short time scales, they become more centralized with increasing maximum node degrees, while for the long time scales they become more distributed, but also more correlated at the same time. Apart from the inter-market dependencies, the detrended cross-correlations between the cryptocurrency market and some traditional markets, like the stock markets, commodity markets, and Forex, are also analyzed. The cryptocurrency market shows higher levels of cross-correlations with the other markets during the same turbulent periods, in which it is strongly cross-correlated itself.
对币安上市的80种流动性最强的加密货币的价格回报时间序列进行了研究,以确定是否存在去趋势化交叉相关性。针对移动窗口的不同位置,对去趋势化相关矩阵进行了频谱分析,并对基于该矩阵计算的最小生成树进行了拓扑分析。加密货币之间的交叉相关性比以往更强。在特定时间尺度上,平均交叉相关性随时间增加,其方式类似于从过去到现在的埃普斯效应放大。最小生成树也改变了它们的拓扑结构,在短时间尺度上,它们随着最大节点度的增加而变得更加集中,而在长时间尺度上,它们变得更加分散,但同时相关性也更高。除了市场间的依赖性,还分析了加密货币市场与一些传统市场(如股票市场、商品市场和外汇市场)之间的去趋势化交叉相关性。在同一动荡时期,加密货币市场与其他市场的交叉相关性更高,在此期间它自身也存在强烈的交叉相关性。