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比特币与以太币交易活动的多重分形交叉相关

文章 arXiv papers · 作者: Marcin Wątorek et al.
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总结

本研究考察 COVID 之后比特币与以太币的高频交易特征。研究使用多重分形去趋势交叉相关分析，分析收益率、单位时间内的平均交易笔数和成交量；该方法适合检测不同时间尺度上的非线性依赖。分析既考察每个序列本身，也考察这两种加密货币之间的关系。

作者报告称，所有指标都呈现多重分形结构，包括资产之间的交叉相关。将一种资产的序列在时间上平移，会部分削弱短尺度交叉相关，但不会将其消除；无论将哪种资产视为领先，均未发现定性差异。在足够长的时间尺度上，同时和滞后的交叉相关达到相同幅度。本文描述的是统计发现，而非交易策略；研究未提供预测检验、样本详情，也没有证据表明测得的依赖关系能够转化为净收益。

核心观点

  • 分析涵盖比特币和以太币的收益率、交易笔数和成交量。
  • 研究使用多重分形去趋势交叉相关分析来考察非线性时间序列依赖。
  • 作者发现，单个序列和跨资产关系都呈现多重分形结构。
  • 将一种资产的序列在时间上平移，会部分削弱短尺度交叉相关，但不会将其消除。
  • 在长时间尺度上，同时和滞后的交叉相关幅度趋于一致；研究未报告领先方向存在定性不对称。

标签

加密资产统计学市场微观结构高频交易
全文
# Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time


# Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time









Unlike price fluctuations, the temporal structure of cryptocurrency trading has seldom been a subject of systematic study. In order to fill this gap, we analyse detrended correlations of the price returns, the average number of trades in time unit, and the traded volume based on high-frequency data representing two major cryptocurrencies: bitcoin and ether. We apply the multifractal detrended cross-correlation analysis, which is considered the most reliable method for identifying nonlinear correlations in time series. We find that all the quantities considered in our study show an unambiguous multifractal structure from both the univariate (auto-correlation) and bivariate (cross-correlation) perspectives. We looked at the bitcoin--ether cross-correlations in simultaneously recorded signals, as well as in time-lagged signals, in which a time series for one of the cryptocurrencies is shifted with respect to the other. Such a shift suppresses the cross-correlations partially for short time scales, but does not remove them completely. We did not observe any qualitative asymmetry in the results for the two choices of a leading asset. The cross-correlations for the simultaneous and lagged time series became the same in magnitude for the sufficiently long scales.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。