This paper investigates the temporal patterns of activity in the cryptocurrency market with a focus on bitcoin, ether, dogecoin, and winklink from January 2020 to December 2022. Market activity measures - logarithmic returns, volume, and transaction number, sampled every 10 seconds, were divided into intraday and intraweek periods and then further decomposed into recurring and noise components via correlation matrix formalism. The key findings include the distinctive market behavior from traditional stock markets due to the nonexistence of trade opening and closing. This was manifest in three enhanced-activity phases aligning with Asian, European, and US trading sessions. An intriguing pattern of activity surge in 15-minute intervals, particularly at full hours, was also noticed, implying the potential role of algorithmic trading. Most notably, recurring bursts of activity in bitcoin and ether were identified to coincide with the release times of significant US macroeconomic reports such as Nonfarm payrolls, Consumer Price Index data, and Federal Reserve statements. The most correlated daily patterns of activity occurred in 2022, possibly reflecting the documented correlations with US stock indices in the same period. Factors that are external to the inner market dynamics are found to be responsible for the repeatable components of the market dynamics, while the internal factors appear to be substantially random, which manifests itself in a good agreement between the empirical eigenvalue distributions in their bulk and the random matrix theory predictions expressed by the Marchenko-Pastur distribution. The findings reported support the growing integration of cryptocurrencies into the global financial markets.

翻译：本文研究了2020年1月至2022年12月期间加密货币市场活动的时序模式，重点关注比特币、以太坊、狗狗币和Winklink。以10秒为采样间隔获取的市场活动指标——对数收益率、交易量和交易笔数——被划分为日内和跨周时段，随后通过相关矩阵形式进一步分解为规律性成分与噪声成分。关键发现包括：由于不存在传统股票市场的开盘与收盘机制，加密货币市场呈现出独特的市场行为特征。这一现象具体表现为三个与亚洲、欧洲和美国交易时段相对应的活跃度增强阶段。研究还注意到每15分钟间隔内出现的奇特活跃激增模式（尤其在整点时刻），暗示了算法交易可能发挥的作用。最值得注意的是，比特币和以太坊的规律性活跃爆发与美国重要宏观经济报告（如非农就业数据、消费者价格指数数据和美联储声明）的发布时间高度吻合。2022年出现了关联度最高的日度活跃模式，这可能反映了同期与美股指数已证实的相关性。研究发现，外部因素（而非内部市场动态）主导了市场动态中的可重复成分，而内部因素则呈现出显著的随机性，这表现为经验特征值分布的主体部分与随机矩阵理论预测的Marchenko-Pastur分布高度吻合。这些发现支持了加密货币与全球金融市场日益融合的趋势。