This paper investigates the temporal patterns of activity in the cryptocurrency market with a focus on Bitcoin, Ethereum, 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 U.S. 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 U.S. 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 U.S. 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月期间以比特币、以太坊、狗狗币和WINkLink为重点的加密货币市场活动的时间模式。市场活动指标——对数收益率、交易量和交易次数（每10秒采样一次）被划分为日内和周内时段，并通过相关矩阵形式进一步分解为规律性和噪声成分。主要发现包括：由于不存在交易开盘和收盘，加密货币市场展现出与传统股票市场截然不同的行为特征。这体现在与亚洲、欧洲和美国交易时段相对应的三个增强活跃阶段。研究还注意到每15分钟间隔内（尤其是整点时刻）出现有趣的活动激增模式，暗示了算法交易可能发挥的作用。最显著的是，比特币和以太坊中反复出现的活跃爆发与美国重大宏观经济报告（如非农就业数据、消费者价格指数数据和美联储声明）的发布时间相吻合。2022年出现了相关性最高的日度活跃模式，这可能反映了同期与美股指数记录到的相关性。研究发现，外部市场动态因素是造成市场动态可重复成分的主要原因，而内部因素则表现出显著的随机性，这体现在经验特征值分布的体部与Marchenko-Pastur分布所表达的随机矩阵理论预测高度一致。这些发现支持了加密货币日益融入全球金融市场的趋势。