发表机构
Yildiz Technical University; Case Western Reserve University（伊斯坦布尔耶尔德兹理工大学; 凯斯西储大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用皮尔逊相关和动态时间规整分析347种加密货币在2020-2024年的价格相似性，发现不同度量揭示不同的关联模式，对投资组合多样化有重要启示。
AI 中文摘要
加密货币市场的波动性和复杂的价格动态对投资组合多样化和风险管理构成挑战。本研究利用来自Binance API的每日OHLCV数据，考察了2020年3月至2024年4月期间347种加密货币的价格相似性。每日动态通过一个有符号的、有上限的日内价格区间指标进行概括，并使用皮尔逊互相关系数（捕捉给定滞后下的线性协同运动）和动态时间规整（DTW）距离（捕捉与滞后无关的形状相似性）来评估配对相似性。数据被划分为三个市场阶段：上升趋势、下跌趋势和随后的上升趋势。在每个时期，识别出互相关最高和DTW距离最低的10对货币。BNB-CAKE、XLM-XRP和MANA-SAND在三个时期中表现出最强的互相关，系数为0.78或更高，且在滞后0处相关性最大，表明同步运动。每个时期中，DTW距离最低的10对中有三到四对与互相关前10名重合，表明这两种度量相关但不可互换。两个同平台粉丝代币尽管互相关较弱，却位列DTW最相似对之一，而一种欧元挂钩资产和黄金支持代币显示出最低的DTW距离，这由低波动性而非共同动态驱动。结果表明存在显著的、依赖于度量的相互关联性，对多样化策略具有启示意义。
英文摘要
The cryptocurrency market's volatility and complex price dynamics challenge portfolio diversification and risk management. This study examines price similarity across 347 cryptocurrencies from March 2020 to April 2024 using daily OHLCV data from the Binance API. Daily dynamics are summarized via a signed, capped intraday price-range metric, and pair similarity is assessed using the Pearson cross-correlation coefficient, capturing linear co-movement at a given lag, and Dynamic Time Warping (DTW) distance, capturing shape similarity independent of lag. Data are segmented into three market phases: an uptrend, a decline, and a subsequent uptrend. For each period, the 10 pairs with highest cross-correlation and lowest DTW distance are identified. BNB-CAKE, XLM-XRP, and MANA-SAND show the strongest cross correlations across the three periods, with coefficients of 0.78 or higher and maximum correlations at lag 0, indicating synchronized movements. Three to four of the ten lowest-DTW pairs coincide with the cross-correlation top 10 per period, showing the measures are related but not interchangeable. Two same-platform fan tokens rank among the most DTW-similar pairs despite weak cross-correlation, while a euro pegged asset and gold-backed token show the lowest DTW distance, driven by low volatility rather than shared dynamics. Results demonstrate substantial, measure dependent interconnectedness with implications for diversification strategies.
