英文标题：
《Clustering patterns in efficiency and the coming-of-age of the
  cryptocurrency market》
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作者：
Higor Y. D. Sigaki, Matjaz Perc, Haroldo V. Ribeiro
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最新提交年份：
2019
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英文摘要：
  The efficient market hypothesis has far-reaching implications for financial trading and market stability. Whether or not cryptocurrencies are informationally efficient has therefore been the subject of intense recent investigation. Here, we use permutation entropy and statistical complexity over sliding time-windows of price log returns to quantify the dynamic efficiency of more than four hundred cryptocurrencies. We consider that a cryptocurrency is efficient within a time-window when these two complexity measures are statistically indistinguishable from their values obtained on randomly shuffled data. We find that 37% of the cryptocurrencies in our study stay efficient over 80% of the time, whereas 20% are informationally efficient in less than 20% of the time. Our results also show that the efficiency is not correlated with the market capitalization of the cryptocurrencies. A dynamic analysis of informational efficiency over time reveals clustering patterns in which different cryptocurrencies with similar temporal patterns form four clusters, and moreover, younger currencies in each group appear poised to follow the trend of their \'elders\'. The cryptocurrency market thus already shows notable adherence to the efficient market hypothesis, although data also reveals that the coming-of-age of digital currencies is in this regard still very much underway.
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中文摘要：
有效市场假说对金融交易和市场稳定有着深远的影响。因此，加密货币是否具有信息效率一直是最近密集调查的主题。在这里，我们使用排列熵和价格对数收益滑动时间窗口上的统计复杂性来量化400多种加密货币的动态效率。我们认为，当这两个复杂性度量值在统计上与随机洗牌数据的值不可区分时，加密货币在时间窗口内是有效的。我们发现，在我们的研究中，37%的加密货币在80%以上的时间内保持有效，而20%的加密货币在不到20%的时间内保持信息有效。我们的结果还表明，效率与加密货币的市值无关。对信息效率随时间变化的动态分析揭示了集群模式，即具有相似时间模式的不同加密货币形成四个集群，此外，每组中较年轻的货币似乎都倾向于跟随其“年长者”的趋势。因此，加密货币市场已经显示出对有效市场假说的显著坚持，尽管数据还显示，数字货币在这方面的到来仍在进行中。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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