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A singular value decomposition approach for testing the efficiency of Bitcoin and Ethereum markets

机译:一种测试比特币和以外人市场效率的奇异值分解方法

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This letter revisits the informationally efficiency of the two major cryptocurrencies Bitcoin (2013- 2021) and Ethereum (2016-2021). The analysis is based on the computation of the singular value decomposition (SVD) entropy of a matrix formed by lagged vectors of price returns. The computed entropy is compared with a reference obtained from uncorrelated time series to decide whether the rows of the lagged matrix are uncorrelated. The procedure was implemented over a sliding window to assess the time variations of the entropy. The results show that the markets are informationally efficient most of time over different scales, except for some short periods that are linked to the 2016-2017 price-boom period and the 2020 Covid-19 economic downturn. (C) 2021 Elsevier B.V. All rights reserved.
机译:这封信重新评估了两大加密货币比特币(2013-2021)和Ethereum(2016-2021)的信息效率。 分析基于通过滞销矢量的矩阵矩阵的奇异值分解(SVD)熵的计算。 将计算的熵与从不相关的时间序列获得的参考进行比较,以确定滞后矩阵的行是不相关的。 该过程在滑动窗口上实现,以评估熵的时间变化。 结果表明,市场在不同尺度上的大部分时间都是有线比的,除了与2016-2017价格 - 繁荣时期和2020年的Covid-19经济衰退相关的一些短期。 (c)2021 elestvier b.v.保留所有权利。

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