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MULTISCALE ENTROPY ANALYSIS OF FINANCIAL TIME SERIES

机译:金融时间序列的多尺度熵分析

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The paper mainly applies the multiscale entropy (MSE) to analyze the financial time series. The MSE is used to examine the complexity of a quantified system. Based on MSE, we propose multiscale cross-sample entropy (MSCE) to analyze the complexity and correlation of two time series. By comparing with the results, we find that both results present remarkable scaling characterization and the value of each log return of financial time series decreases with a increasing scale factor. From the results of MSE, we also find that the entropy of the Europe markets is lower than that of the Asia, but higher than that of the Americas. It means the MSE can distinguish different areas markets. The results of MSCE show that financial plate have high synchrony with the plate of Electron, IT and Realty. The MSCE can distinguish the highly synchronous plates.
机译:本文主要应用多尺度熵(MSE)分析金融时间序列。 MSE用于检查量化系统的复杂性。基于MSE,我们提出了多尺度交叉样本熵(MSCE)来分析两个时间序列的复杂性和相关性。通过与结果进行比较,我们发现这两个结果都呈现出显着的规模特征,并且财务时间序列的每个对数回报的值都随着规模因子的增加而减小。从MSE的结果来看,我们还发现欧洲市场的熵值低于亚洲,但高于美洲。这意味着MSE可以区分不同地区的市场。 MSCE的结果表明,金融板块与Electron,IT和Realty板块具有高度同步性。 MSCE可以区分高度同步的板。

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