结构分解视角下股市波动与政策事件关系的实证研究

所属分类:人工智能/神经网络/深度学习
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上传日期:2019-12-24 19:05:21
上 传 者南嘉
说明:  EEMD 作为前沿的时频分析方法,反映序列自身的尺度特征,通过对序列进行自适应分解,可以揭示序列波动的内在结构特征。本文采用 EEMD 方法分析上证综指发现上证综指主要是由高频分量、低频分量和趋势项分量组合而成,国内股市频繁剧烈的波动主要体现在高频分量和低频分量水平上。
(As a cutting-edge time-frequency analysis method, EEMD reflects the scale characteristics of the sequence itself. By adaptively decomposing the sequence, the inherent structural characteristics of the sequence fluctuation can be revealed. This article uses the EEM method to analyze the Shanghai Composite Index. It is found that the Shanghai Composite Index is mainly composed of high-frequency components, low-frequency components, and trend components. Frequent and violent domestic stock market fluctuations are mainly reflected in the high-frequency and low-frequency components.)

文件列表:
结构分解视角下股市波动与政策事件关系的实证研究_基于EEMD算法_姚卫东.caj (367529, 2019-02-19)

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