How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

被引:18
作者
Gu, Rongbao [1 ]
Shao, Yanmin [2 ]
机构
[1] Nanjing Univ Finance & Econ, Sch Finance, Nanjing 210046, Jiangsu, Peoples R China
[2] Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Stock market; Prediction; DCCA; Entropy; CROSS-CORRELATIONS; GRANGER CAUSALITY; MODELS;
D O I
10.1016/j.physa.2016.02.030
中图分类号
O4 [物理学];
学科分类号
070305 [高分子化学与物理];
摘要
In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:150 / 161
页数:12
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