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Information 2018, 9(11), 276; https://doi.org/10.3390/info9110276

Linkage Effects Mining in Stock Market Based on Multi-Resolution Time Series Network

1
School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
2
East Sea Information Center, SOA China, Shanghai 200136, China
*
Author to whom correspondence should be addressed.
Received: 27 September 2018 / Revised: 29 October 2018 / Accepted: 5 November 2018 / Published: 8 November 2018
(This article belongs to the Section Information Processes)
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Abstract

Previous research on financial time-series data mainly focused on the analysis of market evolution and trends, ignoring its characteristics in different resolutions and stages. This paper discusses the evolution characteristics of the financial market in different resolutions, and presents a method of complex network analysis based on wavelet transform. The analysis method has proven the linkage effects of the plate sector in China’s stock market and has that found plate drift phenomenon occurred before and after the stock market crash. In addition, we also find two different evolutionary trends, namely the W-type and M-type trends. The discovery of linkage plate and drift phenomena are important and referential for enterprise investors to build portfolio investment strategy, and play an important role for policy makers in analyzing evolution characteristics of the stock market. View Full-Text
Keywords: wavelet; resolution; network; evolution; trend; linkage effect; drift phenomenon wavelet; resolution; network; evolution; trend; linkage effect; drift phenomenon
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Xu, L.; Xu, H.; Yu, J.; Wang, L. Linkage Effects Mining in Stock Market Based on Multi-Resolution Time Series Network. Information 2018, 9, 276.

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