Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method

Yao Hongxing () and Lu Yunxia ()
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Yao Hongxing: School of Finance and Economics, Jiangsu University, Zhenjiang212013, China
Lu Yunxia: Faculty of Science, Jiangsu University, Zhenjiang212013, China

Journal of Systems Science and Information, 2017, vol. 5, issue 5, 446-461

Abstract: In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange (SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks.

Keywords: correlation coefficient; local structural centrality; potentially influential stocks; local information similarity index; path similarity index (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:5:y:2017:i:5:p:446-461:n:5

DOI: 10.21078/JSSI-2017-446-16

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