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TRAFST Vol.7 No.2 pp. 92-99

Review:

Group Correlation Structures Embedded in Financial Markets – Comparative Study Between Japan and U.S.

Takeo YOSHIKAWA*1 and Hiroshi IYETOMI*2

*1Graduate School of Science and Technology, Niigata University, 8050, ikarashi 2-no-cho, Nishi-ku, Niigata

*2Faculty of Science, Niigata University, 8050, ikarashi 2-no-cho, Nishi-ku, Niigata

Received:
28 July 2013
Accepted:
6 September 2013
Published:
October 15, 2013
Keywords:
principal component analysis, financial market, RMT: Random Matrix Theory, group correlation, network, frustration
Abstract

We study group correlation structures of financial markets in Japan and U.S. from a network-theoretic point of view. The correlationmatrix of stock price changes, purified by the random matrix theory, is regarded as an adjacency matrix for a network. The weighted links in the networks thus constructed can have negative sign corresponding to anticorrelation between stocks. To identify groups in such a network, we search for the optimum decomposition of nodes which maximizes the total sum of weights of links inside groups. We then find that the network of Tokyo Stock Exchange is decomposed into four groups. The stock prices comove almost perfectly inside the groups and move oppositely across the groups. Also we apply the same analysis to the S&P 500 stocks. The U.S. stock market shows frustrated behavior similar to that embedded in the Japanese market.

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Last updated on Aug. 19, 2017