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Article

Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets

1
Department of Finance, Budapest University of Technology and Economics, Magyar tudosok krt. 2., 1117 Budapest, Hungary
2
Department of Economics, Janos Selye University, Hradná ul. 21., 94501 Komarno, Slovakia
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2018, 11(4), 88; https://doi.org/10.3390/jrfm11040088
Received: 3 November 2018 / Revised: 7 December 2018 / Accepted: 11 December 2018 / Published: 13 December 2018
(This article belongs to the Special Issue Mathematical Finance with Applications)
This paper introduces a spectral clustering-based method to show that stock prices contain not only firm but also network-level information. We cluster different stock indices and reconstruct the equity index graph from historical daily closing prices. We show that tail events have a minor effect on the equity index structure. Moreover, covariance and Shannon entropy do not provide enough information about the network. However, Gaussian clusters can explain a substantial part of the total variance. In addition, cluster-wise regressions provide significant and stationer results. View Full-Text
Keywords: cluster analysis; equity index networks; machine learning cluster analysis; equity index networks; machine learning
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MDPI and ACS Style

Nagy, L.; Ormos, M. Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets. J. Risk Financial Manag. 2018, 11, 88. https://doi.org/10.3390/jrfm11040088

AMA Style

Nagy L, Ormos M. Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets. Journal of Risk and Financial Management. 2018; 11(4):88. https://doi.org/10.3390/jrfm11040088

Chicago/Turabian Style

Nagy, László, and Mihály Ormos. 2018. "Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets" Journal of Risk and Financial Management 11, no. 4: 88. https://doi.org/10.3390/jrfm11040088

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