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J. Risk Financial Manag. 2018, 11(4), 88;

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

Department of Finance, Budapest University of Technology and Economics, Magyar tudosok krt. 2., 1117 Budapest, Hungary
Department of Economics, Janos Selye University, Hradná ul. 21., 94501 Komarno, Slovakia
Author to whom correspondence should be addressed.
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)
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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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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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Nagy, L.; Ormos, M. Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets. J. Risk Financial Manag. 2018, 11, 88.

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