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Identifying Highly Correlated Stocks Using the Last Few Principal Components

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Listed:
  • Libin Yang
  • William Rea
  • and Alethea Rea

Abstract

We show that the last few components in principal component analysis of the correlation matrix of a group of stocks may contain useful financial information by identifying highly correlated pairs or larger groups of stocks. The results of this type of analysis can easily be included in the information an investor uses to manage their portfolio.

Suggested Citation

  • Libin Yang & William Rea & and Alethea Rea, 2015. "Identifying Highly Correlated Stocks Using the Last Few Principal Components," Papers 1512.03537, arXiv.org.
    • Handle: RePEc:arx:papers:1512.03537
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    References listed on IDEAS

    as
    1. Dong-Hee Kim & Hawoong Jeong, 2005. "Systematic analysis of group identification in stock markets," Papers physics/0503076, arXiv.org, revised Oct 2005.
    2. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    3. Driessen, J.J.A.G. & Melenberg, B. & Nijman, T.E., 2003. "Common factors in international bond returns," Other publications TiSEM 06a83942-b625-4d3c-808c-a, Tilburg University, School of Economics and Management.
    4. Perignon, Christophe & Smith, Daniel R. & Villa, Christophe, 2007. "Why common factors in international bond returns are not so common," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 284-304, March.
    5. Driessen, Joost & Melenberg, Bertrand & Nijman, Theo, 2003. "Common factors in international bond returns," Journal of International Money and Finance, Elsevier, vol. 22(5), pages 629-656, October.
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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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