Identifying Highly Correlated Stocks Using the Last Few Principal Components

Libin Yang, William Rea and and Alethea Rea

Papers from arXiv.org

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.

Date: 2015-12
New Economics Papers: this item is included in nep-rmg
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http://arxiv.org/pdf/1512.03537 Latest version (application/pdf)

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Working Paper: Identifying Highly Correlated Stocks Using the Last Few Principal Components (2015)
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