Identifying Highly Correlated Stocks Using the Last Few Principal Components

Libin Yang, William Rea and Alethea Rea

Working Papers in Economics from University of Canterbury, Department of Economics and Finance

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.

Keywords: Principal component analysis; stock selection; diversification; stock portfolios (search for similar items in EconPapers)
JEL-codes: G11 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2015-03-31
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://repec.canterbury.ac.nz/cbt/econwp/1508.pdf (application/pdf)

Related works:
Working Paper: Identifying Highly Correlated Stocks Using the Last Few Principal Components (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cbt:econwp:15/08

Access Statistics for this paper

More papers in Working Papers in Economics from University of Canterbury, Department of Economics and Finance Private Bag 4800, Christchurch, New Zealand. Contact information at EDIRC.
Bibliographic data for series maintained by Albert Yee ().