Identifying Highly Correlated Stocks Using the Last Few Principal Components

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.

MoreLess

Year of publication:	2015-03-31
Authors:	Yang, Libin ; Rea, William ; Rea, Alethea
Institutions:	Department of Economics and Finance, College of Business and Economics
Subject:	Principal component analysis \| stock selection \| diversification \| stock portfolios

freely available

Full text |

More access options

Check Google Scholar

In German libraries (KVK)

I need help

More details

Extent:	application/pdf
Series:	Working Papers in Economics.
Type of publication:	Book / Working Paper
Notes:	15 pages
Classification:	G11 - Portfolio Choice
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011252563