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.