Portfolio Selection Using Tikhonov Filtering to Estimate the Covariance Matrix

TitlePortfolio Selection Using Tikhonov Filtering to Estimate the Covariance Matrix
Publication TypeJournal Articles
Year of Publication2010
AuthorsPark S, O'Leary DP
JournalSIAM Journal on Financial Mathematics
Volume1
Pagination932 - 961
Date Published2010///
Keywordscovariance matrix estimate, Markowitz portfolio selection, ridge regression, Tikhonov regularization
Abstract

Markowitz's portfolio selection problem chooses weights for stocks in a portfolio based on an estimated covariance matrix of stock returns. Our study proposes reducing noise in the estimation by using a Tikhonov filter function. In addition, we prevent rank deficiency of the estimated covariance matrix and propose a method for effectively choosing the Tikhonov parameter, which determines the filtering intensity. We put previous estimators into a common framework and compare their filtering functions for eigenvalues of the correlation matrix. We demonstrate the effectiveness of our estimator using stock return data from 1958 through 2007.

URLhttp://link.aip.org/link/?SJF/1/932/1
DOI10.1137/090749372