@article {15788,
	title = {Portfolio Selection Using Tikhonov Filtering to Estimate the Covariance Matrix},
	journal = {SIAM Journal on Financial Mathematics},
	volume = {1},
	year = {2010},
	month = {2010///},
	pages = {932 - 961},
	abstract = {Markowitz{\textquoteright}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.},
	keywords = {covariance matrix estimate, Markowitz portfolio selection, ridge regression, Tikhonov regularization},
	doi = {10.1137/090749372},
	url = {http://link.aip.org/link/?SJF/1/932/1},
	author = {Park,Sungwoo and O{\textquoteright}Leary, Dianne P.}
}
