Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1137/090749372 | SIAM J. Financial Math. |
Keywords | Field | DocType |
tikhonov filter function,rank deficiency,common framework,stock return,previous estimator,stock return data,tikhonov parameter,correlation matrix,estimated covariance matrix,portfolio selection,portfolio selection problem,covariance matrix,ridge regression,tikhonov regularization | Tikhonov regularization,Covariance function,Mathematical optimization,Estimation of covariance matrices,Portfolio optimization,Covariance matrix,Eigenvalues and eigenvectors,Mathematics,Covariance,Estimator | Journal |
Volume | Issue | ISSN |
1 | 1 | 1945-497X |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungwoo Park | 1 | 233 | 22.06 |
| O'Leary, Dianne P. | 2 | 1064 | 222.93 |