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| Content Provider | Springer Nature Link |
|---|---|
| Author | Guigues, Vincent |
| Copyright Year | 2009 |
| Abstract | We recommend an implementation of the Markowitz problem to generate stable portfolios with respect to perturbations of the problem parameters. The stability is obtained proposing novel calibrations of the covariance matrix between the returns that can be cast as convex or quasiconvex optimization problems. A statistical study as well as a sensitivity analysis of the Markowitz problem allow us to justify these calibrations. Our approach can be used to do a global and explicit sensitivity analysis of a class of quadratic optimization problems. Numerical simulations finally show the benefits of the proposed calibrations using real data. |
| Starting Page | 553 |
| Ending Page | 579 |
| Page Count | 27 |
| File Format | |
| ISSN | 09266003 |
| Journal | Computational Optimization and Applications |
| Volume Number | 48 |
| Issue Number | 3 |
| e-ISSN | 15732894 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2009-06-17 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Markowitz model Sensitivity analysis Covariance matrix estimation Quadratic programming Semidefinite programming Convex and Discrete Geometry Operations Research, Mathematical Programming Optimization Statistics Operations Research/Decision Theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Control and Optimization Computational Mathematics |
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