Sensitivity analysis and calibration of the covariance matrix for stable portfolio selection Export

@article{citeulike:4931114, abstract = {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.}, author = {Guigues, Vincent}, citeulike-article-id = {4931114}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s10589-009-9260-7}, citeulike-linkout-1 = {http://www.springerlink.com/content/90gt00416p46273u}, doi = {10.1007/s10589-009-9260-7}, journal = {Computational Optimization and Applications}, keywords = {economic, math}, posted-at = {2009-06-23 07:55:01}, priority = {2}, title = {Sensitivity analysis and calibration of the covariance matrix for stable portfolio selection}, url = {http://dx.doi.org/10.1007/s10589-009-9260-7} }

TY - JOUR ID - citeulike:4931114 L3 - citeulike-article-id:4931114 N2 - 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. JF - Computational Optimization and Applications TI - Sensitivity analysis and calibration of the covariance matrix for stable portfolio selection KW - economic KW - math AU - Guigues, Vincent UR - http://dx.doi.org/10.1007/s10589-009-9260-7 ER -