| Article ID: | iaor20031282 |
| Country: | Japan |
| Volume: | 11 |
| Issue: | 2 |
| Start Page Number: | 63 |
| End Page Number: | 75 |
| Publication Date: | Jun 2001 |
| Journal: | Transactions of the Japan Society for Industrial and Applied Mathematics |
| Authors: | Yabe Hiroshi, Numata Kazumiti, Hattori Tomoyuki |
| Keywords: | optimization, programming: fractional, programming: mathematical, programming: nonlinear, programming: parametric, programming: quadratic |
In this paper, we consider the maximum probability model and the mean variance model, which arise in portfolio selection problems. We discuss the relationship between the optimality conditions of these two problems, and we propose a method for solving the maximum probability model effectively. Specifically, our new method applies the Goldfarb–Idnani method, which is an effective method for a strictly convex quadratic programming problem, to a kind of parametric quadratic programming problem. Some numerical experiments show good performance of our method.