A Novel Hybrid Model for Portfolio Selection
Resource
Applied Mathematics and Computation 169 (2): 1195-1210
Journal
Applied Mathematics and Computation
Journal Volume
169
Journal Issue
2
Pages
1195-1210
Date Issued
2005
Date
2005
Author(s)
Abstract
As we know, the performance of the mean-variance approach depends on the accurate forecast of the return rate. However, the conventional method (e.g. arithmetic mean or regression-based method) usually cannot obtain a satisfied solution especially under the small sample situation. In this paper, the proposed method which incorporates the grey and possibilistic regression models formulates the novel portfolio selection model. In order to solve the multi-objective quadric programming problem, multi-objective evolution algorithms (MOEA) is employed. A numerical example is also illustrated to show the procedures of the proposed method. On the basis of the numerical results, we can conclude that the proposed method can provide the more flexible and accurate results. © 2004 Elsevier Inc. All rights reserved.
Subjects
Grey model; Mean-variance approach; Multi-objective evolution algorithms (MOEA); Portfolio selection; Possibilistic regression model
Other Subjects
Computer programming; Regression analysis; Grey model; Mean-variance approach; Multi-objective evolution algorithm (MOEA); Portfolio selection; Possibilistic regression model; Mathematical models
Type
journal article
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