A novel algorithm for uncertain portfolio selection
Resource
Applied Mathematics and Computation 173 (1): 350-359
Journal
Applied Mathematics and Computation
Journal Volume
173
Journal Issue
1
Pages
350-359
Date Issued
2006
Date
2006
Author(s)
Abstract
In this paper, the conventional mean-variance method is revised to determine the optimal portfolio selection under the uncertain situation. The possibilistic area of the return rate is first derived using the possibisitic regression model. Then, the Mellin transformation is employed to obtain the mean and the risk by considering the uncertainty. Next, the revised mean-variance model is proposed to deal with the problem of uncertain portfolio selection. In addition, a numerical example is used to demonstrate 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 than the conventional method under the uncertain portfolio selection situation. © 2005 Elsevier Inc. All rights reserved.
Subjects
Mean-variance method; Mellin transformation; Portfolio selection; Possibilistic regression
Other Subjects
Mathematical models; Mathematical transformations; Numerical methods; Problem solving; Regression analysis; Mean-variance methods; Mellin transformations; Portfolio selection; Possibilistic regression; Algorithms
Type
journal article
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