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A novel algorithm for uncertain portfolio selection
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AI
DOI：10.1016/j.amc.2005.04.074.png)
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Abstract
En 中文
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. (c) 2005 Elsevier Inc. All rights reserved.
Keywords:
mean-variance method
portfolio selection
possibilistic regression
Mellin transformation
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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