×

A novel algorithm for uncertain portfolio selection. (English) Zbl 1138.91449

Summary: 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.

MSC:

91G10 Portfolio theory
PDF BibTeX XML Cite
Full Text: DOI Link

References:

[1] Markowitz, H., Portfolio selection, J. finance, 7, 1, 77-91, (1952)
[2] Markowitz, H., Portfolio selection: efficient diversification of investments, (1959), Wiley New York
[3] Markowitz, H., Mean-variance analysis in portfolio choice and capital market, (1987), Basil Blackwell New York · Zbl 0757.90003
[4] Elton, E.J.; Gruber, M.J., Modern portfolio theory and investment analysis, (1995), Wiley New York
[5] Elton, E.J.; Gruber, M.J.; Urich, T.J., Are betas best?, J. finance, 33, 5, 1357-1384, (1978)
[6] Tanaka, H.; Guo, P., Possibilistic data analysis for operations research, (2001), Physica-Verlag New York
[7] Yoon, K.P., A probabilistic approach to rank complex fuzzy numbers, Fuzzy sets syst., 80, 2, 167-176, (1996)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.