An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection

Author

Chen, Wei

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-06-26

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

Portfolio selection is an important issue for researchers and practitioners.

In this paper, underthe assumption that security returns are given by experts’ evaluations rather than historical data,we discuss the portfolio adjusting problem which takes transaction costs and diversification degree ofportfolio into consideration.

Uncertain variables are employed to describe the security returns.

In theproposed mean-variance-entropy model, the uncertain mean value of the return is used to measureinvestment return, the uncertain variance of the return is used to measure investment risk, and theentropy is used to measure diversification degree of portfolio.

In order to solve the proposed model,a modified artificial bee colony (ABC) algorithm is designed.

Finally, a numerical example is givento illustrate the modelling idea and the effectiveness of the proposed algorithm.

American Psychological Association (APA)

Chen, Wei. 2014. An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050166

Modern Language Association (MLA)

Chen, Wei. An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1050166

American Medical Association (AMA)

Chen, Wei. An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050166

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1050166