An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection

• Published in: TheScientificWorld Vol. 2014; no. 2014; pp. 1 - 12
• Main Author: Chen, Wei
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2014; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Economic models; Entropy; Expected values; Fuzzy logic; Fuzzy sets; Heuristic; Investment policy; Investments; Mathematical optimization; Methods; Models, Theoretical; Portfolio management; Random variables; Science; Securities markets; Social sciences; Theory; Uncertainty
• ISSN: 2356-6140; 1537-744X; 1537-744X
• DOI: 10.1155/2014/578182

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.