期刊
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 46, 期 14, 页码 2510-2519出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2013.871366
关键词
portfolio selection; uncertain programming; genetic algorithm; uncertainty theory; investment
类别
资金
- National Natural Science Foundation [61273044]
- Key Project of Hubei Provincial Natural Science Foundation [2012FFA065]
- Scientific and Technological Innovation Team Project of Hubei Provincial Department of Education [T201110]
- Excellent Doctoral Dissertation Cultivation Grant from Central China Normal University, China [2013YBYB41]
In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.
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