NDLI: Comparative Research of Portfolio Model Using Fuzzy Theory

Content Provider	IEEE Xplore Digital Library
Author	Liu Yan-chun Gao Chuang Sun Liang
Copyright Year	2007
Description	Author affiliation: LiaoNing Univ., Liaoning (Liu Yan-chun; Gao Chuang; Sun Liang)
Abstract	By discussing both linear and nonlinear fuzzy situations, we give the relevant model and the solution method. First of all, regarding the target level of investment return and investment risk as the half trapezoidal fuzzy number, we give the fuzzy portfolio selection model of linear satisfaction degree. Then, to describe the investor satisfaction degree of investment return and investment risk better, a logarithmic membership function has been imported. Following, we give the fuzzy portfolio selection model of nonlinear satisfaction degree. Nonlinear optimize model can be transferred to linear programming model, so that model calculation has been simplified significantly. Finally, according to the actual data of Chinese securities market, both of models have been compared by using genetic algorithm. Result indicates that portfolio selection model based on linear and nonlinear membership function includes not only historical data, but also investors' expectation. That accords with human psychology and fact. However, by adopting the nonlinear membership function and adjusting its parameter, it can furthest get portfolio that accords with investor's expectation. Therefore, nonlinear membership function is better than linear membership function.
Starting Page	2091
Ending Page	2096
File Size	488482
Page Count	6
File Format	PDF
ISBN	9787560322780
DOI	10.1109/ICMSE.2007.4422148
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	HARBIN INSTITUTE OF TEC
Subject Keyword	Data security Humans Psychology Conference management Linear programming logistic membership function linear membership function Genetic algorithms Engineering management Investments Decision theory portfolio selection problem fuzzy system Portfolios
Content Type	Text
Resource Type	Article

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