Fuzzy Mathematical Models in Engineering and Management Science
Fuzzy Mathematical Models in Engineering and Management Science
A new perspective for optimal portfolio selection with random fuzzy returns
Information Sciences: an International Journal
A fuzzy goal programming approach with priority for channel allocation problem in steel industry
Expert Systems with Applications: An International Journal
Asset portfolio optimization using fuzzy mathematical programming
Information Sciences: an International Journal
Fuzzy multiple goal programming applied to TFT-LCD supplier selection by downstream manufacturers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Robust portfolio selection based on a joint ellipsoidal uncertainty set
Optimization Methods & Software
A computational study on robust portfolio selection based on a joint ellipsoidal uncertainty set
Mathematical Programming: Series A and B
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Selection of Socially Responsible Portfolios using Goal Programming and fuzzy technology
Information Sciences: an International Journal
Hybrid optimization models of portfolio selection involving financial and ethical considerations
Knowledge-Based Systems
Hi-index | 12.05 |
This paper develops models for selecting portfolios for conventional and socially responsible investment (SRI) mutual funds according to the preferences of the SRI investor. This involves constructing an investment portfolio that takes into account both financial and social, environmental and ethical (SEE) criteria. The optimal portfolio selection problem is solved when the expected returns of the assets as well as the periodic returns are not precisely known. Instead, incomplete information on the parameters of the model is modeled by fuzzy numbers, which include the 'true' values and are consistent with the Decision Maker's beliefs on assets' performance. In this paper, the financial criteria taken into account are the expected return and the difference between the returns of the portfolio and a pre-specified benchmark index i.e. a strategy of tracking error (TE) is followed. Moreover, we assume that the investor's preferences about SEE features of the portfolio are imprecisely known. In order to model these flexible preferences we propose to use fuzzy decision making. The multidimensional nature of the problem leads us to work with techniques of multiple criteria decision making (MCDM), namely goal programming (GP), and the incomplete information is handled by a fuzzy robust approach. The proposed fuzzy goal programming (FGP) model is applied to a database of UK mutual funds.