Thi T. Nguyen and Lee N. Gordon-Brown
Fuzzy Numbers and MCDM Methods for Portfolio Optimization
1593 - 1605
2012
6
12
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/7716
https://publications.waset.org/vol/72
World Academy of Science, Engineering and Technology
A new deployment of the multiple criteria decision
making (MCDM) techniques the Simple Additive Weighting
(SAW), and the Technique for Order Preference by Similarity to
Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in
this paper. Rather than exclusive reference to mean and variance as in
the traditional meanvariance method, the criteria used in this
demonstration are the first four moments of the portfolio distribution.
Each asset is evaluated based on its marginal impacts to portfolio
higher moments that are characterized by trapezoidal fuzzy numbers.
Then centroidbased defuzzification is applied to convert fuzzy
numbers to the crisp numbers by which SAW and TOPSIS can be
deployed. Experimental results suggest the similar efficiency of these
MCDM approaches to selecting dominant assets for an optimal
portfolio under higher moments. The proposed approaches allow
investors flexibly adjust their risk preferences regarding higher
moments via different schemes adapting to various (from
conservative to risky) kinds of investors. The other significant
advantage is that, compared to the meanvariance analysis, the
portfolio weights obtained by SAW and TOPSIS are consistently
welldiversified.
Open Science Index 72, 2012