Fuzzy Adaptive PSO Approach for Portfolio Optimization Problem

被引:0
作者
Soleimanivareki, M. [1 ]
Fakharzadeh, A. J. [2 ]
Poormoradi, M. [3 ]
机构
[1] Islamic Azad Univ, Dept Math, Ayatollah Amoli Branch, Amol, Iran
[2] Shiraz Univ Technol, Fac Basic Sci, Dept Math, Shiraz, Iran
[3] Inst High Educ Samangan Amol, Amol, Iran
来源
JOURNAL OF MATHEMATICS AND COMPUTER SCIENCE-JMCS | 2014年 / 12卷 / 03期
关键词
portfolio optimization; fuzzy adaptive particle swarm optimization; mean-variance model; the efficient frontier;
D O I
10.22436/jmcs.012.03.07
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The mean-variance model of Markowitz is the most common and popular approach in the investment selection; besides, the mathematical planning model proposed by Markowitz is the most effective method of the optimal portfolio selection. However, if there are a lot of investing assets and a lot of market's restrictions, the common optimizing methods are not useful. Moreover, the portfolio optimization problem cannot be solved easily by applying the mathematical methods. In the present study, the heuristic Fuzzy Adaptive Particle Swarm Optimization (PSO) method is proposed to solve three highly applied models of the portfolio problem. Therefore, to fulfil this task the efficient frontier of the investment is drawn by applying the price information of the 50 shares accepted in Tehran stock market from October of 2009 to October of 2013. Results of this study manifest the efficiency of the used method in relation to other heuristic methods.
引用
收藏
页码:235 / 242
页数:8
相关论文
共 10 条
[1]   Multiperiod portfolio optimization models in stochastic markets using the mean-variance approach [J].
Celikyurt, U. ;
Ozekici, S. .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 179 (01) :186-202
[2]  
Chiam S.C., 2008, EXPERT SYSTEMS APPL, P3695
[3]   Particle swarm optimization approach to portfolio optimization [J].
Cura, Tunchan .
NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS, 2009, 10 (04) :2396-2406
[4]   Portfolio selection using neural networks [J].
Fernandez, Alberto ;
Gomez, Sergio .
COMPUTERS & OPERATIONS RESEARCH, 2007, 34 (04) :1177-1191
[5]   Adaptive fuzzy particle swarm optimization for global optimization of multimodal functions [J].
Juang, Yau-Tarng ;
Tung, Shen-Lung ;
Chiu, Hung-Chih .
INFORMATION SCIENCES, 2011, 181 (20) :4539-4549
[6]   MEAN-ABSOLUTE DEVIATION PORTFOLIO OPTIMIZATION MODEL AND ITS APPLICATIONS TO TOKYO STOCK-MARKET [J].
KONNO, H ;
YAMAZAKI, H .
MANAGEMENT SCIENCE, 1991, 37 (05) :519-531
[7]   Heuristic algorithms for the portfolio selection problem with minimum transaction lots [J].
Mansini, R ;
Speranza, MG .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1999, 114 (02) :219-233
[8]   PORTFOLIO SELECTION [J].
Markowitz, Harry .
JOURNAL OF FINANCE, 1952, 7 (01) :77-91
[9]   Multi-period semi-variance portfolio selection: Model and numerical solution [J].
Yan, Wei ;
Miao, Rong ;
Li, Shurong .
APPLIED MATHEMATICS AND COMPUTATION, 2007, 194 (01) :128-134
[10]   A particle swarm optimization approach to the nonlinear resource allocation problem [J].
Yin, Peng-Yeng ;
Wang, Jing-Yu .
APPLIED MATHEMATICS AND COMPUTATION, 2006, 183 (01) :232-242