Using intelligent methods in Solving Constrained Portfolio in Tehran Stock Exchange
Subject Areas : Financial Knowledge of Securities AnalysisEsmat Jamshdi Eyni 1 , Hamid Khaloozadeh 2
1 - کارشناس ارشد مهندسی برق، گروه کنترل، دانشگاه صنعتی خواجه نصیرالدین طوسی
2 - استاد دانشکده مهندسی برق، گروه کنترل، دانشگاه صنعتی خواجه نصیرالدین طوسی.
Keywords: portfolio, Conditional Value at Risk, Particle Swarm Optimization Al, Genetic algorithm, Imperialist Competitive Algori,
Abstract :
The optimal portfolio selection problem to find an optimal way to allocate a fixed amount of capital to a set of available assets which aims to maximize expected returns and minimize risk at the same time, to take place. In this Study is shown that an investor with n risky share, how to reach certain profits with minimal risk. Such a portfolio, efficient portfolio is called. For this purpose, the study of evolutionary algorithms, Genetic Algorithm, Imperialist Competitive Algorithm and Particle Swarm Optimization algorithm, also with regard to the basic constraints on the investment, we use these practical methods to solve the portfolio optimization problem. Practical results for the portfolio optimization problem in the Tehran Stock Exchange, of the30 company's active in the industry with the selection of20companies along with their validation, is obtained. Aims to help investors better and more practical to select different stocks and thus is an effective investment.
* تهرانی، رضا و سیری، علی (1388). کاربرد مدل سرمایهگذاری کارا با استفاده از تجزیه و تحلیل مدل مارکویتز.فصلنامه بورس اوراق بهادار، 6، 137-155.
* خالوزاده، حمید وامیری، نسیبه (1385). تعیین سبد سهام بهینه در بازار بورس ایران براساس نظریه ارزش در معرض ریسک. مجله تحقیقات اقتصادی، 73، 211-231.
* سجادی، زینب و فتحی، سعید (1392). ﺗﺒﯿﯿﻦ ﻓﺮاﯾﻨﺪ ﭼﻬﺎر ﮔﺎﻣﯽ ﻣﺤﺎﺳﺒﻪ ارزش در ﻣﻌﺮضﺧﻄﺮ ﺑﻪ ﻋﻨﻮان ﻣﻌﯿﺎری ﺑﺮای اﻧﺪازهﮔﯿﺮی رﯾﺴﮏ و ﭘﯿﺎدهﺳﺎزی آن در ﯾﮏ ﻣﺪل ﺑﻬﯿﻨﻪﺳﺎزی ﺳﺮﻣﺎﯾﻪﮔﺬاری، فصلنامه دانش مالی تحلیل اوراق بهادار، 20، 1-13.
* راعی، رضا و علی بیگی، هدایت (1389). بهینهسازی پرتفوی سهام با استفاده از روش حرکت تجمعی ذرات.مجله تحقیقات مالی، 29.
* گرکز، م.، عباسی ا. و مقدسی م.(1389). انتخاب و بهینهسازی سبد سهام با استفاده از الگوریتم ژنتیکبر اساس تعاریفی متفاوت از ریسک، فصلنامه مدیریت صنعتی دانشگاه آزاد سنندج، 11، 115-136.
* Anagnostopoulos, K.P., Mamanis, G. (2011). The mean–variance cardinality constrained portfolio optimization problem: An experimental evaluation of five multiobjective evolutionary algorithms, Expert Systems with Applications, 38, 14208-14217.
* Artzener, P.,Delbaen, F., Eber,J. M. & Health, D. (1992). Coherent Measures of Risk.Mathematical Finance,9, 203-228.
* Atashpaz-Gargari, E. (2008). A Decentralized PID Controller based on Optimal Shrinkage of Gershgorin based and PID Tuning using Colonial Competitive Algorithm, Information Journal of Innovative Computing, Information and Control (IJICIC), 353-376.
* Kennedy, J.&Eberhart, R. C. (1995).Particle Swarm Optimization.Presented at the in Proceeding of the 4th IEEE International Conference on Neural Networks.
* Lipinski, P. W. (2013). Portfolio selection models based on characteristics of return distributions, Faculty of Economic Sciences University of Warsaw, 14.
* Markowitz, H. M. (1952). Portfolio Selection.Journal of Finance, 7, 77-91.
* Ogryczak, W. &Sliwinski, T.(2010).Efficient Portfolio Optimization with Conditional Value at Risk.IEEE Proceeding of the 2010 International Multiconference Computer Science and Information Technology (IMCSIT), 901-908.
* Peng-Yeng, Y., Wang, J. Y. (2006). A Particle Swarm Optimization approach to the nonlinear resource allocation", Applied Mathematics Computation, 232-242.
* Rockafellar, R, T.&Uryasev, S. (2002). Conditional Value at Risk for general loss distribution.Journal of Banking and Finance, 26, 1443-1471.
* Torrubiano, R. R.(2012). Cardinality Constraints and Dimensionality Reduction inOptimization Problems. Ph.D. Dissertation, Dept. Computer Science,Universidad AUT_ONOMA de Madrid.
* Ye, Y.,Zhang, Z., Zeng, J. & Peng L. (2008).A fast and adaptive ICA algorithm with its application to fetal electrocardiogram extraction, Applied Mathematics and Computation, 205.
* Xu, R. T., Zhang, J., Liu, O. & Huang, R. Z. (2010).An Estimation of Distribution Algorithm Based Portfolio Selection Approach.IEEE International Conference on Technologies and Application of Artificial Intelligence (TAAI), 18-20.
* Wang, W., Wang, H., Wu, Z.& Dai, H. (2009). A Simple and Fast Particle Swarm Optimization and Its Application on Portfolio Selection.International Workshop on Intelligent Systems and Applications.