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International Journal of Academic Research in Accounting, Finance and Management Sciences

Open Access Journal

ISSN: 2225-8329

Portfolio Optimization by Using Birds Flight Algorithm

Fatemeh Khaleghi Meybodi, Hassan Dehghan Denavi, Abolfazl Sadeghian

http://dx.doi.org/10.6007/IJARAFMS/v4-i2/897

Open access

Markowitz optimization problem so determination of investment efficient set, while the number of investable assets and constraints in the market is low can be solved by mathematical models. But when real-world conditions and limitations to be considered, portfolio optimization problem cannot solve easily using a methods of mathematics. For this reason, portfolio optimization using evolutionary algorithms has been an important topic of discussion today. The main objective of the present study is the solving of portfolio optimization problem (mean – variance model) by using Particle Swarm Optimization (PSO). for this purpose by use the price of 40 accepted shares in stock during the 1385 till 1390 years, is plotted the investment efficient set. Results from this study show that particle Swarm optimization method in portfolio optimization, despite the current limitations is successful.

Azar, A., Momeni, M. (1377). Statistics and its application in the management, SAMT Publishing, Tehran [In Persian].
Bidgoli, E., Talangi, A. (1378). Goal programming model of optimal portfolio choice, science & research Journal - Financial Research, Volume 4, Issue 1, pp. 71-50 [In Persian].
Bidgoli, E., Sarnj, A. (1387). Selection portfolio Using Mean returns standard deviations, returns and liquidity in Tehran Stock Exchange, Accounting and Auditing Studies, Volume 15, Number 53, pp. 3-16 [In Persian].
Chiam, S. C., Tan, K. C., Mamun, A. (2009). A memetic model of evolutionary PSO for computational finance applications. Expert Systems with Applications, 36, 3695-3711.
Cura, T. (2009). Particle swarm optimization approach to portfolio optimization, Nonlinear Analysis: Real World Applications, 10, 2396–240.
Dallagnol, V., Vandenberg, F., & Mous, L. (2009). Portfolio Management Using Value at Risk: A comparison between Genetic Algorithm and Particle Swarm Optimization, International of Intelligent System, 24, 729-766.
Zh, H., Yi, W. (2011). Particle Swarm Optimization (PSO) for the constrained portfolio optimization problem. Expert Systems with Applications, 38, 10161-10169.
Kendall, G. (2005), A Particle Swarm Optimization Approach in the Construction of Optimal Risky Portfolios, Artificial Intelligence and Applications.
Kennedy, J., & Eberhart R. (1995). Particle Swarm Optimization. International Conference on Neural Network, IEEE, pp. 1942-1948.
Koshino, M., Murata, H., & Kimura, H. (2007). Improved Particle Swarm Optimization and Application To Portfolio Selection. Electronics and Communications in Japan, 90, 13-25.
Kryzanowski, L., Galler, M., & Wright D. (1993). Using Artificial Networks to Pick Stocks. Financial Analyst’s Journal, 21-27.
Kuo, R. J., Hong, C. W. (2013). Integration of Genetic Algorithm and Particle Swarm Optimization for Investment Portfolio Optimization. Mathematics & Information Sciences, 6, 2397-2408.
Mansini, R., Speranza, M. G. (1999). Heuristic algorithms for the portfolio selection problem with minimum transaction lots, European Journal of Operational Research, 114:219-233.
Taghavifard, M., Mansouri, T., Khoshtinat, M. (1386). Presented an initiative algorithm for selecting portfolio consideration integer constraints, Journal of Economic Research, No. 4, pp. 69-49.
Tehrani, R., Siri, A. (1388). Efficient investment model used to analyze the mean semi-variance (Markowitz model), Stock Exchange Quarterly, Year II, No. 6, pp. 155-137.
Jahankhani, A., Parsian, A. (1376). Investment management and securities valuation, Tehran University Press, Tehran.
Damouri, D., Fareed, D., Ashhar, M. (1390). Predictive Index Tehran Stock Exchange birds fly algorithm and compare it with traditional models, accounting knowledge, the second year, No. 5, pp. 30-7.
Rai, R. (1381). Portfolio for venture capital: a comparison of neural networks and Markowitz, Message Management, No. 2, pp. 96-78.
Rai, R., Far, P. A. (1389). Advanced Investment Management, Fourth Edition, organizations of education and compiled books of Humanities University (left), Tehran.
Rai, R., Tlangy, A. (1383). Advanced Investment Management, First Edition, organizations of education and compiled books of Humanities University (left), Tehran.
Rai, R., AliBeiki, H. (1389). Portfolio optimization by Cumulative particle motion method and considering the limitations of the model CCMV. Financial Research, Volume 12, Number 29, pp. 40-21.
Abdolalizadeh, S. S., Eshgi, K. (1382). Application of genetic algorithms in the selection of a range of assets from the stock exchange, Journal of Economic Research of Iran, No. 17, pp. 192-175.
Abedini, R. (1390). Portfolio optimization using genetic algorithms, Master's thesis, University of Yazd.
Ghader, M. H., Lotfi, Sh., Esfahlan, S. M. (1389). A review of some intelligent optimization methods, Islamic Azad University, Shabestar unit.
Vatankhah, R. (1388). Control and optimize of cluster movement of robotic mass in methods inspired by nature, MS Thesis, Sharif University including flying birds, genetics.

In-Text Citation: (Meybodi et al., 2014)
To Cite this Article: Meybodi, F. K., Denavi, H. D., & Sadeghian, A. (2014). Portfolio Optimization by Using Birds Flight Algorithm. International Journal of Academic Research in Accounting Finance and Management Sciences. 4(2), 440 – 451.