Abstract—The purpose of this paper is to apply ACO approach to the portfolio optimization mean–variance model. The problem of portfolio optimization is a multiobjective problem that aims at simultaneously maximizing the expected return of the portfolio and minimizing portfolio risk. Present study is a heuristic approach to portfolio optimization problem using Ant Colony Optimization technique. The test data set is the monthly prices since 2008/20/03 up to 2011/20/03 from Tehran stock exchange. The performance of ACO is compared with frontcon function of MATLAB software as an exact method. Further more in an attempt to improve the algorithm performance, risk values obtained by ACO approach, were compared with Lingo optimal results.
The results show that proposed ACO approach is reliable but not preferred to an exact method. According to the significant difference between the risk values of ACO and optimal ones, next studies could emphasize on th e risk optimization process of proposed ACO.
Index Terms—Portfolio Optimization, Ant Colony Optimization (ACO), Multiobjective Optimization.
K. F. Haqiqi is faculty member with Department of Economics and Accounting, Iran Islamic Azad University, Central Tehran Branch, Tehran, Iran.
T. Kazemi is PhD student of Accounting with Department of Economics and Social Science, Shahid Chamran University Of Ahvaz, Ahvaz, Khozestan, Iran (e-mail: email@example.com).
Cite: Kambiz Forqandoost Haqiqi and Tohid Kazemi , "Ant Colony Optimization Approach to Portfolio Optimization – A Lingo Companion ," International Journal of Trade, Economics and Finance vol. 3, no. 2, pp. 148-153, 2012.