Portfolio Optimization Problem Considering Cardinality and Bounding Constraints Using a Metaheuristic Algorithm
محورهای موضوعی : International Journal of Finance, Accounting and Economics StudiesShohreh Zakaei 1 , Mohammadreza Sanaei 2 , Akbar Mirzapour Babajan 3
1 - PhD student of Information Technology Management, Department of Information Technology Management, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - Department of Information Technology Management, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 - Department of Economics, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran
کلید واژه: Optimization, Metaheuristic algorithm, Portfolio, Cardinality constraint,
چکیده مقاله :
The optimal portfolio selection problem is one of the most important problems in finance investigated by many researchers and professors over the last few decades. Of the exact methods and effective approximate solution algorithms, metaheuristic methods have also been successfully proposed to solve some practical and large-scale problems with large numbers of assets and constraints. Hence, in this study, it is tried to optimize the portfolio selection problem by the metaheuristic cuckoo search algorithm (CSA) considering cardinality constraints and show that the mentioned algorithm is capable of achieving suitable solutions. Once the algorithm is designed and run in MATLAB software, the efficient frontier diagram obtained from CSA is close and similar to the efficient frontier diagram obtained from the basic Markowitz model confirming the accuracy and validity of the results obtained from CSA. However, it should be noted that the convergence of the solutions obtained according to CSA is better. Finally, a general comparison between the results obtained from the use of CSA in this study and bee and genetic algorithms in other studies is shown. Based on the results, the average risk return according to CSA is higher than the other two algorithms. Moreover, the portfolio risk according to CSA is lower compared to the other algorithms.
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