Making Decision on Selection of Optimal Stock Portfolio Employing Meta Heuristic Algorithms for Multi-Objective Functions Subject to Real-Life Constraints
محورهای موضوعی : Multi-Criteria Decision Analysis and its Application in Financial Management
Ali Sepehri
1
(Department of Industrial Management- Financial, Kashan Branch, Islamic Azad University, Kashan, Iran)
Hassan Ghodrati Ghazaani
2
(Department of Management, Kashan Branch, Islamic Azad University, Kashan, Iran)
Hossein Jabbari
3
(Department of Accounting, Kashan Branch, Islamic Azad University, Kashan, Iran)
Hossein Panahian
4
(Department of Management, Kashan Branch, Islamic Azad University, Kashan, Iran)
کلید واژه: multi-objective function, Real-Life Constraints, Simulation, Capital Decision Making, Stock Portfolio Optimization,
چکیده مقاله :
The purpose of this study is to make investment decisions with the approach of data envelopment analysis and making decision on selection of optimal stock portfolio employing meta heuristic algorithms for multi-objective functions subject to real-life constraints. The statistical population of this research in capital decision-making and selection of the optimal capital composition is 183 of the selected companies of Tehran Stock Exchange, which were finally 42 companies as justified investment options. After measuring the risk and return of efficient companies, the real limitations of the budget, requirements and expectations of the investor, determination and composition of the investment were formulated as a multi-objective model. For optimal decision, the modified genetic meta heuristic algorithm and MATLAB software with dual operators were used. Elimination of the risk minimization function in sensitivity analysis improved the level of decision return but also led to more risk. Eliminating the maximizing return function improved decision-making risk but also reduced investment return. Elimination of investment requirements and expectations improved returns and increased investment risk, but more companies became involved in optimal investment.
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