2-Phase NSGA II
2-phase NSGA II: an optimized reward and risk measurements algorithm in portfolio optimization. Portfolio optimization is a serious challenge for financial engineering and has pulled down special attention among investors. It has two objectives: to maximize the reward that is calculated by expected return and to minimize the risk. Variance has been considered as a risk measure. There are many constraints in the world that ultimately lead to a non-convex search space such as cardinality constraint. In conclusion, parametric quadratic programming could not be applied and it seems essential to apply multi-objective evolutionary algorithm (MOEA). In this paper, a new efficient multi-objective portfolio optimization algorithm called 2-phase NSGA II algorithm is developed and the results of this algorithm are compared with the NSGA II algorithm. It was found that 2-phase NSGA II significantly outperformed NSGA II algorithm.
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References in zbMATH (referenced in 2 articles , 1 standard article )
Showing results 1 to 2 of 2.
- Yue, Wei; Wang, Yuping; Xuan, Hejun: Fuzzy multi-objective portfolio model based on semi-variance--semi-absolute deviation risk measures (2019)
- Eftekharian, Seyedeh Elham; Shojafar, Mohammad; Shamshirband, Shahaboddin: 2-phase NSGA II: an optimized reward and risk measurements algorithm in portfolio optimization (2017)