Research Article
Solving Portfolio Optimization Problems with Particle Filter
@INPROCEEDINGS{10.1007/978-3-031-04245-4_39, author={Zeming Yang and Guoxing Huang and Yunxian Chen and Weidang Lu and Yu Zhang}, title={Solving Portfolio Optimization Problems with Particle Filter}, proceedings={6GN for Future Wireless Networks. 4th EAI International Conference, 6GN 2021, Huizhou, China, October 30--31, 2021, Proceedings}, proceedings_a={6GN}, year={2022}, month={5}, keywords={Particle filter Portfolio investment Nonlinear function Optimization problem}, doi={10.1007/978-3-031-04245-4_39} }- Zeming Yang
Guoxing Huang
Yunxian Chen
Weidang Lu
Yu Zhang
Year: 2022
Solving Portfolio Optimization Problems with Particle Filter
6GN
Springer
DOI: 10.1007/978-3-031-04245-4_39
Abstract
In order to improve precision of the solution to the portfolio optimization problem, a optimization scheme based on particle filter is proposed. Portfolio optimization problem is modeled by the Markowitz’s portfolio theory, and it is a nonlinear optimization problem with multiple constraints. In this paper, particle filter is considered, to solve portfolio optimization problem. The nonlinear optimization problem is converted to filtering problem of particle filter. Then the nonlinear optimization problem can be solved by particle filter method. To solve portfolio optimization problem, a optimization scheme based on particle is proposed. To improve precision of the solution, crossover and mutation of genetic algorithm is considered in the proposed scheme. Lastly, results of simulation have demonstrated that the proposed optimization scheme outperforms other traditional methods in the precision of the solution of the portfolio optimization problem.
