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Solving Portfolio Optimization Problems with Particle Filter

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6GN for Future Wireless Networks (6GN 2021)

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.

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Correspondence to Guoxing Huang .

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yang, Z., Huang, G., Chen, Y., Lu, W., Zhang, Y. (2022). Solving Portfolio Optimization Problems with Particle Filter. In: Shi, S., Ma, R., Lu, W. (eds) 6GN for Future Wireless Networks. 6GN 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 439. Springer, Cham. https://doi.org/10.1007/978-3-031-04245-4_39

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  • DOI: https://doi.org/10.1007/978-3-031-04245-4_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04244-7

  • Online ISBN: 978-3-031-04245-4

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