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A Genetic Algorithm for Solving Portfolio Optimization Problems with Transaction Costs and Minimum Transaction Lots

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

A mean-variance model is proposed for portfolio rebalancing optimization problems with transaction costs and minimum transaction lots. The portfolio optimization problems are modeled as a non-smooth nonlinear integer programming problem. A genetic algorithm based on real value genetic operators is designed to solve the proposed model. It is illustrated via a numerical example that the genetic algorithm can solve the portfolio rebalancing optimization problems efficiently.

Supported by National Sciences Foundation of China (No. 70301005) and the Liu Hui Center of Applied Mathematics of Nankai University and Tianjin University.

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References

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Author information

Authors and Affiliations

  1. School of Sciences, Tianjin University, Tianjin, 300072, P.R. China

    Dan Lin & Xiaoming Li

  2. School of Management, Tianjin University, Tianjin, 300072, P.R. China

    Minqiang Li

Authors
  1. Dan Lin
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  2. Xiaoming Li
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  3. Minqiang Li
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Lin, D., Li, X., Li, M. (2005). A Genetic Algorithm for Solving Portfolio Optimization Problems with Transaction Costs and Minimum Transaction Lots. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_99

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  • DOI: https://doi.org/10.1007/11539902_99

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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