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Application of Artificial Bee Colony Algorithm to Portfolio Adjustment Problem with Transaction Costs

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  • Wei Chen
  • Hui Ma
  • Yiping Yang
  • Mengrong Sun

Abstract

Compared with the conventional probabilistic mean-variance methodology, fuzzy number can better describe an uncertain environment with vagueness and ambiguity. In this paper, we discuss a portfolio adjusting problem under the assumption that the returns of risky assets are fuzzy numbers and there exist general transaction costs in portfolio adjusting process. In the proposed model, we take the first possibilistic moment about zero of a portfolio as the investment return and the second possibilistic moment about the possibilistic mean value of the portfolio as the investment risk. To solve the proposed model, a modified artificial bee colony (ABC) algorithm is developed for calculating the optimal portfolio adjusting strategy. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and approach.

Suggested Citation

  • Wei Chen & Hui Ma & Yiping Yang & Mengrong Sun, 2014. "Application of Artificial Bee Colony Algorithm to Portfolio Adjustment Problem with Transaction Costs," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-12, June.
    • Handle: RePEc:hin:jnljam:192868
    DOI: 10.1155/2014/192868
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    Cited by:

    1. Zandi-Mehran, Nazanin & Jafari, Sajad & Golpayegani, Seyed Mohammad Reza Hashemi, 2020. "Signal separation in an aggregation of chaotic signals," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Mostafa Zandieh & Seyed Omid Mohaddesi, 2018. "Portfolio Rebalancing under Uncertainty Using Meta-heuristic Algorithm," Papers 1812.07635, arXiv.org.

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