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Multi-Swarm Multi-Objective Optimizer Based on - Optimality Criteria for Multi-Objective Portfolio Management

Author

Listed:
  • Yabao Hu
  • Hanning Chen
  • Maowei He
  • Liling Sun
  • Rui Liu
  • Hai Shen

Abstract

Portfolio management is an important technology for reasonable investment, fund management, optimal asset allocation, and effective investment. Portfolio optimization problem (POP) has been recognized as an NP-hard problem involving numerous objectives as well as constraints. Applications of evolutionary algorithms and swarm intelligence optimizers for resolving multi-objective POP (MOPOP) have attracted considerable attention of researchers, yet their solutions usually convert MOPOP to POP by means of weighted coefficient method. In this paper, a multi-swarm multi-objective optimizer based on p -optimality criteria called p -MSMOEAs is proposed that tries to find all the Pareto optimal solutions by optimizing all objectives at the same time, rather than through the above transforming method. The proposed p -MSMOEAs extended original multiple objective evolutionary algorithms (MOEAs) to cooperative mode through combining p -optimality criteria and multi-swarm strategy. Comparative experiments of p -MSMOEAs and several MOEAs have been performed on six mathematical benchmark functions and two portfolio instances. Simulation results indicate that p -MSMOEAs are superior for portfolio optimization problem to MOEAs when it comes to optimization accuracy as well as computation robustness.

Suggested Citation

  • Yabao Hu & Hanning Chen & Maowei He & Liling Sun & Rui Liu & Hai Shen, 2019. "Multi-Swarm Multi-Objective Optimizer Based on - Optimality Criteria for Multi-Objective Portfolio Management," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-22, January.
    • Handle: RePEc:hin:jnlmpe:8418369
    DOI: 10.1155/2019/8418369
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    Cited by:

    1. Adolfo Hilario-Caballero & Ana Garcia-Bernabeu & Jose Vicente Salcedo & Marisa Vercher, 2020. "Tri-Criterion Model for Constructing Low-Carbon Mutual Fund Portfolios: A Preference-Based Multi-Objective Genetic Algorithm Approach," IJERPH, MDPI, vol. 17(17), pages 1-15, August.

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