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Multi-objective approaches to portfolio optimization with market impact costs

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Abstract

Market impact costs are important factors to portfolio management, which always lead to adverse price fluctuations in trading. As the practical trading volume becomes increasingly large, the Problem of Portfolio Optimization with Market Impact Costs (MICPOP) has become more important. Traditional MICPOPs involve seeking an optimal allocation of capital to a limited number of assets with respect to either additional constraints or a weighted sum of objectives (net return, investment risk). We suggest solving MICPOPs with Multi-Objective Evolutionary Algorithms (MOEAs). Specifically, we formulate MICPOPs as a bi-objective optimization problem. The advantages of MOEAs over state-of-the-art single objective approaches to MICPOPs will be shown through empirical studies. Our study has revealed that a well-known MOEA, namely Nondominated Sorting Genetic Algorithm II (NSGA-II), fails to provide satisfactory solution quality sometimes. Hence, a memetic MOEA for Portfolio Optimization with Market Impact costs (POMI-MOEA), which inherits the global search capability of NSGA-II while introducing a new local search operator, is proposed and evaluated in this paper. Comprehensive experimental studies on 11 portfolio cases have shown the superiority of POMI-MOEA over NSGA-II and other two MOEAs for MICPOPs.

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Acknowledgements

This work is supported in part by the National Natural Science Foundation of China under Grant No.71901205.

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Authors and Affiliations

  1. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China

    Hongze Wang

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Hongze Wang

  3. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Xuerong Li

  4. Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China

    Wenjing Hong & Ke Tang

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  1. Hongze Wang
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  2. Xuerong Li
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  4. Ke Tang
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Correspondence to Xuerong Li.

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Wang, H., Li, X., Hong, W. et al. Multi-objective approaches to portfolio optimization with market impact costs. Memetic Comp. 14, 411–421 (2022). https://doi.org/10.1007/s12293-022-00381-w

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