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A new bi-objective fuzzy portfolio selection model and its solution through evolutionary algorithms

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Abstract

In this paper, a new bi-objective fuzzy portfolio selection model is proposed, for which Sharp ratio (SR) and Value at Risk ratio (VR) of a portfolio are chosen as objectives. SR is an important nonsystematic risk measurement that examines the investment risk by aspiring the diversification of the capital allocation. On the other hand, VR measures the systematic risk, which reduces the largest loss of an investment at a given confidence level. The proposed fuzzy portfolio model assumes both SR and VR as maximization objectives for which the associated fuzzy parameters are considered as triangular fuzzy numbers. The proposed model is solved using multi-objective genetic algorithms, namely multi-objective cellular genetic algorithm (MOCell), archive-based hybrid scatter search (AbYSS), and nondominated sorting genetic algorithm II (NSGA-II). We have used a data set from the Shenzhen Stock Exchange to illustrate the performance of the proposed model and algorithms. Finally, a comparative study in terms of five standard performance metrics is presented, among the MOCell, AbYSS, and NSGA-II algorithms that are mentioned extensively in various research articles to exhibit the best suitable algorithm.

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Acknowledgements

The authors are very much thankful to the Editor and the anonymous referees for their constructive and valuable suggestions to enhance the quality of the manuscript. Moreover, Saibal Majumder, an INSPIRE fellow (Fellowship No.: DST/INSPIREFellowship/2015/IF150410) is indebted to the Department of Science & Technology (DST), Ministry of Science and Technology, Government of India, for providing him financial assistance for the work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Heritage Institute of Technology, Kolkata, 700107, India

    Mohuya B. Kar

  2. Department of Mathematics, National Institute of Technology, Durgapur, 713209, India

    Samarjit Kar

  3. School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China

    Sini Guo & Xiang Li

  4. Department of Computer Science and Engineering, National Institute of Technology, Durgapur, 713209, India

    Saibal Majumder

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  1. Mohuya B. Kar
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Correspondence to Samarjit Kar.

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Kar, M.B., Kar, S., Guo, S. et al. A new bi-objective fuzzy portfolio selection model and its solution through evolutionary algorithms. Soft Comput 23, 4367–4381 (2019). https://doi.org/10.1007/s00500-018-3094-0

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