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TODIM with XGBOOST and MVO metaheuristic approach for portfolio optimization

Author

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  • Veena Jain

    (University of Delhi)

  • Rishi Rajan Sahay

    (University of Delhi)

  • Nupur

    (University of Delhi)

Abstract

This paper presents an innovative and comprehensive approach to portfolio optimization that integrates TODIM, a multi criteria decision making method, with the proposed forecasting model for asset selection and return prediction. The optimization process utilizes the multi-verse optimizer, a powerful metaheuristic algorithm. TODIM is initially employed to select the top 10 companies from the Nifty 100 index based on various financial indicators. Daily return predictions for the selected portfolio are enhanced through an ensemble forecasting approach, BN-XGBoost, which combines BiLSTM and N-BEATS models, with XGBoost serving as a meta-learner to improve accuracy. The portfolio optimization problem, framed as a higher-order asymmetric risk model, incorporates semi-variance, higher order moments of return, and entropy. The proposed optimization framework is compared against a variance-based model, demonstrating superior portfolio performance. This research provides valuable insights for investors seeking advanced strategies to navigate complex financial markets and achieve optimal portfolio outcomes.

Suggested Citation

  • Veena Jain & Rishi Rajan Sahay & Nupur, 2025. "TODIM with XGBOOST and MVO metaheuristic approach for portfolio optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(2), pages 595-612, February.
    • Handle: RePEc:spr:ijsaem:v:16:y:2025:i:2:d:10.1007_s13198-024-02610-6
    DOI: 10.1007/s13198-024-02610-6
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    References listed on IDEAS

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    1. Yuze Li & Shangrong Jiang & Yunjie Wei & Shouyang Wang, 2021. "Take Bitcoin into your portfolio: a novel ensemble portfolio optimization framework for broad commodity assets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    2. Ehrgott, Matthias & Klamroth, Kathrin & Schwehm, Christian, 2004. "An MCDM approach to portfolio optimization," European Journal of Operational Research, Elsevier, vol. 155(3), pages 752-770, June.
    3. Wang, Liang & Zhang, Zi-Xin & Ishizaka, Alessio & Wang, Ying-Ming & Martínez, Luis, 2023. "TODIMSort: A TODIM based method for sorting problems," Omega, Elsevier, vol. 115(C).
    4. Veena Jain & Rishi Rajan Sahay & Nupur, 2024. "Multi-verse metaheuristic and deep learning approach for portfolio selection with higher moments," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(5), pages 1956-1970, May.
    5. Leoneti, Alexandre Bevilacqua & Gomes, Luiz Flavio Autran Monteiro, 2021. "A novel version of the TODIM method based on the exponential model of prospect theory: The ExpTODIM method," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1042-1055.
    6. Fathy, Ahmed & Rezk, Hegazy, 2018. "Multi-verse optimizer for identifying the optimal parameters of PEMFC model," Energy, Elsevier, vol. 143(C), pages 634-644.
    7. Jing-Yi Lai, 2012. "An empirical study of the impact of skewness and kurtosis on hedging decisions," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1827-1837, December.
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