TODIM with XGBOOST and MVO metaheuristic approach for portfolio optimization

Veena Jain (), Rishi Rajan Sahay () and Nupur ()
Additional contact information
Veena Jain: University of Delhi
Rishi Rajan Sahay: University of Delhi
Nupur: University of Delhi

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 2, No 10, 595-612

Abstract: 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.

Keywords: Ensemble forecasting; MCDM; Multi-verse optimizer; Portfolio optimization; TODIM (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-024-02610-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:16:y:2025:i:2:d:10.1007_s13198-024-02610-6

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-024-02610-6

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().