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Robust portfolio optimization with fuzzy TODIM, genetic algorithm and multi-criteria constraints

Author

Listed:
  • Ameet Kumar Banerjee

    (XLRI -Xavier School of Management)

  • H. K. Pradhan

    (XLRI -Xavier School of Management)

  • Ahmet Sensoy

    (Bilkent University
    Lebanese American University)

  • Frank Fabozzi

    (Johns Hopkins University)

  • Biplab Mahapatra

    (XIM, XIM University)

Abstract

This paper adopts the multi-criterion decision-making model of fuzzy-TODIM and genetic algorithm (GA) for optimal portfolio allocation. We applied Markowitz’s portfolio parameters as inputs for the fuzzy TODIM model to rank stocks that are constituents of each index from three different markets. Portfolios are then generated dynamically using three weighting techniques and subject to multi-objective criteria and additional constraints. The results indicate a significant variation in performance metrics between the model-generated portfolios and the market indices. Replication of the procedure produces a similar outcome. Moreover, the out-of-sample tests conducted over 3 years validate the results’ robustness, indicating that fuzzy TODIM, combined with GA, can achieve superior performance in dynamic portfolio allocation.

Suggested Citation

  • Ameet Kumar Banerjee & H. K. Pradhan & Ahmet Sensoy & Frank Fabozzi & Biplab Mahapatra, 2024. "Robust portfolio optimization with fuzzy TODIM, genetic algorithm and multi-criteria constraints," Annals of Operations Research, Springer, vol. 337(1), pages 1-22, June.
    • Handle: RePEc:spr:annopr:v:337:y:2024:i:1:d:10.1007_s10479-024-05865-1
    DOI: 10.1007/s10479-024-05865-1
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