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

Ameet Kumar Banerjee (), H. K. Pradhan (), Ahmet Sensoy, Frank Fabozzi () and Biplab Mahapatra ()
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Ameet Kumar Banerjee: XLRI -Xavier School of Management
H. K. Pradhan: XLRI -Xavier School of Management
Frank Fabozzi: Johns Hopkins University
Biplab Mahapatra: XIM, XIM University

Annals of Operations Research, 2024, vol. 337, issue 1, No 1, 22 pages

Abstract: 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.

Keywords: Portfolio optimization; Genetic algorithm; Multi-criteria decision-making; Fuzzy TODIM; Transaction costs (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-024-05865-1

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