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1 2025

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Ranking of Efficient Fuzzy Portfolios by Hybrid MSBM-TOPSIS Technique

Aggarwal Abha, Gupta Anjana, Verma Rajkumar, Kumari Reenu

Foundations of Computing and Decision Sciences

2025

Vol. 50, No. 1

3--26

This study focuses on ranking of investment portfolios by integrating the Modified Slack Based Measure (MSBM) of Data Envelopment Analysis (DEA) with a multi-criteria decision-making method. Specifically, it extends the MSBM model to evaluate portfolios with positive and negative inputs and outputs in a fuzzy environment using possibilistic mean return of the assets as output and possibilistic variance and semi-variance as inputs. The ranking process involves two stages: first, portfolios are evaluated using an MSBM fuzzy portfolio model, followed by their ranking through the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. This hybrid MSBM-TOPSIS approach provides a robust and reliable ranking system, enabling investors to identify efficient portfolios by leveraging the strengths of both methods. Detailed numerical illustrations are presented here to authenticate the proposed approach and the obtained results are compared with other existing DEA methods that validate the accuracy and feasibility of the proposed technique.