A Fuzzy MCDM Model for Post-COVID Portfolio Selection

Abstract

Purpose- The outbreak of the COVID-19 pandemic is making the global economy succumb under pressure. The effect of the pandemic is notable especially in the context of developing countries like India. The situation is questioning the sustenance of many organizations and has made investors sceptical about their income allocation. Hence, the shift in the global markets calls upon for new criteria to help address future ambiguity. Design/ Methodology/ Approach- The paper proposes a hybrid multi-criteria decision making (MCDM) model for portfolio selection, under fuzziness. The paper draws upon the methodologies of the fuzzy analytic hierarchy process (FAHP) for obtaining the criterion weightage based on inputs obtained from industry peers. The study considers five criteria namely risk, return, liquidity, environmental, and governmental factors. Thus, five types of portfolios offered by an investment firm are ranked based on these criteria using the technique for order preferences by similarity to ideal solution (TOPSIS) method. Findings- The data analysis and results inferred, further support the proposed model. The findings also align with the previous studies undertaken and substantiate the inputs obtained from industry professionals. Also, the discussions are based on the research findings along with implications for multiple stakeholders- prospective investors and academicians. Originality- As part of the study two distinct variables namely environmental and governmental variables were considered in accordance with the future uncertainty of the markets due to pandemic, which have not been used in previous studies.