Does the technique for order of preference by similarity to ideal solution (TOPSIS) help to find winners in mutual funds?

Mutual funds are evaluated based on individual performance criteria, such as average return or sharpe ratio, and risk criteria like standard deviation or beta, providing insight into how well a fund performs relative to its risk level. Selection of mutual funds is often based on past performance, with the anticipation of similar performance in the future. However, the existence of various evaluation methods poses a challenge in identifying the most robust approach. Further, it is imperative to consider multiple metrics and methodologies to obtain a comprehensive understanding. Previous research on mutual fund performance has demonstrated that no single metric is foolproof. Thus, in this study, the final ranking of mutual funds is determined by integrating multiple performance metrics through TOPSIS. After the ranking process, the second phase of the study involves an investigation into the effectiveness of these performance metrics in identifying persistent performers. Therefore, the chosen mutual funds are categorized as winners or losers based on their median ranking for each respective year. Followed this, Winner-Losser cross table was created by comparing the current year performance with the immediately preceding year. To test the hypothesis that mutual fund performance in one period does not carry over to the following year, Malkiel’s Z-test, Brown and Goetzmann’s Z-test, and Khan and Rudd’s Chi-square tests were employed. The result of the study supports the TOPSIS model over single criterion based mutual fund investment decision. TOPSIS method considerably enhance the probability of picking winners and avoiding losers. It is the first research in literature to investigate the performance persistence of mutual funds using TOPSIS.