Comparison of Performance Measures of Pakistani Islamic Mutual Funds using Data Analytics - Khan, Zehra; Yaqub, Muhammad Shahbaz; Ashraf, Yasir (UMT Artificial Intelligence Review, 2023)
The current study attempted to measure and evaluate the performance of 13 Pakistani Shariah compliant mutual funds from the time period (September 2009-August 2017) by using 18 performance measures. It followed the principle that mutual funds are used exclusively for diversification portfolio and mean-variance optimization, following the mutual fund theorem as an investing strategy. The results of few performance measures showed that many funds outperformed the benchmark, while others underperformed. The study also analyzed and compared the performance measures to characterize the relationship between them and investigated if they lead to an identical ranking by using three analysis techniques, namely Pearson’s r, Spearman’s rho, and Kendall’s tau coefficient. The study concluded that there is a high level of correlation among performance measures which indicates that the performance measures classify mutual funds in a similar manner in three sub-periods, that is, 6 months, 1 year, and 3 years. Change of frequency doesn’t disturb their classification ability.