Costas Siriopoulos and Maria Skaperda

Correspondence: Costas Siriopoulos, Konstantinos.Syriopoulos@zu.ac.ae

College of Business, Zayed University, U.A.E.

pdf (621.39 Kb) | doi: https://doi.org/10.47260/bae/7212

Abstract

This study analyses the performance of US Mutual Funds, from the perspective of Long Memory (LM), exploring if the returns of MFs are systematic due to their active management or they are random. The sample was 200 US equity MFs, from four categories, Large Cap, Middle Cap, Small Cap and World Stock, both 1- and 5-stars rating funds according to Morning Star rating. The time period was starting between 1981 and 2006 and ending 2016. Rescaled Range Analysis (R/S) employed for the Hurst exponent estimation, so to detect LM. Using Surrogate Data Analysis (SDA), the study was extended to Hurst exponent estimation for surrogate time series. The findings suggest that the selection of a MF presents a lot of complexity for investors. The 5-star MFs, with high qualified, and so expensive managers, tend to achieve random returns, while the returns of 1-star MFs, are more systematic. These MFs have higher fees than the 5-star MFs, but the management fees paid are quite inferior. This leads to the conclusion, that it might be preferable to pay for gaining an almost the same, but systematic return than to pay for the ties of the manager.

Keywords:

  Hurst exponent, Rescaled Range Analysis, Long Memory, Surrogate Data Analysis, Bootstrap, Mutual Fund Performance, Morning Star.

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